EPA
United States
Environmental Protection
Clinch and Powell Valley
Watershed Ecological Risk
Assessment
-------
-------
EPA/600/R-01/050
September 2002
Clinch and Powell Valley Watershed
Ecological Risk Assessment
National Center for Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Recycled/Recyclable
Printed with vegetable-based ink on
paper that contains a minimum of
50% post-consumer fiber content
processed chlorine free.
-------
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
A watershed ecological risk assessment of the unique Clinch and Powell river system in
southwestern Virginia strongly suggests that (1) coal mining activities and agricultural practices,
past and present, are having adverse impacts on stream habitats, resulting in unacceptable losses
of valuable and rare native fish and mussels and (2) prompt implementation of practical risk-
lowering actions, such as reclaiming abandoned mines, spill prevention, excluding livestock from
streams, and establishing riparian vegetation zones, can mitigate these adverse effects hi the
future.
The free-flowing Clinch and Powell Valley watershed, which drains into Norris Lake in
northeastern Tennessee, has historically had one of the richest assemblages of native fish and
freshwater mussels hi the world. Nearly half of the species historically present are now extinct,
threatened, or endangered. The U.S. Environmental Protection Agency's ecological risk
assessment framework was used to structure a watershed-scale analysis of associations between
land use and in-stream habitat and their effects on fish and mussels.
A pilot study of one of four subwatersheds determined that the fish Index of Biotic
Integrity (IBI) was a useful surrogate for mussel species richness and found the optimal spatial
scale to describe associations between land use, stressors, and biota. These findings were used to
structure the watershed risk analysis of relationships between sources, stressors, and effects.
Percent pasture area, percent crop land, and proximity to active mining, urban areas, or
major transportation routes accounted for more than half of the variance hi fish IBI scores, with
coal mining having the most impact. Native fish and mussel populations appeared to be at
greatest risk as more stressors co-occurred. Our results indicate that a number of sources and
stressors are responsible for the decline in native species hi the Clinch and Powell Valley
watershed, but naturally vegetated riparian corridors may help mitigate some of these effects.
Preferred citation:
U.S. Environmental Protection Agency (EPA) (2002). Clinch and Powell Valley watershed
ecological risk assessment. National Center for Environmental Assessment, Washington, DC;
EPA/600/R-01/050. Available from: National Technical Information Service, Springfield VA-
PB2003-101118, and .
n
-------
CONTENTS
LIST OF TABLES '..'. . • • • • • • • vi
LISTOFFIGURES vii
LIST OF ACRONYMS • x
GLOSSARY ..-.•-.. • • xi
FOREWORD • • xiv
PREFACE xv
AUTHORS, CONTRIBUTORS, AND REVIEWERS ._ xvi
1. EXECUTIVE SUMMARY •-• 1-1
2. BACKGROUND 2-1
2.1. WATERSHED DESCRIPTION . 2-1
2.2. LAND USES IN THE WATERSHED 2-5
3 PLANNING AND PROBLEM FORMULATION - 3-1
3.1. MANAGEMENT GOALS AND RISK ASSESSMENT OBJECTIVES 3-1
3.1.1. Assessment Endpoints - 3-5
3.1.1.1. Assessment Endpoint 1 3-5
3.1.1.2. Assessment Endpoint 2 '• 3-6
3.1.2. Impacts on Abundance, Diversity, and Age Class Structure
of Cave Fauna 3-9
3.2. SOURCES AND STRESSORS CONSIDERED IN THE CLINCH AND
POWELL WATERSHED ASSESSMENT 3-9
3.2.1. Active Coal Mining and Processing 3-10
3.2.2. Abandoned Mine Lands 3-11
3.2.3. Urbanization 3~12
3.2.4. Agriculture—Livestock and Pastureland 3-13
3.2.5. Agriculture—Row Crop 3-13
3.2.6. Point-Source Discharge—Industrial 3-14
3.2.7. Point-Source Discharge—Municipal Sewage 3-15
3.2.8. Silviculture • • • 3"15
3.2.9. Hydrologic Changes 3-17
3.2.10. Introductions and Migration of Nonnative Species 3-17
3.2.11. Recreation 3"18
3.2.12. Other Biota—Predation 3-18
3.2.13. Illegal Harvesting 3'18
3.2.14. Catastrophic Spills 3'19
3.3. SIMPLIFIED CONCEPTUAL RISK MODEL • • 3~20
3.3.1. Degraded Water Quality • 3-20
3.3.2. Physical Stream Habitat Alteration 5-23
3.3.3. Loss of Riparian Corridor 3-24
3.4. ANALYSIS PLAN 3'25
iii
-------
CONTENTS (Continued)
3.5. ANALYTICAL APPROACH 3-25
3.6. PILOT TESTING 3_29
3.7. STATISTICAL ANALYSES '.'.'.'.'.'.'.'.'.'. 3-31
4. PILOT TEST OF RISK ANALYSIS APPROACH ; 4-1
4.1. BACKGROUND 4_1
4.2. RESULTS ''''' 4.3
4.2.1. Riparian Corridor Analyses 4.3
4.2.2. Relationships Among IBI, EPT, and Stream Habitat Measures 4-8
4.2.3. Analyses of Mussel and Fish Data in Copper Creek 4-12
4.2.4. Temporal Comparison of Fish and Mussel Data in Copper
Creek and Evaluation of Agricultural BMPs 4-14
4.3. RISK CHARACTERIZATION FOR COPPER CREEK PILOT TESTING
AND FINDINGS FOR IMPLEMENTING WATERSHED ANALYSIS 4-17
4.4. MANAGEMENT IMPLICATIONS 4-18
5. RISK ANALYSIS FOR THE CLINCH AND POWELL VALLEY
WATERSHED 5_1
5.1. RELATIONSHIP BETWEEN STREAM ELEVATION AND BIOLOGICAL
MEASURES OFEFFECT 5-2
5.2. EFFECTS OF LAND USE ON HABITAT QUALITY MEASURES 5-2
5.3. RELATIONSHIPS BETWEEN LAND USE AND BIOLOGICAL
MEASURES OFEFFECT 5-5
5.3.1. The Fish IBI 5-5
5.3.2. The Macroinvertebrate EPT 5-11
5.3.3. Mussels 544
5.4. RELATIONSHIPS BETWEEN HABITAT MEASURES AND
BIOLOGICAL MEASURES OFEFFECT 5-15
5.5. CUMULATIVE EFFECTS OF LAND USE ON ASSESSMENT
ENDPOINTS 5-17
5.6. SENSITIVITY ANALYSES OF RIPARIAN CORRIDOR BUFFERS 5-27
5.6.1. Methods 5-27
5.6.1.1. Mussels 5-27
5.6.1.2. Fish 5-28
5.6.2. Results and Discussion 5-28
5.6.2.1. Mussels 5-28
5.6.2.2. Fish 5-32
6. RISK CHARACTERIZATION 6-1
6.1. FINDINGS 6-1
6.1.1. Copper Creek Watershed 6-1
6.1.2. Clinch andPowell Watershed 6-1
6.1.3. Unexplained Variance 6-2
6.1.4. Stressor-Response Relationships 6-4
IV
-------
7.
CONTENTS (Continued)
6.2. SOURCES OF UNCERTAINTY \ • • 6-7
6.2.1. Reliability of Source, Stressor, and Biological Data .6-7
6.2.2. Extrapolation of Results Between Biological Measures 6-10
MANAGEMENT IMPLICATIONS OF THE CLINCH AND POWELL
VALLEY ASSESSMENT • • • 7~l
REFERENCES
R-l
APPENDIX A. STAKEHOLDERS INVOLVED IN RISK ASSESSMENT PLANNING .. A-l
APPENDIX B. NATIVE MUSSEL AND FISH SPECIES OF CONCERN IN THE
CLINCH AND POWELL WATERSHED B-l
APPENDIX C. RIPARIAN CORRIDOR LAND USE ANALYSES, UPPER
CLINCHRJVER c~l
-------
LIST OF TABLES
3-1 Stressors and sources identified in the Clinch and Powell watershed 3-10
3-2 Available data used in risk analysis 3.28
3-3 Comparison of land cover for four subwatersheds examined in the Clinch and Powell
watershed risk assessment 3.39
4-1 Summary of Spearman Rank Correlation coefficients between percent agricultural
area and the fish IBI as a function of different combinations of riparian corridor
width and distance upstream for Copper Creek 4-5
5-1 Summary of forward stepwise multiple regression analyses of fish IBI values 5-7
5-2 Summary of stepwise multiple regression analyses of macroinvertebrate EPT value
in relation to potential sources of stressors in the Clinch and Powell watershed 5-13
5-3 Summary of forward stepwise multiple regression analysis of Cumberlandian
mussel species richness as a function of riparian land-use factors 5-15
5-4 Summary of forward stepwise multiple regression analyses of habitat quality
measures in relation to either fish IBI or macroinvertebrate EPT 5-16
5-5 Criteria used to define whether a stressor was present or potentially present at a
site or not present for the mussel CMCP risk analyses 5-23
5-6 Correlation (Pearson Product Moment R values) of land use percentages within
whole drainage areas and within different-size riparian corridors with mussel
richness and abundance 5-29
5-7 Correlation (Pearson Product Moment R values) of total habitat scores and 10
individual habitat parameters with land uses in whole drainage areas and different-
size riparian corridors 5-33
5-8 Correlation (Pearson Product Moment R values) of IBI scores with whole
drainage and riparian corridor land uses for all sites and various categories 5-35
6-1 Summary of stressors affecting assessment endpoints in the Clinch and Powell
watershed risk assessment and lines of evidence used to characterize the
risk and recovery potential from stressors 6-5
VI
-------
LIST OF FIGURES
2-1
2-2
2-3
3-1
3-2
3-3
3-4
4-1
4-2
4-3
4-4
4-5
4-6
Watershed boundaries, major cities* and subwatersheds examined in
this risk assessment • • • •
4-8
Many endemic mussel species in the Clinch and Powell watershed have evolved
sophisticated anatomical structures to attract the appropriate fish host
2-2
2-4
The swiftly flowing waters of the Clinch River provide a source of recreation for
outdoor enthusiasts • 2-6
Framework for ecological risk assessment
The Clinch and Powell watershed harbors several endemic fish species, particularly
insectivorous darters, many of which are now rare and/or threatened and
endangered • • • • •
3-2
3-8
Conceptual risk model for mussels - 3~21
Conceptual risk model for fish • • 3'22
The Copper Creek subwatershed and major land uses
4-2
Summary of fish IBI, EPT, and habitat quality data for nine TVA sites
surveyed in'Copper Creek, 1995-96, as a function of total upland agricultural area
above the sampling point
4-3
Illustration depicting the strength of relationships between land uses and biological
measures as a function of riparian buffer width and distance upstream 4-5
Fish community integrity as a function of agricultural land in the riparian
Some pasture and row crop practices within the floodplain, karst, and lowland
areas pose serious risks to aquatic resources
Forest and agricultural uses in the riparian corridor (200 m wide)
of Copper Creek
4-6
4-6
4-7
4-7 Number of threatened and endangered mussel species collected in different places
on Copper Creek
4-9
Relationships between benthic insect EPT and fish ffil values for TVA CPRATS
sites (1995-96) in Copper Creek alone and for the entire Clinch and Powell
CPRATS dataset •
4-10
Vll
-------
LIST OF FIGURES (continued)
4-9 Relationships between TVA's multimetric stream habitat quality index or stream
embeddedness score (TVA's scoring system) and either invertebrate EFT or fish IBI
score for the Clinch and Powell CPRATS dataset 4-11
4-10 Fish and mussel species richness by river mile in Copper Creek 4-13
4-11 Number of mussel species in Copper Creek 1981 and 1998 4-15
4-12 Fish IBI in 1995-96 in comparison with fish species richness observed in 1969-71
in Copper Creek 4_16
5-1 Relationship between the fish IBI and stream elevation 5-3
5-2 Relationships observed between land-use activities and instream habitat measures
for sites in the Clinch and Powell watershed .. 5-4
5-3 Three-dimensional contour plots illustrating two-way interactions observed between
land uses and effects on instream habitat features 5-6
5-4 Significant relationships observed between land-use sources and IBI for the
entire CPRATS dataset 5_g
*•
5-5 Fish IBI or insect EPT values in relation to proximity to coal mining sources 5-9
5-6 Comparison of acute toxicity results (LC50) for several species 5-10
5-7 Effect of mine type on fish community integrity as a function of the type of mine ... 5-10
5-8 Number of mussel species recorded over time at two sites in Clinch and Powell
watershed affected by large toxic point-source discharge events 5-12
5-9 Significant relationships between land-use activities or habitat quality and
invertebrate EPT score 5_13
5-10 Relationship between stream embeddedness or cover and fish IBI categorized as
either poor (impaired) or good (unimpaired) 5-17
5-11 Significant relationships observed between specific instream habitat quality
measures and the macroinvertebrate EPT index „ 5-18
5-12 Macroinvertebrate (EPT) and fish (IBI) community integrity scores by subwatershed
in the Clinch and Powell watershed „ 5-19
Vlll
-------
LIST OF FIGURES (continued)
5-13 Comparison of mean number of native mussels or number of species observed in
the upper Powell and Clinch Rivers
5-21
5-14 Comparison between historic (pre-1910) and present locations of native mussel
concentrations in the Clinch and Powell watershed 5-22
5-15 Comparison of cumulative stressors in the upper Clinch and Powell rivers ........ 5-23
5-16 Mean number of cumulative sources of stress as one progresses upstream in the
Clinch River
5-24
5-17 Fish JBl (A) and maximum number of mussel species collected (B) in the
Clinch and Powell watershed as a function of the number of stressors present 5-25
5-18 Map of portion of the middle Clinch River watershed showing two mussel
concentration sites in relation to major roadways (a source of episodic spills) and
agricultural areas
5-19 Mussel richness versus percent forested land use in 100-m-wide, 5-km-long
riparian corridors
5-26
5-30
5-20 JBI scores versus average catchment slope (%) • • 5-36
5-21 Mines in the Clinch River watershed • 5"37
IX
-------
LIST OF ACRONYMS
BMP
Best Management Practices
CMCP Cuberlandian Mollusc Conservation Program
CPRATS Clinch-Powell River Action Team Survey
EPA
United States Environmental Protection Agency
EPT
Ephemoptera, Plecoptera, Trichqptera
FWS
United States Fish and Wildlife Service
GIS
Geographic Information System
mi
Index of Biotic Integrity
NCEA-W National Center for Environmental Assessment-Washington, DC
SAMAB Southern Appalachian Man and the Biosphere
TNC The Nature Conservancy
TVA Tennessee Valley Authority
USGS United States Geological Survey
VDEQ Virginia Department of Environmental Quality
VDOT Virginia Department of Transportation
-------
GLOSSARY
Allochthonous Energy: energy created outside the ecosystem. Commonly used to refer to
organic matter produced from photosynthesis in the watershed rather than within the waterbody.
Assessment Endpoint: an explicit expression of the environmental value that is to be protected,
operationally defined by an ecological entity and its attributes.
Benthic: bottom-dwelling.
Best Management Practices (BMPs): methods that have been determined to be the most
effective, practical means of preventing or reducing pollution from nonpoint sources.
Biomagnification: the increased accumulation and concentration of a contaminant at higher
levels of the food web because the contaminants are not broken down within organisms.
Detritus: particles of dead and decaying organic matter.
Embeddedness: the extent to which rocks (gravel, cobble, and boulders) are surrounded by,
covered, or sunken into the silt, sand, or mud of the stream bottom. Generally, as rocks become
embedded, fewer living spaces are available to macroinvertebrates and fish for shelter, spawning,
and egg incubation.
Endemic: native to a particular region.
Ephemeroptera, Plecoptera, Trichoptera (EPT): a measure of the quality of the
macroinvertebrate community, based on the number of species of macroinvertebrates found in
three taxonomic families Ephemeroptera, Plecoptera, Trichoptera.
Extirpation: small-scale eradication of a species.
Extrapolate: to infer or estimate by extending or projecting known information.
Fines: fine paniculate matter (e.g., clay, silt).
XI
-------
GLOSSARY (continued)
Fish Index of Biotic Integrity (ffil): a series of measures that describe the quality of the fish
community, based on characteristics of individual fish (e.g., presence offish tumors), fish
populations (e.g., percent juveniles of a given species), and the composition of the fish
community (presence of pollution-tolerant species).
Fragmentation: the process of transforming large continuous forest patches into one or more
smaller patches surrounded by disturbed areas.
Glochidia: an obligate parasitic larval stage of the mussel that must attach onto the fins,
epidermis, or gills of a suitable host fish.
Instream Cover: area available to aquatic biota for protection, shelter, spawning, and feeding.
Karst: a terrain generally underlain by limestone or dolomite in which the topography is
generally formed by dissolving of rock and that may be characterized by sinkholes, sinking
streams, closed depressions, subterranean drainage, and caves.
Measure of Effect: a change in an attribute of an assessment endpoint or its surrogate in
response to a stressor.
Metrics: ecologically relevant measures of assemblage attributes used to analyze changes due to
stressors.
Recruitment: the addition of new individuals to the existing population.
Refugia: areas that provide organisms with protection from predators, storms, etc.
Riparian: an area that borders a waterbody and serves as a transition zone between aquatic
ecosystems and terrestrial ecosystems.
Riparian Buffer: the width of the streamside vegetated area perpendicular to the stream (e.g., a
50-meter buffer out from the stream).
XII
-------
GLOSSARY (continued)
Riparian Corridor: the length and width of the streamside vegetated area parallel and
perpendicular to the stream (e.g., a 50-meter buffer out from the stream that extends for 1000
meters alongside the stream).
Risk: a measure of the probability that damage to life, health, property, and/or the environment
will occur as a result of a given hazard.
Sedentary: staying in one place.
Sedimentation: the process by which soil particles (sediment) settle to the bottom of the stream
channel. Excessive levels of sedimentation create an unstable and continually changing
environment that is unsuitable for many aquatic organisms.
Stream Order: a hierarchical classification of streams. The smallest, permanently flowing
stream is termed first order, and the union of two streams of order "n" creates a stream order of
"n+1". '.."...
Surrogate Endpoint: a closely related endpoint to be used when data relating the assessment
endpoint to human activities are not available.
Surrogate Indicator: a closely related indicator to be used when data relating the assessment
endpoint to human activities are not available.
Turbidity: a cloudy condition in water due to suspended silt or organic matter.
Type I Error: Falsely concluding that there is no effect, when one is actually occurring.
Xlll
-------
FOREWORD
Risk assessment is playing an increasingly important role in determining environmental
policies and decisions at the U.S. Environmental Protection Agency (EPA). EPA published
Guidelines for Ecological Risk Assessment (U.S. EPA, 1998) to provide a broad framework that
could be applied to a range of environmental problems associated with chemical, physical, and
biological stressors. As ecological risk assessment evolves, it is moving beyond a focus on
assessing the effects of simple chemical toxicity on single species to the cumulative impacts of
multiple interacting chemical, physical, and biological stressors on populations, communities,
and ecosystems. Although EPA has considerable experience in applying the ecological risk
assessment paradigm hi source-based approaches (such as those focused on particular chemicals),
specific guidance on "place-based" approaches (e.g., watersheds and regions) is still limited.
This assessment of the Clinch and Powell Valley watershed was completed to address a
specific environmental problem through application of the risk assessment approaches
represented in the guidelines. Through this assessment, and other watershed scale assessments
like it, the Office of Research and Development is learning how to develop new tools and
approaches to support local environmental decisionmakers. An important component of these
approaches is active participation by local stakeholders. The Clinch-Powell assessment provides
a good example of partnering between government, environmental organizations, and others to
support environmental decision making with strong science.
The Clinch and Powell Valley site was selected because the watershed contains valued
and threatened ecological resources; it had previously collected stressor and effects data; it is
subjected to multiple physical, chemical, and biological stressors; and a number of organizations
are working to protect the ecological resources. This assessment is intended to address concerns
by analyzing stressors and the resulting ecological effects and to stimulate broader public
awareness and participation in decision making for reducing ecological risks. This watershed
assessment report serves as an example on how to use ecological risk assessment principles in a
watershed scale to improve the use of science in decision making.
Michael Slimak
Associate Director of Ecology
National Center for Environmental Assessment
U.S. EPA, Office of Research and Development
xiv
-------
PREFACE
The National Center for Environmental Assessment, Washington, DC (NCEA-W), The
Nature Conservancy, the U.S. Fish and Wildlife Service, the Tennessee Valley Authority and
other organizations developed this watershed ecological risk assessment to help protect the native
mussels and fish of the Clinch and Powell Valley watershed. The document has three purposes:
(1) to provide information to help make more informed decisions on how to protect the valued
ecological resources of the watershed, (2) to provide data and references for future research in the
watershed, and (3) to demonstrate the benefits of applying ecological risk assessment at the
watershed scale. The report is based on the Guidelines for Ecological Risk Assessment (U.S.
EPA, 1998) and advice and support from NCEA, while exercising the necessary flexibility to
implement the risk assessment approach at the watershed scale. To serve as an example for
others seeking to increase the use of science in place-based decision making, the document
includes brief descriptions of the process the workgroup followed and the major analyses
performed even if analytical deliberations were not always conclusive. The literature search
supporting the document was completed in May 2000.
A more concise report of the assessment's findings and methods can be found in
Diamond and Serveiss (2001). A discussion of how this assessment combined ecological risk
assessment with geographical information systems and multivariate analysis as tools to diagnose
relationships between environmental stressors and ecological effects is presented in Diamond and
Serveiss (2002). Lessons learned about applying ecological risk assessment to the watershed
scale, including those acquired from this assessment, are described in Serveiss et al. (2000) and
Serveiss (2002). Discussion on how ecological risk assessment principles can be applied at an
even larger spatial scale (e.g., a region) can be found in Landis and Wiegers (1997) and Wiegers
etal. (1998).
xv
-------
AUTHORS, CONTRIBUTORS, AND REVIEWERS
The National Center for Environmental Assessment (NCEA) within U.S. Environmental
Protection Agency's (EPA's) Office of Research and Development was responsible for preparing
of this document. The draft report and much of the analytical work was prepared under Purchase
Orders Nos. 8W-1421-NASA, OW-0399-NASA and 1W-0903-NALX with Tetra Tech, Inc.,
Owings Mills, MD, and reviewed through Purchase Order No. 68-C-99-238 with Versar, Inc.,
Springfield, VA. Some toxicity testing used for the analysis was performed under Inter-Agency
Agreement #DW14937951-01-2 between EPA and the U.S. Fish and Wildlife Service.
Workgroup Co-Chairs:
Roberta Hylton, U.S. Fish and Wildlife Service, Southwestern Virginia Field Office,
Abingdon, VA
Don Gowan, Clinch Valley Program, The Nature Conservancy, Abingdon, VA
Authors:
Jerome Diamond, Tetra Tech, Inc., Owings Mills, MD
Vic Serveiss, U.S. EPA, NCEA, Washington, DC
Don Gowan, Clinch Valley Program, The Nature Conservancy, Abingdon, VA
Roberta Hylton, U.S. Fish and Wildlife Service, Southwestern Virginia Field Office,
Abingdon, VA
Contributors:
Molly Whitworth1, U.S. EPA, Office of Water, Washington, DC
Richard Carpenter, consultant, Charlottesville, VA
Dennis Yankee, Tennessee Valley Authority, Norris, TN
Steven Ahlstedt1, U.S. Geological Survey, Norris, TN
Other Workgroup Members:
David Hubbard, Virginia Cave Board, Charlottesville, VA
William Kittrell1, Clinch Valley Program, The Nature Conservancy, Abingdon, VA
John Miller, U.S. EPA, Office of Water, currently Office of Science Policy, Washington, DC
Deborah Mills, Virginia Department of Conservation and Recreation, Richmond, VA
'Served previously as co-chair of the assessment.
xvi
-------
Ron Preston, U.S. EPA, Region III, Wheeling, WV
Peggy Shute, Tennessee Valley Authority, Norris, TN
Reviewers:
Agency Reviewers:
Bill Ewald, NCEA, Research Triangle Park, NC
James Andreassen, NCEA, Washhigton, DC
Patricia Cirone, Region X, Seattle, WA
David Bussard, NCEA, Washington, DC
Jeffrey Frithsen, NCEA, Washington, DC
Other Reviewers:
Peter DeFur, Virghiia Commonwealth University, Richmond, VA
Kent W. Thornton, FTN Associates, Little Rock, AR
Mark Southerland, Versar, Inc., Columbia, MD
The authors wish to acknowledge the efforts of the following people: Suzanne Marcy of
NCEA for starting the assessment, John Miller of the Office of Water for managing the group
through problem formulation, Dennis Yankee of the Tennessee Valley Authority and Jeffrey
White of Tetra Tech, Inc., for helping with the'GIS analysis, and Forest Rich of the Tennessee
Valley Authority for facilitating some of the meetings. The authors also wish to acknowledge the
efforts of Terri Konoza of NCEA for managing the document production activities, Patricia von
Brook of the KBM Group for editing support, and Kate Stinson and Heidi Volf of the KBM
Group for word processing support. Since none of the four authors were leaders when the
assessment started, we especially wish to thank those listed as contributors and other workgroup
members for providing us with the necessary continuity.
xvii
-------
-------
1. EXECUTIVE SUMMARY
The Clinch and Powell Valley watershed assessment provides documentation to confirm
suspicions of resource managers that mining, urbanization, and agricultural activities were
adversely impacting native fish and mussels. Resource managers can now make more informed
decisions when selecting actions to protect ecological resources. Analyses showed, for instance,
that 55% of the variability in the fish community could be explained by land use, with minhig
and urban land uses as the most influential factors.
The document has three purposes: (1) to provide information to Federal, State, and local
organizations to help them make more informed decisions on how to protect the valued
ecological resources of the watersheds of the Clinch and Powell rivers, (2) to provide a repository
of literature and analytical efforts for future research in the watershed, and (3) to provide an
example for other watershed and regional assessors seeking to increase the use of environmental
monitoring and assessment data in decision making.
Ecological risk assessment is a process for collecting, organizing, and presenting
scientific information to make it more useful for decision making. The process is a unique form
of ecological assessment and includes the term "risk" because it presumes that a cause and effect
relationship exists and that the relationship can be expressed as a stressor-response curve. The
executive summary and the report itself are organized hi part according to the ecological risk
assessment process, which consists of planning, problem formulation, risk analysis, risk
characterization, and risk communication.
The Clinch and Powell rivers originate in the mountainous terrain of southwestern
Virginia and extend into northeastern Tennessee, flowing into the upper reaches of the Tennessee
River. The watershed covers 9,971 km2 and historically has contained one of the most diverse
fish and mussel assemblages in North America. Most of these populations have declined
dramatically or been eliminated.
For this risk assessment, an interdisciplinary, interagency workgroup of scientists and
resource managers was established. The U.S. Fish and Wildlife Service (FWS), the Tennessee
Valley Authority (TVA), The Nature Conservancy (TNC), the Virginia Department of Game and
Inland Fisheries, the Virginia Cave Board, the Virginia Department of Conservation and
Recreation, the U.S. Environmental Protection Agency (EPA), and the U.S. Geological Survey
(USGS) were represented. The workgroup was co-chaired at various tunes by representatives of
TNC, EPA, USGS, and FWS.
The workgroup developed a management goal and selected assessment endpoints to
analyze the optimal suite of data to be useful for decision making. The management goal was to:
1-1
-------
Establish and maintain the biological integrity of the Clinch and Powell watershed surface and
subsurface aquatic ecosystem.
The workgroup recognized that the valued ecological resources of concern were the
diversity and abundance of native aquatic macroinvertebrates (especially mussels), fish, and cave
fauna. As data on cave fauna were lacking, two assessment endpoints were selected: (1)
reproduction and recruitment of threatened, endangered, or rare native freshwater mussels and (2)
reproduction and recruitment of native, threatened, endangered, or rare fish species. The
assessment endpoints were selected on the basis of their relevance to the management goal, then-
susceptibility to stressors, and their ecological importance. The workgroup acknowledged that
the two assessment endpoints are linked, because most native mussels require a fish host in part
of their life cycle. Because data on mussel species were limited in this assessment, data on an
appropriate surrogate indicator, the fish Index of Biotic Integrity (IBI) (a series of measures of the
fish species present at a sampling site that collectively describe the quality of the fish
community) was used.
The workgroup agreed to focus the assessment on the unimpounded stream segment
above Norris Lake, as only that portion of the watershed provides suitable habitat for the fish and
mussel species of concern. The assessment analyzed data previously collected by the TVA's
Clinch Powell River Action Team Survey (CPRATS) and Cumberlandian Mollusc Conservation
Program (CMCP).
Conceptual models were developed by the workgroup to show the pathways between
sources, stressors, and direct and indirect ecological effects. The models also helped identify and
select the most important pathways for analysis, relationships between assessment endpoints and
sources of uncertainty. The model was later redrawn on the basis of new information, and this
helped define and prioritize subsequent analyses.
The analysis plan for this risk assessment was developed from the conceptual model and
existing concerns or risk hypotheses. It was surmised that agricultural land use would correlate
with various habitat measures, such as sedimentation. It was also surmised that the habitat
measures would correspond to biological measures representative of the assessment endpoints. It
was also believed that impacts from mining and urbanization would have some impact on habitat
quality and, in turn, on biological data. Episodic spills were also thought to have impacted the
valued biota but that this would be difficult to prove quantitatively because water quality data for
the period shortly after spill occurrences were not available. However, qualitative data that were
based on other published literature are incorporated into the conclusions. It is well established
that riparian (stream-side forested) buffers help mitigate adverse impacts from human activities;
however, for this mountainous region, it was unknown how wide and continuous these buffers
would need to be to provide benefits. Knowing the association between larger buffers and
1-2
-------
expected improvements to aquatic fauna helps managers decide whether and to what degree to
maintain a vegetated stream buffer, because they must weigh the costs of restoring riparian
buffers against the benefits provided.
Forward stepwise multiple regression analyses and/or univariate statistical analyses of
data within a geographical information system (GIS) were used to test hypotheses and the
strength of stressor-response relationships hi order to characterize the risk to valued ecological
resources (assessment endpoints). GIS maps were produced to help examine risk hypotheses.
Biological measures were used to characterize fish, mussel, and macroinvertebrate data.
For fish, the fish IBI, was used. Mussel data were measured by species richness (number of
different species) and abundance (the number of mussels present). Macroinvertebrate data were
measured by the number of taxonomic families of Ephemoptera (mayfly), Plecoptera (stonefiy),
and Trichoptera (caddisfly) (EPT) present at a site. These three orders of macroinvertebrate are
known to be sensitive to adverse water quality and are replaced by other macroinvertebrates as
water quality diminishes. Several habitat-quality measures, including bottom sediment
characteristics, bank stability, riparian vegetation integrity, and channel morphology, were also
used to characterize habitat-related stressor exposure.
A pilot study was used to test the proposed analytical approach using a single
subwatershed. Subwatershed analysis was considered a useful analytical approach because
different subwatersheds in the Clinch and Powell basin had a different complement of human
activities and, therefore, stressors present. Copper Creek was chosen for this pilot analysis
because it was the most data-rich subwatershed and because it was a relatively simpler case in
that agricultural uses were the only source of anthropogenic activity. In the pilot study, two
analytical objectives central to this assessment were tested, refined, and found to be useful: (1)
the appropriate spatial scale to test relationships between land-use activities or stressors and
measures of effect was generally determined and (2) the fish IBI was found to be a reliable
surrogate measure of effect for predicting the status of native mussel assemblages. Achieving the
latter objective was especially desirable, because it was known at the outset of this study that
available native mussel data were more limited than either EPT or IBI values.
Besides helping to confirm and refine the methods for performing the watershed
assessment, results from the pilot study of Copper Creek provided documentation to confirm
suspected beliefs. The results listed below indicate that, in this subwatershed, riparian corridors
need to be'protected with natural vegetation (preferably forest) and that effects of human
activities can be dramatic and far-reaching downstream.
• Instream habitat quality and biological integrity were affected more by agricultural
land uses very close to the stream than by agricultural land uses further away (upland),
1-3
-------
• Impacts on native fish and mussels from agricultural land use were distinguishable for
up to one mile downstream,
• Fish community integrity reflected impacts on native mussel species,
• Biological measures were found to be more strongly related to land use than to habitat
measures, and
• A riparian corridor zone 200 meters across (100 m to either side of the stream) and
extending 500 to 1500 meters upstream is the optimal spatial area to work with when
analyzing land-use effects on fish and mussels.
The most successful analytical approaches in the Copper Creek pilot study were applied
to the entire watershed. Because other parts of the watershed are subjected to stressors from the
coal industry and urbanization, the riparian land cover analyses were expanded to include -
• Location of different types of mining activities;
• Location of biota relative to urban/industrial areas;
• The percentage of riparian and upland land use that was forest, pasture, cropland, or
urban; and
• Location of three classes of roads, including major U..S. highways, State roads, and
county roads.
Several types of analyses were performed, and some were found to be more useful than
others. All of the analyses are presented in the report to illustrate the efforts a workgroup may
wish to undertake in performing such an assessment. A summary of major findings from the
various analyses is provided below.
Effects of land use on habitat quality. Forty-two percent of the variability in habitat
quality measures could be explained by upstream land uses within the riparian corridor at a. given
site. Stream sedimentation was lower where cropland was > 3% of total land use. Riparian
integrity was better in areas in which pasture or herbaceous land was < 50% of the total land use.
Instream cover was poor if urban use was > 20% of the surrounding area upstream. Instream
cover and the degree to which the rocks in the stream were surrounded by particulate matter
1-4
-------
(embeddedness) were affected by both the percent pasture herbaceous cover as well as the
percent of urban area nearby.
Relationships between land use and biological measures of effect. Together, riparian land
uses accounted for 55% of the variability in IBI scores among sites with proximity to mining as
the most influential factor. Percent pasture area was directly related to the IBI, whereas
proximity to mining and percent urban land were inversely related. The apparently positive
effect of pasture land on the fish IBI was unexpected because of the negative relationship
between pasture area and riparian integrity. This occurred because mining sites were typically
near forested areas; therefore, in this analysis, higher fish IBI scores were associated with areas
that had less forested cover and more agricultural land. The number of native mussel species was
related to several land uses, including (hi order of significance) percent urban area, proximity to
mining, and percent cropland. However, only about half as much variation in mussel species
richness could be explained by land use (26% vs. 55% for the fish IBI).
Relationships between habitat quality and biological measures of effect. Less of the
variance in the IBI (29%) could be explained by available habitat quality data, as compared to
land use. Embeddedness (or the inverse, clean sediment) and instream cover were most clearly
related to the fish IBI, particularly if the IBI was categorized as either poor or good, based on
TVA's criteria. Sites with either high substrate embeddedness scores or low instream cover
scores had greater than a 90% chance of having poor fish community integrity.
Cumulative stressor index for each site. A cumulative stressor index for each site was
developed on the basis of how many significant sources of stress were within 2 kilometers of the
site. The four stressors were proximity to mining activities, proximity to urban areas, proximity
to major transportation corridors, and percentage of cropland area in the upstream riparian zone.
The fish IBI was inversely related to the cumulative number of stressors present and was
consistently poor or very poor (TVA rating) at sites where all four stressors were present.
Approximately 66% of the sites that had two of the four stressors present had low IBI scores,
indicating poor .fish community integrity at those sites, according to TVA. In nearly all of these
cases (88%), the stressors present were proximity to urban areas and mining. Similar results
were found for the maximum number of mussel species present at a site. Sites that had two or
more stressors had greater than a 90% probability of having fewer than two mussel species
present. Sites with one or no sources of stress had between 4 and 18 species, which is still far
less than the number historically reported.
Riparian corridor dimension analysis. Analyses of mussel data from Tazewell County
indicate that riparian land uses can have varying effects on biota, depending on landscape factors
such as slope, elevation, and stream size. Results of the analyses support the riparian corridor
dimensions used in the assessment. Riparian corridor zones (5-10 km) may be required to
1-5
-------
preserve or restore mussel communities in small, high-slope streams; shorter zones (1-2 km) of
riparian protection may be adequate in larger, lower-gradient streams.
Biota in Copper Creek are adversely impacted by agricultural activities; there are no
mining or substantial urban activities in this subwatershed. The data for the Clinch and Powell
watershed as a whole indicate that mining activities, followed by urbanization, are causing the
greatest adverse impacts on fish and mussel species. Because mining was such a big factor, we
investigated the adverse effects caused by different types of mines. Coal processing plants
appeared to have the greatest effect on fish communities, as compared with other types of mining
or other land-use activities. Thus, stressor impacts appear to be related more to water
contamination than to physical habitat effects. Similar effects were documented for mussels and
other invertebrates.
More stressors were observed to co-occur as we progressed upstream in this watershed,
due to greater coal mining activity and associated transportation corridors and urban centers in
headwater areas, particularly in the Powell River portion of the basin. Episodic chemical or coal
slurry spills, although low in frequency and duration in this watershed, have undoubtedly had a
significant impact on mussel and native fish species abundance and distribution. Many of these
spills have also occurred in headwater areas of the watershed. Therefore, tributary and headwater
populations, which were historically some of the richest faunal locations in the watershed, are
most at risk from extirpation because native species migration and recruitment could be more
difficult.
Several lines of evidence point to the importance of various land-use activities and
riparian corridor integrity as determinants of native mussel and fish distribution in the Clinch and
Powell River basin. Key factors appear to be sedimentation and other forms of habitat
degradation from urban and agricultural areas as well as toxics from coal mining operations and
urban areas. Riparian areas with more forested land cover and less cropland, urban, or mining
activity tended to be associated with less sedimentation, more instream cover for aquatic fauna,
less substrate embeddedness, and higher fish and native mussel species richness. Our results
suggest that if agricultural or urban use upstream is great enough within the riparian zone,
sedimentation effects and subsequent loss of habitat will ensue for some distance downstream
(1-2 km).
Although riparian vegetation can reduce deleterious land-use effects on water quality, it is
not clear that improvement of the riparian corridor alone in this watershed will necessarily result
in recovery of native mussel and fish populations. Little or no recovery of threatened or
endangered mussel or fish species has been observed in this basin despite improved water
quality.
1-6
-------
Results of the risk assessment suggest that the risk of extirpation of native species is
likely to increase as more sources of potential stress co-occur. Previous analyses have indicated
that none of the present mussel concentration sites (i.e., kndwn sites containing relatively large
numbers and kinds of native mussels) are located where coal mining activity is present, and only
about half of the mussel sites appear to be reasonably isolated from major roads, urban areas,
mines, and agricultural areas. This information suggests that native mussel populations are
relatively vulnerable to likely sources of stress in this watershed and that further extinctions or
extirpations are probable unless additional resource protection measures are taken.
Native fish and mussels are at high risk because of habitat fragmentation, which results hi
populations that are too inbred, small in size, and more susceptible to stressors. Populations are
now more widely separated than they were historically, which could lead to reduced recruitment
success and declining populations, especially in the presence of stressors. Therefore, it may be
most tiseful to further protect those populations that appear vulnerable due to proximity to
mining, urban areas, or transportation corridors. Protection and/or enhancement of the riparian
corridor at these sites, as well as protection from toxic spills and discharges, is probably as
important in terms of sustaining native species as stocking new or historically important areas. If
stream habitat as well as water quality can be maintained or improved, present mussel and fish
populations might be able to expand into nearby areas, thus increasing the distribution and
abundance of these species.
Several uncertainties precluded our ability to describe stronger associations between
causes and effects. First and foremost, although there was a lot of biological information
available in the Clinch watershed to work with, it was not very often associated in time and place
with relevant instream chemical or habitat measurements. Because data support the adverse
impacts of spills on mussels, and to a lesser degree fish, the lack of water chemistry data,
especially during spill events, posed problems when attempting to draw associations between
biological condition and known or potential stressors. Second, physical habitat assessment data
were fairly qualitative and relatively infrequent. Third, the macroinvertebrate measure EPT was
associated with a moderate degree of uncertainty, perhaps because family-level taxonomy was
used, resulting in a relatively narrow-ranging index throughout the watershed. Fourth, the
potential relationship between fish IBI and. mussel species richness or abundance observed in the
Copper Creek subwatershed could be explained in more detail than was possible in this risk
assessment. The IBI is composed of a number of metrics, one of which is native species
.richness. We were unable to obtain individual IBI metric values for all sites, though these data do
exist. With additional effort, these data could be obtained and compared with available mussel
data.
1-7
-------
The risk assessment has helped lend further credence to what many resource managers
have long conjectured were problems within the watershed, thereby providing more scientific
support for taking actions to address problems. Based on the assessment findings, conservation
agencies and organizations are considering riparian buffer protection; spill prevention devices
along transportation corridors near streams and restriction of the type of materials transported
over certain bridges; limited access of livestock to streams; better monitoring and control of mine
discharges to streams; maintenance of existing natural vegetation; best management practices
(BMPs) for pasture and agricultural land to reduce sediment loading; and better treatment of
wastewater discharges.
During the assessment, information from several different sources was compiled and
organized into a usable data set. The data set will be useful to FWS, TNC, and others as they
strive to develop plans and make decisions regarding actions to further the recovery of
endangered and rare species. It will also benefit other environmental agencies and organizations
because they can more easily add to and use the data to further assess problems for other
decision-making purposes.
The analyses also provided suggestions for future data collection to make the data more
useful in decision making. For macroinvertebrates, resource managers should consider using
lower-level taxonomy (genus or preferably species) and developing a suite of sensitive reliable
metrics that are demonstrated to respond to human activities. In addition, as only eight sites in
the entire watershed had mussel and IBI or EPT data, taking samples of all fauna at each site
(along with more robust habitat assessment measures) would reduce uncertainty in observed
biological effects.
1-8
-------
2. BACKGROUND
2.1. WATERSHED DESCRIPTION
The Clinch and Powell rivers originate in mountainous terrain of southwestern Virginia
and extend into northeastern Tennessee, flowing into the upper reaches of the Tennessee River
(Figure 2-1). They collectively cover 9,971 km2. The Clinch and Powell watershed historically
has contained one of the most diverse fish and mussel assemblages in North America (Neves,
1991), yet most of these populations have declined dramatically or been eliminated (Neves et al.,
1985). The mainstem Tennessee River and many of its tributaries have been dammed, resulting
in the loss of habitat for many fish and mussel species (Yeager, 1994). However, the upper
regions of the Clinch and Powell rivers represent some of the last free-flowing sections of the
expansive Tennessee River system. Currently, the Clinch and Powell river basin supports more
threatened and endangered aquatic species than almost any other basin in North America (Stein
et al., 2000). Despite the implementation of recovery plans for most of the federally protected
species in this basin, there is evidence that these species are either declining or becoming extinct
at an alarming rate due to impacts from mining, agriculture, urbanization, and other stressors
(Jones et al., 2000).
The upper regions of the Clinch and Powell rivers drain approximately 7,542 and 2,429
km2 (2,912 and 938 sq. mi.), respectively, and vary in elevation between 300 and 750 m. Both
rivers flow southwesterly through parallel valleys and are contained within the Cumberland
(Appalachian) Plateau and the Valley and Ridge physiographic provinces (UCS, 1992) (Figure 2-
1). These two subwatersheds are characterized by steep slopes and poor riparian forest cover,
suggesting relatively high vulnerability of aquatic species to anthropogenic stressors. The
climate of the Clinch and Powell watershed is moderate, with an average temperature of 12.0 °C.
Precipitation varies across the region, from 96.5 to 127 cm. Wide variability in both
precipitation and soil types at the local level is common throughout the region and leads to a high
degree of plant diversity. The watershed is composed largely of forest and agricultural land,
although there are several small urban/industrial areas scattered throughout the basin (see section
2.2).
The Clinch River begins in Tazewell County, VA, and flows for approximately 32.1.9 km
(200 miles) before reaching Norris Lake.. The majority of the Clinch drains the Valley and Ridge
province, although several of the river's western tributaries drain the Cumberland Plateau. The
geology of the Clinch River basin is characterized by large expanses of limestone and dolomite,
resulting in large areas of karst topography (a limestone region characterized by caves and
underground channels). Daily average flow data—the average volume of water that flows past a
2-1
-------
LLJ
w
00
-------
given point for 1 second—show that the Clinch River in Virginia ranges from 5.38 mVsec at
Richlands, near the headwaters, to 45.1 nrVsec at Clinchport. The 7-consecutive-day low flow
on average in a 10-year period (7Q10) is 0.44 and 2.82 mVs for Richlands and Clinchport,
respectively.
The Powell River, a tributary to the Clinch River, begins in Wise County, VA, flows
approximately 193.1 km (120 miles), and enters Norris Lake. The headwaters of the Powell,
including the mainstem and tributaries, primarily drain the Cumberland Plateau. As the Powell
leaves the Cumberland Plateau, it enters the Valley and Ridge province, which is characterized
by extensive parallel ridges with valleys of varying size. Extensive subsurface drainage is
common, with broad areas of karst dotted with caves, sinkholes, and sinking streams. Major
tributaries to the Powell include the South and North Fork Powell rivers. Flow in the Powell
River in Virginia ranges from 3.68 nrVsec on the North Fork Powell near Pennington Gap to
15.21 mVsec at Jonesville, with 7Q10 values of 0.03 and 0.69 m3/sec, respectively.
Because of the mountainous terrain, the watershed maintains a rural character, with a
population of approximately 170,000 (1990 census) in Lee, Scott, Wise, Russell, andTazewell
Counties making up the Virginia portion of the watershed. The urban areas in the watershed
include Wise, Norton, Pennington Gap, Rose Hill, and Big Stone Gap in the Powell River
subwatershed and Tazewell, Rocklands, Cleveland, and St. Paul in the Clinch River
subwatershed.
Untouched by either glaciation or rising seas in recent geologic time, and isolated from
other nearby river systems, the assemblage of fish and freshwater mussel species in the upper
Clinch and Powell rivers is among the most diverse in North America (Ortmann, 1918; Ahlstedt,
1991). The decline of these native species is accentuated by the fact that native mussels evolved
to depend on fish. Unionids (mussels) are sedentary filter-feeding macroinvertebrates that
burrow into a gravel/cobble substrate and remove unicellular algae, zooplankton, detritus, and
silt from the water column (Neves, 1991). They have a unique life cycle that includes an obligate
parasitic larval stage, or glochidia, that must attach onto the fins, epidermis, or gills of a suitable
host fish (Bogan and Parmalee, 1983) (Figure 2-2). The host fish is apparently unaffected by
glochidia parasitization; however, some mussel species can parasitize only certain fish species
(Zale and Neves, 1982a, b). Large numbers of glochidia are released: 100,000-3.5 million either
in spring or midsummer, corresponding not only with the migration and spawning activities of
many resident fish species, but also with relatively low stream flow and potentially high
concentrations of toxic chemicals (Zale and Neves, 1982a, b; Kitchel, 1985). The relatively low
occurrence of glochidia on host fish indicates that most do not reach this point in the life cycle.
The codependence of native mussels on native fish species is believed to have evolved
over millions of years, suggesting that glochidial infestation success rate, though small, is
2-3
-------
Figure 2-2. Many endemic mussel species in the Cinch and Powell watershed have
evolved sophisticated anatomical structures to attract the appropriate fish host. The correct
fish host is needed to complete the mussel's life cprle and enhance species dispersal.
adequate to ensure the dispersal of mussel populations. Following the 1- to 3-week parasitic
phase, the glochidia drop to the substrate and begin feir sedentary free-living phase. Owing to
the fact that they are sedentary and that they have a complex life cycle, unionid mussels cannot
readily migrate or recolonize new stream areas, except during the larval parasitic stage. The
potential results are geographically isolated populations, genetic inbreeding, and reduced
adaptive potential (Stansbery et al., 1986; Ahlstedt, 1»1). Clearly, the survival of unionids is
dependent, in part, on the reproductive success and distributional range of the appropriate host
fish species (Zale and Neves, 1982b; Young and Willams, 1983; Neves et al., 1985; Waiters,
1997).
Previous assessments of Virginia's aquatic brataindicate that the Clinch and Powell
watershed supports more imperiled mussel and fish species than most streams in North America
(Neves, 1991; Jenkins and Burkhead, 1994; Stein et al., 2000). Recent assessments have
reported continued declines and possibly extirpations of native species in several areas of the
watershed (Ahlstedt, 1999; Jones et al., 2000).
Although recovery plans have been developed! for most federally protected species in the
Clinch and Powell rivers, evidence of recovery is lacMig (Sheehan et al., 1989; Jones et al,
2000). Fish and mussel surveys by biologists in Virginia and Tennessee indicate that most rare
2-4
-------
species in this region continue to decline (Angermeier and Smogor, 1993; Ahlstedt, 1999). This
degree of loss is unprecedented among other wide-ranging faunal groups in North America
(Neves, 1991). Thus, the Clinch and Powell watershed, one of the few remaining refugia for
these fauna, has national significance. Reversing the decline or loss of these rich faunal groups is
a test of our commitment to preserving biodiversity on a national scale.
Given (1) its importance as a center of aquatic biodiversity; (2) the profound, diverse, and
yet unqualified effects of human activities; (3) the relatively large amount of existing biological
and land use data; and (4) the ongoing efforts of TNC, FWS, and other organizations, the Clinch
and Powell watershed was selected by EPA as one of several national watershed ecological risk
assessment case studies.
The intent of this project was to (1) collect, organize, analyze, and present available
ecological information to assist resource managers in the Clinch and Powell watershed to
improve their decision making; (2) increase the likelihood that available (and often limited)
environmental monitoring and assessment data will be used appropriately in decision making;
and (3) serve as an example for others seeking to integrate ecological risk assessment with a
watershed or place-based approach.
2.2. LAND USES IN THE WATERSHED
The economy is driven primarily by coal mining and agriculture. More than 40% of
Virginia's coal production lies within the five counties in the basin, where the Cumberland
Plateau is composed of Pennsylvanian sandstone and shale; the remaining 60% is in adjacent
Buchanan and Dickenson counties. Coal production increased from 1980 to 1988. The region's
coal supply is estimated to last for another 25 to 50 years. There are 287 active point-source
discharges from coal processing plants and mine sites, and only a few potentially toxic chemical
contaminants in these discharges are regulated. The upper Clinch River in the vicinity of Swords
Creek, the Guest River, and the upper Powell River upstream from Pennington Gap have been
heavily impacted by sediment, coal fines (fine paniculate coal and refuse rock material), and
acidic runoff from mining activities.
Most of the watershed was intensively logged to clear land for agricultural production in
the late 18th and early 19th centuries. Another logging boom flourished in the late 19th century
into the early 20th century, spurred by national industrial growth as well as salvage harvest of the
American chestnut, which was killed by the disease caused by the fungus Endothiaparasitica.
The logging and forest industry in general declined through the 20th century, although there has
been some production of mine timber supports for the mining industry. Quality hardwood,
timber, and pulp were still exported from the region, but the 1980s and 1990s saw a resurgence
of the forest industry. In the mid-1980s and early 1990s, an oriented strand board plant was
2-5
-------
active in Dungannon, VA. Several large forest industries have recently been established in
Dickenson County, VA, and in nearby West Virginia and Tennessee. Many former miners or
support workers to the mining industry have entered the forests of southwest Virginia to provide
logs to these new forest industries. Although growth of this industry is helping to meet the
economic challenges of the decrease in the mining sector, logging in some areas, without proper
use of best management practices (BMPs), can pose a threat to sensitive aquatic resources.
Agriculture is the other chief economic activity in the Clinch and Powell watershed,
accounting for approximately one-third of its land use. Beef cattle and Burley tobacco are the
primary agricultural products (UCS, 1992). Topographic constraints limit most of these
agricultural activities to the floodplain, where livestock and row crop production are most
feasible and productive. Pesticide runoff, runoff from overgrazed pastures on steep slopes,
animal waste from feedlots, and livestock access to streams and riparian corridors threaten water
quality and ecosystem integrity in the watershed. Aquatic and subterranean ecosystems are
especially vulnerable as a result of increased sediment loading, nutrient enrichment, and
pathogens.
Although the region is currently exhibiting slow economic growth, urban development is
planned in either karst terrain or the floodplain, both of which are sensitive to alteration. For
example, an airport is planned in the Central Lee County karst, perhaps Virginia's most
biologically significant karst area. Despite existing stressors, the region's environmental
resources provide recreational opportunities (Figure 2-3).
Figure 2-3. The swiftly flowing waters of the Clinch River
provide a source of recreation for outdoor enthusiasts.
2-6
-------
3. PLANNING AND PROBLEM FORMULATION
In this watershed, as in any other, the optimal suite of data is not available, and yet
managers must make decisions on the basis of existing information. The purpose of risk
assessment is to analyze available scientific information and present it in a manner that enables
more informed decision making on how to protect the unique biological resources of the Clinch
and Powell watershed. Before starting the risk assessment, some planning is required. During
planning, the managers define the management goals for the watershed (U.S. EPA, 1998). Then,
managers, in consultation with the scientists performing the assessment, reach agreement on the
purpose, scope, and complexity of the risk assessment. The risk assessment begins with problem
formulation, during which risk hypotheses, conceptual models, and a plan for risk analyses are
developed (U.S. EPA, 1998) (Figure 3-1). Next, the analysis phase evaluates the exposure of
valued ecological resources to stressors and the relationships between stressor levels and
ecological effects. During risk characterization, exposure and effects data are integrated to
describe risks and draw conclusions (U.S. EPA, 1998). In this risk assessment, the workgroup
met periodically to share interim findings and refocus remaining analyses. Thus, risk was
characterized and presented several times, and progressively in more detail each time.
Furthermore, the workgroup directly participated in guiding risk analyses as well as risk
characterization in this assessment.
3.1. MANAGEMENT GOALS AND RISK ASSESSMENT OBJECTIVES
Federal, State, and local managers have been working with scientists to study the extent
of water quality alteration in the watershed. The Tennessee Division of Water Pollution Control
conducts frequent water chemistry and benthic community surveys in both the Clinch and Powell
rivers inside Tennessee near Norris Lake. The Virginia Department of Game and Fisheries, the
Virginia Cooperative Fish and Wildlife Research Unit, the Tennessee Wildlife Resources
Agency, and TNC are also conducting studies of water chemistry, mussels, fish, and riparian
vegetation in the Clinch and Powell watershed. The Virginia agencies listed above and FWS are
responsible for protecting endangered species in the area. These agencies also have been
working to educate stakeholders about the unique aquatic and other natural resources and about
efforts to protect them. In addition, TNC has established the Clinch Valley Program to conserve
diversity in the Clinch and Powell and Holston River watersheds while meeting human and
economic needs.
A tremendous amount of information has been collected in this watershed over many
years, but much of it has not been analyzed. Monitoring data have been collected by TNC, TVA,
FWS , USGS, the Virginia Department of Game and Inland Fisheries, and the Virginia
3-1
-------
Planning
(Risk Assessor/
Risk Manager/*
Interested Parties
Dialogue)
Communicating Results
to the Risk Manager
1
Risk Management and
Communicating Results to
interested Parties;
>
Ecological Risk Assessment
PROBLEM FORMULATION :
••'•' *' < <> ;> f'< \- ^y/1.;-;
1 <• * • ' .{
* » s/%
w '*
2 Characterizatioii Chaiisc^rlzafioit
-* of ! Bcol 1 ''- ": '
2% exposure irfftw^tt * ' ^
^ n n ''o '-
V ^ *
~- *** •" / / /
J L '~ '• j L " * x"
" ' S"# ^ v *.
RISK CHARACTERIZATION
«l-
^-
Z
0
O
O
0)
0)
fi)
(0 fi)
£ iT
sr-i
O
•o
o
o
0)
w
Figure 3-1. Framework for ecological risk assessment.
Source: U.S. EPA, 1998
3-2
-------
Department of Conservation and Recreation. Although several hypotheses have been advanced
to explain the decline in native mussel and fish species in other watersheds (Walters, 1996),
•% & ft % '
definitive answers have been lacking. There were suspicions that many of the problems were due
to agricultural, mining, and urban influences as well as episodic spills. A number of studies had
been performed by scientists for various purposes, but no one had performed a compilation and
analysis of the existing data using sophisticated tools such as GISs and mulitvariate analysis.
Furthermore, no effort had ever been undertaken to bring many of the resource managers in the
area together to help determine which analyses of pre-existing data would be most useful to
improve decision making. Resource managers in the Clinch and Powell river basin recognized
that a comprehensive examination of the available data was needed to evaluate the relative
effects of different human activities on native mussels and fish.
The workgroup charged with designing the risk assessment for the Clinch Valley was
convened at a meeting in Dungannon, VA, in 1993. The Clinch and Powell watershed ecological
risk assessment workgroup has been co-chaired since 1993 by members from TNC, FWS, USGS,
and EPA. (See Acknowledgments for list of workgroup members and co-chairs and Appendix A
for a list of stakeholders.) At the 1993 meeting, workgroup members and other stakeholders
characterized the ecological resources present in the watershed and potential problems affecting
those resources. The workgroup then developed an initial description of the risks from an earlier
draft document and decisions were made regarding the scope of the assessment.
TNC conducted a random telephone poll to assess the level of awareness and concerns of
people in southwest Virginia. The results indicated an interest in conserving the water resources
of the region and a strong sense of pride in the natural beauty of the area. Currently, the Upper
Tennessee River Roundtable holds public meetings to gather information to help develop a
strategic plan for the watershed. These meetings reaffirm the concerns previously voiced by
stakeholders in the 1993 meeting and the TNC survey.
Figure 2-1 shows the hydrologic drainage of the Upper Tennessee River Basin and the
watershed boundary for the upper Clinch and Powell rivers. Because there is a significant
reduction in aquatic species diversity caused by impoundments downstream of Norris Lake
(Masnik, 1974; Ahlstedt, 1984; Angermeier and Smogor, 1993), the free-flowing portion of the
watershed was recognized as the best remaining habitat for native mussels and fish in this region
and, therefore, the area most in need of better information and protection. Consequently, the
workgroup decided to assess only the segment of the watershed upstream of Norris Lake. An
overall management goal for the assessment was developed by the workgroup so that the results
would be relevant to regulatory requirements and public concerns. The assessment was also
designed to ensure that assumptions, methods, and conclusions would be scientifically valid and
documented. The broad management goal was to:
3-3
-------
Establish and maintain the biological integrity of the Clinch and Powell watershed
surface and subsurface aquatic ecosystems.
This goal reflected the intent to establish sustainable native populations of flora and fauna
for the riverine, riparian, and karst ecological communities. The workgroup determined that if
biological integrity could be maintained, then water quality—the chief public concern—would
also be protected. Workgroup members identified the watershed's three outstanding ecological
resources:
1. The diversity and abundance of threatened, endangered, or rare native freshwater
mussels.
2. The diversity and abundance of native, threatened, endangered, or rare fish species.
3. The diversity and abundance of cave fauna.
To attain the goal of biological integrity, this ecological risk assessment addressed the first two of
these resources. The potential risks to terrestrial and aquatic communities in caves were not
evaluated because little information on the distribution and abundance of these fauna were
available. Section 3.1.2 discusses how stressors are believed to impact the abundance, diversity,
and age class structure of cave fauna.
The workgroup agreed to consider implementing several management objectives to
maintain or restore the threatened, endangered, or rare native freshwater mussels and fish in the
Clinch and Powell watershed, pending the results of this assessment. Some management actions
under consideration prior to this risk assessment were:
• Implementing BMPs, such as minimum till and treatment of feedlot waste, to reduce
nonpoint-source pollution.
• Containing and treating runoff from mining activities to reduce pollutant load and
sedimentation.
• Installing or improving sewage treatment facilities to reduce inputs of pollutants and
nutrients.
-------
3.1.1. Assessment Endpoints
In a watershed ecological risk assessment, the broad management goal often needs to be
explicitly defined so that it provides a clear focus for the assessment. An important part of
problem formulation involves the selection of ecologically based assessment endpoints that
provide a link between measurable endpoints and the steps necessary to achieve the management
goal (U.S. EPA, 1998). Specifically, risk assessors need to determine the ecological resources of
concern in the watershed; in this case protecting threatened, endangered, and rare native mussel
and fish species.
For each of the ecological resources of concern, assessors need to define a specific
characteristic of interest (e.g., mussel species abundance and diversity). The combination of
valued resource and ecologically relevant characteristic is called an assessment endpoint (U.S.
EPA, 1998). Assessment endpoints are selected on the basis of their relevance to management
objectives, susceptibility to stressors of concern, and ecological importance.
Even though this assessment focuses on fish and mussels, it is termed a watershed
assessment because activities within, and impacts from, the entire watershed are considered in
relation to the assessment endpoints. Furthermore, a better understanding of and further
protection of these native species are likely to confer protection on many other plant and animal
species in the watershed.
If data relating the assessment endpoint to human activities are not available, a surrogate
indicator called a "measure of effect" is used. In this assessment, data for the assessment
endpoint of mussel species diversity and abundance were limited. Therefore, data for an
appropriate surrogate measure, such as mussel species richness or the fish IBI was used. By
clearly defining the ultimate focus of the assessment (e.g., mussel species diversity and
abundance), the uncertainties in the assessment can be better described (e.g., extrapolating
between fish community integrity and mussel species richness).
3.1.1.1. Assessment Endpoint 1
Diversity and abundance of threatened, endangered, or rare native freshwater mussels.
3.1.1.1.1. Importance of endpoint. The Clinch and Powell watershed supports more of
Virginia's imperiled mussel species than any other basin in Virginia and most places in North
America (Ahlstedt, 1991) (Appendix B, Table B-l). Therefore, protection of threatened and
endangered mussel species' and their habitats has high ecological and societal value. Diversity
and abundance are the specified attributes because they provide an indication of a specie's ability
to maintain viable populations over time in a given region. These attributes support maintaining
self-sustaining native populations and the goal of maintaining biological diversity.
3-5
-------
Remnants of the unique mussel assemblage exist as fragmented populations and presently
occur only in a few streams in North America, including the Clinch and Powell watershed.
These drainages have the greatest number of federally listed endangered aquatic species (18) and
also one of the largest concentrations of endemic species (19) in the United States (Stein et al.,
2000) (Appendix B, Table B-l).
3.1.1.1.2. Risks to endpoint. Threatened and endangered mussel species are susceptible to a
range of anthropogenic disturbances as well as natural perturbations, including sedimentation,
toxic chemicals, prolonged drought, low stream current velocity, and loss of riparian corridor
integrity. Many of these species are particularly sensitive to these stressors during the glochidia
or larval stage. Threatened and endangered mussel species are excellent indicators of benthic
macroinvertebrate habitat quality and stream water quality in general (Bogan and Parmalee,
1983; Goudreau et al., 1993; Kitchel, 1995; Warren et al., 1995).
Mussels are susceptible to any land use or natural phenomenon that (1) ultimately reduces
host fish survival and reproduction, (2) degrades surface-water quality, (3) reduces or eliminates
usable benthic habitat, or (4) interferes with or undermines their normal filter-feeding process.
Thus, mussels are at risk from a variety of human activities in the watershed, including poor
agricultural practices; urban runoff; wastewater discharges; runoff from mining, poor forestry
practices, roads, and other transportation corridors; and possibly competition from the
introduction of exotic species such as the zebra mussel (Dreissena polymorpha) and Asiatic clam
(Corbiculafluminea).
Because available data on mussels were limited primarily to mussel species richness, this
measure was used as a surrogate for the assessment endpoint of diversity and abundance of
threatened, endangered, or rare native freshwater mussels. The direct relationship between
presence of a particular species and mussel assemblage characteristics such as diversity and
abundance is plausible because many studies have demonstrated direct correlations between
species richness and diversity or abundance of mussels (Dennis, 1985; Ahlstedt, 1991; Ahlstedt
and Tuberville, 1997).
3.1.1.2. Assessment Endpoint 2
Diversity and abundance of threatened, endangered, or rare native fish species.
3.1.1.2.1. Importance of endpoint. The Southeast has the highest diversity of freshwater fishes
in the United States (Etnier and Starnes, 1994). These obligate riverine fishes historically have
existed in relatively stable environments (Jenkins and Burkhead, 1994), but this has changed
rapidly over the past century. Some species are not able to withstand the physical and chemical
3-6
-------
alterations to their habitats that have occurred because of human activities in the watershed
(Yeager, 1994). As a result, local extirpations and extinctions have taken place. About 30% of
the federally listed endangered fish species and 40% of the species that are proposed candidates
for listing are located in the Southeast, indicating downward trends in the quality of southeastern
aquatic habitats. The free-flowing portions of the Clinch and Powell rivers upstream of Norris
Dam are major refugia for many fish species endemic to the Tennessee River drainage. Of the 85
fish species reported from these systems, about one-third are federally listed as endangered or
threatened, are candidates for listing, or are listed for protection by Tennessee or Virginia (Etnier
and Starnes, 1994) (Appendix B, Table B-2). Because there are so many endangered, threatened,
or protected species, the fish assessment endpoint is of high ecological and societal value.
Within the past century, the entire Tennessee River proper and many of its tributaries
have been physically altered by impoundments, resulting in destruction and fragmentation of
these rich riverine communities (TVA, 1970; Freeman, 1987; Angermeier and Smogor, 1993;
O'Bara et al., 1994). Because many of the rare fish species in this watershed are insectivorous
(Jenkins and Burkhead, 1994) (Figure 3-2), protection of native fish species habitat protects
many of the invertebrates as well. Many of these rare fishes are primarily benthic or have
specific aquatic habitat requirements for spawning and/or feeding, and most are relatively
short-lived (Masnik, 1974; Etnier and Stames, 1994). The assessment endpoint attributes of
diversity and abundance are specified because the goal of self-sustaining populations of native
fish species identified in this risk assessment will be evidenced by diverse, abundant populations
within the watershed. Similarly to mussels, native fish species are also extremely sensitive to the
negative impacts brought about by geographic isolation and immediate loss of habitats due to
impoundment. Small, isolated populations of fish not only suffer from lack of gene flow but are
also highly susceptible to localized extirpations from catastrophic events such as toxic chemical
spills, prolonged drought and low stream flow, and high water temperatures.
The degree of native fish species recruitment is related to several habitat and water
quality features that are important to the survival and reproduction of many fish and invertebrate
species in the Clinch and Powell watershed. Furthermore, specific fish species serve as hosts for
the obligate parasitic glochidia stage of the native mussel species, as mentioned previously.
Thus, recruitment of native fish species is an important factor in the recruitment of mussel-
species.
3.1.1.2.2. Risks to endpoint. Fish reproduction and recruitment are especially susceptible to
sedimentation, turbidity, and exposure to toxic chemicals, each of which can result in local
extirpations, leaving disjunct populations that are even more susceptible to extinction. Habitat
alteration, either through riparian corridor destruction, hydrologic modification, or livestock
3-7
-------
Figure 3-2. The Clinch and Powell watershed harbors several endemic fish species,
particularly insectivorous darters, many of which are now rare and/or threatened and
endangered.
watering, is also an important stressor for fish recruitment. There are several sources of toxic
chemicals (i.e., pesticides, herbicides, metals, oils, and greases), including runoff from urban
areas, row-crop agriculture, mining, transportation corridors, and silviculture areas or from
atmospheric deposition. Toxic chemicals affect potential invertebrate prey as well as the fish
themselves, which could result in either reduced food for fish consumption or biomagnification
of certain pollutants through the food web.
Sedimentation is believed to be a potentially important stressor to native fish populations
in this watershed because it reduces suitable spawning sites and, thereby, fish recruitment. It
originates from a number of sources, including livestock watering; soil erosion from urban,
mining, and agricultural runoff; riparian corridor modification; and poor silviculture practices. It
also has indirect effects on fish by changing the type and abundance of food items that may be
available.
\
Direct fish habitat alteration is possible if the riparian corridor is eliminated or greatly
reduced. Stream bank cover and clean benthic gravel and rubble for spawning and cover are
often important habitat features for many native fish species in the Clinch and Powell watershed
(Jenkins and Burkhead, 1994). These habitat features are jeopardized if the riparian corridor is
degraded. Furthermore, these same features are necessary for the survival and reproduction of
many of the invertebrate prey used by native fish in this watershed.
3-8
-------
3*1.2. Impacts on Abundance, Diversity, and Age Class Structure of Cave Fauna
Although not analyzed in this risk assessment, the impacts of human activities on the
abundance, diversity, and age class structure of cave fauna were qualitatively considered.
Several activities in the watershed could directly or indirectly affect subsurface water quality or
cave fauna habitats. Toxic chemicals originating from agricultural runoff, mining activities, or
trash disposal can enter sinkholes or caves, where they can then be potentially transported over a
broad subsurface area and affect multiple caves. Excess nutrients and pathogens from livestock
grazing in highlands or from agriculture could also conceivably reach the subsurface system,
resulting in excessive bacterial growth, anoxia, and perhaps increased disease rate of cave fauna.
Degradation of water quality due to toxic chemicals, excessive nutrients, or pathogens is
expected to have direct effects on cave fauna survival and reproduction and, therefore, their
abundance, diversity, and age structure.
A second type of stress on cave fauna is habitat modification due to either drastic changes
in subsurface water flow or increased sedimentation. Sedimentation due to mining and poor
agricultural or silviculture activities is believed to be a potentially important stressor to cave
fauna because it could lead to anoxia and habitat destruction. In addition, use of sinkholes for
soil and debris disposal can cause back-flooding and siltation of ground water. The presence and
effects of sedimentation in relation to cave fauna abundance and diversity are poorly documented
at this time.
Effects of other potential activities in this watershed, such as transportation corridors,
failed septic systems, or leaking sewers, are also poorly documented for this watershed but may
be inferred from land use analysis of cave fauna data (see Analysis Plan). Hydrologic
modification could conceivably alter cave and subsurface water quality, depending on the
location of the activity in the watershed. Also, many of these activities could result in deleterious
changes in subsurface flow or sedimentation for aquatic cave fauna.
32. SOURCES AND STRESSORS CONSIDERED IN THE CLINCH AND POWELL
WATERSHED ASSESSMENT
Table 3-1 summarizes the various stressors, and sources of those stressors, initially
considered by the workgroup. The following section discusses each potential source, the
stressors that might originate from the source, and general statements about the relative
importance of each source or stressor to the watershed, based on resource managers' many years
of experience.
3-9
-------
Table 3-1. Stressors and sources identified in the Clinch and Powell watershed
Stressor
Degraded Water Quality
Toxic chemicals
Pathogens
Nutrients
1 Sources
Catastrophic spills
Urbanization
Point-source discharges
Atmospheric deposition
Urbanization
Urbanization
Atmospheric deposition
Physical Habitat Alteration
Sedimentation
Riparian modification
Instream destruction
Coal mining
Hydrologic changes
Transportation
Agriculture
Hydrologic changes
Agriculture
Hydrologic changes
Biotic Interactions
Exotic species introductions
Overexploitation
Agriculture
Coal mining
Transportation
Agriculture
Agriculture
Agriculture
Urbanization
Urbanization
Urbanization
Accidental (Asiatic clam, zebra mussel)
Recreational (brown trout, rainbow trout)
Other biota
Over harvesting
Poaching
3.2.1. Active Coal Mining and Processing
Stressors: Toxic chemicals, sedimentation
Coal mining is restricted to the western region of the watershed, along the Cumberland
Plateau. Areas known to be most heavily impacted by coal activities include the upper Clinch
River in the vicinity of Swords Creek and the Guest River and the upper Powell River upstream
from Pennington Gap. Although this region makes up less than 20% of the total watershed area,
the impacts of mining are evident throughout the watershed. Both nonpoint and point-source
pollution impacts occur from mining.
Point-source discharges from active mines and processing plants are potential threats to
the riverine ecosystem. Hydraulic fluid releases associated with mining activities have caused
known fish kills (BM, 1990). There are 287 active coal mining point-source discharges in the
Clinch and Powell watershed. Discharges from coal processing plants and mine sites are
currently regulated by the U.S. Bureau of Mines, and discharges are monitored for pH, total iron,
3-10
-------
total manganese, and total residue. However, a wide range of potentially toxic compounds, such
as hydraulic fluids, frothing agents, modifying reagents, pH regulators, dispersing agents,
flocculants, and media separators that are used in mining and coal processing are currently
unregulated and not monitored, and they may be discharged to the rivers (BM, 1990; Cherry et
al., 1995). Furthermore, the compliance of these discharges is not known with certainty.
Enforcement of discharge compliance is also unclear, as both the Bureau of Mines and the
Virginia Department of Environmental Quality (VDEQ) may not coordinate activities
adequately.
Sediment runoff and coal fines from haul roads, active mining sites, and abandoned mine
lands lead to sedimentation of surface waters, which can inundate mussels in the substrate with
fine sediments that may also be toxic (Sheehan et al., 1989). The Powell River, particularly
above Pennington Gap, VA, was so adversely impacted from coal mining operations that it was
dredged to remove contaminants. On Christmas Day of 1972, the Powell River ran black from
coal fines in the water column. Coal fines, which may be transported downstream during
scouring from high water flows, are a major component of the substratum in some parts of the
upper Powell River. This form of sedimentation has had deleterious effects on benthic
organisms, particularly freshwater mussels, which are sessile and do not recover as easily as
mobile organisms such as fish and insects. Sedimentation from continued mining operations is
still a significant ecological stress.
Finally, coal mining activities have led to several catastrophic spills within the past 21
years at least. Accidental releases from coal slurry impoundments and toxic chemicals from
mine sumps have been recorded (BM, 1998; Hylton, 1998) (see Catastrophic Spills, below).
Effects of active coal mines and processing plants were quantitatively analyzed in this risk
assessment.
3.2.2 Abandoned Mine Lands
Stressors: Sedimentation, toxic chemicals
Acidic soils exposed during mining activities cause acid mine runoff that finds its way
into the river and reduces the pH of the water. If one assumes that active mining point sources
are being adequately controlled through the Federal Clean Water Act, then many of the observed
impacts are coming from abandoned mine lands. More than 45,000 acres of disturbed mine
lands occur within the watershed, of which 9,200 acres are abandoned mine lands developed and
then abandoned before Federal controls. The projected cost to reclaim the abandoned mine lands
is more than $100 million, and little or no information is available on the water quality impacts
of these lands.
3-11
-------
Extensive development of the coalfields of southwestern Virginia before the 1977 Federal
Surface Mining Law's reclamation requirements has resulted in significant watershed and stream
impacts from both acid mine drainage (including low pH and exceedingly high metal
concentrations such as iron, manganese, and aluminum) and embedded stream conditions (from
sedimentation due to barren or semibarren land condition and slope instability). In specific
subwatersheds of the Powell River, metal concentrations have surpassed acute and chronic
toxicity thresholds by orders of magnitude, threatening aquatic life, livestock, and humans. In
one heavily impacted watershed, Ely Creek, pHs ranging from 2.5 to 2.9 resulted in measures of
benthic abundance and diversity of zero and a total loss of fish. As abandoned mine lands are
incompletely identified in this watershed, we qualitatively examined this source of stress in this
risk assessment.
3.2.3 Urbanization
Stressors: Toxic chemicals, pathogens/nutrient enrichment, sedimentation, riparian zone
modification
Historically, southwest Virginia and northeast Tennessee have suffered economically
because of their geographic remoteness, rugged terrain, inadequate transportation, and poor
education. Consequently, efforts are underway to encourage industrial growth in the region, as
evidenced by the Virginia General Assembly's creation of the Southwest Virginia Economic
Development Commission, which was established to improve social and economic development
in the region. Much of the commission's focus has been on improving the transportation
infrastructure (e.g., Virginia State Highway 58), providing assistance and incentives to business,
marketing southwest Virginia, and developing natural resources. Industrial park expansions,
landfills, prisons, and airports, as well as construction of a new major highway transecting the
area, are proposed in the watershed.
The karst areas may be impacted if plans for a new airport and prison are implemented. It
appears that the prison will be constructed in an area and manner that will minimize impacts to
the karst system. FWS, the Virginia Division of Natural Heritage, and the Virginia Cave Board
will be working closely with a number of partners to mitigate negative impacts from the
proposed airport.
Nonpoint-source pollution from urbanization is probably a very important factor in
riparian zone modification. It may contribute to elevated temperature, embeddedness, scouring,
depositions, and other instream habitat effects. The effects of urbanization were quantitatively
analyzed in this risk assessment.
3-12
-------
3.2.4 Agriculture—Livestock and Pastureland
Stressors: Toxic chemicals, pathogens/nutrient enrichment, sedimentation, riparian zone
modification, habitat destruction
The Bi-State Task Force report to the governors of Tennessee and Virginia identified
nonpoint-source pollution as the single most important source of water pollution in the Clinch
and Powell watershed. Much of this pollution can be attributed to the poor agricultural practices
used throughout the watershed, including overgrazed pastures on steep slopes, animal waste from
feed lots, and livestock access to streams and riparian corridors.
Approximately 175,000 acres of pastureland with greater-than-acceptable soil loss
tolerances (based on Soil Conservation Service tolerance criteria) occur in the Clinch and Powell
watershed. Almost 75,000 head of livestock, mostly cattle, graze in the watershed. The majority
of these livestock depend on the river or other perennial streams for water, creating a situation in
which degradation of riparian corridors, along with increased nutrient, bacterial, and viral input
to the waterways, is common.
Runoff from steep grazing lands may be significant, but the actual extent of
sedimentation caused by this type of runoff is unknown. Likewise, the total amount of erosion of
streambanks and organic waste pollution resulting from cattle access to streams has not been
measured. However, it continues to.be significant at a number of sites within the Clinch and
Powell watershed. The extent of instream habitat destruction caused by cattle trampling the
streambeds has not been determined. Effects of pastureland were quantitatively analyzed in this
risk assessment.
3.2.5. Agriculture—Row Crop
Stressors: Toxic chemicals, sedimentation
About one-third of the land in the Clinch and Powell watershed is devoted to agriculture.
The extent of pesticide runoff in the watershed is unknown, but tobacco plot-associated toxic
chemicals are known to affect karst habitats.
Sedimentation caused by runoff from agricultural lands is expected to have a large
impact, especially on benthic organisms in the area. In addition, sedimentation changes cave
stream substrates and affects invertebrate habitats. Much of the land that is flat enough to be
used for row crops is contained within floodplain areas. Many natural resource agencies and
groups are working to encourage better farming practices that include greenways to reduce
runoff, but much of the floodplain is still being cultivated without greenways. Effects of row ,
crop agriculture were quantitatively analyzed in this risk assessment.
3-13
-------
3.2.6. Point-Source Discharge—Industrial
Stressor: Toxic chemicals
There are currently 34 industrial point-source discharges within the Clinch and Powell
watershed, exclusive of coal-related discharges. The majority of these discharges are associated
with small businesses and are classified as minor. Only two major industrial discharges are
present in the watershed, one at Foote Mineral on Stock Creek, Scott County, VA, and the other
at the Appalachian Power Company's Clinch River Plant (APCO), a coal-fired power plant
located at Clinch river mile 267.5. The cumulative impact of these point sources is poorly
understood.
Approximately 960 tons of fly ash is produced daily at the APCO coal-burning power
plant as a result of the high ash content of the coal used at the plant. Water withdrawn from the
Clinch River is used to transport the ash in a slurry to large lagoons, where the ash settles. The
APCO plant discharges various contaminants to the rivers, including copper (Cu), which is
especially toxic to molluscs. Cooling tower blowdown effluent averaged 857 |ig Cu/L (3-7 (ig
Cu/L, ambient) in 1977-87. Condenser pipe replacement in 1987 reduced Cu discharge to
100-150 }ig Cu/L. The plant, under order from the Virginia Department of Environmental
Quality (VDEQ), has been retrofitted to further reduce copper concentrations in the effluent. The
new copper standards for the plant are 12 jig Cu/L. After the initial reduction to 150 ng Cu/L,
snail recovery was seen 2 years later at a research station 0.9 km below the discharge (Reed,
1993), but molluscan recovery has been much slower (Stansbery et al., 1986). The ability of the
new standard to protect the aquatic ecosystems has not yet been validated. It is not known
whether unregulated toxic chemicals may be discharged at this and other industrial facilities in
the watershed.
The Cypress Foote Mineral plant discharged various contaminants to Stock Creek above
Speer's Ferry on the Clinch River. Tests in Stock Creek by VDEQ verified impairment to the
creek from the plant and that the discharge may have been contributing to mussel declines at
Speer's Ferry. Cyprus Foote Mineral has closed its plant on Stock Creek. However,
underground seeps from mine tailings are still contributing high concentrations of lithium and
aluminum.
Furthermore, industrial facilities such as the APCO plant have been responsible for
catastrophic toxic spills that resulted in severe ecological effects (see Catastrophic Spills, below).
Point-source locations were identified and considered qualitatively in this risk assessment.
Where point sources were associated with urban or barren land cover (a common phenomenon),
urban effects captured at least some of the effects of point sources.
3-14
-------
3.2.7. Point-Source Discharge—Municipal Sewage
Stressors: Toxic chemicals, pathogens/nutrient enrichment
Currently, 119 municipal discharges are within the watershed. These include discharges
from all the major municipalities in the Clinch Valley as well as from treatment plants at active
mining sites. Most municipalities are now in the process of upgrading to secondary treatment
standards. Final upgrades have been completed at Richlands and Tazewell on the Clinch River,
Pennington Gap on the Powell River, and Coeburn/Norton/Wise on the Guest River. Some
extremely rural areas, such as St. Charles on the Powell River and Dante/Hamlin/Castlewood on
the Clinch River, continue to discharge raw sewage to the rivers. Pathogens originating from
poorly treated municipal wastewater or from failed septic systems and leaking sewers have been
shown to cause deleterious effects on fertilized ova (eggs) in the marsupia of female mussels,
thus affecting reproduction (Fuller, 1974). However, the extent of this stressor in the watershed
is unknown and thought to be insignificant.
VDEQ has banned the use of halogen compounds such as chlorine for disinfection at
municipal treatment plants because of the toxicity of halogens to aquatic life. A few treatment
plants have not yet been retrofitted with alternative disinfection systems and continue to use
chlorine as a disinfectant, with dechlorination mechanisms in place to treat the effluent. A
failure of the dechlorination apparatus and subsequent discharge of chlorine from these plants
poses an enormous threat to the river in areas such as Cleveland, VA, where an exemplary
mussel community lies immediately downstream of the plant outfall. Cleveland has now been
upgraded to ultraviolet disinfection. Municipal point sources are associated with urban areas by
definition and were therefore implicitly analyzed along with urban effects in this risk assessment.
3.2.8. Silviculture
Stressors: Sedimentation, degradation of riparian areas
This region was cleared extensively upon European settlement and during later migration
of people into the area in the late 18th and early 19th centuries. Clearing was driven by the need
for agricultural production—both commodity grain and tobacco crops—and for grazing land for
cattle and sheep. Logging, with large crews and supported by railroad and tramway systems, was
conducted at the turn of the 20th century to sustain American industrial growth and to salvage
lumber from the American chestnut when this tree was devastated by the chestnut blight. The
wood- and coal-burning engines used by the logging crews sparked devastating forest fires,
which were not adequately controlled for decades—until the 1930s. As logging declined and
fires were aggressively suppressed by State and Federal agencies, forests began to regenerate.
This recovery was supplemented with the creation of the Jefferson National Forest, whereby
large Federal land holdings within several ranger districts were, and remain, dedicated to forest
3-15
-------
management and protection of forest resources. Today, the region experiences the greatest forest
fire risk and activity in the State, but annual losses average less than 5,000 acres per year in the
watershed owing to enforcement of the Virginia 4 PM Burning Law, other associated fire laws,
and one of the most successful forest fire prevention efforts in.the nation.
Harvesting of forest resources continued throughout the 20th century, supplementing the
mining industry with timber supports, providing quality hardwoods to furniture and dimension
lumber production, and pulp for fine papers to a Kingsport, TN, paper mill. During the 1980s
and 1990s, new industries and the availability of former mining industry workers to harvest
lumber prompted a resurgence of forest industry in the region. Establishment of an oriented
strand board plant in Dungannon (Scott County), VA, has particularly influenced great increases
in annual acres logged in several counties of the Clinch and Powell watershed. New forest
industries in West Virginia, Kentucky, Tennessee, and Virginia will continue the trend of
increased logging of the region's forest resources.
In a 1995 analysis of potential nonpoint-source pollution in Virginia's 493 hydrologic
units, performed in concert with soil and water conservation districts and the U.S. Department of
Forestry, 20% of the units were assessed as having a "high" potential for nonpoint-source
pollution from forest harvesting. Rankings were determined in part by topography and current
logging activity. Of the 24 hydrologic units located within the Clinch and Powell watershed, 15
were ranked "high" for nonpoint-source pollution potential from logging, eight ranked
"medium," and one ranked "low." Nonpoint-source pollution potential from logging includes
erosion and sedimentation, with lesser impacts from petroleum contamination from log decks
and areas where equipment is concentrated. When riparian areas are logged, removal of shade
also impacts water quality and aquatic resources through increased water temperatures and
declines in dissolved oxygen. Removal of sources of detritus and woody debris can also
negatively impact aquatic habitats. State BMPs specifications require retention of at least 50% of
the basal area in designated streamside management areas. These areas consist of a minimum of
50 feet on either side of the stream, with increasing widths based on topography. A two-zoned
riparian buffer is currently under review, in which areas immediately adjacent to the stream
would be more rigorously protected.
The U.S. Department of Forestry enforces the Silvicultural Water Quality Law, which can
penalize loggers, landowners, and forest producers if potential and actual nonpoint-source
pollution from Silvicultural operations is not addressed via a system of informal
recommendations, reviews, stop-work orders, and hearings. Since passage of the law in 1992*
enforcement in southwest Virginia has been aggressive and is supplemented with continual
formal and one-on-one educational efforts targeted at loggers, landowners, and forest products
3-16
-------
producers. As silviculture is still a very minor activity in the watershed, we did not analyze this
stressor in this risk assessment. ,
3.2.9. Hydrologic Changes
Stressor: Habitat destruction
No significant manmade hydrologic changes are known to have occurred or are planned
upstream of Norris Dam in Tennessee. Before completion of Norris Dam in 1936, the Powell
and Clinch rivers were historically free-flowing, merging with the Tennessee River and then with
the Ohio River, and eventually reaching the Mississippi River. Now these rivers flow into the
Norris Lake impoundment at Norris, TN, and are thus isolated from the rest of the drainage
system. The impact of this type of isolation on the rivers is unknown. Although it is reasonable
to assume that some loss of species exchange has occurred because of Norris Lake, this is
believed to be a relatively minor source of stress. Therefore, this stressor was not evaluated
further in this risk assessment.
3.2.10. Introductions and Migrations of Nonnative Species
Stressors: Competition, infection
The Clinch and Powell watershed, like most natural systems, has been invaded by non-
native species. The first aquatic nonnative mollusc species recorded was the Asiatic clam
(Corbiculafluminea), first seen in the watershed in the 1970s. A second invader, the zebra
mussel (Dreissenapolymorpha), is presently found throughout the mainstem Tennessee River
and the lower half mile of the French Broad River. Little is currently known about the impacts
of, or controls for, these organisms. Researchers at Virginia Tech are currently studying impacts
of Corbicula on native mussel populations.
The Asiatic clam was first discovered in the Tennessee River in 1959 (Gardner et al.,
1976). Since that time, it has become widespread and extremely common .throughout the Clinch
and Powell watershed. It is the most common mollusc species in the region. Competitive
interaction between the Asiatic clam and native mussel fauna is still not clearly understood, and
further research is required.
The zebra mussel, native to the Black and Caspian seas, has spread extensively
throughout the Great Lakes region since its discovery in Lake Erie in 1988 (O'Neil, 1991). It has
caused devastating impacts to industrial and municipal intakes, natural food chains, and
commercial and recreational fishing. No effective means have been developed to control this
species, and much concern has been raised about its potential negative impacts on native mussel
fauna in the Clinch and Powell watershed. FWS has predicted that as many as 10 species of
mussels found in the watershed are likely to become extinct with the establishment of the zebra
3-17
-------
mussel. However, thus far, the zebra mussel has not been able to establish populations in
flowing rivers and streams, because the larvae require more lentic conditions.
Little is known about the impacts of introduced fish on native fish.
We did not analyze this stressor in this risk assessment because of a general lack of
information. This may be an important stressor to consider in future phases.
3.2.11. Recreation
Stressor: Normative species, overexploitation
Aggressive, nonnative species such as the Asiatic clam and zebra mussel may be spread
through the watershed via recreational boating, but the likelihood is not known. There is little
boating in the watershed because there are few deep-water reaches. Some Whitewater canoeing
occurs in the watershed, but it is not extensive. The extent of recreational fishing on the native
fish populations is unknown but is considered to be very minor, given the low population density.
Therefore, this stressor was not considered further in this risk assessment.
3.2.12. Other Biota—Predation
Stressor: Overexploitation
Increasing populations of muskrats and other predators, such as racoons (Procyon lotor)
and map turtles (Graptenys), prey on hundreds—and perhaps thousands—of molluscs in the
watershed each year. The relative impact of predation, although not well documented, may be a
significant threat to mussels because of the abundance of muskrats in the watershed. In addition,
muskrats tend to select smaller species of mussels, which, in many cases, are the most
endangered species. Observations by some scientists indicate that muskrat predation appears to
be inhibiting the recovery of endangered mussel species in the Clinch and Powell watershed and
is likely placing some populations of the endangered pigtoe mussel (Fusconaia edgariand) in
jeopardy of extirpation. Information about this stressor is severely lacking and, therefore, could
not be analyzed in this risk assessment. This may be a stressor to consider in future phases.
3.2.13. Illegal Harvesting
Stressor: Overexploitation
Earlier in the 20th century many mussels were harvested for the button industry. Today
that type of harvesting is illegal, but it still occurs to an unknown extent. This is believed to be a
very minor source of stress in the watershed, and it is unlikely to become major, given the low
population density in the watershed and much larger, legal sources of mussel harvesting in other
basins (e.g., Ohio River, Mississippi River). Therefore, this source of stress was not further
evaluated in this risk assessment.
3-18
-------
3.2.14. Catastrophic Spills
Stressors: Toxic chemicals, sediments
Catastrophic spills of toxic materials into surface waters of the Clinch and Powell
watershed have long been recognized as a major water quality stressor. Past spills have been
high-magnitude, short-duration, low-frequency events that undoubtedly caused extensive long-
term impacts on native species in the basin. Because of the unpredictable and episodic nature of
these spills, we were unable to quantitatively incorporate this stressor into the risk analyses.
However, we made attempts to evaluate catastrophic spills by analyzing effects of proximity to
transportation corridors and mining, both of which have been major sources of spills. We also
considered spills qualitatively in risk characterization.
The 1996 Virginia Water Quality Report identified six known fish kills, ranging in size
from 11 to 11,355 fish. Four kills were the result of accidental spills of cement during
construction activities. Historical examples include an October 1993 42-car coal train
derailment, which resulted in 4,200 tons of coal being spilled adjacent to the Clinch River at
Dungannon, VA. This spill was not reported to VDEQ for several days, and cleanup of the site
required several weeks.
The APCO plant has been responsible for two large episodic events that affected Clinch
River ecological communities. In June 1967,440 acre-feet of caustic ash poured into Dump's
Creek and then into the Clinch River. For 4 days, the slug of ash traveled downstream, killing all
fish it encountered in the vicinity of Carbo and many more for 66 miles of the Clinch River in
Virginia and 24 miles in Tennessee. The alkaline excursion was reported to be responsible for
eliminating bottom-dwelling fish-food organisms for approximately 5-6 km and snail and mussel
populations for 18 km (Cairns et al, 1971). Approximately 216,600 fish were killed in Virginia
and Tennessee by the episode. Snails and mussels were eliminated for almost 12 miles
downstream.
Studies conducted by Virginia Tech showed that fish and aquatic insects became
reestablished relatively quickly following the spill (Grossman et al., 1973). Insect communities
showed downstream recovery (i.e., further downstream stations had higher density and diversity)
in 1969, but molluscan communities had not recovered for at least 30 km below the spill site.
Presently, mussels have not yet recolonized the 9- to 10-mile portion of the river below the plant.
Differences in invasion and colonization potential between the two groups of organisms
underscore the importance of monitoring molluscan populations, because they are slower to
recover.
In 1970, before molluscan populations had recovered to prior density, an acid spill
occurred at the APCO plant. The area affected was less extensive than that of the fly ash spill:
13.5 miles downstream to St. Paul, VA. Approximately 5,300 fish were killed (Grossman et al.,
3-19
-------
1973). After the spill, no surviving mayfly or molluscan species were found for 18 km below the
spill. Within 6 weeks, diversity of arthropod benthic organisms had recovered, but mussel
species had not.
The potential for future spills is not clear. A catastrophic spill can originate at industrial
facilities located along the rivers or from accidents along transportation corridors that cross or
parallel the waterways and karst systems. Additionally, catastrophic spills can result from illegal
dumping into waterways or sinkholes. These spills can pose a potentially enormous threat to the
riverine ecosystem, as previously described. It is acknowledged that many spills of toxic
chemicals may have occurred in the past and been unreported.
Unfortunately, little information has been accumulated on storage and transportation of
toxic materials in the basin, and the full potential for impacts to the fauna is unknown.
Consequently, the development of contingency plans will be limited until additional information
on toxic material transport and storage can be obtained.
3.3. SIMPLIFIED CONCEPTUAL RISK MODEL
The conceptual model describes pathways between human activities (sources of stress),
stressors (which may be physical, chemical, or biological in nature), and assessment endpoints
(U.S. EPA, 1998). The model yields predictions or risk hypotheses of how human activities
affect the valued ecological resources (assessment endpoints) and is based on ecological
experience and best professional judgment. The two conceptual models, one for each assessment
endpoint analyzed in this risk assessment, were developed by the workgroup as part of problem
formulation and are described below and in Figures 3-3 and 3-4. The models shown do not
portray all possible sources and stressors and the pathways by which they might impact
ecological resources within the watershed. Developing and presenting such a comprehensive
model was found to be neither helpful nor resource-efficient in the context of this risk
assessment. Only those pathways or relationships that were considered most ecologically
important in this region by resource managers are depicted in Figures 3-3 and 3-4. These more
simplified conceptual models were very useful for identifying potential data sources (and data
gaps) and tracking progress in specific risk analyses. Stressors and their sources were grouped
into three major categories: degraded water quality, physical habitat alteration, and biotic
interactions (Table 3-1). The following sections briefly discuss known or assumed effects of
these different types of stressors on assessment endpoints in this risk assessment.
3.3.1. Degraded Water Quality
Host fish survival and reproduction are affected by several of the same sources and
stressors as mussels (see Figure 3-3), thus accentuating these stressor effects on mussels. Toxic
3-20
-------
(A
0)
an
KjpiSf!'" 'fl ,j_'ii|l '*"• P* •' I \
l^gricultuf e j
MBnelands
i
!U' . ".-, "'" '"' ."• i
IT ivpctrtrlr
_
I
-------
Instream
Habitat
Destruction
Instream \ /"^.. /"""N
Habitat ) (^Sedimentation^)
Riparian
Modification
QPathogensJ)
Impaired
Invertebrate
Habitat
Decreased
Allochthonous
Inputs to Stream
and Increased
Heat and Light
Decreased
Invertebrate
Survival and
Reproduction
Reproduction, Recruitment of Threatened,
Endangered, or Rare Fish Species
Figure 3-4. Conceptual risk model for fish.
3-22
-------
chemicals such as heavy metals or chlorine, which are discharged by some municipal and
industrial wastewater dischargers in the watershed, and pesticides originating from agricultural
activities in the watershed are known to have severe effects on mussel survival and recruitment
(Havlik and Marking, 1987; Sheehan et al., 1989; Goudreau et al., 1993; Reed, 1993). Mine
water discharges may contain other pollutants, such, as hydraulic oils, foaming agents, surfactant
materials, and greases that can be extremely toxic to filter-feeders such as mussels (BMI, 1990;
Lingenfelser, 2000). These pollutants may enter the stream via surface water discharges or
underground springs and caves that surface somewhere else in the watershed. Thus, mussels and
fish may be affected by subsurface as well as surface water quality. Urban stormwater runoff and
untreated or failing septic system waste also may release pollutants, compounding toxic stress to
mussels and fish. The fact that mussels are sedentary and benthic makes them even more of a
target for water pollutant exposure (Sheehan et al., 1989). The siphoning mode of feeding used
by mussels also makes them susceptible to bioaccumulative effects of organic pollutants (Tessier
et al., 1984; Kauss and Hamdy, 1991; Livingstone and Pipe, 1992).
3.3.2. Physical Stream Habitat Alteration
A variety of activities in the watershed could result in deterioration of instream benthic
habitats. Any activity resulting in increased sediment deposition and substrate embeddedness
instream reduces the amount of available benthic habitat necessary for successful mussel larval
settlement, growth, and survival (Bates and Dennis, 1978; Way et al., 1990) and fish spawning
and feeding habitat (Freeman, 1987). This in turn directly affects recruitment of mussel and fish
populations. Thus, soil runoff resulting from poor agricultural practices, livestock trampling
instream, elimination of the riparian corridor, and urbanization could directly influence the
amount of available habitats for mussels and fish.
Significant alterations in stream flow or channel modification are other stressors that
could directly affect mussel and fish habitat availability and, therefore, mussel and fish diversity
and abundance. In addition to large-scale human activities that can severely modify aquatic life
habitat, such as dams and dredging, more subtle forms of habitat alteration may be important in
the Clinch and Powell watershed, such as (1) riparian corridor and stream bank destabilization
due to transportation corridors and poor agricultural and silviculture practices, (2) high-flow
regions and benthic scour due to large industrial and municipal wastewater discharges and urban
stormwater runoff, and (3) bank failure, channel widening, and subsequent channel depth and
current velocity reduction due to livestock watering instream. Turbidity resulting from
sedimentation or livestock wading and watering instream further affects mussel and fish survival
and recruitment by interfering with, or reducing the effectiveness of, normal feeding and larval
survival (Stansbery and Stein, 1976; Dennis, 1981,1985).
3-23
-------
Another major stressor in the form of physical habitat alteration is the loss of the riparian
corridor. The workgroup recognized that the magnitude of various stream effects (e.g., water
quality or physical habitat alterations) on stream biota is likely to be a function of the riparian
corridor integrity present. Therefore, loss of riparian corridor warrants separate and more
extensive discussion.
3.3.3. Loss of Riparian Corridor
The composition and connectivity of riparian vegetation are potentially affected by
several different human activities in the watershed, including livestock grazing, agricultural row
crop, forestry, mining, silviculture practices, urban development, wastewater discharges,
transportation corridors, hydrologic modification, and perhaps acid rain deposition (Minshall,
1993; Richards and Host, 1994). Most of these activities result in thinning or removal of the
natural riparian vegetation (particularly the canopy). This alteration could have several effects,
including loss of soil and nutrients, soil instability, and bank erosion or failure (Cooper et al.,
1987), thereby altering the species composition and connectivity of the riparian corridor as a
whole. Each of these stressors directly affects the abundance and composition of plant species
capable of inhabiting the riparian zone and, ultimately, channel stability. Loss of soil and bank
failure affect sedimentation instream, which is a major potential stressor for the assessment
endpoints examined in this risk assessment.
Lack of an intact and connected riparian corridor is expected to reduce mussel and fish
populations through other habitat-related stressors. Riparian canopy removal or thinning
increases light and heat penetration to the stream bank, resulting in higher temperatures and
lower dissolved oxygen saturation instream, both of which could be deleterious to mussel and
many fish species. Riparian vegetation also captures sediment from overland flow, retards
floodwater, and captures fertilizer and other chemicals in runoff from agriculture fields (Cooper
et al., 1987; Osborne and Kovacic, 1993; Richards and Host, 1994). Also, removal of the natural
riparian corridor (either from agricultural, urban, transportation, or forestry activities) reduces or
eliminates the important exchange of nutrients and allochthonous energy between the stream and
its floodplain, resulting perhaps in reduced food availability for mussels, other invertebrates, and
fish (Gregory et al., 1991).
Removal of riparian forests can greatly diminish sediment and nutrient trapping
capabilities of areas immediately adjacent to streams. Certain aquatic invertebrate species have
declined in other systems because there are fewer riparian refugia during floods and other periods
of environmental stress and because of a reduction in detritus and woody debris that historically
served as the major energy source (Minshall, 1993). Thus, riparian corridor alteration is treated
3-24
-------
as a stressor in this risk assessment in the sense that stream habitat quality and perhaps water
quality could be degraded if riparian corridor connectivity is impaired by human activities.
3.4. ANALYSIS PLAN
'„
The goal of risk analysis is to draw meaningful and statistically supported relationships
based on available data. Initially, the relationships presented in the conceptual models (section
3.3) formed the basis of hypotheses that we planned to analyze using data collected in the
watershed over many years. This risk assessment initially assumed that certain stressor and
effects data would be available from different subwatersheds. As the workgroup began to
explore different hypotheses in this risk assessment, it modified the analytical approach in
accordance with the data actually available and the results of initial analyses. For example, water
chemistry data were lacking in this assessment, which limited our ability to analyze relationships
between water quality stressors and either land uses or biota. It was ultimately decided to
evaluate the following risk hypotheses:
Physical Habitat Alteration Hypotheses
• Greater riparian connectivity or forested riparian vegetation is associated with greater
diversity and abundance of mussels, other macroinvertebrates, and native fish.
• Watershed areas dominated by agricultural, urban, or mining land uses are associated
with poorer habitat quality and biological diversity than are forested or naturally
vegetated areas.
Water Quality Hypothesis
• Proximity to nonpoint-source runoff from agricultural activities and urban areas and
point-source discharges (including coal mining discharges) result in detrimental
structural changes to native mussel and fish populations.
3.5. ANALYTICAL APPROACH
To test these hypotheses, the general analysis scheme entailed identifying potential
patterns or relationships between different land uses and stressor measures. Relationships
between land-use activities and measures of effect representing the assessment endpoints were
also examined. Interpretation of the results from these two sets of analyses allows inferences to
3-25
-------
be made about the relationships between specific stressors, or combinations of stressors, and
assessment endpoints.
The objectives of the analysis phase are to gain a better understanding of (1) the extent to
which ecological resources are exposed to stressors resulting from human activities and (2) the
likely effects that may occur. These exposure and effects characterizations are then integrated
into an overall-estimate of risk in the next phase, risk characterization.
The analysis of risk in this assessment relies on current and past land-use practices and
measurements taken at specific sites in strategic subwatersheds in the Clinch and Powell
watershed. Past stressors and effects were then used to evaluate future risks of similar sources
and stressors in other parts of the watershed. Watershed risk assessments are complex because of
the co-occurrence of stressors and multiple pathways by which stressors impact assessment
endpoints. The multiple sources, stressors, and pathways and their co-occurrence at such a large
spatial scale lead to greater uncertainty and reduced associations among specific sources,
stressors, and ecological responses. The complexity of the assessment is further compounded by
the lack of an optimal suite of data.
Furthermore, there may be problems combining data from many sources, especially if
collected for another purpose (TTFM, 1995; MDCB, 1999). The technology is not yet available
to develop associations at such large spatial scales between multiple sources (e.g., agriculture,
forestry, and urbanization), stressors (e.g., impaired water quality, sediments, and toxic
substances), and observable biological effects; the data requirements are enormous as well.
Consequently, for watershed ecological risk assessments, exposure estimates may need to be
aggregated at the landscape level, whereby exposure is inferred from source or land-use
information. Alternatively, analyses may need to be limited to the most disruptive stressor. This
risk assessment was initiated in part to develop an approach for addressing the complexity of this
task, because no precedence exists on how to perform such assessments.
Given these limitations, we first examined relationships between land use and biological
data, as both these types of information were relatively reliable and available. Exposure
information, (i.e., inferred condition of habitat impacted by various physical and chemical
stressors) was based on knowledge from a few sites in the watershed. On the basis of available
data in the watershed and information from the literature, we evaluated the effect of nearby land
uses on the condition of physical habitat and biota as a surrogate for quantitative profiles of
exposure and effects. Thus, the exposure-effects distinction, typically the norm in chemical risk
assessments, was not as useful in this assessment because of a lack of adequate stressor data.
The land cover Dataset used in this risk assessment was derived from classified Landsat
Thematic Mapper imagery (Hermann, 1996). This Dataset was created as part of the Southern
3-26
-------
Appalachian Assessment, and imagery was classified into 17 discrete categories using the
following scheme: - . . -
1. Northern Hardwood Forests
2. Mixed Mesophytic Hardwood Forests
3. Oak Forests
4. Bottomland Hardwood Forests
5. White Pine/Hemlock Forests
6. Montane Spruce-Fir Forests
7. Southern Yellow Pine Forests
8. White Pine/Hemlock/Hardwood Forests
9. Mixed Pine/Hardwood Forests
10. Herbaceous
11. Barren
12. Agriculture-Pasture
13. Agriculture-Copeland
14. Wetlands
15. Developed
16. Water
17. Indeterminate-Clouds, Shadows
For risk analyses, the different forest categories were aggregated into one forest category.
All terrain data (e.g., elevation and slope) were derived from a mosaic of 30-meter resolution
USGS digital elevation models (USGS, 2001). The stream network data used was EPA's River
Reach (RF3) data (U.S. EPA, 2000). Point locations of mines and processing plants came from
the U.S. Bureau of Mines MAS Dataset (Causey and Douglas, 1998).
Table 3-2 summarizes available biological and habitat measures of effect used in this risk
assessment. The vast majority of these data were collected by TVA staff as part of regular
monitoring programs, including the CPRATS (N = 155 sites) and the CMCP (N = 60 sites). The
CPRATS sampling program is a fixed-station design that relies on targeted samples stratified by
stream size 'and general area of the watershed. The CMCP program is a targeted sampling design
that relies on historic mussel information as well as habitat quality, as judged by field
malacologists.
Each of the hypotheses stated in this section required a series of measurement endpoints
or metrics for analysis incorporated into a GIS. Critical data on environmental stressors, sources
of stressors, and biological resources were mapped to help identify co-occurrences. Source and
3-27
-------
Table 3-2. Available data used in risk analysis
Riparian corridor and instream
habitat quality
Invertebrates
Fish
Substrate embeddedness
Epifaunal substrate
Riparian forest cover
Channel width
Channel depth
Eoodplain width
Vegetative cover
Bank integrity
Sediment erosion rate
Instream cover
Substrate particle size
Presence/absence of wood vegetation
Habitat quality index
Mussel species presence/ absence
Mussel size classes8
Mussel species abundance3
Benthic macroinvertebrate EPT
Native mussel species richness
Threatened and endangered
mussel species richness
Pleurocerid snail species abundance"
Sediment toxicity to mussels
(various species and life stages)
and other invertebrate fauna"
Aquatic acute and chronic toxicity to
mussels (various species and life
stages) and other invertebrate fauna8
Threatened and endangered fish
presence/absence
Fish IBI scores
Habitat suitability indices
'Data were available for a limited number of sites within the watershed.
stressor data layers included land cover, stream drainages (USGS Stream Reach File 3), road
density, locations of point-source dischargers and mines, and stream habitat quality indices.
Biological data relied on in this risk assessment included the fish IBI, native mussel species
richness and abundance, and the macroinvertebrate EPT family index. Most biological and
habitat data analyzed in this study were collected between 1980 and 1996, although some historic
data (pre-1920) were also used. Some data were also obtained from FWS sampling records for
threatened and endangered species and from papers published by other researchers.
Water quality data (e.g., concentrations of toxic chemicals in effluents and streamwater)
were fairly limited in both spatial distribution and extent of information. Few priority pollutants
have been routinely monitored in this watershed. Therefore, we relied on available conventional
pollutant data derived from EPA's Storage and Retrieval System (STORET), as analyzed by
Zipper et al. (1991); discharge reports for the major industrial and municipal wastewater
facilities; and available information contained in EPA's BASINS (Version 2.0) database, which
includes some relevant data in EPA's permit compliance system.
The IBI is an index of fish community integrity that is composed of 12 different metrics
(in the version used) or components of the fish community, ranging from individual-level
characteristics (e.g., incidence of tumors or lesions) to community-level characteristics (e.g.,
percentage of sunfish or darter species or specific feeding guilds) (Karr and Chu, 1999). The IBI
is scored so that one can discriminate among sites that have poor, fair, good, or excellent fish
community integrity. The scores are derived by comparison with selected reference sites within
the watershed being characterized (Barbour et al., 1999; Karr and Chu, 1999). Reference sites
3-28
-------
represent the best conditions existing at the time and serve as a control or baseline. The
individual scores are added and the composite scores are then grouped into integrity categories
(poor, fair, good, or excellent), based on comparison with the reference site. Sites with IBI
scores corresponding to poor or fair condition indicate an impaired or stressed fish community;
IBI scores corresponding to good or excellent condition indicate an unimpaired fish community.
Although it would have been useful to examine the 12 separate IBI measures (Norton et al.,
2000) in addition to the composite scores, at the time of this study only the composite IBI scores
were accessible for analyses. Use of only the composite IBI scores potentially introduced
uncertainties in our risk analyses, as discussed later in this report.
The EPT is an index representing the number of macroinvertebrate taxa belonging to the
taxonomic orders Ephemeroptem (mayfly), Plecoptera (stonefly), or Trichopera (caddisfly).
These three orders of macroinvertebrates are generally thought to be relatively more pollution-
intolerant than other taxonomic orders (Lenat, 1984).
The fish IBI and macroinvertebrate EPT measures are believed to have a fairly high level
of confidence because, by and large, most streams in this watershed are wadeable during normal
flow conditions, affording relatively high sampling efficiency. Furthermore, both types of fauna
(as well as mussels) have been sampled for more than 30 years by TVA biologists, using standard
protocols. Macroinvertebrate samples were collected from riffle areas only. Fish were sampled
via electroshocking, sometimes from a boat in occasional pool areas.
3.6. PILOT TESTING
We performed preliminary analyses on the effects of different sources and stressors on
endemic mussel and fish species in four subwatersheds: Copper Creek, the Guest River, the
upper Clinch River, and the upper Powell River. Copper Creek drains into the upper Clinch
River and the Guest River drains into the upper Powell River. The four subwatersheds comprise
a range of different land uses, particularly differences in coal mining activity, pasture and crop
area, and urban area (Table 3-3). Rigorous analyses were not feasible because of the lack of
biological data in some subwatersheds. Comparisons of available biological data among
subwatersheds and between the Clinch and Powell rivers and analyses of data for the watershed
as a whole were used to infer relationships and augment the existing body of knowledge relating
sources and/or stressors and native species distribution. The lower segments of the Clinch and
Powell rivers were addressed by references to the literature but were not analyzed extensively
because of resource limitations.
Before conducting risk analyses for the watershed as a whole, we first pilot-tested our
analytical approach in one subwatershed to address two analysis objectives central to this
assessment: (1) to identify the appropriate spatial scale to test relationships between land-use
3-29
-------
Table 3-3. Comparison of land cover for four sub watersheds examined in the
Clinch and Powell watershed risk assessment
Land Cover
Forest (%)
Copeland (%)
Pasture (%)
Urban (%)
Number of mines3
Upper Clinch
River
• 53.7
0.6
44.5
1.1
8
Upper Powell
River
. 89.6
3.1
2.4
4.2
21
Guest River
84.1
<0.1
10.4^
2.6
•26
Copper Creek
57.7
1.3
40.9
<0.1
0
'Mines and coal preparation plants.
activities or stressors and measures of effect and (2) to identify whether the benthic
macroinvertebrate measure (i.e., the EPT index) or the fish IBI is a reliable surrogate measure of
effect for predicting the status of native mussel assemblages. Achieving the latter objective was
especially desirable, because it was known at the outset of this study that available native mussel
data were more limited than either EPT or IBI values. Copper Creek was chosen for this pilot
analysis because it was the most data-rich subwatershed and because it was a relatively simpler
case in that agricultural uses were the major source of anthropogenic activity (Table 3-3).
To address the first objective, Arc View (v. 3.0, ESRI, Redlands, CA) was used to
examine several different stream riparian widths (50,100,200, and 400 m) and several different
distances upstream of each sampling point (100,200,500,1000, and 2000 m). This analysis was
designed to evaluate the optimal spatial scale to determine the relative influence of riparian
corridor or valley agricultural activities on resulting biological integrity or habitat quality at a
site. Percent agricultural land cover (pasture and Copeland) was then calculated for each
different combination of riparian width and distance upstream for each of nine fish and
macroinvertebrate sites sampled by TVA between 1995 and 1996 in its CPRATS program. The
relationship between percent agricultural land cover and the fish IBI, the macroinvertebrate EPT,
and habitat quality indices for the different combinations was determined using Spearman rank
correlation (p=0.05). The IBI, the EPT, and the habitat quality index were also analyzed in
relation to riparian percent agricultural land cover upstream of each sampling point for the entire
subwatershed.
Recognizing there was uncertainty in relying on only Copper Creek data to determine
appropriate land-use dimensions for risk analyses, a similar analysis was undertaken to quantify
this uncertainty. Mussel data collected in the upper Clinch (Jones et al., 2000) and a subset of
3-30
-------
IBI data from the CPRATS Dataset were used in these analyses. Section 3.6 describes the
specific methods used for these subsequent analyses.
The fish IBI and the EPT were evaluated as potential surrogate mussel indicators
(analysis objective 2 above) by regressing either mussel abundance or species richness at 27 sites
in Copper Creek (TVA CMCP 1981 data) (TVA, 1981) with calculated fish IBI measures based
on data collected by Masnik (1974) at similar locations. The EPT was further evaluated as a
surrogate mussel indicator by qualitatively examining mussel abundance and species richness at
nine sites that were adjacent to the nine TVA EPT collection sites in Copper Creek.
Results of pilot analyses were used to define the approach for investigating stressors and
sources for each biological sampling location in the Clinch and Powell watershed in subsequent
analyses. A coverage was created using Arc View to display the location of potential human
sources of stress (e.g., urban centers) along with TVA's CPRATS sites for the entire watershed.
With ArcView Spatial Analysis (ESRI), a 2-km area was created around each sampling site to
identify the sources present at that site. Data from these coverages were then aggregated into a
single table and imported into Statistica for analysis.
Subwatersheds that exhibited low, moderate, or high levels of certain land uses in
comparison to others in the basin (Table 3-3) were also compared to determine probable causes
of biological responses.
3.7. STATISTICAL ANALYSES
TVA, under the supervision of the workgroup, developed and entered land-use, habitat,
and biological data into a GIS using Arc/INFO (v. 7.04, ESRI) and partitioned in various ways
using ACCESS (Microsoft) to obtain databases that were amenable to various statistical analyses
(Statsoft, v. 5.0, Tulsa, OK) to support analysis of impacts on assessment endpoints identified in
this risk assessment.
Relationships between stressors or sources and biological measures of effect were
identified using forward stepwise multiple regression analyses (p<0.05 for the overall model). In
forward stepwise multiple regression analyses, independent variables are entered one at a time to
analyze how much each one adds to the explanation of the dependent variable. Independent
variables included percentages of various land uses and number of mines in the riparian corridor
as well as in the immediate drainage upstream of biological sampling points. Type I error was
controlled by limiting analyses to no more than one factor (independent variable) per 10 sites and
by including only those variables that increased the overall R2 by at least 10%. Variables with p
values > O'.OS were considered in multiple regression analyses only if their F value was
sufficiently high to be entered into the model and if the resulting R2 value was at least 10%
greater. Multiple regression analyses were supplemented with relevant bivariate plots and
3-31
-------
univariate statistics (e.g., analysis of variance [ANOVA] t-test; /?<0.05) to confirm regression
results.
In addition, some variables such as the ffil, the EPT, and certain land-use data (e.g.,
distance from mines or urban areas) were categorized in various ways to determine whether
nonlinear or categorical relationships were present between sources and biological measures of
effect. For each biological sampling point, the effect of proximity to the nearest urban centers,
major roadways, or coal mine activities upstream was calculated and categorized as either <1 km,
1-2 km, or > 2 km, based on the preliminary riparian corridor analyses mentioned above.
Biological and habitat data were subjected to one-way ANOVA using these three proximity
categories as class variables and significance defined as p
-------
4. PILOT TEST OF RISK ANALYSIS APPROACH
4.1. BACKGROUND
Before implementing the risk analysis plan in the problem formulation, we pilot tested the
proposed analytical approach in a single subwatershed to address several specific questions:
• What is the appropriate spatial scale to test relationships between land-use activities
and stressors or measures of effect?
• What is the appropriate spatial context to test relationships between riparian corridor
vegetation (integrity) and measures of effect?
• What is the relative effect of upland versus riparian land-use activities on stream
habitat indices and measures of effect?
• To what extent can stream habitat indices be related to measures of effect?
• Is either the EFT or the fish IBI a reliable surrogate measure for native mussel
assemblage measures?
The Copper Creek subwatershed (Figure 4-1) was chosen to pilot-test our analytical
approach for several reasons. First, more data on fish, mussels, macroinvertebrates, and habitat
measures exist for this subwatershed than for the others. Second, the Copper Creek watershed
has relatively little urban or mining influences, compared with other subwatersheds in the Clinch
and Powell basin (Table 3-3), which made it easier to interpret effects of varying spatial scale or
upland/riparian comparisons on biota. Third, the Copper Creek subwatershed is fairly small
(34,344 ha) and therefore relatively manageable in terms of addressing the above questions.
Fourth, only this subwatershed had older (1960s to 1970s) and more recent (1990s) fish and
mussel data that could be used to interpret the effect of implementing agricultural BMPs in the
1980s. Finally, there were adequate mussel, IBI, and EPT data to determine the degree to which
either IBI or EPT values could be used as surrogate measures of effect for the mussel community.
4-1
-------
n
-------
4.2. RESULTS
4.2.1. Riparian Corridor Analyses
Initially, we examined percentages of different land uses upstream of each of the nine
CPRATS biological sampling points in Copper Creek. This analysis was used to examine upland
land-use effects on stream habitat and biological measures of effect (as defined in Table 3-2).
Figure 4-2 summarizes results of this analysis. The fish IBI showed weak negative relationships
with percent agricultural (crop and pasture) area upstream, whereas the EFT appeared to be
unrelated to upstream agricultural area. TVA's habitat quality index also appeared to be
unrelated to percent agricultural land use upstream. Thus, upland agricultural area appeared to
have little relationship to measures of effect examined in this analysis.
We then examined land-use effects at various riparian distances from the stream and
different distances upstream. Each biological sampling point was buffered at several different
distances surrounding the stream: 50,100,200, and 500 m and at 100,200,500, and 1000 m
upstream. Land-use proportions were then computed for each of these combinations for each
sampling point. We were particularly interested in contrasting the effects of percent forested area
Fish community integrity
60
Invertebrate community integrity
20
10 22 40 78 94 100
% Agricultural Use
Instream Habitat Quality Index
40
10 22 40 78 94 100
% Agricultural Use
0 5 10 22 40 78 94 100
% Agricultural Use
Figure 4-2. Summary of fish IBI, EPT, and habitat quality data for nine TVA
sites surveyed in Copper Creek, 1995-96, as a function of total upland agricultural
area above the sampling point. Habitat quality data were not collected by TVA at
two sites.
4-3
-------
or percent pasture area in these different riparian areas and ffil or EPT scores. Relationships
were not strong because sample size was limited (N = 9); however, significant correlations
between either percent forested area or percent pasture and the IBI appeared to be evident in
intermediate-size riparian areas (200 m buffer width and 500 to 1000 m upstream) (Table 4-1;
Figure 4-3). More refined land-use analysis of the CPRATS sites, using a 200 m buffer (100 m
on each side of the stream) and a 500 to 1500 m distance upstream, suggested an inverse
correlation between percent agricultural land in the riparian corridor and the ffil (Figure 4-4).
Analyses based on shorter or longer distances upstream (< 500 m or >1500 m) or narrower or
wider riparian widths appeared to result in poorer correlations between land use and the ffil. The
EPT was not as closely related to riparian land-use percentages as was the ffil. As many of these
sites were between 5 and 15 km away from each other, there was some uncertainty as to whether
there may have been cumulative effects of riparian corridor impacts for longer distances
upstream of each sampling point. This source of uncertainty was examined further using upper
Clinch River mussel data and fish ffil data for the watershed as a whole (see Chapter 5).
Correlation analyses using the nine CPRATS sites (six of which had habitat scores)
indicated no significant correlations between either percent upland agricultural land use or
riparian agricultural land use and habitat metrics such as embeddedness and instream cover
(Pearson correlation analysis, p>0.05). However, the sample size was very small.
Results of these preliminary analyses suggest that riparian vegetation characteristics
upstream of the sampling point are probably more important than total upland agricultural area in
defining native fauna integrity if the riparian area is not too narrowly defined; that is, 100 m on
either side of the stream (200-m width altogether) and several hundred meters upstream. This
riparian area could constitute a stream-specific optimal riparian management area .within which
to better prioritize protection efforts (Figure 4-5). The stronger relationships between riparian
land use and biota shown with these riparian corridor dimensions suggest that the fauna were
responding to influences outside and upstream of the immediate stream reach sampled. Given
limited resources, then, optimal benefits to fish, and perhaps invertebrates, would be realized by
focusing restoration efforts on the riparian corridor within a 500 to 1500 m distance upstream
and 100 m to either side of the stream for the site of interest.
We also explored the effect of riparian forest connectivity or continuity on ffil and EPT
values in Copper Creek. A 14-acre analysis window was used in which the stream was buffered
by 100 m on either side, with each window approximately 1275 m long. Percent forested area
was then computed within the 14-acre window. This analysis was repeated for the length of
Copper Creek and its major tributaries (Figure 4-6). Comparing ffil and EPT data for the nine
CPRATS sites with the forest connectivity information, we estimated that a riparian area
consisting of <50% forest or <500 m of continuous forest anywhere within a 1275-m segment
4-4
-------
Table 4-1. Summary of Spearman rank correlation coefficients between percent
agricultural area and the fish ffil as a function of different combinations of riparian
corridor width and distance upstream for Copper Creeka
Riparian width (m)
50
100
200
400
Distance upstream of biological sampling point (m)
100
0.09
0.19
0.14
0.09
200
0.14
0.24
0.18
0.14
500
0.10
0.26
0.30*
-0.18
1000
0.06-
0.09
0.34*
-0.20
2000
0.04
-0.11
-0.11
-0.19
"N=9
'«_»'
E
fi
•4-"
W
o
co
.£
*«
7J
400
300
200
100
50
POOR
50 100 200 500 1000
Distance upstream of site (m)
1500 2000
Figure 4-3. Illustration depicting the strength of relationships between land uses
and biological measures as a function of riparian buffer width and distance
upstream.
4-5
-------
60
50
40
ffl
i30
ul
20
10
5 10 22 40 78 94 100
% Agricultural Use
Figure 4-4. Fish community integrity as a function of agricultural land in the
riparian corridor (riparian corridor defined as 100 m to either side of the stream
and 1,500 m upstream).
Figure 4-5. Some pasture and row crop practices with the floodplain, karst, and
lowland areas pose serious risks to aquatic resources.
4-6
-------
N
w ~^*y E * * Headwater
s
Legend
Sample Sites
/\/ Steams and Rivers
Land Cover
Forest
Agriculture
fif f Miscellaneous
2024 Kilometers
Figure 4-6. Forest and agricultural uses in the riparian corridor (200 m wide) of Copper
Creek. Numbers represent macroinvertebrate EPT score and fish BI values in TVA's
CPRATS database, 1995-1996.
4-7
-------
had > 75% probability of being associated with impaired fish community integrity. A
relationship between the number of threatened and endangered mussel species present at a site
and surrounding land uses was also suggested, as shown in Figure 4-7. Riparian areas that were
more forested, particularly near the lower part of Copper Creek, exhibited higher numbers of
threatened and endangered mussel species than sites with more pastureland cover.
Several lines of evidence suggest that the distribution and abundance of mussels and fish
observed in Copper Creek are a function of stressors and not watershed or drainage area. First,
historically, many of the headwater areas of Copper Creek and other tributaries to the Clinch and
Powell Rivers supported a great diversity and abundance of mussels (Ortrnann, 1918) and native
fish species (Masnik, 1974). Thus, even small drainage basins in this watershed previously
supported diverse and abundant native fauna—far more than what is supported currently.
Second, very recent mussel surveys by Ahlstedt (1999) at many of the same sampling stations in
Copper Creek showed a decline in mussel species richness and abundance since the last survey,
in 1981. Ahlstedt reported increased sedimentation instream at most sites, which is consistent
with suggested stressor effects. Finally, even in our current analyses, there are several sites in
upstream areas of Copper Creek that have similarly high IBI values as those at sites near the
mouth. This observation would be unlikely if watershed area were the driving factor behind the
IBI values.
That result suggests that near-field (< 100 m) streamside riparian restoration efforts, for
example, might not be an effective means of enhancing fish or mussel diversity. Larger riparian
areas (as specified above) would need to be maintained. Furthermore, local instream habitat
characteristics may not be related to upland land uses if there is a wide vegetated riparian
corridor in those areas. Relationships with family-level EFT were less apparent.
4.2.2. Relationships Among IBI, EPT, and Stream Habitat Measures
On the basis of only the nine EPRATS Copper Creak sites, the IBI was uncorrelated with
the EPT r = 0.50, /?=0.17); however, both endpoints were significantly correlated on the basis of
entire CPRATS dataset (N = 95 sites, r = 0.52, /?<0.01) (Figure 4-8). Neither the IBI nor the EPT
was correlated with TVA's overall habitat quality index r = 0.20, and 0.22, respectively, p>0.50)
(Figure 4-9); however, both biological indices were correlated with lack of embeddedness r =
0.26,^=0.04 for the IBI and r = 0.29, p=0.02 for the EPT) (Figure 4-9), signifying that substrate
quality was a statistically significant feature affecting fish and invertebrate assemblage integrity
in the subwatershed as a whole. This analysis also suggests that TVA's multimetric habitat
quality index may dampen or mask the effects of specific habitat characteristics on aquatic
biological communities. Therefore, for the analysis of the entire watershed, it was useful to also
4-8
-------
inl
g
w
03
ffl
8
u
I
u
g
a
I
T3
£
o
u
13
o
8
8
&
13
W
I/I
d
TJ
6
bfl
§
T3
§
T5
§
1«
-------
Relationship between EPT and IBI for the 9 Copper Creek CPRATS sites
CD
54
48
42
36
30
24
11
65
55
45
CD
35
25
15
13
15
17
19
EPT
Relationship between IBI and EPT for the entire CPRATS dataset
12
16
20
EPT
Figure 4-8. Relationships between benthic insect EPT and fish IBI values
for TV A CPRATS sites (1995-96) in Copper Creek alone and for the entire
Clinch and Powell CPRATS dataset.
aN = 9;r = 0.50
bN = 95;r = 0.52
4-10
-------
£
•o
"5
U
£
n
CO
_co
•o
CO
m
CD
-is
JO
Relationship
"
o 1
1
a 0 o
CD OO O
o o
O CO O O
4> o
as oi o
o a> o o
o o oo p o
CO O O \O
O OJ . CD
CD 0
o o op o o
lo o o
0 CD Ot 00
o oco 1
1 o
N 00 Jt O CO CM 05 Tf
U)
CO
m
to
CO
•O CO
CD .a
•o "•'
TJ t
CD o
£ IS-
* a! g
= §
is
s !-
8|
Ifl Tl *
* g 8
5 =
S3 2
s 1
1 §
8 II
i ?
CO -0
c -a
o co
••3 -g
"03 UJ
a:
r - . '
» LJ Si UJ
S Jg CD (0
Q Q) ID
"5*
T^^^ 2
D ^
03 co
> 1
Ceo
if
w T3 O
w pS ^^
c SJ _,
•o ^ ~
•a S C
"S O j..
CM ^ ^ «
b r ^
O vj
2 «
B5
"c 2
•r. o
.^8
o 3 O
*-» O
ivnavH
111
X
1
^J*
3
a
<££
CO
_co
i-
•o
CO
•fc
UJ
c
CD
,1
CD
•Q
1
CO
1
13
CD
a
...
O 0
OI
CDO O
0
000 C
o
o
0 <
oo ca
0
0 0
OO 0
o o
Q
0 0
* CO C
o
CO
b o
o
i
5T
D | O
0
q
3 1
oo
CO
0
o
oo o
o
O 0
o
0
o
o
o o
o
§ 3 SI 5 5
1 W I IQWLJ
j. v J.IQ vn
o
CA
CO
CD
CO c ^"*
•<- -D In
CD CO
T3 ^
o •*
•Q 2
E —
CD In
_, 4^ CO
» S 8
H E a
1 li
•o ^
c: ;!
« s
co HO,
ffl 2
c £
CD q
CD O
& tfi
CD i>
*t c
"w "°
c s
0 J§
s 1
?°
UJ
C
ct
i
H
>R
^\
^
0
1
t
0
i
)
1
0
1 [ u
D_n
H"
D CO CM 00
N t- T-
Idi
C C
TO C
CO C
2 £
C
1
i
i
i
L
.
J
Q
•* •
CD
CO
•2
1
i
— J
'
<
^y
(D G FjH
2 03 j-
• !*.
.a ^
C *^
** t-
" O
S /""S
2 ^
S o
H
OS "
** trt
^ N^
U< E
*^ [r]
8 § «
g W 08
"c ^ ^
5 ^ u
0 S
« jj .a-£
JC "^
c ^
•^* ».
cS CD
13 •£
Pi -53
* ^C3
^^ c
i
« 'P
5 h C
3>8
ll
4-11
-------
examine relationships between biological measures and individual habitat quality metrics in
addition to relationships with the multimetric habitat index as a whole. Analysis of fish EBI
measures and embeddedness indicated that fish biological integrity was impaired in 90% of the
cases that had high or substantial substrate embeddedness (ANOVA, /?=0.03) (Figure 4-9).
In general, embeddedness affects macroinvertebrate and fish assemblages indirectly by
reducing the amount of available habitat for shelter, refugia, spawning, egg incubation, etc. As
rocks become embedded with fine sediment, the amount of interstitial space available for benthic
organisms in the substrate decreases. Thus, significant embeddedness of available substrates will
potentially impair the integrity of the biological communities.
In general, the IBI appeared to be a more robust and sensitive measure of effect than the
EFT for delineating habitat quality and land-use effects. One possible reason for this result is
that the EPT is based on family-level taxonomy. Although the EPT is often sensitive to various
habitat and chemical stressors (Lenat, 1984; Diamond et al., 1999), several recent studies have
indicated that family-level invertebrate metrics are less sensitive than genus- or species-level
metrics to environmental perturbations (Karr and Chu, 1999). Furthermore, the EPT is only one
potentially useful metric reflecting macroinvertebrate assemblage integrity (Barbour et al., 1999).
Another possibility is that the EPT may recover from spills or other episodic events relatively
quickly and, therefore, may not be as sensitive an indicator of past water quality effects as either
native mussels or fish.
4.2.3. Analyses of Mussel and Fish Data in Copper Creek
We examined spatial relationships of native mussel and fish species richness in Copper
Creek (Figures 4-1 and 4-6). Native mussel and threatened and endangered species data were
derived from TVA's CMCP survey conducted in 1981 (32 sites). Fish data (35 sites) were
obtained from Masnik (1974). Figure 4-10 plots the species richness values observed for both
fauna as a function of stream river mile. With two exceptions (river miles 6-9 and 25-30) there
was a reasonable fit between the two fauna because both generally tend to peak or trough at
similar locations along Copper Creek. This suggests that both species richness measures were
responding to similar stressors and/or that mussel species richness is in part dependent on the
presence offish host species. In general, greatest mussel species richness was observed in the
lower 3 miles of Copper Creek, coincident with the large forested riparian area there. Areas in
the "gorge," approximately 7 to 10 miles upstream of the mouth, had fewer mussel species,
coincident with the fact that this area is within and directly downstream of a large agricultural
(pasture) area of the watershed. However, this area had relatively high fish species richness.
4-12
-------
sepeds |assni/\j jo jeqwriN
CM
in
in
oo co
CM
_
0
CO
.C W
W 3
in
m
co
m
CM
in
in
8
IO
o
10
in
o\
•3
CO
1
•s
ffi
I
O (J
0)
m
CM
o
CM
in
in
s
•a
CA
oo
CO
ft)
4
g
fe
4-13
-------
Although these results could also be explained by a general increase in species with
increased drainage area, fairly high fish and mussel species richness values were observed in the
upper part of the creek, where upstream forested riparian area was also relatively extensive,
though not as continuous as in the lower part of the creek. Overlaying mussel species richness
• values with the forest connectivity data layer (Figure 4-7) also suggested that mussels were
responding, at least in part, to the extent of naturally vegetated riparian corridor area bordering
Copper Creek. These results suggest that the extent of upstream riparian forested area is a
critical factor that affects both mussel and fish assemblages in Copper Creek and that both types
of fauna are not responding only to stream flow or drainage area.
Follow-up mussel sampling in Copper Creek in 1998 (Ahlstedt, 1999) indicated a general
decline in the number of mussel species, the number of endangered species, and mussel
abundance for most Copper Creek sites as compared with the 1981 CMCP survey (Figure 4-11).
The report noted increased sedimentation at several sites, primarily because of livestock watering
and runoff from pastures within the riparian corridor. These results indicate that riparian corridor
integrity alone will not ensure adequate aquatic life habitat and maintenance of mussel
populations if upstream sedimentation is severe enough.
Mussel and fish data from Copper Creek support the hypothesis that both types of fauna
are more responsive to riparian conditions than to more distant upland uses. Clearly, local stream
geomorphic features also are likely to affect fish and mussel assemblages, because forested
riparian corridor area only partially explained distribution and abundance of either fauna.
Unfortunately, quantitative habitat quality measures were not collected concurrently with the fish
or mussel data, and therefore we could not analyze habitat-biota relationships with those data.
However, numerous studies have documented the important effects of local geomorphology and
habitat quality on mussel (Stansbery et al., 1986; Church, 1996) and fish species richness
(Angermeier and Smogor, 1993) in this watershed.
4.2.4. Temporal Comparison of Fish and Mussel Data in Copper Creek and Evaluation of
Agricultural BMPs
In this analysis, we compared the fish species richness values collected by Masnik (1974)
with the fish IBI values measured in CPRATS during 1995-96 and the mussel data collected by
Ahlstedt in 1981 and again in 1998 (Ahlstedt, 1999). In the intervening years, agricultural BMPs
designed to reduce sediment runoff into the stream were implemented at several sites in the
Copper Creek watershed.
Figure 4-12 depicts fish results for those sites in which there were overlapping data from
the two surveys. Data are expressed on a relative scale because we compared two different
indices: the IBI and fish species richness. In each case, data for each site were expressed as a
4-14
-------
o
CD
1—
CD
LO
10
O
IO
LO
CO
® 00
I
«
fe
1
«
1
*.
-^v
^^^^t
>>
^
x^
.
o jg
- co ~
0)
^
oi
lO
" CM
O
CM
- J*;
^
V. 9
•^.
o\
Os
1— 1
•d
§
T— 1
00
ON
rH
J^
9^
u
a,
o
U
c
*fH
CO
.2
1
09
CO
CO
. 3
- io
CM O 00 CD
^ T—
sepeds |essny\| |o jequinN
(4-4
o
4-15
-------
10 12 24 32 43 43 50
River Mile
1969-71
1995-96
Figure 4-12. Fish IBI in 1995-96 compared with fish species richness observed in
1969-71 in Copper Creek. Data for each year area expressed as a relative fraction of the
highest value obtained in that year.
fraction of the highest value observed for the eight or nine sites available. The results suggested
a similar trend with river miles in both time periods, possibly indicating similar conditions for
the two time periods. Relatively higher fish IBI scores were observed in 1995-96 at river miles
2,10,12 and at the first of two sites at mile 43 as compared with other sites. This indicates
relatively greater improvement in conditions at these sites in 1995-96 as compared with other
sites. This result suggests some beneficial effect of BMPs, particularly at river mile 2, which was
downstream of several BMP sites in the watershed. However, the mussel data shown in Figure
4-10, which were also collected before and after BMPs were implemented in Copper Creek,
suggested little beneficial effect of BMPs on mussel populations. Indeed, Ahlstedt (1999)
reported increased sedimentation at many sites, including several in the lower part of Copper
Creek downstream of several BMP sites. Thus, contrary to the results for fish, it appears that the
implemented BMPs had little if any beneficial effect on mussels and that sedimentation was not
controlled. However, the extent and location of the BMPs, as well as the way in which they were
performed in this subwatershed, may not have been sufficient to reduce agricultural sediment
effects in Copper Creek..
4-16
-------
5. RISK ANALYSIS FOR THE CLINCH AND POWELL VALLEY WATERSHED
Results of Copper Creek pilot analyses indicated that it was useful to analyze biological
measures of effect, such as the fish IBI, and compare them with riparian corridor integrity, land
use, and stream habitat quality measures. We extended these analyses to the CPRATS dataset as
a whole, which comprised 153 sites located throughout the Clinch and Powell watershed. Data
for fish, benthic macroinvertebrates, and habitat quality had been collected at many of these sites
between 1995 and 1997.
In addition to using percentages of various major land uses (herbaceous-pasture,
cropland, forest, and urban/barren land) as potential sources of stress, we also incorporated
proximity to mining activities, major roads, and urban centers as sources. For these analyses, we
created a coverage using ArcView, displaying the location of mines, coal preparation plants, or
urban centers and CPRATS sites in the Clinch and Powell watershed. Using ArcView Spatial
Analysis, 1- and 2-km buffers were created around each of the mines or urban centers. These
distances were based on the results of the Copper Creek pilot testing, which suggested distances
of 1 to 2 km upstream of a sampling point as being a relevant distance for evaluating land-use
sources and effects. Three site categories were created, based on the location of the CPRATS
sites: sites less than 1 km, sites 1 to 2 km, and sites greater than 2 km from a mine or urban
center. Transitional sites that were on or very close to the 2-km border were eliminated.
Proximity of a site to roads was included in this analysis as a surrogate indicator of sources of
episodic spills. Transportation corridors, and particularly roads, have been sites of several truck
accidents that resulted in spills of toxic materials. We also anticipated some habitat effects due
to sedimentation from road construction and maintenance. Three classifications of roads were
examined: four-lane State or U.S. paved roads, two-lane county or State paved roads, and
dirt/gravel roads. The data were then aggregated into a single table and imported into Statistica
for statistical analysis.
Forward stepwise multiple regression analysis was used to relate potential sources of
stress (land-use percentages, proximity to urban or mining influences, and proximity to the three
classes of road) to the fish IBI and the macroinvertebrate EPT. However, prior to examining
effects of sources, we characterized effects of site elevation on biological measures of effect,
because the entire CPRATS dataset covered a wide range of elevations and drainage areas, which
could confound interpretations of land-use effects.
5-1
-------
5.1. RELATIONSHIP BETWEEN STREAM ELEVATION AND BIOLOGICAL
MEASURES OF EFFECT
The IBI exhibited a significant increase as elevation decreased (r = 0.54,/xO.Ol) (Figure
5-1), but the EPT and habitat quality measures were less related to elevation (r = -0.19, ^=0.05
and r = -0.16, p=0.16, respectively). We expected greater fish and possibly EPT richness at
lower elevations, because river reaches at lower elevations are broader and offer more diverse
habitats for aquatic fauna (Vannote et al, 1980). Also, the available species pool or species
richness is usually related to watershed area and, consequently, inversely related to elevation
(Vannote et al., 1980; Karr and Chu, 1999). However, lower reaches also may be at greater risk
from the cumulative impact of upstream stressors (Karr and Chu, 1999). Thus, competing
factors may affect EPT species along a stream length, resulting in complex geographic patterns.
The effect of elevation on the IBI was best demonstrated by categorizing IBI scores as
either "impaired" or "unimpaired" (using TVA's ratings) and comparing the mean IBI values for
these two categories against elevation (Figure 5-1). t-Test analysis indicated significantly lower
IBI scores at higher elevation sites (p<0.01). Cumulative frequency analysis indicated that sites
higher than 500 m in elevation had better than an 85% probability of having unsatisfactory or
impaired fish community integrity.
Because nearly half of the CPRATS sites that had concurrent habitat and biological
information were located between 350 and 450 m elevation, and there was no elevation effect on
the IBI or the EPT within this range, we concentrated subsequent multiple regression analyses for
sites within 350 and 450 m elevation. A broader elevation range resulted in significant elevation
effects. Fewer than 5% of the sites (5 out of 153) were < 350 m in elevation.
5.2. EFFECTS OF LAND USE ON HABITAT QUALITY MEASURES
Relationships between land cover and those stream habitat features measured by TVA in
its habitat quality assessment (see Table 3-2) were analyzed using forward stepwise multiple
regression analysis. This analysis produced few significant relationships between land uses or
sources and habitat features reported at a given site, based on an elevation range of 350 to 450 m
(R2 = 0.42, p-Q,04, N = 85). This result may be due to a lack of statistical power; we did not
have a balanced representation of sites that had different land use combinations in our analyses.
Figure 5-2 summarizes significant relationships observed between land use and habitat.
Stream sedimentation was lower where cropland was <3% of total land use. Riparian integrity
was better in areas in which pasture/herbaceous land was < 50% of the total land use. Instream
cover was poor if urban land use was ^20% of the surrounding area upstream. Together, these
relationships suggest that instream habitat will have the highest probability of being satisfactory
5-2
-------
m
65
55
45
35
25
15
250
CD
O> O
O> (D
O O O O O
(DO O
""" -Q O O O 0
"•--.. *'---.(D C
""••-op"''---^"-c
o
o
00 O 0
o
o
o
o
o o o oo "
O CED
O 00
o o
o
o
"•--.. ""--/""vo, o o
o o ''--.""•0-."'-o... o o
o ""---./6'o>.. ""•----.. o
o ""--opbo-.., ""••---..
O nm o ~O,. ""-O..O 1
O O O CO COO '-O. '"•-.,
O O
-------
Cropland vs. Stream Sedimentation
Pature / Herbaceous Land vs. Riparian Vegatatlon Integrity
80
LOW
Mean+/-SD
Mean i-ASE
Mean
£ 40
£
I 20
Stream Sedimentation
100
80
•a
2 M
m 40
c
I 20
Poor Good
Riparian Integrity
Z Mean+/-SD
Q Mean+/-SE
a Mean
Urban / Barren Land Use vs Instream Cover
ss
0
I
•201*
Poor Fair Good Excellent
Instream Cover
JC Mean+/-SD
n Mean+/-SE
° Mean
Figure 5-2. Relationships observed between land-use activities and instream habitat measures
for sites in the Clinch and Powell watershed, based on TVA's CPRATS dataset and a restricted
elevation range of 350-450 m (N = 85).
if cropland or pasture land is relatively low and urban influences are small or spatially removed.
Proximity to roads did not appear to be significantly related to habitat measures (p>0.2).
Examination of sites at higher elevations (500 to 600 m) did not yield significant
relationships between habitat measures and sources. However, some relationships were observed
between stream channel stability and sources (R2 = 0.20, p=0.08, N = 39). Sources in order of
significance in the regression model were four-lane roads, percent cropland, proximity to active
mining, and percent pastureland; however, p values for all source variables were > 0.13. No
other habitat measures yielded a significant regression model. Thus, most of the variability in
habitat measures of effect was not explained by the source data available.
Contrary to expectations, habitat quality scores and important habitat metrics, such as
embeddedness or sedimentation, were not significantly different in relation to distance from coal
mines for the entire CPRATS dataset (ANOVA, p>0.50). We anticipated an increase in fines
and embeddedness at sites closer to active mines. These results may be due, in part, to the fact
5-4
-------
that other land uses such as cropland or pasture also can result in increased sedimentation and,
therefore, we were less apt to observe a specific effect of mining on sedimentation. Ample
evidence from a number of sources has documented increased sedimentation from coal fines in
the upper Powell and North Fork Powell rivers (Dennis, 1985; Wolcott and Neves, 1994; VDEQ,
1996), and these habitat impacts were highly correlated with decreases in mussel species richness
and abundance.
Some interactions between land-use factors and resultant habitat features were evident, as
shown in three-dimensional contour plots (Figure 5-3). Instream cover and embeddedness were
affected by both the percent pasture/herbaceous cover and the percent urban area nearby. Both
land uses contribute sediment to the stream and reduce available substrate diversity, which
contributes to embeddedness and poor cover for fish and invertebrates. The lower the percentage
of either use, the better the instream cover and the lower the instream embeddedness (Figure 5-
3A and 3B, respectively). This result is consistent with the fact that instream cover is, in part,
inversely related to the amount of embeddedness present. However, we observed unexpectedly
high embeddedness and instream cover scores (i.e., good cover and low embeddedness) at
intermediate urban percentages (-30% urban cover) when percent pasture cover was low
(< 30%). This result probably illustrates the fact that certain land-use combinations are less
represented than others, which is a limitation of the available data set. This data constraint is a
potential confounding factor in risk analysis for any watershed, given the general sparcity of
available data.
Riparian corridor integrity was affected primarily by the percent pasture/herbaceous land
upstream (as observed in Copper Creek), but mining or urban proximity also appeared to play a
role: in both cases riparian integrity suffered with close proximity to mining or urban influences
(Figure 5-3C and 3D, respectively). Thus, a combination of both agricultural area in the
immediate vicinity of a site and urbanization or mining upstream appeared to yield poor riparian
integrity.
5.3. RELATIONSHIPS BETWEEN LAND USE AND BIOLOGICAL MEASURES OF
EFFECT
5.3.1. The Fish IBI
Given the previous established relationship between elevation and the fish IBI (Figure 5-
1), these analyses focused on sites at an elevation between 350 and 450 m, for which elevation
was not a confounding effect (p>0.2). Forward stepwise multiple regression analyses indicated
that proximity to mining was the most significant factor related to the IBI values and that percent
pasture area was directly related to the IBI, whereas proximity to mining, percent cropland, and
percent urban land were inversely related (Table 5-1). Proximity to roads was not a significant
5-5
-------
t), .
^r^wS^VA
IDDDDl
O
B
O
W
5-6
-------
Table 5-1. Summary of forward stepwise multiple regression analyses of fish IBI
values, obtained in TVA's CPRATS dataset for the Clinch and Powell Watershed,
and land-use factors
Model
CPRATS sites between 350
and 450 m in elevation
N
38
R2
0.55
Influencing factors
Proximity to mining
Percent pasture area
Percent cropland
Percent urban
Association
-
+
-
-
Partial R2
0.18
0.15
0.06
0.04
P
0.013
0.019
0.15
0.23
factor in the regression model. However, 45% of the variability in IBI scores was unexplained by
our model, indicating that (1) the composite nature of IBI scores may conceal relationships
between fish assemblage and land uses; (2) other site-specific factors, such as hydrologic regime,
proximity to accidental chemical spills, or other water quality effects are significant sources of
stress in this system; or (3) statistical power was hampered by unequal representation of sites
with different land-use combinations.
The relatively beneficial effect of pasture/herbaceous land on fish community integrity for
the watershed as a whole and at mid-elevations (Figure 5-4) was unexpected, based on the pilot
analyses using data from Copper Creek only (section 4.2). However, it should be noted that
extrapolation between watersheds in these analyses was subject to some uncertainty because
stream size is not constant across subwatersheds (but see section 5.6). The indication of a
relative beneficial effect of pasture/herbaceous land on fish community integrity probably
resulted because (1) there is historically greater livestock pressure in Copper Creek than in
most other agricultural areas in the Clinch and Powell watershed (Don Gowan, TNC, at the
Clinch assessment workgroup meeting, December 1,1998), (2) pastures have potential nutrient
enrichment effects on fish communities, and (3) mining and urban areas are comparatively far
more detrimental sources of stress than pasture areas as a whole on fish in this watershed. In
fact, we observed that percent forested land cover was greater near mining activity than it was
farther away (ANOVA, N = 152, F = 5.93, p=0.003), and it was negatively correlated with
pasture land cover (r = -0.80, p<0.05). As a result, sites with higher IBI scores (i.e., better fish
community integrity) were associated with less forested cover than sites with lower IBI scores
(poorer fish community integrity; N = 137, t = 3.01, p=0.003). Thus, this analysis confirms that
proximity to mining has a profound effect on fish communities in this watershed.
5-7
-------
Coal Processing Plants
IM
E 7
1 5
2 -*
a -
« J
o o
O 2
§°
Pasture / Herbaceous Land
(T-test, p = 0.02, N = 137)
IBI Poor IBI Good
Urban / Barren Land
(T-test, p = 0.02, N = 137)
ou
70
60
50
40
30
20
10
0
i
i
i
I i
Poor Good
ZC ±Std.Dev.
C3 ±Std. Err.
° Mean
oy
30
25
20
15
10
5
0
-5
I = I
r— •— '
Poor Good
HI ±Std. Dev.
CU ±Std. Err.
° Mean
Figure 5-4. Significant relationships observed between land-use sources and the IBI for
the entire CPRATS data set (N = 155).
Mining and urban areas appeared to have clear, negative effects on the IBI (ANOVA,
p<0.01) (Figures 5-4 and 5-5). One potential stressor from mining is discharge of toxic
contaminants. For example, a prior study (BMI, 1990) found that the hydraulic fluid typically
used in longwall (deep) coal mine machinery is highly toxic to many types of aquatic species and
especially to larval mussels (Figure 5-6). Although actual exposure concentrations of this *
material in the stream have not been documented, it is known that at least two different fish kills
on the North Fork Powell (1986 and 1988) were caused by acutely toxic discharges of hydraulic
fluid (BMI, 1990). Water-quality impacts from coal mining are also suggested by examining the
relative effects of different types of mining activities on the fish IBI. Figure 5-7 shows that the
fish IBI is more depressed downstream of either coal processing plants or surface mines, as
compared to sites with no mining activity present (ANOVA, p< 0.05). Both of these coal mining
activities contribute water quality and physical (coal fines) stresses on aquatic biota.
A recent study conducted by FWS (Lingenfelser, 2000) on samples collected from several
coal processing plant discharges in the Clinch and Powell watershed yielded similar information.
Chemical and lexicological quality of the samples as well as benthic macroinvertebrate
assemblage integrity were evaluated by FWS downstream of four different facilities. Several
species were subjected to toxicity testing, including glochidia and juveniles of two surrogate
5-8
-------
ffl
oo
50
45
40
35
30
25
20
4R
*
N =
C
*
31 N =
3 I
•
»
*° | C
N =
] I
81
< 1 Km 1 - 2 Km > 2 Km
Distance from nearest Mining Activity
* = significantly different from sites > 2km from mining
I ±Std. Dev.
CU ±Std. Err.
° Mean
IB
16
14
12
t
ui 10
8
6
A
*
N = 25
n
•
° I
D
N=28
N = 58
< 1 Km 1 - 2 Km > 2 Km
Distance from nearest Mining Activity
* = significantly different from sites > 2km from mining
±Std. Dev.
±Std. Err.
Mean
Figure 5-5. Fish IBI or insect EPT values in relation to proximity to coal mining
sources. Data derived from TVA's CPRATS dataset (1995-1997).
5-9
-------
Fish Mussel larvae Mayfly Snail Water flea
Figure 5-6. Comparison of acute toxicity results (LC50) for several species, based on laboratory water
exposures of a hydraulic oil commonly used in coal longwall mining machinery in the Powell River
subwatershed. The higher the LC50, the less toxic the chemical. Actual species tested included
Pimephales promelas (fathead minnow), Villosa spp. (mussel), Stenoneina spp. (mayfly), Physella spp.
(snail), and Ceriodaphnia dubia (water flea).
Source: BMI1990.
No Mine Proccessing Plant Surface Sub-Surface
Type of Mine within 2 Km of Site
Figure 5-7. Effect of mine type on fish community integrity as a function of the type of
mine.
= significantly different from sites having no mining activity present within 2 km.
5-10
-------
mussel species, the amphipod sediment indicator species Hyalella azteca and the EPA freshwater
indicator species Ceriodaphnia dubia and Pimephales promelas.
Iron, nickel, and selenium occasionally exceeded EPA water quality criteria at the process
discharges, and several other metals approached water quality criteria. No other contaminants
were detected in these samples. A few samples were reportedly toxic to Ceriodaphnia and
Hyalella:, however, data were limited both in terms of number of samples and types of sites
tested. Benthic macroinvertebrate sampling indicated generally poor assemblage integrity
downstream of all coal processing discharge sites, as exemplified by fewer taxa, number of
individuals, pollution-sensitive taxa such as the EPT, and lower diversity of taxa, as compared
with either reference or upstream sites. Thus, these preliminary data also indicate deleterious
effects of coal processing activities on aquatic life in the Clinch and Powell watershed.
The impacts of urbanization on watersheds are well documented (Jones and Clark, 1987;
Karr, 1991; Schueler, 1994). They include increased sediment loads, nutrient input, and toxic
input. These problems are exacerbated by the increase in impervious surfaces prevalent in urban
areas. Stream degradation occurs at relatively low levels of imperviousness (10-20%) (Schueler,
1994).
One site-specific factor that could be important is point-source pollution such as
industrial or municipal wastewater discharges. Effects of point sources were not explicitly
included in our analyses because of the few significant dischargers and the fact that many of the
major ones were assumed to be encompassed in the urban land use classification. Other
information collected during this risk assessment indicated significant effects of large point
sources on native mussels and other aquatic life (Cairns et al., 1971; Grossman et al., 1973;
Goudreau et al., 1993).
Another stressor difficult to characterize in this risk assessment is catastrophic spills of
toxic materials. Figure 5-8 summarizes the types of effects observed after catastrophic spills at
Westmoreland Coal Company and the APCO power plant on the Powell and Clinch rivers,
respectively. In 1998, a large coal slurry impoundment on the upper Powell River failed,
resulting in a massive fish kill and substantial mortality of native mussels for a distance of more
than 20 miles downstream (Hylton, 1998). A 1999 truck accident on the upper Clinch River in
the Cedar Creek area resulted in substantial loss of mussels, including more than 300 threatened
and endangered mussels.
5.3.2. The Macroinvertebrate EPT
The invertebrate EPT score exhibited more limited relationships with sources than did the
IBL Forward stepwise multiple regression analyses indicated that the EPT was related to percent
urban area, proximity to roads, and percent pastureland for sites between 350 and 450 m in
5-11
-------
70
60
w 50
-------
Table 5-2. Summary of stepwise multiple regression analyses of macroinvertebrate
EFT value in relation to potential sources of stressors in the Clinch and Powell
watershed. Based on TVA's CPRATS data set.
EPT sites 350-500 m
elevation
34
0.29
Influencing Factors
=====
Percent urban area
Percent pasture
Proximity to mining
0.14
0.08
0.07
0.033
0.127
0.145
20
16
HI
Percent Urban Land vs. the EPT
111
Urban Land vs. the EPT
20 40 60 80 100
% Urban / Barren
EPT Assessment vs. Percent Urban Area
16
12
4
n
n
3 T
_ o
T
T
a
1
Percent Urban Land
(0
60
50
| 40
20
10
0
Poor
Good
HI Mean+SD
Mean-SD
CHI Mean+SE
Mean-SE
o Mean
EPT
IH Mean+SD
Mean-SD
HZ! Mean+SE
Mean-SE
a Mean
Figure 5-9. Significant relationships between land-use activities or habitat quality and
invertebrate EPT score. (R2 = 0.29) .e
5-13
-------
macroinvertebrates recolonized damaged areas relatively quickly (within 1 year) (Grossman et
al, 1973), whereas native mussels and fish have largely not recolonized this area of stream as of
this writing (Figure 5-8). Thus, the EPT may recover from spills or other episodic events
relatively quickly and, therefore, may not be as sensitive an indicator of past water quality effects
as either native mussels or fish.
5.3.3. Mussels
TVA's CMCP data were used for these analyses. Unfortunately, data for only 33 sites (in
addition to the 32 sites in Copper Creek discussed in section 4.2) were readily available, although
far more data are known to be archived in TVA's database. Resource constraints did not allow
these other data to be retrieved and incorporated into the GIS. Other published information was
used, when relevant, to help supplement our analyses and aid in interpreting the data.
CMCP data were available for river miles 73 to 166 on the Powell River and 159 to 322
on the Clinch River. Data available for each site included number of mussels, number of native
and endangered species collectively, and number of endangered species only.
Forward stepwise multiple regression analysis indicated that none of the riparian land use
factors were significantly related to mussel density for both rivers combined or for either river
separately (p>0.20). A significant model could not be constructed for native mussel abundance,
indicating that the factors available had little explanatory value for this measure of effect.
Number of native mussel species, however, was related to several variables, including (in order
of significance) percent urban area, proximity to mining, and percent cropland (Table 5-3). Sites
further upstream, far from towns or mining, or having agricultural land use instead of urban or
mining activity directly around and upstream of the site tended to have a greater number of
mussel species present (R2 = 0.26, F = 3.01, /xO.03).
However, this model explained only 26% of the variability in mussel species richness,
indicating that other unmeasured factors affect mussel distribution in these rivers. As most of
these sites were located on the mainstem rivers, land-use combinations were limited in our
analysis, reducing statistical power. The likely factors contributing to the unexplained variability
in mussel species richness are (1) site-specific geomorphic characteristics such as substrate
particle size, flow and current velocity, and orientation of bedrock ridges (Church, 1991), (2)
proximity to episodic spills that could not be adequately analyzed in this risk assessment, and (3)
fish host assemblage in the area varies from year to year.
Subsequent analyses of mussel data in the upper Clinch subwatershed indicated
significant relationships between riparian land-use factors and mussel species richness,
particularly if geomorphological factors such as drainage slope are taken into account (see
section 5.6).
5-14
-------
Table 5-3. Summary of forward stepwise multiple regression analysis of
Cumberlandian mussel species richness as a function of riparian land-use factors.
Data are from TVA's CMCP database
Model
All CMCP sites
33
0.26
Significant factors
!•
Percent urban area
Proximity to mining
Association
Partial R2
=====
0.09
0.05
0.007
0.05
Results of the foregoing analyses in this section indicate that riparian land uses accounted
for, at most, 55% of the variability in biological measures, although certain land use-response
relationships were clearly evident. The riparian corridor dimensions used in our analyses were
derived from data for the Copper Creek subwatershed and then extrapolated to other streams.
However, it should be noted that the assumptions about extrapolating from small to large systems
must include system characteristics (see section 5.6). Larger streams such as the upper Powell or
upper Clinch rivers could conceivably have different relationships between land uses and
biological measures. Thus, upland land uses or larger riparian areas may need to be considered
in future assessments for this watershed to confirm relationships between land uses and
biological measures of effect.
5.4. RELATIONSHIPS BETWEEN HABITAT MEASURES AND BIOLOGICAL
MEASURES OF EFFECT
Table 5-4 summarizes results of stepwise multiple regression analyses on habitat
measures and both the fish IBI score and the macroinvertebrate EPT. These analyses used the
entire elevation range of sites in the CPRATS dataset because elevation was uncorrelated with
habitat measures (p>0.2). In addition to the individual habitat metrics measured by TVA, the
overall habitat score for a site reported by TVA was also used as an independent variable in the
analysis because it was uncorrelated with any of the metrics (R = 0.20, p>0.10).
Figure 5-10 shows relationships between either embeddedness (or the inverse, clean
sediment in the figure) or instream cover and the fish IBI, categorized as either poor or good
(based on TVA's criteria). In both cases, better IBI scores were associated with more cover and
clean substrate. Streams with either embeddedness scores of <2.0 or instream cover scores of
< 3 had a greater than 90% chance of having poor fish community integrity. Given that we
observed negative relationships between pasture/herbaceous land cover or urban proximity and
embeddedness (Figure 5-2), it is not surprising that both of these land-use activities have effects
5-15
-------
Table 5-4. Summary of forward stepwise multiple regression analyses of habitat
quality measures in relation to either the fish IBI or the macroinvertebrate EPT.
Data are from TVA's CPRATS dataset for sites between 350 and 500 m in elevation
Model
IBI
EPT
N
81
65
R2
0.29
0.23
Significant Factors
Instream cover
Channel stability
Embeddedness
Habitat score
Epifaunal substrate
Channel stability
Epifaunal substrate
Instream cover
Habitat score
Embeddedness
Association
+
+
-
+
-
+
-
+
+
-
Partial R2
0.12
0.10
0.07
0.06
0.01
0.10
0.06
0.04
0.05
0.02
0.002
0.006
0.024
0.026
0.252
0.014
0.055
0.105
0.067
0.228
on fish assemblage integrity (Figure 54). The EPT was significantly related to instream channel
stability and epifaunal substrate, a measure of the substrate complexity or heterogeneity in
particle size and woody snag material for benthos (Figure 5-11). Both of these habitat measures
are important features that directly affect macroinvertebrate diversity (Karr and Chu, 1999;
Barbouretal., 1999).
The relatively small variability in biological measures explained by habitat measures in
these analyses (total variance explained in either the EPT or the IBI does not exceed 30% in
regression analyses) (Table 5-4) suggests that chemical stressors may play a significant role.
Unfortunately, we were unable to characterize chemical stressors because of a lack of relevant
data. There are only two long-term water quality stations in the entire watershed, both located in
the lower part of the watershed. Potential chemicals of concern, such as pesticides, coal mining
chemicals, and heavy metals were largely unmeasured. Thus, water quality stressors were
inferred in this risk assessment on the basis of nearby land use/source activities in association
with biological effects and habitat quality information. However, the habitat data used were
highly qualitative, which may add uncertainty to these analyses. Our experience suggests that
some investigator bias cannot be avoided in using such qualitative assessment protocols. These
results underscore the difficulties in deriving stressor-response relationships on a watershed
scale.
5-16
-------
Relationship between clean stream sediments and the fish IBI
(T-test, p = 0.02, N =80)
8O C
O.D
W oo
~ 3.2
0)^0
E 2-8
"§ 2.4
S i •
— 1.6
I t
I
| D I
3 I
Poor
Good
HI iStd.Dev.
CH ±Std. Err.
D Mean
Relationship between instream cover and the fish IBI
" (T-test, p< 0.001, N = 80)
£4.4
8 4.0
§ 3.2
C £>,\J
g 2.4
1 2.0
I i
1
n..» l^/-
. __,
1C ±Std. Dev.
CD ±Std. Err.
° Mean
Figure 5-10. Relationship between stream embeddedness or cover and the fish IBI, categorized
as either poor (impaired) or good (unimpaired), based on TV A's criteria.
5.5. CUMULATIVE EFFECTS OF LAND USE ON ASSESSMENT ENDPOINTS
Another analysis was structured to assess the cumulative effects of land use on
assessment endpoints. The EPT and IBI scores were examined by subwatershed, recognizing
that the type and intensity of stressors varied among subwatersheds (Table 3-3). Both the EPT
and the IBI were lowest in the Guest River subwatershed (ANOVA, /?<0.05) (Figure 5-12). The
EPT was also significantly lower in the upper Powell than in either the Copper Creek or the
upper Clinch River subwatersheds (ANOVA, /xO.05) (Figure 5-12). The ffil was not
significantly different for these three subwatersheds (Figure 5-12). The Guest River has had
intense coal mining activity and acid mine drainage for many years and few other land-use
stressors, such as urban or pasture influences. The upper Powell subwatershed is similar,
although there is slightly more urban area than in the Guest River subwatershed. Thus, coal
mining activities appear to have had the greatest influence on insect and fish abundance and
distribution in the Clinch and Powell watershed as a whole.
5-17
-------
Instream Channel Stability
N = 65; t = -3.058, p = 0.003
instream Channel Score
«+.o
4.4
4.0
3.6
3.2
2.8
2.4
2.0
1 D |
D .
bad
good
HZ ±Std. Dev.
CD ±Std. Err.
° Mean
EPT
4.2
3.6
*
%
a
-
II
ui
2.4
1.8
1.2
Epifaunal Substrate
N=65;t = -2.506, p = 0.013
Poor / Fair Good / Excellent
EPT "
3_ ±Std. Dev.
Z] ±Std. EIT.
n Mean
Figure 5-11. Significant relationships observed between specific instream habitat quality
measures and the macroinvertebrate EPT index.
5-18
-------
UJ
18
14
10
Upper Clinch Copper Creek Guest River Upper Powell
CQ
65
55
45
35
25
15
Upper Clinch Copper Creek Guest River Upper Powell
Figure 5-12. Macroinvertebrate (EPT) and fish (IBI) community integrity scores by
subwatershed in the Clinch and Powell watershed based on TVA's CPRATS dataset.
Boxes represent standard errors of the mean and whisker bars represent standard
deviations of the mean.
5-19
-------
Distribution and abundance data for mussels were not as readily available on a
subwatershed basis as they were for insects and fish. Using the limited CMCP data for the Clinch
and Powell rivers (33 sites), we observed no statistical difference in either abundance or number
of species of Cumberlandian mussels between the two rivers (Figure 5-13), although species
richness was close to being significantly higher in the Clinch River 0?=0.07) (Figure 5-13). It is
well known that most of the historic (pre-1910) mussel bed locations in both rivers have declined
dramatically or been eliminated (as denoted by the reduction in red areas in Figure 5-14). Coal
mining activity is one of the factors causing this pattern.
Li a second type of analysis, land uses that have been determined to cause the most stress,
based on either previous stepwise multiple regression analyses presented or professional
experience of the workgroup, were expressed as a binary function: 0 if the particular type of land
use was not present or nearby (within 2 km) and 1 if the land use was present. Prior analyses
(Figure 5-7) demonstrated that gradients of effects based on proximity to land uses were riot
readily apparent but that threshold responses were. Table 5-5 summarizes the criteria used to
designate a 0 or a 1 for those selected land uses causing the most adverse impacts. All criteria
were based on results observed previously in risk analyses using the CPRATS data summarized in
Figure 5-4 and Table 5-3.
Using the criteria in Table 5-5, we then computed a cumulative stressor index for each
site. This index ranged from 0 to 4 because four significant sources of stress were considered.
Because of the paucity of mussel data in the Guest River, only CMCP data from the Clinch and
Powell rivers were used in this analysis. t-Test analysis indicated that the cumulative stressor
index was greater in the Clinch River than in the Powell River (Figure 5-15) (t = -2.24, p<0.05)
because of the greater frequency of urban/industrial sources and U.S. highways near the Clinch
River. Mining is the chief source of stress in the upper Powell. In the Clinch River, the
cumulative stress index increased as one progressed upstream (N = 14, r = 0.74,/?<0.05)(Figure
5-16) because of more mining and urban influences in the upstream part of the river. A direct
relationship between number of stressors and river mile was not observed in the Powell River
(N = 19, r = 0.03, p>0.10), probably because of the concentration of mining activity in that
subwatershed.
We observed an inverse relationship between the cumulative number of stressors and
either the fish IBI or the maximum number of mussel species present at a site (Figure 5-17). Sites
having two or more of the four stressors listed in Table 5-5 had greater than a 90% probability of
having impaired fish community integrity and fewer than two mussel species present. Sites with
one or no sources of stress had between 4 and 10 mussel species on average and, generally, an
unimpaired fish community (Figure 5-17). The maximum number of mussel species observed in
5-20
-------
t=-1.35, p = 0.18
I
CO
120
100
80
60
< 40
"o
(A
« 20
S
0
-20
Powell Clinch
RIVER
±Std. Dev.
CZl ±Std. Err.
n Mean
= -1.84,p = 0.07
12
10
-------
Historic mussel
distribution
KENTUCKY
Towns
Rivers
Counties
Present mussel
distribution
KENTUCKY
—"• ' .
NNES
VIRGINIA
$ Towns
Rivers
Counties
Figure 5-14. Comparison between historic (pre-1910) and present locations of native mussel
concentrations in the Clinch and Powell watershed. Red areas indicate mussel beds.
5-22
-------
Table 5-5. Criteria used to define whether a stressor was present or potentially
present at a site (code = 1) or not present (code = 0) for the mussel CMCP risk
analyses
Land use
=====
Mining
Criteria
site >2 km from active mining or coal processing upstream = 0; otherwise = 1
Cropland
site >10% cropland = 1; otherwise = 0
Urban
site k 10% urban = 1; otherwise = 0
Roads
site >2 km from road = 0; otherwise = 1
1234
Powell River
8
0 1 2 3 4
Clinch River
Stressor Sum
Figure 5-15. Comparison of cumulative stressors in the upper Clinch and Powell rivers.
A higher index indicates more stressors present.
5-23
-------
180
220 260
River Mile
300
340
Figure 5-16. Mean number of cumulative sources of stress as one progresses upstream in the
Clinch River (r = 0.74).
this dataset was 18, which is comparable to some of the better mussel sites in the entire Clinch
and Powell watershed, though still far less than the historical number of species reported (> 35
species at many sites; Ortmann, 1918). This result, combined with the previous observation that
fish and mussel species richness decreased with increased elevation (i.e., further upstream) even
in the absence of significant sources of stress (because of the species-drainage area relationships
discussed previously), suggests that mussels, fish, and perhaps other aquatic life are especially
vulnerable in upstream reaches of the Powell and Clinch rivers. This pattern has also been
evidenced by the fact that many current threatened and endangered mussel species were
historically present in fair numbers in small tributaries and headwater areas of the Clinch and
Powell watershed (Figure 5-14) (Ortmann, 1918; Ahlstedt, 1991). As discussed previously,
episodic chemical spills, physical habitat degradation, and riparian corridor impairment would be
expected to have greater effects in headwater areas or small tributaries in the watershed, where
dilution and stream size are much reduced compared to mainstem areas.
In a preliminary attempt to examine potential exposure and vulnerability of native mussels
to multiple stressors identified in this risk assessment, we used the GIS in Arclnfo to map the sites
largest mussel populations in relation to mines, major roadways, urban centers, and riparian
agricultural areas. There are currently no known mussel concentration sites in the upper Powell
and Guest Rivers, consistent with the more intensive coal mining in that area. Figure 5-18 shows
5-24
-------
A
60
50
40
30
20
10
T -r
D
T
IBI impairment threshold
T
0123
Cumulative Stressors
Mean+SD
Mean-SD
Mean+SE
Mean-SE
D Mean
1 2
Number of Stressors
Figure 5-17. Fish IBI (a) and maximum number of mussel species collected
(B) in the Clinch and Powell watershed as a function of the number of Stressors present.
5-25
-------
Agriculture
Major U.S. Highway
B
Secondary Roaj
2.5 Km
Figure 5-18. Map of portion of the middle Clinch River watershed showing two mussel
concentration sites, Pendleton Island (A) and Burtons Ford (B), in relation to major roadways (a
source of episodic spills) and agricultural areas.
5-26
-------
how two examples of known mussel concentrations in the watershed with associated land-use
factors analyzed this risk assessment. For example, Pendleton Island is adjacent to a major
U.S. highway and directly downstream of significant agricultural riparian areas. However, other
mussel sites, such as Burtons Ford, appear to be located farther away from these stressors and
therefore may be less vulnerable to risk. Of the 10 mussel concentration sites examined, only
about half appear to be reasonably isolated from major roads, mines, and agricultural areas. This
information suggests that native mussel populations are relatively vulnerable to risks in this
watershed and that further extinctions or extirpations are likely to occur unless considerable
resource protection measures are taken.
5.6. SENSITIVITY ANALYSES OF RIPARIAN CORRIDOR BUFFERS
The fixed riparian corridor dimensions used in the previous risk analyses (2 km length
upstream of each sampling point and 100 m to either side of the stream regardless of stream size)
were recognized as a major potential source of uncertainty. Riparian zone condition may have
different effects on stream biota, depending on any number of natural variations in landscape and
stream characteristics. In this section we examine the sensitivity of riparian buffer dimension
effects by assessing relationships between land use and biotic communities (mussels and fish)
using a variety of riparian and upland buffer dimensions in the context of natural landscape and
hydrologic variations. Additionally, we assess the importance of natural morphological and
geographical variations to the condition of mussel and fish assemblages throughout the watershed
and how these variations are related to anthropogenic influences.
5.6.1. Methods
5.6.1.1. Mussels
We assessed relationships among mussel abundance and richness, elevation, slope, and
morphological data from 49 sites in the upper Clinch River watershed (Tazewell County) using
data collected by Jones et al. (2000). From this initial list of sites, a subset (15) was randomly
selected for analysis of upstream land use. Numerous sites were close to one another, especially
on the mainstem, so a random selection of sites was used to eliminate redundancy in upstream
percentages within these drainage areas and within riparian corridors of variable widths and
lengths (100 and 200 m wide; 1,2,5, and 10 km long). Pearson product moment correlations
(p<0.10) were used to test relationships between buffer characterization and mussel species
richness or abundance. Qualitative analysis of mine and road locations as well as field
observations reported by Jones et al. (2000) concerning site-specific stressors (e.g., open sewage
pipes, oil, etc.) were also used to explain variations in broadscale landscape relationships with
5-27
-------
mussel data. Mussel collection methods may be a source of data uncertainty because sample area
and effort were not standardized across sites.
5.6.1.2. Fish
From the initial suite of 155 CPRATS sites from the entire watershed, 30 outside the
Copper Creek subwatershed were randomly selected for analysis of riparian land-use relationships
with fish BI scores, elevation, slope, drainage area, and habitat data. Small headwater and large
mainstem sites were removed from the random selection process in an attempt to reduce natural
variability among sites. GIS methods and corridor sizes were the same as those used for the
mussel data analysis. Pearson product moment correlations (p<0.10) were used to test
relationships among buffer characterization, fish IBI scores, overall habitat quality scores, and 10
individual habitat parameters (see Table 3-2). ffil data were available for 29 of the 30 sites and
habitat data were available for 16 sites.
5.6.2. Results and Discussion
5.6.2.1. Mussels
Initial analyses of land-use percentages within whole drainage areas of the 15 randomly
selected sites indicated that there was little correlation between any land-use type and mussel
abundance or richness (Table 5-6). Riparian land use, however, was correlated with mussel
richness (Table 5-6). The proportion of forested land in all corridor dimensions was positively
and significantly correlated with mussel species richness, with the highest correlation occurring
within 100-m-wide and 5-km-long corridors (Table 5-6 and Figure 5-19). The amount of urban
land within riparian corridors appears to adversely affect mussel richness, with 2- and 5-km-long
corridors showing the highest correlation with the number of mussel species at a site. Pasture
land in 100-m-wide, 5-km-long corridors was inversely correlated with mussel richness.
Streams were grouped into different classes of order, slope, and elevation to assess the
importance of riparian zone dimensions to mussel assemblages. Analyses of riparian corridor
dimensions in high-order (> 4th order) and low-order (3rd or 4th order) streams yielded little
distinction between the two site classes in terms of relationships with mussel fauna characteristics
(i.e., 100 m x 5 km corridors for high- and low-order streams had the highest correlation with
mussel richness). Elevation was also investigated as a possible mediating factor, based on
analyses presented in section 5.1, but it did not show any distinctive relationships with land use
and mussel richness.
5-28
-------
Table 5-6. Correlation (Pearson product moment R values) of land-use percentages
within whole drainage areas and within different-size riparian corridors with mussel
richness and abundance3
Riparian corridor
Whole drainage basin
100 mx 1km
100mx2km
lOOmxSkm
100 mx 10 km
200 mx 1 km
2QOmx2km
200mx5km
200 mx 10 km
Land use
Forest
Urban
3asture
7orest
Jrban
Pasture
Forest
Urban
Pasture
Forest
Urban
Pasture
Forest
Urban
Pasture
Forest
Urban
Pasture
Forest
Urban
Pasture
Forest
Urban
Pasture
Forest
Urban
Pasture
Mussel richness
0.12
0.35
-0.20
0.62
-0.46
-0.33
0.6S
-0.49
-0.39
0.77
-0.40
-0.59
0.65
-0.08
0.15
0.62
-0.43
-0.39
0.69
-0.46
-0.43
0.62
-0.28
-0.47
0.62
0.01
0.19
Mussel abundance
-0.20
-0.03
0.20
0.11
-0.05
-0.07
-0.19
-0.06
0.25
-0.07
-0.13
0.18
0.07
-0.14
-0.22
0.11
-0.04
-0.08
-0.16
-0.01
0.21
-0.16
-0.05
0.19
0.05
-0.08
-0.21
"Bold values are significant at p<0.10
^ = 13; two outliers removed because of the site-specific factors
5-29
-------
c» 4
I
JC
I 2
-1
10
20
60
30 40 50
Forest (100m x 5km corridors)
Figure 5-19. Mussel richness versus percent forested land use in 100-m-wide, 5-km-long riparian
corridors.
70
Average catchment slope was the only landscape factor that appeared to have an affect on
which corridor dimensions were most correlated with mussel richness. Using a slope of 33% as a
threshold (because it provided a relatively even split of the 13 sample sites used for this analysis,
two sites having been removed because of site-specific factors), the amount of forested land
within 100 in x 5 km corridors appeared to be the best predictor of mussel richness for streams
with > 33% average slope (Table 5-6; Appendix C, Figure C-l). However, in streams with
average catchment slopes < 33%, shorter corridors (1 Ion) seemed to show a stronger relationship
with mussel richness (Appendix C-, Figures C-l to C-3).
The above results suggest that streams with higher slopes may require longer upstream
forested riparian areas than low-slope streams because of the greater influence that runoff may
have in higher-gradient areas. These results support those described for Copper Creek risk
analyses (Chapter 4). Land use in 1-km-long corridors upstream of the sampling point was the
best predictor of mussel characteristics in both the low-catchment-slope Tazewell County sites
and in the Copper Creek sites, most of which had slopes similar to those of the low-slope
Tazewell County sites. These results also suggest that using a 2-km-length corridor upstream of
5-30
-------
each sampling point throughout the watershed may have underestimated land-use effects in higher
gradient sites. Although these data yielded indications of riparian corridor sizes that may be most
efficient for predicting mussel fauna characteristics, the results should be used cautiously because
of the limited number of data points.
Although land-use relationships with mussel species richness were observed, these
patterns may also be due to natural variability in stream characteristics, specifically stream order
and elevation. Low-elevation or high-order stream sites had more mussel species than high-
elevation or low-order sites (t-test, /?<0.05) (Appendix C, Figures C-3 and C-4). However, as
both elevation and stream order were correlated with proportion of riparian forest (r = -0.76,
/K0.05 [elevation vs. forest within a 100 m x 5 km riparian buffer]) it is difficult to determine
whether mussel species richness is influenced more by land use or by stream order/elevation.
Within a given elevation or stream order group, there was little correlation between riparian
forestland and mussel species richness, which suggests that mussel richness is, in fact, related
more to stream size or elevation than to riparian land use. Furthermore, the small number of sites
that constitute test groups in our analyses makes it difficult to statistically assess these alternative
hypotheses. Finally, the variability in land-use percentages may not be wide enough in this
dataset to allow broad-scale relationships to be distinguished.
Correlation analysis indicated no significant relationships between land use and mussel
abundance (Table 5-6). This observation may be due to natural differences between smaller and
larger streams in regard to mussel abundance. Small (3rd or 4th order) and large (> 4th order)
streams were analyzed separately, and relationships between land use and mussel abundance were,
in fact, observed. High-order streams that had more than 50% forested land within the riparian
buffer—defined as 100 m wide and 1-2 km long—had significantly more mussels (median = 68)
than sites with less than 50% riparian forest, (median = 23; t-test, p<0.05) (Appendix C, Figure
C-5). Relationships between land use and mussel abundance were also observed in low-order
streams; however, the pattern was the opposite of what was expected. Streams that had more than
30% forested cover in riparian buffers 100-200 m wide and 1-2 km long had fewer mussels
(median = 7) than those that had less than 30% forested riparian land (median = 197; t-test,
p<0.05) (Appendix C, Figure C-6). Land use within longer corridors (5 and 10 km) of low-order
streams showed less correlation with mussel abundance.
The inverse relationship between forested land cover and mussel abundance in low-order
streams may be due to other landscape factors such as slope and elevation, which are also
correlated with land use, as explained previously. Both mussel richness and abundance decreased
as elevation increased (i.e., richness and abundance are lower in headwater areas than in the
mainstem) (Appendix C, Figure C-7), as noted in previous analyses of both the CMCP and
CPRATS datasets (section 5.1). Average slope of the drainage, area upstream of a site showed
5-31
-------
little correlation with mussel richness or abundance when all sites within the Clinch River
watershed were evaluated. However, in high-order streams (i.e., sites primarily on the mainstem),
mussel abundance and richness increased with slope of the drainage area (Appendix C, Figure
C-8). These higher slope areas are located toward the lower end of the mainstem (Appendix C,
Figure C-9), which also is more highly forested (Appendix C, Figure C-10) than the rest of the
watershed. Higher-sloped sections of the mainstem may contain cleaner, less embedded substrate
that is more suitable for mussel colonization than lower-slope areas, where fine sediment can
more easily settle on the stream bottom, smothering gravel and cobble substrate.
In low-order (smaller) streams, the relationship between slope and mussel richness or
abundance, although less'pronounced, is the opposite of that observed for the mainstem
(Appendix C, Figure C-ll). Steep slopes in these headwater areas may result in scouring during
high flows, reducing the amount of suitable mussel habitat. Furthermore, these headwater areas
often contain large amounts of boulder and bedrock substrate which, although natural for these
areas, may be unsuitable for mussel colonization and/or fish host distribution. Thus, knowing the
drainage slope as well as elevation and stream size reduced uncertainties in predicting effects of
land use on native mussel communities.
In addition to the effects of land use, elevation, and slope on mussel fauna characteristics,
site-specific factors also may have significant effects. According to Jones et al. (2000), several
sites appeared to be contaminated by sewage from leaks or open pipes. For example, the water at
site 41 smelled of oil and, concurrently, site 49 had no mussels and all crayfish were dead,
suggesting toxic inputs. These site-specific factors can be observed as outliers of some of the
broad-scale patterns observed for the watershed (Appendix C, Figures C-12 and C-13). Drought
conditions in some headwater streams may also limit mussel reproduction (because of the reliance
on fish populations) and colonization.
5.6.2.2. Fish
5.6.2.2.1. Habitat. Our initial results (section 5.2) indicated that there was little correlation
between land use and habitat. However, when the influence of riparian land use was considered,
relationships were apparent (Table 5-7). Overall habitat quality increased with the percent of
riparian forest (100 and 200 m x 1 km corridor dimensions) and decreased as urban land increased
(all corridor dimensions). Individual habitat parameters, including bank vegetative protection,
bank stability, and riparian vegetative protection were positively correlated with forested land in
1- and 2-km-long corridors. The amount of urban land within most corridor sizes was inversely
correlated with all of the individual habitat parameters except channel flow and riparian
vegetation.
5-32
-------
Table 5-7. Correlation (Pearson product moment R values) of total habitat scores
and 10 individual habitat parameters with land uses hi whole drainage areas and
different-size riparian corridors8
I
Riparian corridor
Whole drainage basin
! ! fc i • ! S8 ! i
ii i i i l I : -
!l ! I ilfif ;1|
"a 2 i: -88 -9 o 2
; * o ; 0.08; -0.12 0.30; 0.10 0.23
Forest i 0.62 j 0.47 0.03; 0.50: 0.28
Urban | -0.80' -0.70 -0.81 1 -0.71 j 4.91
Pasture 1-0.221-0.13^ 0.37|-0.16; 0.19
iForest i 0.47i 0.43; -0.05; 0.44; 0.13
•Urban -0.81 •• -0.72 , -0.82 i -0.73 ii -0.93
jPasture i-0.12;;-0.08i 0.37;-0.i4: 0.27
iForest 0.19; 0.211-0.19; 0.13-0.09
lUrban i -0.72 i -0.58 -6.83! 4.55 4.87
c i i -!
.2 ! 5 >
1 ' i i-L^
,S 0£ ' C 3 J£ Q)
•0 U. « *{ C Q)
^ i S olim ?
-0.22J-0.24i 0.16 -0.08
-0.23j 4.52 0.45 -0.22,
0.22 i 0.26 -0.1 5i 0.08
0.33 1 0.34 0.32 1 0.66
!4.52i4.84 0.16! 4.58
: -0.12J 0.101-0.42 -0.391
1 0.29's 0.15 0.31 .0.51
i 4.53! 4.85 0.18i4.58
1-0.13J 0.21 -0.411 -0.28
Bank stability
Riparian
vegetation
0.01 | 0.31
-0.19 -0.04
O.OOJ-0.30
0.72 1 0.62
4.57 -0.21
-0.44 -0.43
0.57 0.40
4.57 -0.23
-0.32 i -0.24
; 0.101-0.13! 0.35 0.23! 0.29 0.35
I -0.41 1 -0.79 0.25 4.50
ipact,,rA ! .6.04: -0.07S 0.35; -0.04! 0.27; -0.05; 0.28! -0.37i -0.13
100m x 10 km
200 m x 1 km
iForest i -0.15! -0.20! -0.12; -0.151 -0.24 j ^-^^^l^L^^L
-0.48 -0.2<
i -0.18 -0.25
-0.05 -0.03
turban ~ : -fl-fioi Ji.43rb.79. JJ.46i -0.75! -0.40! -0.65! 0.30j -0.391 -0-37 -0.19
'Pasture i -0.11 "< -0.13; 0.29= -0.17! 0.21
1-0.14; 0.191-0.17 -0,17
! -0.23 i -0.23
Forest ; 0.57j 0.41 0.02; 0.52! 0.23! 0.40 0.30j 0.24 U.byj U.b&, U.54
yrh^n "Tji.82i4.7i-0.82! 4.72; -0.921-0.53:4.85; 0.16[4.59 4.58 ,-0.23
[Pasture -0.17' -0.05: 0.36 --0.18. 0.24! -0.19! 0.141 -0.33; -U.31
200 m x 2 km
-0.36! -0.32
.Forcrt . 0^4: Oflfl -Ons: 041. 0.11: 0.32, 0.14i 0.32; 0.4bi U.OU; u.30
-Ty^n i/jgi ^07? Ji 82 4.73 4.93,4.5314.851 0.1814.57 4.56 -0.22
^pa-ture r^iOi'T04rn"^--n-l3: 0-27^-0.15; 0.21 1 -0.39! -0.22 -u.2/",-u.*s
200 m x 5 km
:Forest ; 0 16! 0 161-0.17! 0.09' -O.K
)[J).08 1-0.14 1 0.35: 0.1c
I 0.24 U.oo
-rg^n ' . ^73r^ ^ : j» »! JJ.57: 4.9!)! -0.43; 4.79i 0.27i -0.49 -0.4B1 -U.20
" Sputum • ^.03! -0.03' 0.32 -0.02: 0.27 j -0.04; 0.281-0.37' -0.10 -0.1 J> -U./4
200 m x 10 km
iFnrPQt -015: -021 -0 10; -0.15 -0.23 j -0.09, -U.31 i 0.3/i-O.Oyi-U.Ub -U.U3
,Urban fjj.62! -0.46 4.81^-0.49 1 4.79! 4.42j -p^61iJ^1i4J9j^7h0.20
p^ure""^"l1T-0 12" a27:<).17 0.201-0.14: 0:171 -0.151 -0.17; -0.22^.24
"Bold values are significant at p<0.10 (N = 12)
To assess whether natural landscape variability influenced the way in which riparian land
use affected habitat, stream habitat data were analyzed according to drainage area, elevation, and
slope categories. For smaller streams (< 50 km2 drainage) and high-elevation streams (> 450 m)
(N = 7), additional land use/habitat relationships were apparent (p<0.10): pasture within most
riparian' corridors was inversely correlated with overall habitat scores (r~-0.9) as well as channel
flow
-------
scores (i.e., sediment deposits increased with upstream pasture land) (r—0.75). For larger streams
(> 50 km2) and lower-elevation streams (< 450 m) (N = 5), nearstream land use did not predict
habitat quality. For streams with average percent catchment slopes > 36% (N = 7), development
was inversely correlated with all habitat parameters (r = -0.68 to -0.91, p<0.10) except
sedimentation, channel flow status, and riparian vegetation. In lower-sloped streams (< 36%
slope) (N = 5), the same habitat scores were more closely correlated (inversely) with land use in 1-
and 2-km-long corridors. When compared with our previous findings (section 5.2), these results
suggest that riparian land use may influence stream habitat more than land use within the entire
drainage area, and that habitats in smaller, higher-elevation streams may exhibit more riparian
land-use effects than larger, lower-elevation streams. Because of limited data, however, it is
difficult to assess the riparian corridor dimensions that exhibit the greatest influence on habitat
quality. Furthermore, the results described above should be used cautiously because of the small
amount of data available for analyses.
5.6.2.2.2. 1BL Various riparian land uses were correlated with IBI scores (Table 5-8). In all
corridor sizes, pasture and urban land were correlated (positively and inversely, respectively) with
IBI scores. Forested land in 5- and 10-km-long corridors was inversely correlated with IBI.
Relationships between forested and pasturelands and IBI scores are opposite those normally
expected for these types of land uses. These results are similar to those described in Section 5.3,
which emphasized the influence of mining (found mostly in forested areas) on IBI scores. IBI
scores decreased as average catchment slope increased (Figure 5-20). To reduce confounding
factors, streams with slopes > 36 and < 36% were investigated separately. For streams with '
slopes > 36%, IBI scores decreased as riparian urban land increased (all corridor sizes) (Table 5-
8). For streams with slopes < 36%, only urban land within longer corridors (5 and 10 km) and
within whole catchments seemed to influence IBI scores (Table 5-8). The percentage of forested
land and the average catchment slope are both related to the number of mines in a region (Figure
5-21). Therefore, investigating high- and low-slope areas separately allows assessment of
landscape factors not correlated with slope. In fact, urban land was the only land-use correlated
with IBI after slope was standardized (and presumably the influence of mining was less of a
factor), indicating that urban land was the only land use with a detectable influence on IBI scores.
Elevation was investigated as a possible factor affecting the way in which riparian corridor
characteristics influence IBI scores, as noted in section 5.1. For streams with minimum elevations
of > 370 m, IBI scores increased with nearstream pasture and cropland and decreased as urban
land increased (Table 5-8). Within entire drainages of streams in this elevation category, forested
land was inversely correlated with IBI scores. Land-use correlations were less evident for lower-
elevation streams (minimum elevations < 370 m). These observations seem to further
5-34
-------
Table 5-8. Correlation (Pearson product moment R values) of IBI scores with whole
drainage and riparian corridor land uses for all sites and various categories, based
on slope, elevation, and drainage area.3
i
i
Bl score
Riparian corridor j Land use (n=22)
100 m x 1 km Forest -0.15
Urban -0.54
I Pasture 0.46
100 m x 2 km Forest -0.16
Urban -0.45
j Pasture 0.43
100mx5km Forest i -0.39
Urban i -0.50
Pasture i 0.49
100 m x 10 km Forest • -0.42
Urban -0.38
Pasture ! 0.42
200 m x 1 km Forest i -0.21
Urban i -0.52
I Pasture ! 0.51
200m x2 km j Forest -0.16
i Urban i -0.44
Pasture 0.46
200 mx 5km Forest ' -0.45
Urban -0.48
Pasture > 0.53
200 m x 10 km \ Forest : -0.44
Urban -0.40
Pasture 0.45
Whole Drainage j Forest -0.55
! Urban -0.39
[Pasture 0.59
; ; Bl score
i i (site
Bl Score ; Bl score '' elevation
(slope >36; j (slope <36; j >370 m)
n=12) ! n=10) : (n=12)
-0.05 i -0.13 -0.35
-0.57 -0.54 ; -0.56
0.49 0.39 ; 0.65
0.03 i -0.11 : -0.37
-0.55 i -0.42 ! -0.56
0.35 . 0.34 : 0.61
-0.22 ' -0.07 -0.42
-0.60 ' -0.63 : -0.51
0.36 , 0.28 '• 0.55
-0.44 i -0.15 : -0.46
-0.54 ! -0.49 ' -0.42
0.24 I 0.24 ; 0.52
-0.09 • -0.23 t -0.43
-0.54 -0.53 i -0.55
0.51 : 0.45 0.68
0.01 > -0.07 ' -0.37
-0.48 i -0.47 : -0.56
0.39 ' 0.32 0.61
! -0.24 '> -0.10 < -0.44
-0.57 -0.66 -0.50
i 0.37 0.32 0.56
i -0.45 ; -0.17 : -0.46
i -0.53 j -0.56 , -0.44
• 0.25 0.25 0.53
i -0.31 -0.13 -0.61
i -0.51 i -0.62 i -0.44
i 0.38 0.21 : 0.66
Bl score I
(site
elevation
<370m) i
(n=10)
0.07
-0.47
0.26
0.04
-0.35 L
0.25 I
-0.38
-0.40
i 0.43 |
i -0.47
! -0.22 !
! 0.36
, 0.04 i
I -0.47
: 0.36
i 0.10 i
: -0.40
' 0.31
! -0.44
j -0.40
; 0.49
; -0.50
: -0.24
0.39
i -0.44
! -0.32
i 0.47
i
Bl score
(drainage
area>50sqj
km)(n=10)
-0.09
-0.69
0.51
-0.01 i
-0.65
0.40
-0.39
-0.67
0.48
-0.46
-0.68 _^
0.51 _,
-0.26 i
-0.64
0.61
-0.08
-0.57
0.48
-0.48
-0.63
0.54
-0.51
•0.64
0.55
-0.54
-0.65
0.55
Bl score
(drainage
area <50 sq
km) (n=12)
-0.21
-0.38
0.43
-0.28
-0.24
0.47
-0.42 =
-0.33
0.51
•0.42
-0.23
0.41
-0.22
-0.40
0.45
-0.27
-0.26
0.46
-0.44
-0.34
0.54
-0.42
-0.27
0.41
•0.60
-0.16
-t "
i 0.67
"Bold values are significant at p<0.10
illustrate the influence of mining on fish assemblage status. Because mining in this region is
found mostly in high-elevation forested areas (Figure 5-21), effects from mining may explain why
in these higher-elevation forested and pasture areas exhibit correlations with streams that are the
opposite of what is normally expected.
Streams of different drainage sizes were separated to further investigate IBI relationships
with riparian landscape characteristics. In large streams (catchment size > 50 km2), IBI scores
decreased as nearstream and whole-drainage urban land increased, whereas in smaller streams
5-35
-------
o
W
5
ut
50
46
At
38
34
30
09
2
2 2
•
3 3
D 3
•
•
i •
•
4 3
•
3 ' 4
• *
•
2 4
3 !5C
Average Catchment Slope
Figure 5-20. IBI score versus average catchment slope (%).
(catchment size < 50 km2), urban land was not significantly correlated with IBI scores (Table 5-8).
In these smaller streams, pasture land in 5-km corridors and whole-drainage areas was positively
correlated with IBI scores. Again, this observation is most likely due to an association of
particular land uses with mining activities; pastureland is inversely related to mines. Average
catchment slope within these different-sized drainage areas also was predictive of IBI scores. For
large streams, IBI scores were inversely correlated with average catchment slope (r = -0.79; N =
14). When elevation is considered, the correlation becomes even stronger: IBI scores of large
streams with average elevations, of < 550 m were closely correlated with average catchment slope
(r=-0.90; N = 9). The correlation of slope with IBI scores for small streams was insignificant.
A confounding factor in the relationship of slope with larger stream IBI scores, however, is
that slope is also correlated with forest, pasture, and cropland in these areas. An important point
here is that previous results (section 5.3) have shown that these land uses are not the primary
factors affecting IBI scores; mining in these particular land-use areas was determined to have the
most influence on IBI scores. Although slope was correlated with IBI scores in large streams, this
is most likely due to the greater presence of mining in steeper, more highly forested areas, as
described in section 5.3, and not to any direct effects of slope on fish assemblages. Urban land,
however, was not correlated with mining activities, indicating that urban land does in fact affect
IBI scores in large streams. Although our data do not demonstrate an influence of urban land
5-36
-------
-------
50
so
< Mines
Land Use/Land Cover
B3^ Forest
rgHWdUmls
DevtIoped/BarrM
Cropland
Hefbjceous/P&ture
Wit«r
Indeterminate
o Data
100 Miles
Figure 5-21. Mines in the Clinch River watershed. Green areas indicate forest in
the upper figure; dark red areas in the lower figure indicate high-slope areas.
on smaller streams, any relationships may be confounded by the greater abundance of mines in
upland areas, where these streams are more often located.
In summary, results of additional analyses examining the effects of riparian corridor
dimension on relationships between biota and land use generally support those obtained using
Copper Creek information (Chapter 4). However, for smaller, high-gradient (i.e., generally high-
elevation) stream locations (which represent < 5% of the total sites examined in the CPRATS
dataset), a shorter riparian corridor length (1 km rather than 2 km, as used in our risk analyses)
would have yielded more accurate results concerning land-use effects on biota at those sites.
Thus, for many of the sampling locations examined in risk analyses in Chapter 5 (including
TVA's CPRATS dataset), there appears to be a moderate degree of certainty in our results.
5-37
-------
6. RISK CHARACTERIZATION
6.1. FINDINGS
6.1.1. Copper Creek Watershed
The pilot study conducted in Copper Creek to refine the methodological approach for the
entire watershed assessment was also useful in describing the cause of problems in that
subwatershed. It is likely that embeddedness and sedimentation affect the abundance and
distribution of invertebrate and fish species in Copper Creek, as both habitat characteristics were
directly related to the amount of agricultural land use in the riparian corridor and the measures of
biota (Figures 4-4 and 4-5). Optimal benefits to fish, mussels, and perhaps other invertebrates
would be realized by maintaining the riparian corridor for 500 to 1500 m upstream and for
100 m on either side of the stream for the site of interest (Figure 4-3). Fish taxa richness was
found to be a useful surrogate measure for mussel species richness where mussel data were
lacking (Figure 4-11).
6.1.2. Clinch and Powell Watershed
Relationships between land use and habitat quality in the Clinch and Powell watershed
suggest that agricultural and urban land uses contribute sediment to the stream, increasing
embeddedness and reducing cover for fish and invertebrates (Figure 5-2 and 5-3). Individual
habitat parameters, including bank vegetative protection, bank stability, and riparian vegetative
protection, were positively correlated with forested land in 1- and 2-km-long corridors. Near-
stream pasture and developed land, especially along small streams, were associated with
degradation of overall habitat quality as well as instream habitat, bank stability and vegetation,
and channel morphology. Land uses with biota comparisons indicated that up to 55% of the
variability in fish IBI could be explained, with proximity to mining and urban land use having the
most adverse effects (Table 5-1, Figure 5-5). Not only were all types of biota adversely affected
by increasing amounts of mining and urban areas in relative proximity to the sampling site, but
fish IBI scores actually improved at sites located near pasture lands. This was contrary to results
found for the pilot study in the Copper Creek watershed (Figure 4-5), where proximity to pasture
lands was associated with less mussel species richness. This occurred because the Copper Creek
subwatershed is not heavily influenced by mining or urban areas. Thus, the Clinch and Powell
analysis indicates that far more adverse effects on biota in this watershed occur from mining and
urban areas than from pastureland. However, habitat degradation from near-stream pastureland
would likely be a more obvious stressor if toxic mining effects were removed.
6-1
-------
Because anthropogenic land use is prevalent throughout all regions of this watershed,
other landscape characteristics, such as catchment slope, elevation, stream size, and site-specific
factors, may act as determinants of mussel species richness and abundance in certain areas of the
watershed. Sediment deposition and scouring in response to landscape-dependent flow
variations throughout the watershed may result in differences in habitat quality and,
consequently, differences in mussel fauna. There is some indication that high-slope catchment
areas require longer riparian corridors to ensure mussel species richness, whereas shorter riparian
areas are adequate in areas with lower catchment slopes.
It was difficult to assess the influence of different-sized riparian zones and the land uses
within riparian corridors on fish assemblage integrity because of the confounding effects of
mining activities and the limited amount of data. However, our analyses confirm the conclusions
of previous analyses in Chapter 5 that describe mining and urban land as being the major factors
affecting fish assemblages (i.e., stressors from these sources are the limiting factor to fish
assemblage integrity). Habitat quality, which was shown to affect ffil scores (Section 5.4),
appeared to be influenced more by riparian land use than by whole-drainage-area land use.
Furthermore, habitat quality in small, high-elevation, and high-gradient streams seemed to be
more influenced by riparian conditions than did the habitat in larger, lower-elevation, and lower-
slope streams. Additionally, these results support those presented in section 5.5 that describe the
detrimental effects of multiple stressors on fish assemblages.
Although mining and urban land are the only landscape factors that can be implicated as
stressor sources using current data, it is likely that other land-use features are also detrimental to
fish assemblages. Analysis of riparian land use indicates that streamside pasture and possibly
other human land uses were detrimental to habitat quality; however, because of the toxic effects
from mines (which are more often located in forested areas and absent from pasture lands), land-
use effects on fish via habitat degradation (e.g., sedimentation due to pasture runoff) were not
evident. Therefore, although reducing stressors from mining operations is likely to improve
overall fish IBI scores, it is not clear that this will restore ffil scores to relatively unimpaired
reference sites in the watershed. Once mining-related stressors are reduced, land-use-related
habitat degradation may become the limiting factor to fish assemblage integrity.
6.1.3. Unexplained Variance
All of our risk analyses indicated that nearly half of the variance in biological measures of
effect was still unexplained, given the land cover and habitat data available. More detailed
analyses of riparian corridor land uses and physical attributes of catchments (e.g., slope,
6-2
-------
elevation) improved the relationships between sources and measures of effects (Section 5.6).
However, our analyses indicate that other factors could have impacted IBI and mussels, including
• Wastewater discharges and other point and nonpoint sources that could release toxic
constituents downstream (Lingenfelser, 2000),
• Episodic toxic spills (Jones et al., 2000),
• Habitat fragmentation, and .
• Lack of sufficient fish hosts at the necessary spawning times (Sheehan et al., 1989).
Results of our analyses suggest that these types of site-specific factors may be important
in explaining variability in fish and mussel abundance and distribution. Although not explicitly
.included in our analyses because of data limitations, mussel species richness data collected over
93 years show sharp declines in native mussels following spills of toxic materials (Figure 5-8;
Sheehan et al., 1989). Several toxic spills have occurred in this basin over the past 30 years,
including a 1999 truck accident that spilled concentrated ammonia into Cedar Creek in the upper
Clinch River, resulting in a large fish kill and mortality of at least 300 federally threatened or
endangered mussels (Jones et al., 2000). Mussels have still not recovered from these spills,
possibly because of residual sediment contamination (Van Hassel and Gaulke, 1986), which may
impair survival of mussel glochidia and larvae (Kauss and Hamdy, 1991).
The lower amount of variance explained by land use for the EPT (Tables 5-1 and 5-2), as
compared to the fish IBI, could be due in part to the coarse taxonomy used for invertebrates
(family level) and potential loss of information (Barbour et al., 1999). However, we cannot rule
out the fact that invertebrates have relatively short life cycles and may be able to recolonize or
recruit individuals quickly following stress. Several researchers, including Cairns et al. (1971),
Minshall et al. (1983), and, in this watershed, Grossman et al. (1973) have noted relatively rapid
recolonization of macroinvertebrates following episodic events. However, as native mussels and
fish have yet to recolonize this area of stream, EPT may not be as sensitive an indicator of past
water quality effects as either native mussels or fish.
The even lower amount of variance explained for mussels species richness in our analyses
(Table 5-3) could be due to a number of other factors, including
6-3
-------
• Site-specific geomorphic characteristics such as substrate particle size, flow and
current velocity, and orientation of bedrock ridges (Church, 1996),
• Proximity to episodic spills that could not be adequately analyzed in this risk
assessment, and
• Variance from year, to year in fish host assemblage in the area.
6.1.4. Stressor-Response Relationships
Relationships between habitat quality and biological measures of effect showed that biota
were influenced positively by instream cover and negatively by embeddedness. Given that we
observed negative relationships between pastureland cover and riparian integrity and proximity to
urban lands and embeddedness, it is not surprising that these types of land use affect fish
assemblage integrity. This idea is further supported by analyses presented in Section 5.6 lhat
show positive correlations between near-stream anthropogenic land uses (i.e., pasture and
developed land) and habitat degradation, particularly in smaller, higher-elevation, higher-sloped
streams.
The relationship between the cumulative number of stressors at a site and mussel species
richness or fish BBI (Figure 5-17) suggests that fish and native mussel populations are relatively
vulnerable to risks in this watershed. The more stressors present, the more likely further
extinctions or extirpations will take place unless additional resource protection measures are
taken.
Several lines of evidence described above (and summarized in Table 6-1) point to the
importance of various land-use activities and the riparian corridor integrity as determinants of
native mussel and fish distribution in the Clinch and Powell watershed. Lines of evidence
include analysis of field data collected by TVA and other organizations, as well as information
from published studies in other watersheds. Key factors appear to be sedimentation and other
forms of habitat degradation from urban and agricultural areas, as well as toxic chemicals from
coal mining operations and urban areas.
The importance of riparian zone characteristics on instream habitat quality and aquatic
fauna observed in this study has been reported in many other lotic systems (Minshall et al., 1983;
Cooper et al., 1987; Gregory et al., 1991). This study further clarified that the strongest
relationships between forested riparian areas in Copper Creek and biological and habitat
measures occurred with a riparian width of 200 m and 500 to 1,000 m upstream of the sampling
site. Areas within these limits that had predominantly forested land cover tended to have less
64
-------
a fr
u> •
.9 «
"S TH
^ ,^i *£J ^^ |^ h~H ^
•^^ co »•£] r™* r^ P«5 t*
Sedimentation, toxic
chemicals, lack of fish
host, low flows/drought
Glochidia
(larvae)
Sedimentation, toxic
chemicals, low
flows/drought
Juveniles
Sedimentation, toxic
chemicals
£
f
^2
0
CO
1
£
• i— *
•4—1
2
S'S
ss -c ^ -d
j=j '& h I | | g §
IllliliiS
§
Reduced
reproducti
Literature
„
Sedimentation, low flo\\
high temperature
Spawning
,g
l!
(U
CO
Literature review;
analyses of land-u
and TVA habitat
assessments
Toxic chemicals,
sedimentation, lack of
flow
.T3 J3
SI
3 2
^ So
J3
•*— »
i^
a.--a
ii
*3
U e3
CO r^
Literature review;
analyses of land-i
habitat, and TVA
CPRATS fish IBI
(u
Toxic chemicals, lack o:
flow, high temperature
1
CO
1
fc
6-5
-------
sedimentation, more instream cover for aquatic fauna, less substrate embeddedness, higher fish
and native mussel species richness, and a higher number of threatened and endangered species
than did riparian areas that had > 50% agricultural area (crop or pasture). However, a 1999
mussel survey of this stream showed a loss of mussel species when compared with a similar
survey performed in the 1980s, apparently from more pervasive sedimentation in the stream and
frequent wading in water by livestock (Don Gowan, TNC, at the Clinch Assessment Workgroup
meeting, December 1,1998). Thus, if agricultural or livestock use within the upstream riparian
zone is great enough, sedimentation effects and subsequent loss of habitat will ensue for some
distance downstream, depending on stream gradient, flow, and channel morphology, even though
forested riparian areas may be present at a given site (Lenat, 1984; Richards and Host, 1994).
Analyses from Tazewell County (Section 5.6) indicate that riparian land uses can have
varying effects on biota, depending on landscape factors such as slope, elevation, and stream
size. Preservation or restoration of mussel communities in small, high-slope streams may require
long zones (5-10 km) of riparian protection; shorter zones (1-2 km) of riparian protection may
be required in larger, lower-gradient streams. Analysis of habitat data from stations throughout
the Clinch River watershed also demonstrated the importance of riparian zones to stream
integrity. Urban and pasture land use in riparian zones appeared to affect overall habitat quality
as well as individual habitat components (including instream habitat, bank characteristics, and
morphological features) more than did whole-drainage land use.
Although riparian vegetation can reduce deleterious land-use effects on water quality
(Lowrance et al., 1984; Gregory et al., 1991; Osborne and Kovacic, 1993), it is not clear that, in
this watershed, improvement of the riparian corridor alone in this watershed will result in
recovery of native mussel and fish populations. Several researchers have reported significant
effects of upland land uses on surface water quality, depending on the spatial pattern of those
uses in the watershed (Omernik et al., 1981). In the Clinch and Powell watershed, there have
been several reports of little or no recovery of threatened or endangered mussel or fish species,
despite improved water quality (O'Bara et al., 1994; Dennis, 1985; Ahlstedt, 1991). Recent
mussel introduction efforts (Sheehan et al., 1989) may improve mussel recruitment and
population stability, but the lack of recovery thus far may be due to too few host fish in the area
(Zale and Neves, 1982a, b; Walters, 1996,1997) or residual sediment toxicity (Van Hassel and
Gaulke, 1986; Sheehan et al., 1989). This assessment was unable to evaluate these factors, and
there is a general lack of relevant information on such effects in the Clinch and Powell watershed
and other systems.
Another suggested cause for the decline in mussels over the past 70 years is more
frequent summer drought conditions and lower base flows in general throughout the watershed
6-6
-------
(Ahlstedt and Tuberville, 1997). A study conducted by The Nature Conservancy (Richter, 1996)
of various hydrologic measures at the only two long-term USGS gauge stations in the watershed
(Cleveland and Spear's Ferry on the Clinch River) concluded that there were few significant
trends over time. However, the study also reported lower August flows in recent decades and
less "flashiness," or changes in hydrograph rises and falls. The latter measure may be due to
greater reforestation of the watershed in recent years, but it could also be due to fewer prolonged
or large precipitation events. Lower summer flows would be detrimental to mussels and native
fish, particularly if riparian vegetation in the upper watershed and tributaries is removed, thus
increasing water temperatures (Vannote et al., 1980; Morris and Corkum, 1996).
With any endemic population, there is a high risk of extirpation from habitat
.fragmentation, resulting in populations that are too inbred and small in size and that are more
susceptible to stressors. Native mussels and fish in the Clinch and Powell watershed may be no
exception. Populations are now more widely separated than they have been historically, which
could lead to reduced recruitment success and declining populations. For this reason, it appears
to be most useful to concentrate protection efforts on those populations that appear most
vulnerable because of their proximity to mining, urban areas, or transportation corridors.
Protection and/or enhancement of the riparian corridor at these sites, as well as protection from
toxic spills and discharges, is as important to sustaining endemic species as stocking new or
historically important areas. If stream habitat as well as water quality can be maintained or
improved, present mussel and fish populations might be able to expand into nearby areas, thus
increasing the distribution and abundance of these species.
6.2. SOURCES OF UNCERTAINTY
Two general types of uncertainty were encountered in this assessment: (1) uncertainty
concerning the reliability of source, stressor, and biological data; and (2) uncertainty concerning
extrapolation of results from one biological measure to another or from one subwatershed to
another.
6.2.1. Reliability of Source, Stressor, and Biological Data
Direct stressor data for this risk assessment were fairly limited, both in terms of the
quantity and types of data available. TVA's habitat quality assessment information, obtained in
conjunction with fish and benthic macroinvertebrate data in the CPRATS, was the major source
of physical stressor data. This information is highly qualitative, and it is an indirect measure of
actual physical stressors. We assumed, for example, that high substrate embeddedness at a site
was a reflection of a high loading of fine material from the surrounding land activities. There is,
6-7
-------
however, an unknown degree of uncertainty associated with this assumption. Detailed physical
descriptions of each sampling site were not available or evaluated in this risk assessment. It is
possible that certain sites may have been natural deposition areas, for example (owing to gradient
and channel morphology), which would have led to erroneous associations between surrounding
land uses or riparian vegetation characteristics and instream habitat measures. Given TVA's
sampling protocol for selecting sampling sites, this is probably a minor source of uncertainty in
our analyses, but it is a source nonetheless.
A more serious source of uncertainty associated with TVA's habitat data is that they are a
qualitative index and each habitat measure is rated on an ordinal scale of 1 to 4. In some
analyses (e.g., multiple regressions) these measures were treated as continuous variables, which
may have introduced unknown biases. Furthermore, we assumed that there was consistency in
the way in which sites were characterized, that is, there was little or no subjective bias in how
habitat measures were derived for each site. Although this assumption is likely to hold, given
TVA's documented training and habitat assessment protocols, our experience suggests that some
investigator bias cannot be avoided when using qualitative assessment protocols. One
recommendation to resource managers is to continue conducting physical habitat assessments
along with biological collection efforts but to consider using more robust habitat assessment
techniques, such as the revised Rapid Bioassessment Protocol (Barbour et al., 1999).
The combined potential effect of the above sources of uncertainty are perhaps best
illustrated in the habitat quality measures reported for the upper Powell River. Contrary to
workgroup expectations and some published data, we were unable to identify a significant
relationship between either stream embeddedness or sedimentation and proximity to mining or
number of mines nearby. This apparent paradox could be explained, in part, by uncertainties
related to the qualitative nature of the habitat measures (including the fact that only four different
values are possible) and by uncertainties related to natural geomorphic differences among sites
that may mask land use-habitat quality relationships.
A related source of uncertainty is the reliance on dual-threshold categories of stress rather
than on a gradient of stress values in much of this risk assessment. Threshold characterizations
are acknowledged to be somewhat approximate and empirically defined in this risk assessment.
More complete spatial coverage of stressor data would enable us to more quantitatively analyze
gradient stressor-response effects.
Aside from physical habitat stressors such as sedimentation, this risk assessment
recognized the potential importance of chemical stressors in the watershed. Unfortunately, we
were unable to characterize chemical stressors owing to a lack of relevant data. The entire
watershed has only two long-term water quality stations, both of which are located in the lower
6-8
-------
part of the watershed. Although trend analyses were performed on the available data by
statisticians at Virginia Tech University, BJacksburg, VA (Zipper et al, 1991), nearly all of these
analyses were for conventional pollutants (biochemical oxygen demand, pH, fecal coliform).
Potential chemicals of concern such as pesticides, coal mining chemicals, and heavy metals were
poorly represented in STORE! and other databases because they were largely unmeasured.
Thus, water quality stressors were largely inferred in this risk assessment, based on nearby land-
use/source activities in association with biological effects and habitat quality information. An
example of this inference process is the biological effects data presented for a hydraulic oil
commonly used in coal mining and related effects of proximity to mines (where this oil is used)
on mussel and fish abundance and distribution in the upper Powell River.
The biological data used in this risk assessment were also subject to some of the same
uncertainties as the habitat quality information. Some sites may have had relatively poor faunal
representation because of natural geomorphic features that would mask statistical relationships
between biota measures and land use or habitat quality characteristics. For example, it has been
demonstrated that native mussel abundance is related, in part, to the orientation of bedrock
ridges, which is a consequence of the direction of stream flow, the local geology, and location
with respect to the inside or outside bend of the stream. None of these parameters were included
in TVA's habitat measures, although they could perhaps be modeled by using available geology,
topography, and digital elevation information in the GIS. TVA's CMCP mussel data are perhaps
less susceptible to this source of uncertainty than are fish or macroinvertebrate measures because
trained experts chose mussel sampling locations on the basis of historical knowledge and an
experienced understanding of preferred mussel habitat. However, trained experts do not always
locate preferred habitat or the best reference sites. Therefore, it should be noted that the presence
of trained experts does not always translate into lower uncertainty.
As noted in several of our risk analyses, the macroinvertebrate measure EPT was
associated with a moderate degree of uncertainty because family-level taxonomy was used,
resulting in a relatively narrow-ranging index throughout the watershed. One recommendation to
resource managers is to consider using lower-level taxonomy (genus or, preferably, species) and
developing a suite of sensitive reliable metrics that are demonstrated to respond to human
activities. Fish H3I data were likely to have less associated uncertainty, because the metrics in
this index have been demonstrated to be sensitive in a number of other watersheds. However,
fish collection methods often have unknown or unqualified efficiency, resulting in uncertain
reliability in fish abundance and distribution data. Unfortunately, fish collection efficiency is
typically not uniform across different-sized streams or different habitat types. Therefore, there
6-9
-------
might be a bias in some of the fish IBI data, resulting in potentially inappropriate comparisons
across sites. The magnitude, of this source of uncertainty is unknown.
6.2.2. Extrapolation of Results Between Biological Measures
The two assessment endpoints of interest in this risk assessment were concerned v/ith
native mussel and native fish species. Although substantial information has been collected
throughout the watershed for both types of fauna, much of these data were not used in this risk
assessment because (1) they were not easily accessible (i.e., TVA's CMCP mussel data were
archived on TVA's mainframe computer, and documentation of data codes was lacking) or (2)
they were not provided in time for this project schedule (e.g., the Virginia Heritage database for
fish and mussels). As a result, we supplemented available mussel data with fish IBI and
macroinvertebrate EFT measures in the hope that we could extrapolate source/stressor-effect
relationships to native mussels and fish. However, as demonstrated in our risk analyses, there
was a high degree of uncertainty associated with extrapolating EPT measures to native mussel
data; EPT did not necessarily respond to sources or stressors in a similar manner as mussels.
Fish IBI, however, was a reasonable surrogate indicator for native mussel species richness,
although there is some uncertainty (albeit lower than for EPT) in the quantitative relationship
between these two fauna.
The apparent relationship between fish IBI and mussel species richness or abundance
could be explained in more detail than was possible in this risk assessment. IBI is composed of a
number of metrics, one of which is native species richness. We were unable to obtain individual
IBI metric values for all CPRATS sites, but these data do exist. With some further effort, these
data could be obtained and compared with available CMCP mussel data. Such an analysis would
also yield a direct measure relevant to the native fish assessment endpoint. However, any
comparisons between native mussel and IBI or EPT data will be limited by the lack of overlap in
sampling locations between CMCP and CPRATS data. As stated in our risk analyses, only eight
sites in the entire watershed had mussel and IBI and/or EPT data. A recommendation to resource
managers is to consider at least a pilot sampling program in which all fauna are sampled at each
site (along with more robust habitat assessment measures), so that this source of uncertainty can
be addressed and hopefully minimized.
6-10
-------
7. MANAGEMENT IMPLICATIONS OF THE CLINCH AND POWELL
VALLEY ASSESSMENT
The assessment process, in particular the development of the conceptual model and the
performance of the mulitvariate analyses, furthered a better understanding of environmental
problems. In assessing environmental risk, a number of Federal, State, and local environmental
agencies and organizations came together to share data, explore and develop solutions, and
undertake actions within the watershed. Risk assessment findings should also help direct the
efforts of the newly formed Upper Tennessee River Basin Roundtable, which is composed of
various individuals, agencies, and organizations that have an interest in protecting the watershed.
Results should be useful to the roundtable as it begins comprehensive strategic planning for
watershed protection. Additionally, the numerous watershed coalition groups within the basin
can use the findings of the risk assessment to direct their efforts to protect and improve water
quality within their watershed.
Pending the results of this assessment, the workgroup agreed to consider implementing
several management objectives to maintain or restore the threatened, endangered, or rare native
freshwater mussels and fish in the Clinch and Powell watershed. These management objectives
are:
• Create and maintain vegetated riparian zones in urban, agricultural, industrial, and
other developed areas to reduce nonpoint-source pollution and enhance habitat.
• Implement BMPs, such as minimum till and treatment of feedlot waste, to reduce
nonpoint-source pollution.
• Contain and treat runoff from mining activities to reduce pollutant load and
sedimentation.
• Install or improve sewage treatment facilities to reduce inputs of pollutants and
nutrients.
• Adequately treat industrial discharges to reduce input of toxic pollutants.
• Create and maintain stormwater retardation and holding facilities for highways and
developed areas to reduce sedimentation and runoff.
7-1
-------
Risk assessment participants developed and improved understanding of the
interrelationships between various components of the ecosystem and the manner in which human
activities contribute to environmental problems within the watershed. The process of risk
assessment helped lend further credence to what many professional resource managers had long
conjectured about problems within the watershed, thereby providing more scientific support for
taking actions to address problems. For example, there is now a better understanding of the
contribution of sediment to the river from cattle grazing. Such risk assessment findings will be
useful to USFWS and TVA personnel, who can now share this information with farmers and
encourage them to take actions, such as building fences to keep cattle out of streams.
Key findings from the Copper Creek pilot study include the following:
• Optimal benefits to fish, mussels, and perhaps other invertebrates would be realized by
maintaining the riparian corridor for a minimum of 500-1,500 m upstream and 100 m
to either side of the stream for the site of interest. This riparian area could constitute a
stream-specific, optimal riparian management area within which to better prioritize
protection efforts.
• Local riparian mitigation techniques (< 100 m upstream of site) might not be as
effective in enhancing fish or mussel diversity as somewhat larger riparian mitigation
efforts. Local instream habitat characteristics may not be related to upland land uses if
there is a wide vegetated riparian corridor in those areas.
Key findings from the analyses of the entire watershed include the following:
• Longer riparian corridor lengths (2-5 km) may be more appropriate in higher-gradient
streams to predict effects of land uses on fish and mussels.
• Shorter riparian corridor lengths (1 km) may be appropriate in low-gradient reaches
(e.g., some parts of the mainstem Clinch and Powell rivers) to protect biota from
deleterious land use effects.
• Mine effluents and spills appear to have the greatest overall effect on mussels and fish,
as compared to other human-activity sources in the watershed.
7-2
-------
• Urban land use had significant effects on stream habitat, mussels, aquatic insects, and
fish. Nonpoint-source runoff as well as wastewater treatment effluents may be
responsible for these effects.
• Accidental chemical spills have had drastic effects on native mussel populations in
several parts of the watershed. These spills are primarily associated with major
transportation corridors (U.S. highways and railroad tracks) and large industrial
facilities.
• Pasture and other agricultural activities were often associated with impaired stream
habitat.
• Because of the strong inverse relationship between mining activities and biota in this
watershed, other land use effects on stream habitat and biota were difficult to
determine. Once mining stressors are addressed, native mussel and fish populations
may improve to a point; then land use-related habitat degradation may be a limiting
factor for these fauna.
Examples of management actions that will be considered by the USFWS and TNC on the
basis of the overall risk assessment findings include
• Restoring additional abandoned mine lands throughout the watershed.
• Studying further the chemical makeup of discharges from coal mining and processing
facilities and the toxicity of these discharges to aquatic species;
• Increasing the extent of forested riparian areas adjacent to and upstream of critical
aquatic habitat sites for mussels and fish;
*• Implementing better spill control mechanisms on roadways and railroads near sensitive
streams and more spill contingency plans for the watershed, which will enable the
Virginia Department of Transportation and other agencies involved in constructing
highway projects on or near waterways to design those projects to reduce catastrophic
events and minimize impacts of accidental spills;
7-3 '
-------
• Studying further the impacts of urban development on aquatic species and working
with planning and development agencies to identify and implement appropriate
measures to protect aquatic resources;
• Improving monitoring and control of allowable limits of constituents from coal mining
operations;
• Restricting the type of materials transported over certain bridges; and
• Installing BMPs for pasture and agricultural land to reduce sediment loading and
implementing better treatment of wastewater discharges.
There are costs associated with implementing management decisions, and trade-offs must
be made. As part of a follow-on study, the University of Tennessee obtained grant funding to
determine how Clinch Valley residents would evaluate trade-offs involving environmental
quality and economic factors in the Clinch Valley. The outcomes of the risk characterization
were directly used in the survey design. Residents were asked to state their preferences between
hypothetical management options that provided differing levels of quality of aquatic life,
sportfishing, songbirds and other wildlife and that also had differing impacts on regional income.
The risk characterization had demonstrated relationships between (1) degree of riparian
agriculture and fish IBI and (2) proximity to coal mining operations and fish ffil. Therefore, in
the survey, one set of hypothetical management options evaluated consisted of agriculture-free
riparian zones of varying widths, and another set included changes in coal sector income that
would be implicit in policies to de-emphasize that sector (Kahn et al., 2001). Survey results,
when analyzed, will enable decisionmakers to score specific options as to their likely acceptance
by the community, including individuals' willingness to be taxed or to accept compensation as
part of implementing a given management strategy.
The watershed ecological risk assessment compiled and organized information from
several sources into a usable data set, which is available from NCEA-W. This will benefit
environmental managers as various agencies and organizations can more easily add to and use
the data to further assess problems for other decision making purposes. For instance, the
Southern Appalachian Man and the Biosphere (SAMAB) program will benefit from
incorporating the recently developed data set into its database. The data and findings will be
used by FWS to undertake environmental review of various federally funded and/or permitted
projects, such as those considered under the authority of the Section 404 of the Clean Water Act
7-4
-------
and the Surface Mining Control and Reclamation Act. The data set will be available to agencies
aid organizations such as FWS and TNC as they strive to develop plans and make decisions
negirding actions to further the recovery of endangered and rare species.
Private landowners and natural resource managers in industry can use the findings to
minimize and avoid impacts of activities on rare species and other fish and wildlife and also to
develop habitat conservation plans for these species. Information developed thronigjli the
assessment may also aid managers and conservation groups in efforts to obtain grants and
assistance from various State- and federally sponsored programs. The vast majority of actions to
remedy environmental problems within the watershed are likely to be accomplished without any
diieet regulatory actions and should benefit local economies and environments.
7-5
-------
-------
REFERENCES
Ahlstedt, SA. (1984) Twentieth century changes in the freshwater mussel fauna of the Clinch River (Tennessee and
Virginia). Walkerana 5:73-122.
Ahlstedt, SA. (1991) Cumberlandian mollusk conservation program: mussel surveys in six Tennessee Valley
streams. Walkerana 5:123-160.
Ahlstedt, SA. (1999) A survey of the native mussel populations of Copper Creek (Clinch River system) in
Southwestern VA. Prepared by American Aquatics, Inc., Oak Ridge, TN, for U.S. Fish and Wildlife Service,
Abingdon, VA.
Ahlstedt, SA; Tuberville, JD. (1997) Quantitative reassessment of the freshwater mussel fauna in the Clinch and
Powell Rivers, Tennessee and Virginia. In: Cummings, K; Buchanan, A; Mayer, C; et al, eds. Conservation and
management of freshwater mussels II: initiatives for the future. Proceedings of an Upper Mississippi River
Conservation Committee Symposium, October 16-18,1995, St. Louis, MO. UMRCC, Rock Island, IL, pp. 72-97.
Angermeier, PL; Smogor, RA. (1993) Final report: assessment of biological integrity as a tool in the recovery of
rare aquatic species. Virginia Department of Game and Inland Fisheries, Richmond, VA (June 1993).
Barbour, MT; Gerritsen, J.; Snyder, BD; et al. (1999) Rapid bioassessment protocols for use in streams and
wadeable rivers: periphyton, benthic macroinvertebrates and fish. 2nd ed. EPA/841-B-99-002. U.S. Environmental
Protection Agency, Office of Water, Washington, DC.
Bates, JM; Dennis, SD. (1978) The mussel fauna of the Clinch River, Tennessee and Virginia. Sterkiana 69-70:3- ,
23.
BMI (Biological Monitoring, Inc.). (1990) Toxicity effects of a deep mine water sump discharge containing a
hydraulic oil at Westmoreland Coal Co., Big Stone Gap, VA. Biological Monitoring, Inc., Blacksburg, VA.
BMI. (1998) Estimation of exposure and effects from a mine tailings release upstream of endangered species
critical habitat. Presented at Society of Toxicology and Chemistry annual meeting, November 15-19,1998,
Charlotte, NC.
Bogan, AE; Parmalee, PW. (1983) Tennessee's rare wildlife. Volume II: the mollusks. Knoxville, TN: University
of Tennessee Press.
Cairns, J, Jr.; Grossman, JS; Dickson, KL; et al. (1971) The recovery of damaged streams. Am Soc Biol Bull
18:79-106.
R-l
-------
Causey, I; Douglas, J. (1998). MAS/MILS mineral location database information. U. S. Geological Survey, Spatial
Data Delivery Website, http://minerals.usgs.gov/sddp/doc/faq/mineralavailabilitysystem.faq.html
Reston,VA.
Cherry, DS; Rutherford, LG; Dobbs, MG; et al. (1995) Acidic pH and heavy metal impacts into stream watershed
and river ecosystems by abandoned mined lands, Powell River, Virginia. Virginia Polytechnic Institute and State
University, Blacksburg, VA., 95-3,57pp.
Church, GW. (1996) Factors affecting distribution and abundance of native bivalves in the Clinch River. Ph.D.
dissertation. Virginia Polytechnic Institute and State University, Blacksbur, VA.
Cooper, JR; Gilliam, JW; Daniels, RB; et al. (1987) Riparian areas as filters for agricultural sediment. Soil Sci Soc
Am 151:416420.
Grossman, JS; Cairns, J; Kaesler, RL. (1973) Aquatic invertebrate recovery in the Clinch River following hazardous
spills and floods. Virginia Water Resources Research Center, Virginia Polytechnic Institute and State University,
Blacksburg, VA. Bulletin 63.
Dennis, SD. (1981) Mussel fauna of the Powell River, Virginia and Tennessee. Sterkiana 71:1-7.
Dennis, SD. (1985) Distributional analysis of the freshwater mussel fauna of the Tennessee River system with special
reference to possible limiting effects of siltation. Tennessee Wildlife Resources Agency, Nashville, TN. No. 85-2.
Diamond, JM; Serveiss, VB. (2001) Identifying sources of stress to native aquatic species using a watershed
ecological risk assessment framework. Environ Sci Technol 35(24):4711-4718.
Diamond, JM; Serveiss, VB. (2002) Diagnosing causes of native fish and mussel species decline in the Clinch and
Powell River watershed, Virginia, USA. Environ Toxicol Chem. Accepted.
Diamond, J; Daley, C; Barbour, M. (1999) Evaluating whole effluent toxicity as an indicator of instream biological
condition. Water Environment Research Foundation, Alexandria, VA. Technical report 94-HHE-l.
Etnier, DA; Starnes, WC. (1994) Fishes of Tennessee. Knoxville, TN: University of Tennessee Press.
Fisher, S; Gray, L; Grimm, N; et al. (1982) Temporal succession in a desert stream ecosystem following flash
flooding. EcolMonogr 52:93-110.
Freeman, JC, Jr. (1987) Results offish surveys in the Tennessee River drainage, 1979-1981. Brimleyana 13:99-121.
Fuller, SL. (1974) Spatial competition between Corbicula manilensis (Philippi) and freshwater mussels (Unionidae)
in the Waccamaw River basin of the Carolinas. Assoc South Biol Bull 23:60.
R-2
-------
Gardner, JA; Woodall, WR, Jr.; Staats, JR; et al. (1976) The invasion of the Asiatic clam in the Altamalia River,
Georgia. Nautilus 90:117-125.
Goudreau, SE; Neves, RJ; Sheehan, RJ. (1993) Effects of wastewater treatment plant effluents on freshwater
molluscs in the upper Clinch River, Virginia, USA. Hydrobiologia 252:211-230.
Gregory, SV; Swanson, FJ; McKee, WA; et al. (1991) An ecosystem perspective of riparian zones. BioScience
41:540-551.
Havlik, ME; Marking, LL. (1987) Effects of contaminants on naiad molluscs (Unionidae): a review. U.S. Fish and
Wildlife Service, Research Publication 164:1-20.
Hermann, K, ed. (1996) The Southern Appalachian Assessment Database, http://www.samab.org/data/data.html In:
Southern Appalachian Man and the Biosphere Program. US Geological Survey. Knoxville, TN
Hylton,R. (1998) Setback hinders endangered mussel recovery. Triennial Unionid Report 16:24-25.
ITFM (Interagency Task Force for Monitoring). (1995). The strategy for improving water quality monitoring in the
U.S. U.S. Geological Survey, Reston, VA. Report #OFR95-742.
Jenkins, RE; Burkhead, NM. (1994) The freshwater fishes of Virginia. American Fish Society, Bethesda, MD.
Jones, RC; Clark, CC. (1987) Impact of watershed urbanization on stream insect communities. Water Resources
Bull 23(6): 1047-1055.
Jones, J; Patterson, M; Good, C; et al. (2000) Survey to evaluate the status of freshwater mussel populations in the
upper Clinch River, VA. Final Report. U.S. Fish and Wildlife Service, Abingdon, VA.
Kahn, JR; Stewart, S; O'Neill, R; et al. (2001) A trade-off weighted index approach: integrating economic and
ecological analysis. In: Bosch, D, ed. Proceedings of the integrated decision-making for watershed management
symposium: processes and tools; January 7-9, Chevy Chase, MD. Bosch, D;ed. VWRRCP72001. Virginia
Polytechnic Institute and State University, Blacksburg, VA; pp. 311-325.
Karr, JR. (1991) Biological integrity: A long neglected aspect of water resource management Ecological
Applications, Vol. 1, No. 1; pp. 66-84.
Karr, JR; Chu, EW. (1999) Restoring life in running waters: better biological monitoring. Washington, DC: Island
Press.
Kauss, P; Hamdy, Y. (1991) Polycyclic bromatic hydrocarbons in surficial sediments and caged mussels of the St.
Mary's River. Hydrobiologia 219:37-62.
R-3
-------
Kitchel, HE. (1985) Life history of the endangered shiny pigtoe pearly mussel, Fusconaia engariana, in the North
Fork Holston River, Virginia. M.S. thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA.
Landis, WG; Wiegers, JA. (1997). Design considerations and a suggested approach for regional and comparative
ecological risk assessment. HumEcol Risk Assess 3(3):287-297.
Lenat, DR. (1984) Agriculture and stream water quality: a biological evaluation of erosion control practices.
Environ Manage 8:333-344.
Lingenfelser, S. (2000) Environmental Contaminants Program off-refuge investigations sub-activity. U.S. Fish and
Wildlife Service, Gloucester, VA. Draft interim report, project 9850002.1.
Livingstone, D; Pipe, R. (1992) Mussels and environmental contaminants: molecular and cellular aspects. Dev
Aqua Fish Sco 25:425464.
Lowrance, R; Todd, R; Fail, J, Jr.; et al. (1984) Riparian forests as nutrient filters in agricultural watersheds.
Bioscience 34(6):374.
Masnik, MT. (1974) Composition, longitudinal distribution, and zoogeography of the fish fauna of the upper Clinch
system in Tennessee and Virginia. Ph.D. dissertation, Virginia Polytechnic Institute and State University,
Blacksburg, VA.
MDCB (Methods and Data Comparability Board). (1999). Position Paper: Towards a definition of a performance-
based approach to laboratory methods. http://wi.water.usgs.gov/pmethods/PBMS/position.html.
Minshall, GW. (1993) Stream-riparian ecosystems: rationale and methods for basin-level assessments of
management effects. In: Jensen, ME; Bourgeron PS, eels. Eastside forest ecosystem health assessment. Vol. 2.
Ecosystem management: principles and applications. Portland, OR: Pacific Northwest Research Station, U.S. Forest
Service.
Minshall, GW; Andrews, D; Manuel-Faler, C. (1983) Application of island biogeographic theory to streams:
macroinvertebrate recolonization of the Teton River. In: Barnes J; Minshall G, eds. Stream ecology. New York:
Plenum Press, pp. 279-298.
Morris, T; Corkum, L. (1996) Assemblage structure of freshwater mussels (Bivalvia: Unionidae) in rivers with
grassy and forested riparian areas. J N Am Bethel Soc 15:576-586.
Neves, RJ. (1991) Mollusks. In: Terwilliger, K, ed. Virginia's endangered species. Blacksburg, VA: McDonald
and Woodward; pp. 251-320.
Neves, R; Weaver, L; Zale A. (1985) An evaluation of host fish suitability for glochidia of Villosa vanuxemi and V.
nebulosa (Peleypoda:Unionidae). Amer Mid Natur 113:13-19.
R-4
-------
Norton, SB; Cormier, S; Smith, M; et al. (2000). Can biological assessments discriminate among types of stress? A
case study from the eastern corn belts plains ecoregion. Environ Toxicol Chem 19(4):1113-1119.
O'Bara, CJ; Eggleton, MA; McAdoo, LM; et al. (1994) Clinch River biotic assessment part 1: macrobenthic and fish
communities. Tennessee Wildlife Resources Agency, Nashville, TN.
OTfeil, Jr., CR. (1991) The zebra mussel (Dreissena polymorpha): an unwelcome North American invader. New
York Sea Grant, Cornell Cooperative Extension, State University of New York, Brockport, NY.
Omernik, JM; Abernathy, AR; Male, LM. (1981) Stream nutrient levels and proximity of agricultural and forest
land to streams: some relationships. J Soil Water Conserv 36:227-231.
Ortmann, AE. (1918) The nayades (freshwater mussels) of the upper Tennessee drainage with notes on synonomy
and distribution. Proc Am Phil Soc 52.
Osborne, LL; Kovacic, DA. (1993) Riparian vegetated buffer strips in water-quality restoration and stream
management. Freshwater Biol 29:243-258.
Reed, DK. (1993) Impact zone delineation for biological assessment of power plant effluent effects on snail
populations in the Clinch River. Ph.D. dissertation, Virginia Polytechnic Institute and State University, Blacksburg,
VA.
Richards, C; Host, G. (1994) Examining land use influences on stream habitats and macroinvertebrates: a GIS
approach. Water Res Bull 30:729-738.
Richter, BD. (1996) An analysis of hydrologic changes in the Clinch River of Virginia. Biohydrology Program.
The Nature Conservancy. Hayden, CO.
Schueler,T. (1994) The importance of imperyiousness. Watershed Protection Techniques 1(3): 100-111.
Serveiss, V; Norton, SB; Norton, DJ. (2000) Watershed ecological risk assessment The Watershed Academy, US
EPA; on-line training module at http://www.epa.gov/owow/watershed/wacademy/acad2000/ecorisk.
Serveiss, VB. (2002) Applying ecological risk principles to watershed assessment and management. Environ
Manage 29(2):145-154.
Sheehan, RJ; Neves, RJ; Kitchel, HE. (1989) Fate of freshwater mussels transplanted to formerly polluted reaches of
the Clinch and North Fork Holston Rivers, Virginia. J Freshwater Ecol 5:139-149.
Stansbery, DH; Stein, CB. (1976) Changes in the distribution ofIofluvialis(Szy) in the upper Tennessee River
system (Gastropoda: Pleuroceridae). Bull Am Malacologist Union 1976:28-33.
R-5
-------
Stansbery, DH; Stein, CD; Watters, GT. (1986) The distribution and relative abundance of unionid mollusks in the
Clinch River in the vicinity of Appalachian Power Company's Clinch River plant at Carbo, Virginia (Clinch river
miles 264-270). Ohio State University Research Foundation, Columbus, OH. Project 764801/71733.
Stein, B; Kutner, L; Adams, J. (2000) The status of biodiversity in the United States. The Nature Conservancy.
New York: Oxford University Press.
TVA (Tennessee Valley Authority). (1970) Tennessee Valley streams: their fish, bottom fauna, and aquatic habitat,
Powell River basin. Division of Forestry, Fisheries, and Wildlife Department, Norris, TN.
TVA. (1981) Cumberlandian mollusc conservation program report: Copper Creek, Clinch River basin. Division of
Forestry, Fisheries, and Wildlife Department, Norris, TN.
Tessier, A; Campbell, PG; Anclair, IP; et al. (1984) Relationships between the partitioning of trace metals in
sediments and their accumulation in the tissues of the freshwater mollusc Elliptic camplanata in a mining area. Can
J Fish Aquat Sci 41:1463-1472.
U.S. EPA (Environmental Protection'Agency). (1998) Guidelines for ecological risk assessment. EPA/630/R-
95/002F. Office of Research and Development. Washington, DC.
U.S. EPA. (2000) The U.S. EPA Reach File Version 3.0 Alpha Release (RF3-Alpha) Technical Reference..
http://www.epa.gov/owow/monitoring/rf/techref.html. Office of Water. Washington, DC.
USCS (U.S. Soil Conservation Service). (1992) Clinch River basin land and water resources study for hydrological
units. Abingdon, VA.
USGS (U.S. Geological Survey). (2001) Digital Elevation Models, http://rockyweb.cr.usgs.gov/elevation/
dpi_dem.html#document. Rocky Mountain Mapping Center. Sioux Falls, SD.
Van Hassel, JH; Gaulke, AE. (1986) Site-specific water quality criteria from instream monitoring data. Environ
Toxicol Chem 5(5):417-426.
Vannote, R; Minshall, G; Cummins, K;etal. (1980) The river continuum concept. Can J Fish Aquat Sci 37:130-
137.
VDEQ (Virginia Department of Environmental Quality). (1996) Virginia water quality assessment 1996.
Richmond, VA.
Wallace, JB; Vogel, D; Cuffney, T. (1986) Recovery of a headwater stream from an insecticide-induced community
disturbance. J North Am Benthol Soc 5:115-126.
R-6
-------
Warren, LW; Klaine, SJ; Finley, MT. (1995) Development of a field bioassay with juvenile mussels. J North Am
BentholSoc 14:341-346.
Waiters, T. (1996) Small dams as barriers to freshwater mussels (Bivalvia, Unionidae) and their hosts. Biol
Conserv 75:79-85.
Watters.T. (1997) Individual-based models of mussel-fish interactions: a cautionary study. In: Cummings, K;
Buchanan, A; Mayer, C; eds. Conservation and management of freshwater mussels H: initiatives for the future.
Proceedings of an Upper Mississippi River Conservation Committee Symposium, October 16-18,1995, St. Louis,
MO. UMRCC, Rock Island, IL, pp. 61-71.
Way, C; Miller, A; Payne, B. (1990) The influence of physical factors on the distribution and abundance of
freshwater mussels in the upper Tennessee River. Nautilus 103:96-98.
Wiegers, JK; Feder, HM; Mortensen, LS; et al. (1998) A regional multiple stressor rank-based ecological risk
assessment for the fjord of Port Valdez, AK. Hum Ecol Risk Assess 4(5): 1125-1173.
Wolcott, L; Neves, R. (1994) Survey of the freshwater mussel fauna in the Powell River, Virginia. Banisteria 3:3-
14.
Yeager, BL. (1994) Impacts of reservoirs on the aquatic environment of regulated rivers. Tennessee Valley
Authority, Resource Group, Water Management. Norris.TN.
Young, M; Williams, J. (1983) Redistribution and local recolonization by the freshwater pearl mussel. J Conchol
31:225-234.
Zale, AV; Neves, RJ. (1982a) Fish hosts of four species of Pampsilae mussels (Unionidae) in Big Moccasin Creek,
Virginia. Can J Tool 60:2535-2542.
Zale, AV; Neves, RJ. (1982b) Reproductive biology of four freshwater mussel species (Unionidae) in Virginia.
Fresh Invert Biol 1:17-28.
Zipper, CE; Holtzman, GI; Rheem, S; et al. (1991) Understanding surface water quality trends in Southwestern
Virginia. Virginia Polytechnic Institute and State University, Water Resources Research Center, Blacksburg, VA.
R-7
-------
-------
APPENDIX A
STAKEHOLDERS INVOLVED IN RISK ASSESSMENT PLANNING
-------
Table A-l. Agencies and conservation organizations active in the Clinch and
Powell watershed
Federal
government
TV A, Clinch River Action Team
U.S. Environmental Protection Agency
Department of Interior
U.S. Fish and Wildlife Service
U.S. Geological Survey
National Biological Service
Office of Surface Mining
Department of Agriculture
U.S. Forest Service
Natural Resource Conservation Service
Consolidated Farm Services Agency
Rural Economic and Community
Development
State
government
VIRGINIA
Department of Conservation and Recreation
Division of Natural Heritage
Division of Soil and Water Conservation
Division of Parks and Recreation
Department of Agriculture and Consumer Services
Soil and Water Conservation Districts
Department of Forestry
Department of Game and Inland Fisheries
Department of Mines, Minerals, and Energy
Division of Mined Land Reclamation
(and other divisions)
Department of Environmental Quality
Virginia Cave Board
TENNESSEE
Tennessee Wildlife Resources Agency
Department of Environment and Conservation
Division of Natural Heritage
Division of Water Pollution Control
Division of Abandoned Mine Land
Reclamation
Department of Agriculture
Division of Forestry
Division of Plant Sciences
Soil and Water Conservation Districts
Department of Housing and Urban Development
Planning District Commissions
Organizations
VIRGINIA
The Nature Conservancy
Black Diamond Resource Conservation and
Development Council
Coalition for Jobs and the Environment
Clinch/Powell Sustainable Development Initiative
Southern Environmental Law Center
Sierra Club
Audubon Naturalist Society
TENNESSEE
The Nature Conservancy
Clinch-Powell Resource Conservation and Development
Council
Citizens for Wilderness Planning
Save Our Cumberland Mountains
Tennessee Ornithological Society
Tennessee Scenic Rivers Association
Friends of the Clinch and Powell Rivers
Sierra Club
Universities
and colleges
Virginia Polytechnic Institute and State University
Tennessee Technological University
University of Tennessee
East Tennessee State University
Tusculum College
Virginia Highlands Community College
Southwestern Virginia Community College
Empire Community College ;
Clinch Valley College
University of Virginia
A-2
-------
APPENDIX B
NATIVE MUSSEL AND FISH SPECIES OF CONCERN IN
THE CLINCH AND POWELL WATERSHED
-------
Table B-l. Mussel species in the Clinch and Powell watershed
UC = Upper Clinch; CC = Copper Creek; LR = Little River; PR = Powell River; Hist = Historical; Ext = Extant
Species
(** = Cumberlandian)
Actinonaias ligamentina
Actinonaias pectorosa **
Alasmidonta marginata
Alasmidonta viridis
Amblema plicata
Cumberlandia monodonta
Cyclonaias tuberculata
Cyprogenia stegaria
Dromus dromas **
Elliptic crassidens
Elliptic dilatata
Epioblasma arcaeformis**
Epioblasma biemarginata
Epioblasma brevidens **
Epioblasma capsaeformis **
Epioblasma florentina walkeri**
Epioblasma haysiana**
Epioblasma lenoir**
Epioblasma lewisi**
Epioblasma tortulosa gubernaculum**
Epioblasma triquetra
Fusconaia barnesiana**
Fusconaia cor **
Fusconaia cuneolus **
Fusconaia subrotunda
Hemistena lata
Lampsilis abrupta
Lampsilis fasciola
Lampsilis ovata
Lampsilis ovata ventricosa
Lasmigona costata
Lasmigona holstonia
Lemiox rimosus **
Leptodea fragilis
UC
Hist
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
UC
Ext
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
CC
Ext
X
X
X
X
X
X
X
X
X
X
X
LR
Ext
X
X
X
X
X
X
PR
Hist
X
X
X
X
X
X
X
X
x •
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
PR
Ext
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
B-2
-------
Table B-l. Mussel species in the Clinch and Powell watershed (continued)
Species
(** = Cumberlandian)
Lexingtonia dolabelloides**
Ligumia recta
Medionidus conradicus **
Pegias fabula**
Plethobasus cyphyus
Pleurobema coccineum
Pleurobema cordatum
Pleurobema oviforme**
Pleurobema plenum
Pleurobema rubrum
Potamilus alatus
Ptychobranchus fasciolaris
Ptychobranchus subtentum **
Quadrula cylindrica
Quadrula cylindrica cylindrica
Quadrula cylindrica strigillata
Quadrula intermedia**
Quadrula pustulosa pustulosa
Quadrula sparsa**
Strophitus undulatus
Toxolasma lividus**
Truncilla truncata
Villosa fabalis
Villosa iris
Villosa perpurpurea **
Villosa trabalis**
Villosa vanuxemensis vanuxemensis **
TOTAL:
UC *
Hist
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
UC
Ext
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
cc
Ext
X
X
X
X
X
X
X
X
X
LR
Ext
X
X
X
X
X
X
PR
Hist
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
PR
Ext
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Source: Steve Ahlstedt, U.S. Geological Survey, presented at a Clinch and Powell Workgroup Meeting, 1997.
B-3
-------
Table B-2. Fish species in the Clinch and Powell watershed
H = Historical record
Species
(** = Introduced)
Ambloplites rupestris
Ameiurus melas**
Ameiurus natalis
Ammocrypta clara
Ammocrypta pellucida
Aplodinotus grunniens
Campostoma anomalum
Carassius auratus **
Carpiodes carpio
Carpiodes cyprinus
Carpiodes velifer
Catostomus commersoni
Clinostomus funduloides
Cottus baileyi
Cottus bairdi
Cottus carolinae
Cottus sp (broadbanded sculpin)
Ctenopharyngodon idella**
Cycleptus elongatus
Cyprinella galactura
Cyprinella monacha
Cyprinella spiloptera
Cyprinella whipplei
Cyprinus carpio **
Dorosoma cepedianum
Dorosoma petenense **
Ericymba buccata**
Erimystax cahni
Erimystax dissimilis
Erimystax insignis
Esox masquinongy **
Etheostoma blennioides
Etheostoma caeruleum
Etheostoma camurum
Etheostoma cinereum
Upper Clinch
06010205
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copper Creek
06010205
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
x •
X
Guest River
06010205
X
X
X
X
X
X
X
Powell River
06010206
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
B-4
-------
Table B-2. Fish species in the Clinch and Powell watershed (continued)
Species
.(** = Introduced)
Etheostoma flabellare
Etheostoma kennicotti
Etheostoma percnurum
Etheostoma rufilineatum
Etheostoma simoterum
Etheostoma stigmaeum jessiae
Etheostoma swannanoa
Etheostoma tippecanoe
Etheostoma vulneratum
Etheostoma zonale
Fundulus catenatus
Gambusia affinis **
Hiodon tergisus
Hybognathus hankinsoni
Hybopsis amblops
Hypentelium nigricans
Ichthyomyzon bdellium
Ichthyomyzon gagei
Ichthyomyzon greeleyi
Ictalurus furcatus
Ictalurus punctatus
Ictiobus bubalus
Ictiobus cyprinellus
Ictiobus niger
Labidesthes sicculus
Lagochila lacera
Lampetra aepyptera
Lampetra appendix
Lepisosteus oculatus
Lepisosteus osseus
Lepomis auritus **
Lepomis cyanellus
Lepomis gibbosus**
Lepomis gulosus
Lepomis macrochirus
Upper Clinch
06010205
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copper Creek
06010205
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Guest River
06010205
X
X
X
X
X
Powell River
06010206
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
B-5
-------
Table B-2. Fish species in the Clinch and Powell watershed (continued)
Species
(** = Introduced)
Lepomis megalotis
Lepomis microlophus**
Luxilus chrysocephalus
Luxilus coccogenis
Lythrurus ardens
Lythrurus lirus
Macrhybopsis aestivalis
Micropterus dolomieu
Micropterus punctulatus
Micropterus salmoides
Morone chrysops **
Morone saxatilis **
Moxostoma anisurum
Moxostoma carinatum
Moxostoma duquesnei
Moxostoma erythrurum
Moxostoma macrolepidotum
Nocomis micropogon
Notemigonus crysoleucas**
Notropis ariommus
Notropis atherinoides
Notropis buchanani
Notropis leuciodus
Notropis photogenis
Notropis rubellus
Notropis rubricroceus
Notropis sp. (palezone shiner)
Notropis sp. (sawfm shiner)
Notropis spectrunculus
Notropis telescopus
Notropis volucellus
Noturus eleutherus
Noturus flavipinnis
Noturus flavus
Noturus stanauli
Upper Clinch
06010205
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copper Creek
06010205
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Guest River
06010205
X
X
X
X
X
X
,
Powell River
06010206
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
B-6
-------
Table B-2. Fish species in the Clinch and Powell watershed (continued)
Species
(** = Introduced)
Oncorhynchus mykiss **
Percina aurantiaca
Percina burtoni
Percina caprodes
Percina copelandi
Percina evides
Percina macrocephala
Percina maculata
Percina sciera
Phenacobius crassilabrum
Phenacobius uranops
Phoxinus erythrogaster
Pimephales notatus
Pimephales promelas **
Pimephales vigilax
Polyodon spathula
Pomoxis annularis
Pomoxis nigromaculatus
Pylodictis olivaris
Rhinichthys atratulus
Rhinichthys cataractae
Salmo trutta **
Salvelinus fontinalis **
Semotilus atromaculatus
Stizostedion canadense
Stizostedion vitreum
TOTAL:
Upper Clinch
06010205
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copper Creek
06010205
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Guest River
06010205
X
X
X
X
X
X
Powell River
06010206
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Source: Adopted from Jenkins and Burkhead, 1994
B-7
-------
-------
APPENDIX C
RIPARIAN CORRIDOR LAND USE ANALYSES,
UPPER CLINCH RIVER
-------
•g »
•c 3
"
1 2
-1
10
20
30 40 50
% Forest (100m x 5km corridors)
60
70
Figure C-l. Mussel richness versus the percentage of forested land within 100-m- wide, 5-km-
long riparian corridors; streams are separated according to an average catchment slope threshold
of 33%.
7
6
5
w 4
I 3
1 2
1
-1
10
90
110
30 50 70
% Forest (200m x 1km corridors)
Figure C-2. Mussel richness versus the percentage of forested land within 200-m- wide, 1-km-
long riparian corridors; streams are separated according to an average catchment slope threshold
of 33%.
C-2
-------
7
6
5
» 4
w
O <3
1 2
1
-1
Elevation>625m
Elevation<625nn
10
20
30 40 50
% Forest (100m x 5km corridors)
60
70
Figure C-3. Mussel richness versus forested land in 100 m x 5 km corridors with sites divided into site
elevation categories (m).
C-3
-------
CO
o>
o
•n
"oJ
(0
(0
Low
Stream order
HZ. Non-outlier max
Non-outlier min
CU 75%
25%
Q Median
o Outliers
* Extremes
Figure C-4. Mussel richness in high (>4th order) and low (3-4th order) order streams.
C-4
-------
0)
g
(B
•D
I
10
280
240
200
160
120
80
40
Forest>50%
Forest<50%
Non-outlier max
Non-outliermin
CD 75%
25%
° Median
100m x 1km corridors
Figure C-5. Abundance of mussels in relation to forested land within 100-m-wide, 1-km-long
riparian corridors of high-order streams (>4th order).
c
280
220
160
1.00
40
-20
Forest>30%
Forest<30%
Non-outlier max
Non-outliermin
CH 75%
25% ,
n Median
100m x 2km corridors
Figure C-6. Abundance of mussels in relation to forested land within 100-m -wide, 2-km-long
riparian corridors of low-order streams (>4th order).
C-5
-------
Mussel richness (Left axis)
Mussel abundance (Right axis)
560 600 640
Elevation (m)
J-50
720
Figure C-7. Relation of mussel richness (left Y-axis) and abundance (right Y-axis) to site
elevation (m) for high-order streams (^ order).
Mussel richness (Left axis)
Mussel abundance (Right axis)
n»
550
450
350
31.6
32.0
32.4 32.8 . 33.2
Average catchment slope (%)
33.6
34.0
Figure C-8. Relation of mussel richness (left Y-axis) and abundance (right Y-axis) to average
catchment slope (%) for high-order streams (>4* order).
C-6
-------
ot.u
33.6
!r 33.2
Q.
"in
| 32.8
JT
O
8
a>
§? 32.4
I
32.0
31.6
5(
I
iii
•
' %" '
1 ' '" '• '•"'•»-
,
>
• • — • — ' —
-.
l§
•
0 520 540 560 580 600 620 64
Elevation (m)
Figure C-9. Site elevation (m) versus average catchment slope (%) for high-order streams (>4t!l
order).
55
o
LL
S,51
CO
is '
D 50
51)0
520
540
600
620
640
560 580
Elevation (m)
Figure C-10. Drainage area forested land (%) versus site elevation for high-order streams (>4th
order).
C-7
-------
-1
•fl
"*•••• Mussel richness (Left axis)
"°^ Mussel abundance (Right axis)
•a..
26 30 34 38 42 46
Average catchment slope (%)
50
550
450
350
250
150
50
'54
-50
Figure C-ll. Relation of mussel richness (left Y-axis) and abundance (right Y-axis) to average
catchment slope (%) for low-order streams (3rd or 4th order).
1
U
•c
-1
480
• No site-specific factors
D Site-specific degradation
D •
• •
D ••• •
0 • •
520
560
600
Elevation (m)
640
680
720
Figure C-12. Mussel richness versus site elevation for both sites with specific stressors and
those with no site-specific stressors; site-specific degradation is seen here as outlier sites from
broad-scale patterns.
C-8
-------
(A 4
1
I 3
-1
10
• No site-specific factors
D Site-specific degradation
20
60
70
30 40 50
Forest % (1 00m x 5km corridors)
Figure C-13. Mussel richness versus corridor forested land for both sites with specific stressors
and those with no site-specific stressors; site-specific degradation is seen here as outlier sites
from broad-scale patterns.
C-9
-------
-------
-------
United States
Environmental Protection
Agency
National Center for
Environmental Assessment
Washington, DC 20460
Official Business
Penalty for Private Use
$300
Please make all necessary changes on the below label,
detach or copy, and return to the address in the upper
left-hand corner.
If you do not wish to receive these reports CHECK HEREd;
detach, or copy this cover, and return to the address in the
upper left-hand comer.
PRESORTED STANDARD
POSTAGE & FEES PAID
EPA
; PERMIT No. G-35 !
EPA/600/R-01/050
September 2002
------- |