EPA
United States Environmental Protection Agency
Region 10
1200 Sixth Avenue
Seattle, WA 98101
Alaska • Idaho • Oregon • Washington
IWRRI
Idaho Water Resources Research Institute
University of Idaho
Moscow, ID 83843
July 1999 EPA910-R-99-014
Aquatic Habitat Indicators
and their Application to Water
Quality Objectives within the
Clean Water Act
*
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EPA910-R-99-014
Aquatic Habitat Indicators
and their Application to Water Quality
Objectives within the Clean Water Act
Stephen B. Bauer1 and Stephen C. Ralph2
1999
Idaho Water Resources Research Institute1
University of Idaho
Moscow, Idaho 83843
United States Environmental Protection Agency Region 102
1200 Sixth Avenue
Seattle, WA 98101
Additional copies may be requested by contacting EPA Region 10
1-800-424-4372
http://www.epa.gov/r1 Dearth
This document should be cited as:
Bauer, Stephen B. and Stephen C. Ralph. 1999. Aquatic habitat indicators and their application to water
quality objectives within the Clean Water Act. EPA-910-R-99-014. US Environmental Protection Agency,
Region 10, Seattle Wa.
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Aquatic Habitat Indicators
DISCLAIMER
The purpose of the document is to further the objective consideration of the scientific basis for the use of
aquatic habitat indicators under the authority of the Clean Water Act, and to foster the exchange of
information and ideas among governmental, non-governmental, tribal scientists and interested citizens.
A thorough policy and legal analysis has not been made of the findings described in this document. The
views expressed in this document are the authors' and do not necessarily reflect those of EPA, the
University of Idaho or other institutions with which the authors are affiliated. Rather, they reflect the
opinions of the authors as shaped by their experiences, interpretation of the scientific and technical
literature and their understanding of the input provided by their colleagues at workshops and as a result of
document review. These contributions are gratefully acknowledged. The authors accept full
responsibility for any omissions or misinterpretations of facts, and invite others to share their alternative
ideas on advancing the goal of defining objective measures of success for recovery and protection of
aquatic ecosystems.
The document has been funded through a cooperative agreement of the U.S. Environmental Protection
Agency Region 10 and the University of Idaho Water Resources Research Institute. It has been
subjected to the agency's peer review process and has been approved for publication.
ACKNOWLEDGEMENTS
We appreciate the thoughtful discussion of the natural resource specialists that attended one-day
workshops in Alaska, Oregon, Washington, and Idaho. We have carefully considered all their ideas and
incorporated them into this document as much as possible. We especially wish to acknowledge a
number of colleagues that contributed their time and effort on the document. Robert Denman wrote the
initial section on stream and landscape classification and provided additional comments. Steve Paustian
described the habitat indicators for Southeast Alaska listed in an appendix as well as contributing his
ideas and expertise to the project. Philip Kaufman provided the results and helpful guidance on the
quality assurance data from the Environmental Monitoring and Assessment Program. Don Zaroban, Rick
Hafele, Doug Drake, Dale McCullough, and Doug Martin took time out of their busy schedules to provide
comments on several drafts. Marcia Lagerloef assisted us in understanding the potential application to
water quality standards and provided comments on numerous drafts. Lana Shea Flanders and Chris
Mead helped organize and facilitate the workshop in Juneau, Alaska. Don Martin and Ken Feigner
provided moral and financial support throughout the project. Jennifer Golden developed data bases,
compiled the literature, and formatted the document many times along the way. Inez Hopkins helped
compile the bibliography. We wish to thank everyone for his or her invaluable assistance.
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Aquatic Habitat Indicators
ABSTRACT
The objective of this paper is to evaluate the application of aquatic habitat variables to water quality
objectives under authority of the Clean Water Act (CWA). The project is limited to freshwater, lotic
aquatic habitats in the Pacific Northwest and Alaska with an emphasis on salmonid habitat. Habitat
variables were placed into one of the following categories - flow regime, habitat space, channel structure,
substrate quality, streambank condition, riparian condition, temperature regime, and habitat access.
Candidate habitat variables were evaluated for their relevance to the biotic community, responsiveness to
human impacts, applicability to target landscapes, and measurement reliability. The most critical
obstacles for use of habitat variables at the regional level (state specific water quality criteria for Region
10 EPA) are the quantification of biological effect and the unreliability of the measurement system.
Inherent variability and unreliable data quality preclude the use of numeric values for habitat variables as
compliance indicators in statewide water quality criteria. Rather, habitat variables should be used as
diagnostic indicators of beneficial use attainment and pollution control performance, and should be
developed and calibrated at local or ecoregional scales as stratified by landscape and stream
characteristics. Currently only a few habitat variables meet the evaluation criteria established by the
authors for use under CWA authority, specifically large woody debris, pool frequency, and residual pool
depth. It is recognized that this limited set of variables will not satisfy the ecological habitat requirements
needed to protect cold water biota. Recommendations to increase the applicability of habitat indicators to
CWA objectives include an interagency (and international) effort to evaluate landscape classification of
aquatic areas, identify and measure reference area condition at ecoregional scales, and develop a
systematic approach for habitat indicator quantification. In the interim the authors recommend a re-
examination of the narrative water quality standards in EPA Region 10 to provide more specificity in
regards to salmonid habitat protection. Water quality standards should also specify the process whereby
numeric criteria can be established at the local or ecoregional scale.
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Aquatic Habitat Indicators
Table of Contents
Executive Summary and Recommendations i
Key Points i
Recommendations for Future Actions v
1. Introduction 1
Scope of Project 1
Objectives 2
Methods 2
Terminology 2
Declines in Fisheries and Water Quality 3
Role of Habitat Indicators in the Clean Water Act and Endangered Species Act 4
2. Challenges in Developing Habitat Quality Indicators 9
Natural Variability 9
Lack of Reference Conditions to Serve As Benchmarks 10
The Effect of Natural Disturbance on Stream Conditions 10
Measurement Quality Considerations 11
Use of Habitat Variables Within the Clean Water Act 11
3. Salmonid Habitat Requirements and Land use effects 13
Introduction 13
Migration of Adults 13
Spawning and Incubation 14
Rearing Habitat 14
Alteration of Salmonid Habitats by Land-Use Practices 15
4. A Landscape Context for Habitat Indicators 22
Temporal and Spatial Scales 22
Hierarchical Context 22
Control Factors and Scale 22
Classification Systems 23
Derivation of Habitat Indicator Variables and Stream Classification 24
A Hierarchical Approach for Habitat Indicators 25
Stratification at the Stream Reach Level 27
Summary 29
5. An Approach to Habitat Quality Indicators 30
Types of Indicators 30
Input vs. Output Approaches to Ecosystem Management 31
Using Indicators in ESA Review 31
Suggested Approach for Habitat Quality Indicators under the CWA 31
Scenarios for Interpretation of Diagnostic Indicators 32
Assessment Scale 33
Narrative and Numeric Criteria 33
6. Evaluation of Potential Aquatic Habitat Indicators 34
Indicators in Relation to Clean Water Act Objectives 34
Sorting Potential Narrative and Numerical Indicators 39
Potential Habitat Components and Habitat Variables 41
Sorting Potential Aquatic Habitat Indicators 43
Streambank and Riparian Condition 48
Water Column Chemistry, Habitat Access & Watershed Condition 49
7. Assessment and Monitoring 51
Introduction 51
Monitoring Design 51
Data Quality Objectives 53
Use of Physical Habitat Variables in Monitoring 55
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Aquatic Habitat Indicators
Measurement of Habitat Variables 56
Case Study of Precision of Physical Habitat Variables 57
Detecting Differences 58
Utility of Existing Habitat Assessment Methods 59
Summary 60
8. Application of Aquatic Habitat Indicators to CWA Programs 61
Application to Water Quality Standards 61
Literature Cited 70
Appendices
APPENDIX A: Example of Aquatic Habitat Indicators in the Rocky Mountain Ecoregion 79
Introduction 79
The Natural Conditions Database of Salmon River Basin 79
Summary 88
Literature Cited 88
APPENDIX B: Selected Fish Habitat Indicators from the Tongass National Forest,
Alaska Region 89
Introduction 89
Hierarchical Framework 89
Description/Selection of Habitat Indicators 89
Summary of Habitat Objectives 90
Summary and Recommendations 91
References 92
APPENDIX C: Summary of Recommendations for Salmonid Habitat Quality 96
APPENDIX D: BIBLIOGRAPHY 99
Available at EPA Region 10 web site,
http://www.epa.gov/r1 Dearth/
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Aquatic Habitat Indicators
List of Illustrations
Figure 1. Water resource integrity (Yoder 1995) 5
Figure 2. Potential complexity of aquatic ecosystems 10
Figure 3. Decision diagram for selecting habitat variables 39
Figure 4. The role of ultimate vs. proximate factors 23
Figure 5. Hierarchical scheme of landscape and stream network 26
Figure 6. Gradient classes for channel grouping 28
Figure 7. Illustration of precision and accuracy 54
Figure 8. Detecting differences -The triangle of factors 58
Figure 9. Percentiles of LWD/mile, pool frequency, residual pool depth, and percent fines 68
Table 1. Types of habitat alteration and effects on salmonid in the Pacific Northwest 19
Table 2. Habitat parameters used in monitoring programs in the Pacific Northwest 36
Table 3. Selected habitat criteria used in federal programs in the western United States 37
Table 4: Summary of pathways and habitat indicators for ESA determinations 38
Table 5: Habitat components, pathways of effects, and potential habitat variables 42
Table 6. Summary of contemporary spatial scale classifications 25
Table 7. Precision estimates for selected quantitative and semi-quantitative variables 58
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Aquatic Habitat Indicators Executive Summary
EXECUTIVE SUMMARY AND RECOMMENDATIONS
The objective of this project was to evaluate the potential inclusion of aquatic habitat indicators into water
quality programs as one component of a developing EPA strategy to address declining salmonid
populations in the Pacific Northwest. Habitat indicators, like water quality criteria and biological
indicators, can be used to evaluate the protection of beneficial uses which are the cornerstone of water
quality standards. Aquatic habitat indicators (variously referred to as habitat variables, parameters,
metrics, etc.) are commonly used to evaluate biotic integrity and fish production capability.
We initially set out to formulate habitat target values based on the best available information from the
literature and databases on reference area condition. After consideration of the currently available
information, we concluded that developing numeric values at a regional scale would not be technically
feasible. The literature supports the importance of habitat characteristics for salmonid fish communities
and the documented alteration of habitat quality by human activities. However, both the numeric values
that are contained in the literature and numeric values available from reference area databases exhibit
too broad a range of expression to identify target values. Using information at this scale to set target
values has the potential to contribute either to incremental habitat deterioration or to set inapplicable
target values across large geographic areas. Instead, we describe an approach for developing target
values at an ecoregional scale; this approach is summarized in the key points and recommendations for
future action which follows.
This project includes a bibliography of the literature associated with habitat indicators. The bibliography
was not included in the paper copy because of its large volume. The bibliography is available on the EPA
Region 10 web site at http://www.epa.gov/r10earth/.
Key Points
1. Relevance of Aquatic Habitat Indicators to Clean Water Act Objectives
Aquatic habitat indicators can address two interrelated objectives of the Clean Water Act (CWA). The first
objective is to determine whether designated beneficial uses are attainable in the water body and to what
degree these uses are supported. The second objective is to evaluate the effect of pollutant sources on
beneficial uses and assess the need for change in pollution controls. The first objective, assessing the
status of beneficial use, extends beyond the aquatic organism to the aquatic environment required to
sustain a certain aquatic population over time. Habitat quality, like water chemistry and biological
integrity, provides a method to determine if the environment supports the target aquatic community.
The second objective reflects a major emphasis of water quality programs to provide feedback on the
effectiveness of regulatory and management programs. In nonpoint source programs, monitoring is
categorized under implementation and effectiveness objectives: implementation monitoring addresses
whether the Best Management Practices (BMP's) were installed according to plans or regulations; and,
effectiveness monitoring, as more comprehensive, attempts to determine whether the management
practices effectively protect beneficial uses. Habitat indicators can play a role in assessment of
practices, but they need to be part of a comprehensive monitoring program that includes on-slope
assessment of management practices, watershed processes, and the effect of these pollutants and
altered processes on channel and habitat quality.
2. Challenges to Using Aquatic Habitat as an Indicator
Concerns with development and application of habitat variables to water quality programs can be grouped
into five primary issues: the high degree of natural variability in stream systems, the lack of reference
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Aquatic Habitat Indicators Executive Summary
conditions to serve as benchmarks, the effect of natural and past land-use disturbance on stream
conditions, the problems associated with measuring habitat variables, and lastly the use and application
of habitat measures within the context of the CWA.
Although variability is inherent in aquatic systems, there is an observed pattern of habitat conditions that
are necessary to support aquatic communities. These requirements are best known for salmonid species
and can in turn serve, to some degree, as indicators of cold water lotic communities. Spatial variability
can be addressed by grouping similar habitats at different scales, e.g. habitat type, stream reach, sub-
watersheds, etc., within a landscape setting. Temporal variability needs to be addressed via an
evaluation of the way in which watershed processes, natural disturbance, and human activities interact
over short and long-term time frames. Habitat conditions in unmanaged (or minimally managed)
watersheds provide the benchmark by which to judge the adequacy of current conditions in supporting
beneficial uses. Yet, the lack of adequate representatives of reference areas for many ecoregions has
been cited as one of the most difficult challenges in developing numeric indicators. Extreme floods, fire,
mass wasting and erosion events, which occur at infrequent but regular intervals, are part of the dynamic
environment that shapes stream ecosystems. Use of habitat indicators in water quality programs must
account for the effect of these natural disturbance events on habitat variability.
Although there is a general understanding of the habitat components required to support salmonid
species, and by extension aquatic cold water communities, standard protocols similar to the standard
methods used for water chemistry have not been developed and agreed upon in a formal manner by the
scientific community. The lack of uniform methods with acceptable levels of precision, accuracy, and
comparability accepted by a broad cross-section of the scientific community is an obstacle to measuring
habitat quality.
Some generic misconceptions regarding the potential use of habitat indicators in the CWA may stand as
a roadblock to collaboration and problem solving. For example, there is a perception that establishing a
numerical indicator somehow establishes a requirement to manage streams toward some uniform design
and, therefore, encourages land managers to use artificial means to achieve these endpoints.
Additionally, the perception exists that establishing water quality criteria would provide license to degrade
high quality streams. Neither of these outcomes is provided for in CWA guidance or policy.
3. Use of Aquatic Habitat Variables as Diagnostic Indicators
Variables used to measure environmental quality have been categorized as compliance, diagnostic, and
early warning indicators (Cairns et al. 1993). There is an implicit requirement that the values used as
compliance indicators can be measured with known levels of precision and accuracy, that the biological
effects are associated with a numerical value, and that these numerical values are applicable within the
prescribed geographic area. The numerical water quality criteria familiar to water quality professionals
serve as an example of the variables used as compliance indicators. Criteria for water chemistry
variables are set at a threshold of effect for target organisms based on laboratory bench tests of acute
and chronic effects. Since these criteria are used in a regulatory context, a high standard for data quality
is required.
Our evaluation does not support the use of habitat indicators as compliance indicators at this time for
several reasons. First, the habitat value generally cannot be readily tested or reproduced in a laboratory
bench test similar to water quality criteria. A quantitative, repeatable biological threshold can not be
readily identified for the majority of habitat variables, since the numeric value has to come from
observations of the habitat component in unmanaged landscapes in which it will be applied. Second, the
high natural variability of habitat conditions prevents the development of defined numerical criteria with
the scientific rigor generally required for numerical water quality criteria. Third, the measurement systems
for habitat variables, comprised of standard operating procedures and quality control/quality assurance
programs, have not been developed to the degree necessary to meet data quality objectives.
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Aquatic Habitat Indicators Executive Summary
At the current state of development, habitat variables may be best suited as diagnostic indicators of
beneficial use support and as performance measures of nonpoint source controls. Diagnostic measures
fit well within the regulatory framework for nonpoint source activities, which depends on the iterative
evaluation of management practices. The habitat variable measures the outcome of management
actions on water quality and water resource integrity. In concert with measures of on-slope pollutant
sources and evaluation of watershed processes, a habitat indicator assists in diagnosing whether
management practices have had an adverse impact on the aquatic environment. Instream measures
assess beneficial use support, but they can not be used alone to assess management actions since the
current stream condition integrates past activities, current actions, and natural disturbance. Historical and
upstream activities in the watershed can readily cause a lag effect in the stream channel condition, thus
disconnecting the adjacent management action from the current habitat condition.
4. Indicators Must be Applicable within Diverse Landscapes and Stream Networks.
Landscape and stream geomorphic features strongly influence habitat variables. Classification systems
provide a way to partition and account for the variability observed in aquatic habitats as a result of these
features. Ecoregions and stream classification systems provide a framework for organizing habitat
components, habitat variables, and numerical indicators. Level III Ecoregions, compiled at 1:250,000
map scale, may provide a sufficient first iteration for categorizing watersheds in order to evaluate potential
reference conditions for many habitat variables. Further sub-division of Ecoregion organization may be
useful in providing a more homogeneous organization of watersheds but may also be a daunting task
given the limited amount of data on reference conditions. A nested hierarchical classification system
provides a tool to categorize potential natural conditions and establish expected target conditions in which
fish and aquatic communities have developed; yet, a meaningful organization of stream networks
ultimately depends on the identification of geomorphically similar stream reaches. Fundamental factors in
organizing stream reaches are stream gradient, confinement, and stream power (bankfull width or basin
area). Classification systems that incorporate these factors should be useful in developing a spatial
framework for habitat indicators.
The habitat indicator needs to be assessed at a spatial scale appropriate to the management or
programmatic question. Habitat variables are generally measured at the habitat unit scale (e.g. pool,
riffle, or glide), but they should be assessed at the stream reach scale. While localized, site-specific
factors can influence the habitat at the habitat unit level, comparison between stream segments or to
reference watersheds should be done at the stream reach scale - a level of organization more meaningful
to interpretation of external factors. The stream reach is defined by recognizable, geomorphic
characteristics that influence habitat quality. These units can then be scaled up to address questions at
the sub-watershed or watershed level.
5. Assessment and Monitoring Issues
Habitat inventory procedures generally lack the sensitivity necessary to detect environmentally significant
change. Many habitat protocols were developed for inventory purposes which rely largely on subjective
evaluation and are, therefore, subject to observer bias. To be useful in a water quality program context,
habitat variables need to be measured with a known degree of precision and accuracy. The monitoring
framework that has been developed for water quality variables consisting of established Standard
Methods for analytical analyses, Standard Operating Procedures for field methods, and QA/QC
procedures serve as a template for habitat measurement systems. Currently no accepted parallel
systematic framework for assuring the data quality for habitat monitoring is in place.
Data quality objectives need to be established and evaluated as part of the measurement system if
habitat variables are to be useful as diagnostic indicators or as environmental targets for Total Maximum
Daily Loads (TMDL's). Measured quantitative data should be selected where feasible to overcome the
observer bias inherent in qualitative methods. Quantitative methods for measuring habitat are becoming
more accessible and faster with the use of more efficient survey techniques such as Total Station Survey
equipment and GPS survey technology. Quantitative channel measurements that are standard
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Aquatic Habitat Indicators Executive Summary
procedures in hydrology and geomorphology should be adopted as ways to increase quantitative
measurement of habitat quality. Measurement goals should place less emphasis on the number of
stream miles assessed and more on the ability to measure conditions with an acceptable precision. The
trade off between costs of quantitative methods and expected benefits in detecting change will also need
to be considered.
6. Potentially Useful Aquatic Habitat Indicators
We evaluated the existing habitat parameters used by state and federal agencies in monitoring programs
and the habitat variables used as Riparian Management Objectives (PACFISH, USFS 1995) or as habitat
indicators for evaluation of proposed activities under the Endangered Species Act (ESA) (NMFS 1996).
Variables that directly measure a habitat characteristic can be grouped into one the following categories
of aquatic ecosystem components:
• Flow Regime
• Habitat Space and Channel Structure (including LWD)
• Substrate Quality and Size
• Streambank Condition
• Riparian Condition
• Temperature Regime
• Water Quality Constituents
• Habitat Access
The first five components relate to physical habitat and were evaluated in this paper. Temperature, water
quality constituents, and habitat access are listed to illustrate the holistic requirements of cold water biota,
but they are outside the scope of this project. To evaluate the utility of habitat variables for CWA
purposes, we compared the existing aquatic habitat variables against the recommended characteristics
for environmental indicators described in the literature. In summary, there are four major characteristics
to consider in assessing habitat measures as environmental indicators:
1) The indicator must be relevant to the environmental/biotic endpoint,
2) be applicable to the landscape and stream network in which they are used,
3) be responsive to human-caused stressors, and
4) exhibit adequate measurement reliability and precision.
Only a few habitat variables satisfy these evaluation criteria. These variables are placed into two
categories, Tier 1 and Tier 2, based on our professional opinion of the degree to which they satisfy the
evaluation criteria. The categorization into tiers is a communication device and is not intended to provide
any policy direction. Tier 1 variables satisfy all the criteria to a large extent and are considered potentially
useful to Clean Water Act programs. Tier 2 contains habitat variables that have a known biological effect
and are sensitive to human impact but are questionable regarding the measurement sensitivity and
reliability or the ability to quantify the biological effect. Tier 1 variables include large woody debris
frequency, pool frequency, and residual pool depth. Tier 2 variables include percent fine sediment and
bank stability rating. Habitat should be evaluated via a suite of variables as is routinely done in field
studies. The limited set of variables are not expected to satisfy an ecological stream protection goal but
simply reflect the pragmatic evaluation of currently available habitat measures.
Three routinely measured habitat variables - large woody debris frequency, pool frequency, and residual
pool depth - are used to evaluate the component of habitat categorized as Habitat Space and Channel
Structure. These habitat variables also serve to evaluate flow effects, since the alteration of water
quantity is manifested in the change in channel habitat space. Large woody debris and pool frequency
are relevant to aquatic biota, are responsive to human impacts over the long term, and can be measured
quantitatively. Salmonid species in forested ecosystems have evolved in streams in which large woody
debris plays a major role in forming habitats, providing cover, influencing sediment processes, and
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Aquatic Habitat Indicators Executive Summary
altering stream energy and nutrient cycling. Pool frequency is a critical indicator of habitat space, and
residual pool depth is a quantitative measure of pool quality influenced by flow alteration and
sedimentation.
Fine sediment deposited in critical spawning habitat has a demonstrated effect on reducing egg-to-fry
survival and can fill in the voids in substrate utilized by juvenile fish as cover. However, there are
unresolved questions regarding the applicability of field measurement protocols, their precision, and the
interpretation of this kind of data in relationship to laboratory defined sediment impacts. While a large
body of literature supports the fact that fine sediments are detrimental to salmonid and other aquatic
biota, remaining questions about the adequacy of field methods and their comparability to laboratory
studies need to be resolved. The authors recognize that other professionals have looked at this issue
and have concluded that the existing body of information supports establishing numerical values. These
differences of opinion are expected given the current status of the scientific information.
A similar consideration applies to the current evaluation methods for rating bank stability. Naturally stable
banks result from the protection afforded by bank material and protective riparian vegetation which resists
the force of flowing water and are recognized as providing important space and hiding cover for fish. The
majority of bank stability methods involve a subjective rating of some combination of vegetative cover,
bank material, and evidence of slumping or sloughing. The concern with current bank stability
evaluations is the subjective nature of the measurement system. At the present time, the various
methods of rating bank stability do not meet the necessary level of objectiveness and repeatability.
7. Numerical Format and Data Interpretation
The methods used to express the values for physical habitat are important. A single target value or a
simple series of values for different stream types are not sufficient to express the inherent variability in
aquatic ecosystems. Numeric values need to be expressed in terms of both the central tendency and the
spread in a data distribution. The median, interquartile range, and percentiles, for example, are useful
ways to display data, as these measures are resistant to the effect of outlying values in comparison to
classical parametric measures (Helsel and Hirsh 1995).
Displaying the data as percentiles also provides the opportunity to set the objective within the policy
framework. For example, a higher percentile may be established in a stream where watershed protection
has been given a high priority, such as for protection of refugia for endangered species.
8. Application to Water Quality Standards and Total Maximum Daily Loads (TMDL).
Current water quality standards in EPA Region 10 states (Alaska, Idaho, Washington, and Oregon)
address habitat protection in a very cursory manner. Narrative criteria related to aquatic habitat or, more
specifically, salmonid fish habitat could be substantially strengthened based on existing known fish
habitat requirements. Narrative criteria could address a number of critical habitat components more
explicitly, which would be very useful in program applications such as development of TMDL's. Narrative
criteria could also describe the process for development of ecoregional or site-specific numeric criteria.
Numeric criteria could be tiered to these narrative statements as more specific information becomes
available for individual ecoregions or groups of ecoregions. Development of numeric habitat targets for
specific TMDL's can be completed currently at a watershed or sub-basin scales depending on the
availability of reference area data or historic information. These localized efforts at developing habitat
targets would contribute to the development of ecoregional numeric habitat indicators.
Recommendations for Future Actions
During the process of evaluating the current situation, we identified several primary issues related to
application of aquatic habitat indicators. The issues were identified initially in canvassing the literature
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Aquatic Habitat Indicators Executive Summary
and discussing the situation with aquatic specialists. These issues fall into four general categories:
reference areas and landscape stratification, monitoring protocols and study design, application to water
quality standards and TMDL's, and interagency coordination in addressing these technical issues. These
topics can be addressed, if not resolved, via a systematic interagency and interdisciplinary effort at the
state and federal (and provincial) level. For example, the definitive approach for landscape stratification
of aquatic habitats has not yet been designed, although many of the pieces to this puzzle are likely in
place. The first approximation of regional stratification could be pulled together through a working group
of geographers, aquatic and terrestrial ecologists, hydrologists, and fisheries biologists. However,
sufficient impetus would be required to bring all the appropriate specialists together in pursuit of this goal.
There is also a need to emphasize applied research as a vital element of the solution. Oftentimes, state
agencies or other governmental units are asked to tackle issues without sufficient resources, information,
or expertise. Several of these issues could be addressed if there were sufficient integration of water
quality programs and research efforts.
Reference Areas and Landscape Stratification
Landscape and stream network classification provide a logical means for stratifying stream habitats into
logical units. Stratification is needed to define the target condition appropriate to the local landscape and
reduce the effect of spatial variability. Aquatic specialists are familiar with geomorphic stream
classification, stratification by ecoregion, and the hydrologic unit system. What is currently missing is the
systematic application of stratification at a regional scale to facilitate identification of potential reference
areas across state boundaries. Numerous case studies of stratification have been applied in specific
programs or geographic areas which can serve as examples.
Candidate reference areas at various scales (i.e., from isolated tracts to large land blocks) can be
identified from the current body of land use planning documents and geographic products. Reference
areas at a coarser scale can be identified from roadless areas, designated wilderness areas, national
parks, and other protected areas. At a finer scale, there are often small blocks of land that have been
protected over time for various reasons that may be useful as reference areas. In addition to the written
documentation, natural resource workers in land management agencies have a wealth of experience
which could be tapped to identify potential reference areas.
In some areas persistent and widespread habitat alterations have eliminated natural areas that could be
used to describe reference condition. There is clearly no easy way to fill in the data gaps on habitat
conditions that have been severely altered. The EPA guidance for developing biological criteria have
suggested a logical approach to identifying reference condition where no reference sites occur (Gibson
1996). The decision tree suggests ways to utilize "minimally disturbed" areas and ecological modeling to
fill in the information gaps. A related approach is to expand the search for suitable reference conditions
outside of the local geographic area or local ecoregional area. There would appear to be good potential
for cataloging reference conditions by expanding the geographic scope of the inquiry to British Columbia
and Alaska. These efforts would require some broader research initiative beyond the usual regional
approach which focuses on the Pacific Northwest states.
A remaining and persistent challenges to aquatic habitat protection and recovery is the lack of an
organized, focused cooperative venture to define and complete the essential field trials necessary to test
the use of habitat indicators at discrete basin scales. Given the overwhelming need to judge the success
of recovery plans for salmon and bulltrout listed under the ESA, to evaluate the effectiveness of federal
court-mandated water quality recovery plans (a.k.a. TMDL's), and to ensure that state water quality
standards are fully protective of aquatic species - now seems to be the perfect opportunity for State,
Tribal and Federal resource agencies to collaborate in such an effort. To that end, the authors
recommend that the agencies seek funding from EPA, the National Science Foundation, or similar groups
to conduct the needed research and development. This objective should be identified as a key element in
the implementation of the Clean Water Action Plan (EPA 1998). The Clean Water Action Plan provides a
framework and potential funding source to facilitate efforts such as these among key natural resource
agencies. Some specific action items might include:
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Aquatic Habitat Indicators Executive Summary
• Identify potential partnerships in this effort within the natural resource agencies - EPA, USFWS,
NMFS, USFS, BLM, National Park Service, USGS Biological Survey, etc. as well as agencies in
British Columbia and Alberta, Canada.
• Initiate a federal interagency and international effort to evaluate the landscape classification of
aquatic areas at larger scales to incorporate lands in Alaska and British Columbia.
• Identify approaches and organizational units that can contribute to the pool of reference area data
and assist in filling data gaps.
• Develop a systematic uniform approach to collect further information over the long term in order
to describe undisturbed habitat conditions.
Monitoring Protocols and Study Design
General agreement exists among aquatic scientists regarding which stream habitat components are
important to aquatic organisms. There is a lack of consistency, however, in the way that habitat variables
are measured and and the degree of quantification necessary for a monitoring objective. Consequently,
the data quality (precision and accuracy) of the information is often unknown, and the data from different
programs is not comparable. Many of the habitat data collection efforts are only at an inventory level of
effort, but the information is used to render decisions that may be unsupported by the underlying quality
of the data.
Even well documented habitat inventory methods have been found to be subjective and inadequate to
characterize fish habitat for addressing land management questions (Peterson and Wollrab 1999).
Inventory scale monitoring using qualitative procedures may be useful for certain natural resource
programs, but decisions regarding compliance with water quality standards or adequacy of BMP's need to
be based on data with known precision and accuracy. For this reason, it would be useful to initiate a
comprehensive review of existing methods with an emphasis on their ability to achieve identified data
quality objectives. In the interim, agencies should consider shifting resources to fewer more quantitative
surveys that emphasize a decision analysis approach. Several quantitative channel survey protocols
provide the basic framework for habitat evaluations (Harrelson et al. 1994, Kuntzch et al. 1998). Some
specific actions might include:
• A comprehensive evaluation of the ability of habitat protocols to produce data of an acceptable
quality. This review should be an interdisciplinary, interagency review based on the technical
adequacy of the habitat variables rather than on a consensus process.
• Development of standardized methods for habitat monitoring similar to the measurement
framework that exists for water chemistry variables, e.g., Standard Methods, Standard Operating
Procedures manual, and Quality Assurance/Quality Control procedures.
• In the interim, agencies should review their approach to habitat monitoring, evaluate whether
current methods are capable of answering the critical water quality program decisions, and
consider the long term utility of fewer quantitative surveys over inventory and reconnaissance
procedures.
Application to Water Quality Standards and TMDL's
Narrative criteria for aquatic habitats in state standards should be substantially strengthened based on
existing known fish habitat requirements. Narrative criteria could specify the desired condition for a
critical habitat components more explicitly, e.g., salmonid spawning and rearing habitat. The narrative
criteria should also describe the process by which site specific numerical criteria could be developed and
VII
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Aquatic Habitat Indicators Executive Summary
approved. These process statements would be expected to stimulate regional or local work groups to fill
in the information gaps for the region. Since TMDL's are by nature locally specific, the watershed group
or agency in charge of the problem assessment could follow the steps (stratification, reference area data,
historic conditions, etc.) to develop habitat targets meaningful to the watershed or sub-basin.
Interagency Coordination
As described above, we believe that much of the information needed to make progress on habitat
stratification, reference area identification, and monitoring protocols exists in some format within the state
and federal natural resource agencies. Bringing the agency resources together toward resolving these
questions requires a systematic scientifically based approach. Research units of the federal agencies
have the technical resources to accomplish this task, but they would need to be brought together in a
focused, goal specific manner. The effort we envision will require funding for a directed project and
cannot be accomplished in a less rigorous manner such as an extracurricular consensus process.
VIM
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Aquatic Habitat Indicators
SECTION 1
Introduction
Application of Aquatic Habitat Indicators to Water Quality Objectives
within the Clean Water Act
EPA Region 10
Steve Bauer and Steve Ralph
"Biologists are rather better at reinventing wheels than most scientists! We publish more and longer
papers, so older seminal ideas, like fossils in geological strata, tend to become quickly buried out of
sight." H. B. N. Hynes (1994)
The process of science may sound messy and disorderly. In a way it is.
Carl Sagan (1996)
1. INTRODUCTION
In considering measures of stream habitat, we
rely on the foundation of work already completed
by biologists, hydrologists, and other stream
observers summarized in literature reviews,
symposia proceedings, and recent collections of
papers. Much is to be gained by connecting the
information on aquatic stream habitat from the
field of fisheries, hydrology, geomorphology,
water quality, and bio-assessment. We have
compressed the thoughts of various aquatic
ecologists and take responsibility for any errors
that arise as a result.
Scope of Project
The EPA and state water quality agencies are
increasingly asked to evaluate the CWA goals
from a holistic perspective that integrates water
chemistry, biotic integrity, and habitat integrity.
The increased species listings under the ESA
and the increase in water bodies listed under
Section 303(d) have precipitated the need to
evaluate habitat requirements of beneficial uses
as an important component of the overall health
of the aquatic ecosystem. As a consequence,
EPA initiated this review of the technical basis
and feasibility of incorporating aquatic habitat
indicators into water quality programs.
The scope of the project is limited to the physical
freshwater habitat structure of lotic aquatic
ecosystems. We do not discuss key habitat
characteristics of associated wetlands, lakes,
estuaries or near shore marine environments.
We specifically targeted the literature search
and information review to salmonid species of
fish (salmon, trout, char) as indicators of cold
water biotic communities. Salmonid habitat
relationships have been extensively studied
because of their importance to sport,
commercial and tribal fisheries in comparison to
other aquatic organisms. In addition, fisheries
and land management agencies routinely collect
stream habitat information, and consequently
there is a better available data base on fish
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Aquatic Habitat Indicators
SECTION 1
Introduction
communities than on other organisms. There is
less information on habitat requirements in large
rivers and on specific habitat relationships with
invertebrate and algal communities. We
recognize these biota are critical components of
stream ecosystems, but habitat relationships
have not been studied as extensively as with
salmonid fish.
Degradation of aquatic habitats by nonpoint
source activities is recognized as one of the
major causes for the decline of anadromous and
resident fish stocks in the Pacific Northwest
(Williams et al. 1989, Nehlsen et al. 1991). Non-
point source activities can modify the physical
processes that provide important habitat
features. Habitat quality is currently used as
supportive information in water quality
assessment programs, but habitat is only
minimally addressed as an endpoint in state
water quality standards. This effort will identify
where feasible the rationale and key elements of
a plan to develop a set of fish habitat condition
indicators for possible inclusion in water quality
programs.
Objectives
The original objective of the project was to
evaluate the merits and feasibility of defining
numeric values for desired habitat
characteristics for salmonid fish communities in
the Pacific Northwest. Comments received at
technical workshops and from other agencies
suggested that the emphasis on numeric targets
was too restrictive. In response, we expanded
the scope to address the expression of
indicators to include narrative statements.
Habitat indicators, whether expressed in a
narrative or numeric manner, are needed within
the context of the CWA as well as the ESA in
order to define conditions required for the
protection and recovery of salmonid populations.
Without these defined measures of instream
habitat, we have a limited basis for judging the
adequacy of protection measures and the
effectiveness of recovery efforts for salmon and
trout populations.
An additional objective was suggested by
comments from federal agency professionals
involved in implementation of the ESA, since
habitat indicators serve a different role in the
ESA than in the CWA. We have attempted to
compare and contrast the roles and application
of habitat indicators between these two laws as
we have evaluated these habitat variables.
Methods
Rather than conduct a comprehensive literature
review, we focused on the summary of the
literature that has been compiled in various
synthesis documents and special publications.
We then targeted literature sources with a
special significance to particular habitat
indicators or that provided the conceptual basis
for habitat monitoring and assessment.
Because of the general lack of agreement
evident in agency programs, we canvassed
professionals in the field regarding their ideas on
the development and use of habitat indicators
via workshops in Region 10. A concept paper
based on an initial review of the literature was
distributed to habitat professionals in the Pacific
Northwest. One-day workshops were then held
in Washington, Oregon, Idaho, and Alaska with
approximately 40 resource professionals to
solicit their ideas and discuss potential
approaches. Their advice and input provides
the basis for this report. A second draft of the
concept paper was then distributed for an
internal review at EPA Region 10 and to
technical habitat specialists within the NMFS
and USFWS. In addition, a special work
session entitled "Environmental Indicators of
Freshwater Salmonid Habitats" was held at the
October 1998 Western Division meeting of the
American Fisheries Society. This approach and
other perspectives on this important issue were
presented at that forum.
Terminology
It is useful to first standardize some terminology
related to habitat indicators. Habitat
component is used to refer to an element of the
habitat where an organism occurs (Armantrout
1998) and is considered generally synonymous
with stream attribute or pathway. A habitat
variable is a quantifiable measurement of a
habitat component (synonymous with
parameter). Water quality criteria, as used in
the CWA, refers to elements of state standards,
expressed as numerical quantities or narrative
statements, that represent the quality of water
needed to support a particular beneficial use
(USEPA 1994c). The term "habitat indicatoi"
is used in this document to emphasize the
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Aquatic Habitat Indicators
SECTION 1
Introduction
condition of the habitat rather than the more
regulatory connotation usually associated with
the term "criteria".
Declines in Fisheries and Water
Quality
Habitat Degradation and Fisheries
Declines
Decline in salmon and trout populations is a
predominant theme in the Northwest closely
linked to habitat degradation. Evaluations of the
status of Pacific salmon (Oncoryhnchus spp.)
have concluded that many stocks have become
extinct over the last century and that many other
stocks currently are declining and risk extinction
(Konkel and Mclntyre 1987, Nehlsen et al. 1991,
Nehlsen 1997). Habitat degradation has been
associated with over 90% of the documented
extinctions or declines of these fish species
(Williams et al. 1989, Nehlsen et al. 1991).
Declines in populations of mussels and crayfish
have also been attributed to habitat degradation
(Williams et al 1993, Taylor et al. 1996). Forest
practices, agriculture, livestock grazing, road
building, urbanization, and dams have
contributed to the habitat decline. Factors not
regulated by the CWA - commercial and sport
harvest, hatchery production, migration
corridors, and ocean conditions - have also
contributed to the decline of Pacific salmon
(Stouder, Bisson, and Naiman 1997).
The causes for extinctions or declining stocks of
Pacific salmon are complex and differ from basin
to basin, but habitat degradation (including
losses caused by dams) was explicitly identified
as a factor in the declines of 194 of the 214
stocks and was believed to be the principal
factor in the declines of 51 at-risk stocks
(Nehlsen et al. 1991). Modification of aquatic
habitats is generally related to one or more
fundamental components of stream ecosystems:
channel structure, hydrology, sediment input,
riparian forest alteration, and exogenous
material. Effects of these modifications on
salmonid fishes and their ecosystems include:
loss of overwintering habitat, shift in species
balance, loss of cover from predators, loss of
suitable spawning areas, reduced inter-gravel
survival of eggs and alevins, reduced survival of
juveniles and outmigrating smolts resulting from
altered timing of discharge-related life cycle
cues, increased primary production and possible
anoxia associated with elevated water
temperature, and other effects (Gregory and
Bisson 1997).
Water Quality Condition
The increased listings of water quality limited
water bodies in Region 10 are symptomatic of
the water quality problems in the Pacific
Northwest. Litigants have been successful in
gaining court orders to increase the number of
streams listed on State 303(d) reports. For
example, Idaho's 1996 list now contains 951
stream segments (Idaho Division of
Environmental Quality 1997). The pollutant
category "sediment" provides a surrogate for
habitat degradation associated with nonpoint
source activities. A summary of the list indicates
that 90% of the streams are listed due to
sediment impacts. (Fewer stream segments,
15%, are listed under the category "habitat
alteration", but this category refers specifically to
direct channel alterations and does not provide a
dimension of the habitat impacts.) Oregon's
1996 list contains approximately 900 water
bodies, half of which are listed exclusively for
elevated temperature (Oregon Department of
Environmental Quality 1996).
The magnitude of aquatic habitat degradation in
the Pacific Northwest and its relationship to the
decline of fish populations have been
demonstrated. However, an accurate appraisal
of the scope of the water quality problem related
to habitat decline remains illusive. Identifying
habitat quality will not contribute to stream
recovery without a connection to action plans.
Nonetheless, the identification of habitat as an
environmental endpoint is a fundamental tool
that is currently missing from the nonpoint
source management program despite its wide
acceptance as a fundamental component of
water quality assessment.
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Aquatic Habitat Indicators
SECTION 1
Introduction
Role of Habitat Indicators in the
Clean Water Act and Endangered
Species Act.
Introduction
Understanding the purpose and rationale for
addressing habitat within the CWA is the initial
step in selecting applicable indicators. Two
different, but related, objectives for habitat
indicators are evident in CWA programs. The
first is the assessment of the status of the
aquatic environment in supporting beneficial
uses. The second is to gauge the effectiveness
of management practices in preventing pollution
and protecting beneficial uses. These objectives
can entail the selection of different sets of
indicators.
Although this paper's focus is on habitat
indicators for the CWA, we do compare the
objectives and application of habitat indicators
within the CWA to those uses prescribed within
the ESA. There is a desire among federal
agencies to use similar indicators to avoid
potential conflicts between regulatory programs.
However, agency policy in applying habitat
indicators may be different for the CWA and
ESA, because these laws are intended to fulfill
different missions. Understanding the nature of
these differences and similarities between the
CWA and ESA is necessary to address issues of
regulatory overlap.
Clean Water Act Goals
The goal of the CWA is to "restore and maintain
the chemical, physical, and biological integrity of
the nation's waters." James Karr (1991)
highlighted the shortcomings of relying solely on
nonbiological measures, such as chemical
quality, to evaluate attainment of this goal.
Since that time EPA and state agencies have
increased efforts to incorporate biological criteria
and bioassessment into the water quality
programs.
Increased understanding of what is required to
support beneficial uses of water has broadened
the definition of water resource integrity to
include flow regime, chemical quality, biotic
factors, energy sources, and habitat structure
(Figure 1). Physical and chemical variables
form the core set of measures traditionally used
in managing water quality programs. Managing
these factors alone will not protect beneficial
uses, because other biotic and abiotic factors
are integral to the expression of water resource
integrity.
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Aquatic Habitat Indicators
SECTION 1
Introduction
Alkalinity
*—"X. \ "
Solubilities \ \ $
—^___^
Adsorption
Temperature
DO
Velocity -«
Nutrients
Organics
Hardness
Land Use
Ground
Water
Sediment &
Flow Regime
High/Low
Extremes
1 ^
1 Precipitation
W & Runoff
Parasitism
s <•
Biotic
Factors
f /
Disease
_V
Reproduction
Competition
WATER
RESOURCE
INTEGRITY
Feeding Predation
Nutrients
Sunlight
Seasonal
f Cycles
Riparian __
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Sinuosity
Current
(~* Width/Depth
BankStability
Organic Matter
Inputs 1°and2°
Production
Substrate
-'f I
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Canopy Instream
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Figure 1. Water resource integrity (Adapted from Yoder 1995).
The importance of direct measurement of
biological integrity to water quality programs is
formally recognized in EPA policy and guidance
(USEPA 1987, USEPA 1991). Forty-seven
states employ some form of biological
monitoring using macroinvertebrate
assemblages, and 25 states have fish
assemblage monitoring programs. Three states
- Ohio, Maine, and Florida - have incorporated
numeric biological criteria into their water quality
standards, and many other states have work in
progress (Southerland and Stribling 1995).
One potential downside to using biological
measures as endpoints is that biological
populations, especially migratory fish
assemblages, exhibit high natural variability due
to factors unrelated to nonpoint source activities
such as climate, harvest, natural disturbance,
and ocean productivity. For example,
interannual variations of 40-70% are the general
rule for coho salmon, steelhead, and sea-run
cutthroat trout (Summary of studies in Bisson et
al. 1997). In a review of fish assemblage
studies, Grossman, Dowd, and Crawford (1990)
noted that the high variability in fish
assemblages can make it difficult to detect the
effects of human caused disturbances.
Disturbance events likewise affect habitat
variability, but these habitat variables are not
subject to the extreme, and often inexplicable,
cycles observed with fish populations.
Combining habitat, as a measure of the physical
integrity of the stream, with direct measures of
biological integrity will provide a more powerful
way to measure progress in achieving the goals
of the Act.
Habitat attributes are collected as an integral
part of bioassessment procedures (Plafkin et al.
1989, Hayslip 1993). However, habitat
attributes are routinely measured qualitatively
and are used primarily as explanatory variables
in data interpretation. Developing habitat
structure as a direct measure of water resource
integrity will improve the linkage to nonpoint
source activities. Poff and Ward (1990) address
the rationale for using physical habitat as a
template for stream biota: "In lotic ecosystems,
physical habitat structure is of critical importance
to the distributions and abundances of
organisms. In general, greater spatial
heterogeneity at the scale of organisms results
in greater microhabitat and hydraulic diversity
and hence in greater biotic diversity." In large
areas of the Northwest's forests and
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Aquatic Habitat Indicators
SECTION 1
Introduction
shrub/grasslands, the predominant effect of land
management is to reduce stream habitat
diversity and, thereby, reduce the complexity of
the biotic community.
Incorporating habitat indicators into the existing
water quality standards requirement for physical,
chemical, and biological criteria fills an important
gap in water quality management. The
cumulative effects of land (and water) use and
related alterations are largely responsible for the
degradation of watersheds in the Pacific
Northwest by way of the physical alteration of
stream ecosystems and the processes
accounting for their characteristics. Establishing
habitat as a measurable endpoint is an essential
tool to improve the cause-and-effect evaluation
of nonpoint source activities and to establish
programmatic endpoints. Assuring that water
quality programs are on target is important
environmentally, socially, and economically.
Best management practices and TMDL's that
are not targeted to problem resolution will waste
resources in the interim and exacerbate the
environmental problem through inaction and
delay.
Nonpoint Source Management Process
Ideally, nonpoint source pollution evaluation and
control is implemented through an iterative
management process. The CWA's goal of
maintaining and restoring the physical, chemical,
and biological integrity of the Nation's waters is
fundamental to state water quality programs.
EPA has authority (Section 303 of CWA, 33
U.S.C. 1313) to review and approve or
disapprove state water quality standards based
on consistency with the CWA. Water quality
standards must contain use designations, water
quality criteria (both narrative and numeric)
sufficient to protect these uses, and an anti-
degradation policy. Numeric criteria for aquatic
biota typically address temperature, pH,
dissolved oxygen, toxic contaminants, and
turbidity.
Best management practices for nonpoint source
activities are often comprised of other state
agency regulations for forest practices, mining,
or channel alteration that have been reviewed
for consistency with state standards. Monitoring
of BMP efficacy occurs through state-wide
audits and site-specific water quality studies.
BMP's are updated when they are found to be
ineffective in protecting beneficial uses. The
"feedback loop" is also applied at other degrees
of resolution - basin, watershed or specific
stream reach.
Habitat quality indicators can aid water quality
management at a number of programmatic
steps: (1) beneficial use designation,
attainability, and status, (2) BMP evaluation, (3)
project evaluation and water quality certification,
(4) National Environmental Policy Act (NEPA)
review, (5) watershed analysis endpoints, and
(6) restoration endpoints.
Beneficial use designation is a cornerstone of
the CWA. Application of criteria and pollution
control requirements for each waterbody
depends on the use designation. Use
attainability is based on physical, chemical, and
biological factors including habitat features
(USEPA 1994c). A quantitative approach to use
attainability decreases the uncertainty in water
pollution control programs and helps focus
limited resources. In current practice, use
attainability and status determinations depend
heavily on bioassessment protocols using
macroinvertebrate and fisheries assemblages.
Habitat is measured primarily in a qualitative
fashion in order to assist in the interpretation of
the biotic data. Evaluation of potential
designated uses would be improved by
concurrently evaluating habitat conditions using
more quantitative approaches.
Determining beneficial use status, e.g.,
supported vs. threatened, is the next basic step
in the application of a water quality evaluation to
management programs. If uses are not fully
supported due to water quality impacts, the state
has the obligation to identify the cause and take
corrective action including development of
TMDL's. State 303(d) lists of Water Quality
Limited Waters are based on noncompliance
with criteria and on beneficial use status
evaluations. The more accurate these status
determinations are the more appropriate will be
the requirements for pollution control.
Role of Habitat Indicators in the
Endangered Species Act
Habitat indicators are used within the ESA to
evaluate proposed federal actions as part of
Section 7 consultations in terms that define the
risks to listed species. Essentially, they serve to
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Aquatic Habitat Indicators
SECTION 1
Introduction
define the components of "proper functioning
conditions," which reflect those habitat features
necessary to support listed species' recovery.
Guidelines for making ESA "determinations of
effect' for proposed actions are contained in two
similar documents by NMFS and USFWS
(NMFS 1996 and USFWS 1998). The
documents differ with respect to the subject
species, but otherwise use a similar process.
The described application of habitat indicators to
ESA determinations is taken from these
documents.
An analysis of proposed activity for Section 7
consultation involves the following steps:
(1) define the biological requirements of listed
species;
(2) evaluate the relevance of the environmental
baseline to the species' current status;
(3) determine the effects of the proposed or
continuing action on listed species; and,
(4) determine whether the species can be
expected to survive with an adequate
potential for recovery under the effects of
the proposed or continuing action, the
environmental baseline and any cumulative
effects, as well as consider measures for
survival and recovery specific to other life
stages.
The guidelines are intended to provide a
consistent, logical line of reasoning to determine
when and where adverse effects occur and why
they occur. The guidelines do not address
jeopardy nor identify the level of take, adverse
effects which would constitute jeopardy, or high
risk to the species/population of concern.
Jeopardy is determined on a case by case basis
involving the specific information on habitat
conditions and the health and status of the fish
population.
The guidance documents contain definitions of
ESA effects, a matrix of pathways of effects, and
indicators (including habitat indicators) of those
effects. A proposed action is evaluated by
analyzing the environmental baseline and the
effects of the proposed action(s) on the relevant
indicators. Using the guidelines, the Federal
agencies and non-federal parties can make
determinations of effect for proposed projects
(i.e. "no effect", "may affect, "not likely to
adversely affect", and "likely to adversely
affect"). These determinations of effect will
depend on whether a proposed action or group
of actions hinders the attainment of relevant
environmental conditions identified in the matrix
as pathways and indicators, and/or results in
"take", as defined in ESA.
The terminology used in these guidance
documents provides an indication of how habitat
indicators can be used differently in the
consultation process than from CWA programs.
"Pathways" organizes portions of the aquatic
ecosystem, e.g. water quality, habitat access,
habitat elements, channel condition, etc., in a
manner that facilitates connections to input
processes. "Indicators" refers to specific
measures of the pathways and includes a mix of
narrative statements and numeric targets. For
example, temperature (numeric) and turbidity
(narrative) are response variables used to
indicate whether the water quality pathway is
properly functioning. Narrative statements, for
example, about the level of "chemical
contamination" are also included as indicators
for pathways.
The Pathways and Indicators are used to predict
effects of proposed actions. The evaluation
involves a holistic approach, since the intent is
to prevent harm to the listed species (taking).
The evaluation of effects, therefore, includes
both input processes and the response of the
channel and habitat to the activity. The
evaluation also needs to address watershed
scale effects and cumulative effects. The
evaluation is based on the best available
information about the species requirements and
the potential effect of the action. Default values
for numeric targets are based on available
information, which emphasizes a conservative
approach to protecting the species. In
circumstances where these default values do
not apply to a specific watershed, the evaluator
is expected to provide more biologically
appropriate values and document this decision.
Contrast Between Habitat Indicators in
CWA and ESA
The mission of the CWA versus the ESA may
lead to a different selection of indicators or the
selection of a different numeric value for the
same indicator. Implementing agencies need to
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Aquatic Habitat Indicators
SECTION 1
Introduction
understand these similarities and differences
and develop a complementary process that in
combination contributes to the long-term
ecological health of the aquatic resource.
There are similarities as well as differences in
the purpose and application of indicators
between these two major laws. The habitat
components important to the salmonid
populations are the same - cool water, water
free of contaminants, diverse habitat structure
with an alteration of pools and riffles, intact
riparian systems, etc. However, the underlying
mission and application to programs will
necessarily lead to a different selection and
usage of habitat indicators. These distinctions
involve the different application of indicators
within the program framework, the allowable
degree of risk, and the justification required for
adopting the indicator.
ESA consultation involves predicting effects of
proposed actions. The evaluation procedure
examines both the upslope inputs and
processes as well as the habitat response.
Because ESA specifically addresses species at
risk of extinction, the selection of default
numerical values errs in favor of the species.
Federal ESA agencies have the authority to
develop and adopt project review procedures
administratively with little outside external
review.
Water quality standards and criteria focus on the
outcomes, i.e. the chemical, physical, and
biological integrity of a water body. Habitat
indicators, either narrative and numeric, can be
integrated into this system. The evaluation of
upslope input variables occurs as part of the
review of the BMP's adequacy as well as
through implementation and effectiveness
monitoring. These input variables are not
included in water quality criteria since the criteria
are directed at defining the quality of the
environment necessary to support the beneficial
use. Numeric criteria are generally set at the
threshold of effect for a parameter - not at the
level of least risk for the aquatic species. The
process of establishing criteria involves multiple
layers of review prior to adoption. The
procedure establishes a balance between
protection of the beneficial use and the social
and economic effects of the decision.
In summary, habitat indicators under the CWA
are intended to aid in measuring the quality of
the aquatic environment in order to protect and
maintain the beneficial uses. As such, habitat
variables focus on the in-channel conditions and
not on the upslope and input processes. Under
ESA, indicators are used to evaluate the effect
of future actions and to address both the input
(often upslope) variables as well as the in-
channel habitat variables. Default numeric
values are identified as a starting point for
certain habitat components, and these indicator
values can be adjusted to fit the landscape
where sufficient local information exists. The
different missions inherent in these laws, and
their implementing policies and regulations, may
indeed lead to a different selection of indicators
or a different magnitude in the default values of
a single indicator. Agencies should seek to
understand these similarities and differences
and develop a process such that the
implementation of these laws is perceived as
complementary rather than as conflicting.
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Aquatic Habitat Indicators
SECTION 2
Challenges in Developing Habitat Quality Indicators
2. CHALLENGES IN DEVELOPING HABITAT QUALITY
INDICATORS
As an integral part of developing an approach to
habitat quality indicators, we canvassed the
literature and workers in the field regarding the
technical limitations to the development of
numerical indicators. Although habitat quality is
recognized as a limiting factor for fisheries and
aquatic biota, little concensus exists on how to
measure habitat quantitatively and how to
evaluate the results. Difficulties in implementing
biotic/ habitat assessment and criteria
development have been addressed in a number
of recent summaries - Biological Monitoring of
Aquatic Ecosystems, Loeb and Spacie (1994);
Biological Assessment and Criteria, Davis and
Simon (1995); and, Pacific Salmon & Their
Ecosystems, Stouder, Bisson, and Naiman
(1997).
Concerns with development and application of
criteria identified in these summaries can be
grouped into five primary issues: the high
degree of natural variability in stream systems,
the lack of reference conditions to serve as
benchmarks, the effect of natural disturbance on
stream conditions, problems associated with
measuring habitat variables, and lastly the use
and application of habitat measures within the
context of the Clean Water Act. We will
summarize these challenges before discussing
some possible remedies and approaches to
developing habitat indicators.
Natural Variability
Stream ecosystems are inherently variable.
Various combinations of climate, geology,
vegetation and landform have created a mosaic
of habitats in which aquatic biota have evolved.
Over geologic time scales, these factors control
the characteristics of watershed processes that
operate to define instream habitats. The
diversity of physical habitats sustains various
salmonid species and their life histories and has
allowed locally-adapted populations to evolve in
order to take advantage of these variable
conditions. Habitats vary in their pattern, profile
(gradient), and channel dimensions, which, in
turn, control flow characteristics, water velocity,
substrate, bank shape, overhead cover,
temperature, and associated vegetative
communities.
Bisson et al. (1997) noted that the most
important aspect of identifying Desired Future
Condition (FEMAT 1993), a concept similar to
habitat quality indicators, is to address the
natural variability inherent in both habitat and
fish populations and to accommodate for the
natural disturbance regime of a watershed. Poff
and Ward (1990) describe the potential
complexity of aquatic ecosystems as arising
from the interaction of spatial, temporal, and
ecological scales. The detection of recovery
from natural or anthropogenic disturbance
depends on selecting the appropriate spatial and
temporal scales for the ecological response
variable. The return of the system to an
endpoint (DFC or habitat criteria, for example)
which approximates the pre-disturbance state is
the central question. Recovery from
anthropogenic disturbance can be conceived as
a function of the biota's experience with
historical natural variation. Poff and Ward (1990)
suggest that streamflow characteristics, thermal
regime, and substrate characteristics are the
minimum elements needed to characterize the
physical template for ecological studies and
management evaluations.
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Aquatic Habitat Indicators
SECTION 2
Challenges in Developing Habitat Quality Indicators
Spatial Scale
Small
microhabitat
pool/riffle
watershed
region
Large
Temporal
Scale
Fast
diel
seasonal
multi-annual
geological
Slow
Ecological
Scale
Individual •<-
behavior
physiology
species migrations
nutrient dynamics
Community
->• Ecosystem
Figure 2 Potential complexity of aquatic ecosystems as the interaction of spatial, temporal, and
ecological scales. Poff and Ward 1990.
Lack of Reference Conditions to
Serve As Benchmarks
Reference areas provide the template for habitat
conditions in which native aquatic biota have
evolved. Habitat values from reference areas
provide both a measure of what constitutes
"good" conditions as well as a measure of the
variability of conditions in which native species
have evolved. Reference areas are not used as
the target conditions but, rather, as a scalar in
order to provide a measure of the potential
conditions which result from natural disturbance.
There is little agreement on what areas
represent reference conditions and what degree
of human disturbance is allowable for sites to be
used as reference conditions. In the Pacific
Northwest, most grass and shrub land areas
have been altered by grazing for decades. In
forested zones, roadless areas and mature
forests represent the best potential for reference
conditions. However, even these areas may
have been compromised by historical or current
fire management, wildland grazing, mining
exploration, or recreational uses.
Experience in the bioassessment program has
shown that the determination of the health of
individual candidate reference sites is one of the
most difficult aspects of biocriteria development
(Hughes 1995). For example, it was observed
that several states have used fundamentally
altered ecosystems to serve as reference sites,
which understandably undermines the purpose
and intent of identifying reference conditions.
The majority of stream inventory and monitoring
programs have been directed at measuring
habitat in managed and impacted areas, so little
data is available in the areas that potentially
represent reference conditions. An exception to
this observation is the Natural Conditions data
collected by the Intermountain Research Station
in the Salmon River Basin of central Idaho
(Overton et. al 1995). In this instance, the USFS
collected habitat measures in primarily roadless
areas in which natural disturbance regimes
(such as fire, flood, and drought) were
considered the primary influence.
The Effect of Natural Disturbance on
Stream Conditions
The quandary for addressing human-caused
impacts on aquatic ecosystems is the
recognition that natural disturbances play a
major role in the development of habitats.
Habitat condition can change dramatically as a
result of storms, fires, and mass wasting events.
If this is so, how does one distinguish the
harmful effects of human disturbance from
similar changes introduced as part of the natural
disturbance regimes?
The concept of natural disturbance as a positive
factor in salmonid habitat formation is described
10
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Aquatic Habitat Indicators
SECTION 2
Challenges in Developing Habitat Quality Indicators
in the following statement from Bisson et al.
(1997):
"The natural disturbance regime is the
engine that drives habitat formation for
salmon. Short-term impacts of natural
disturbances on salmon populations are
often negative. Death may result, habitat
may be destroyed, access to spawning or
rearing sites may be blocked, or food
resources may be temporarily reduced or
eliminated. However, many types of
natural disturbances introduce new
materials into stream channels that are
essential for maintaining productive
habitat. Mass soil movements such as
earthflows and debris avalanches
contribute coarse sediment and woody
debris (Swanson et al. 1987). Wildfires
and windstorms contribute both coarse
and fine debris as well as nutrients
(Minshall et al. 1989). Floods entrain
nutrients, sediment, and particulate
organic matter of all sizes (Bayley 1995).
Volcanic eruptions create new soil, form
new riparian terraces, and create new
stream channels and lakes."
The distinction between the effects of natural
and human induced disturbance on aquatic
ecosystems is in the rate of recovery. Natural
disturbances occur as pulse disturbances versus
human disturbance, which occurs as a
continuing or press disturbance. Pulse
disturbance causes a relatively instantaneous
alteration after which the system recovers to its
previous state. Invertebrate and salmonid
populations can rebound rather quickly following
natural disturbance (Wallace 1990, Bisson et al.
1997). A press disturbance causes sustained
alteration in the ecological processes, thereby
moving the system to a new state. In general,
press disturbances result in longer recovery
times due to alteration of the physical habitat as
occurs with mining activity, clear-cut logging,
and channelization (Yount and Niemi 1990).
A related problem confounding the application of
habitat indicators within a regulatory context has
to do with the persistence of disturbances
associated with past land management practices
(legacy effects). For example, benefits from the
use of effective land management practices to
abate sediment input can be difficult to judge by
measuring instream conditions because of the
recovery periods involved with sediment flushing
through a river system. Similarly, because of a
lag effect in the result of an action taken on a
hillside, it is difficult to judge the true risk and
outcome of, for example, clearing and grading
activities on unstable terrain.
Measurement Quality Considerations
Habitat inventory and monitoring is usually
conducted as a component of fisheries
management programs or land management
planning and evaluation involving timber,
grazing, and mining on public lands. In some
cases, study objectives were only vaguely
defined, assumptions were never explicitly
tested, and study design considerations were
not given appropriate consideration. Monitoring
programs typically suffer from chronic under-
funding and low priority status compared to
other management activities. Data collected for
an environmental assessment or specific project
often are not analyzed beyond a file report. As a
consequence, habitat monitoring data often
lacks reproducibility at a location, comparability
between sites, and continuity of institutional
memory in the evaluated watersheds.
Habitat inventories were developed primarily as
aids to land management decisions with an
emphasis on speed of collection rather than on
repeatability. These primarily subjective
methods and the data derived from them are not
amenable to quantitative analysis. Poole et al.
(1997) found that habitat unit classification, a
basic foundation of stream habitat surveys, was
inadequate for measuring trends over time due
to the lack of repeatability. Desired attributes for
variables used as habitat quality indicators
includes repeatability, transferability, precision,
as well as sensitivity to human impacts and
natural variability. The subjectivity of many
current habitat protocols precludes their ability to
meet these necessary attributes.
Concerns with Use of Habitat
Variables Within the Clean Water Act
In part, the concerns with developing habitat
quality indicators are related to misconceptions
about what role water quality criteria play in both
water quality programs and land management
activities.
11
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Aquatic Habitat Indicators
SECTION 2
Challenges in Developing Habitat Quality Indicators
The concerns with developing numerical habitat
criteria generally fall into one of three categories:
1) criteria become management targets, thus
allowing higher quality areas to be degraded; 2)
instream criteria promote technological quick
fixes, i.e., a band-aid treatment rather than fixing
the cause of degradation; and, 3) national or
regional criteria are applied inappropriately at
the watershed scale in a one-size-fits-all
approach.
Water quality criteria are not intended as
management targets, and no provision in the
Clean Water Act implies that degradation of
streams to the criteria level is acceptable. The
philosophy of maintaining high quality waters is
a basic tenet of the Clean Water Act, which is
explicitly expressed in the Antidegradation
Policy (USEPA 1994c). The policy to protect
high quality waters at existing levels is a
requirement for approval of state water quality
standards. The policy, however, has not been
applied uniformly by EPA and the states, and
consequently, the intent of protecting high
quality waters has not been realized.
Criteria for water quality measures have typically
been established at a level designed to protect
aquatic biota from acute and chronic effects.
Setting the criteria level is a balancing act
between acceptable risk to aquatic biota and the
costs to society. It is not the intent or policy of
the Clean Water Act to use criteria as surrogates
for management goals. Criteria are assessment
endpoints to help evaluate progress toward
meeting goals and objectives as well as
evaluating BMP effectiveness. Antidegradation
policy makes it clear that water quality criteria
are not management targets to which streams
can be managed down.
A criticism of establishing fixed one-size habitat
criteria is that it promotes inappropriate
technological fixes that treat the effect and not
the cause. Some managers take an active
approach to fixing stream problems that is not
supported by scientific evaluation of the
outcome. Addition of structural elements has
been promoted in fisheries management in the
past, but there is little evidence of significant and
long-term improvement in fisheries production
from such practices (Beschta 1997). Judged on
the basis of the evolving principles of ecosystem
management, many structural approaches
cannot be construed as restoration. As the
ecosystem management approach is
implemented, there will be less reliance on direct
manipulation of instream structures. Use of
ecologically inappropriate means to achieve
instream criteria are not an adequate rationale to
abandon criteria development, rather the
emphasis should be placed on ecologically
sound stream restoration.
Habitat indicators will have to be responsive to
the variability in the stream ecosystems to
provide a viable tool for assessing and
managing nonpoint source activities. One
approach to tailoring "criteria" to meet the needs
and variable expression of aquatic habitat
involves stratification. Methods to spatially
stratify stream systems by landscape and
channel geomorphology are widely used and
integrated into resource management programs
(Kratz et al. 1994, Rosgen 1996, Frissell et al.
1986). Although these approaches are not
standardized across the Northwest, the
underlying principles are well accepted. Habitat
indicators should be developed to reflect
landscape and aquatic ecosystem variability and
system potential. Habitat criteria based on
single or limited values, which are not
representative of the local environment, will not
be accepted by the scientific community.
Rather, we should encourage the use of a suite
of habitat indicators, both in-channel and
upslope, to provide a more comprehensive and
reliable basis for interpretation of the cause-
effect relationships associated with water
resource concerns. These concepts are
discussed in detail in the following sections of
this report.
12
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Aquatic Habitat Indicators
SECTION 3
Salmonid Habitat Requirements and Land use effects
3. SALMONID HABITAT REQUIREMENTS AND LAND
USE EFFECTS
Introduction
Literature which summarizes salmonid fisheries
habitat requirements is reviewed in several
documents: An ecosystem approach to
salmonid conservation (Spence et al. 1996J;
Habitat requirement of salmonids in streams
(Bjornn and Reiser 1991); Forestry impacts on
freshwater habitat of anadromous salmonids
(Murphy et al. 1995), Fisheries handbook of
engineering requirements and biological criteria
(Bell 1986), and essential fish habitat for four
species of salmon (NMFS 1998). Pacific Salmon
and their Ecosystems (Stouder et al. 1997) is an
excellent compendium of articles on salmonid
fish status, factors contributing to their decline,
and restoration needs and opportunities. The
summary table of effects of land uses on
salmonid habitats is taken from the article
"Degradation and Loss of Anadromous
Salmonid Habitat in the Pacific Northwest" by S.
Gregory and P. Bisson (1997) with permission
from the authors. The following section is
adapted from these two documents.
Habitat requirements for salmonid fishes are
organized by life-history stages, because the
fish utilize different micro-habitats depending on
their life stage and size. Bjornn and Reiser
(1991) discuss habitat requirements in relation
to five major life stages: migration of maturing
fish to natal streams, spawning by adults,
incubation of embryos, rearing of juveniles, and
downstream migration of fish. Within these life
stages, habitat requirements have been divided
into physical and chemical attributes that
correspond roughly to three of the factors in
Karr's organization of water resource integrity
(Yoder 1995). These factors include water
chemistry (temperature, dissolved oxygen, and
turbidity), flow regime (streamflow, water
velocity, and depth), and habitat structure
(space, substrate, and cover).
Despite the body of literature on the habitat
requirements of salmonids, there is little
concensus on the ability to describe these
requirements quantitatively for individual
species. Several recent reviews of species
status were unable to identify specific habitat
thresholds. Stream channel stability, habitat
complexity, substrate composition were
identified as prominent factors that influence bull
trout populations; however, no tolerance
thresholds for these characteristics were
recommended (Rieman and Mclntyre 1993). In
reviewing the conservation assessment for
inland cutthroat trout, Young (1995) states that,
although the basic components of habitat are
understood, there is little information about what
constitutes ideal or optimal habitat for this
species.
These examples illustrate the difficulty of
developing habitat indicators at the species level
from the existing literature. An alternative
approach is to identify and protect the general
habitat characteristics of stream ecosystems
necessary to support healthy fish populations
and, perhaps more importantly, the processes
that promote their development. The summary
of habitat requirements that follows, adapted
primarily from Bjornn and Reiser (1991), focuses
on the structural habitat features of stream
systems. It is included here to identify the
importance of habitat in supporting salmonid fish
as a beneficial use and is directed toward the
non-fish biologist in the water quality field.
Migration of Adults
Adult salmon returning to their natal streams
must reach spawning grounds at the proper time
and with sufficient energy reserves to complete
their life cycles. Stream discharge, water
temperatures, and water quality must be suitable
13
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Aquatic Habitat Indicators
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Salmonid Habitat Requirements and Land use effects
during at least a portion of their migration
season.
Salmon and trout respond to stream
temperatures during their upstream migrations.
Delayed upstream migrations as a result
excessively warm water temperature have been
observed in salmon and steelhead. Stream
temperatures can be altered by removal of
streambank vegetation, alteration of the channel
shape to a wider and shallower profile, as well
as withdrawal and return of water for agricultural
irrigation.
Cover for salmonids waiting to spawn or in the
process of spawning can be provided by
overhanging vegetation, undercut banks,
submerged vegetation, submerged objects such
as logs and rocks, floating debris, deep water,
turbulence, and turbidity. Cover can protect fish
from disturbance and predation. Some
anadromous fish, Chinook salmon and steelhead
for example, enter freshwater streams and arrive
at the spawning grounds weeks or months
before they spawn. If the holding and spawning
grounds have little cover, such fish are
vulnerable to disturbance and predation over a
long period.
Spawning and Incubation
Substrate composition, cover, water quality, and
water quantity (i.e. seasonal stream flow
characteristics) are important habitat elements
for salmonids before and during spawning. The
quality of the substrate, water depth, and
velocity defines the area suitable for spawning,
but the suitability of the substrate for spawning
depends mostly on fish size; large fish can use
larger substrate materials than can small fish.
Steelhead, for example, use substrate in the
range of 1 - 10 cm compared to rainbow trout
that use substrate in the 0.6 - 5 cm range.
Cover is important for adults in species that
spend several weeks maturing near spawning
areas.
Successful incubation of embryos and
emergence of fry depend on many chemical,
physical, and hydraulic variables: dissolved
oxygen, water temperature, biochemical oxygen
demand in the water column and deposited in
the redd, substrate size (including the amount of
fine sediment), channel gradient and
configuration, water depth above the redd,
permeability and porosity of the gravel, and
velocity through the redd. Water quality
standards require more restrictive standards for
temperature and dissolved oxygen for salmonid
spawning, and standards have generally not
addressed the effect of fine sediment due to the
difficulty in establishing quantitative thresholds.
Streambed particles in the redd at the end of
spawning as well as organic and inorganic
particles that settle into the redd affect the rate
of water interchange, the oxygen available to the
embryos, the concentration of wastes, and
emergence of alevins. During redd construction,
spawners displace fine sediments and organic
material, which improves the conditions for the
survival of embryos. Fine sediment inevitably
moves back into the redd environment after
construction. The amount of fine sediment
deposited and the depth to which it intrudes
depend on the size of substrate in the redd, flow
conditions in the stream, and the amount and
size of sediment being transported. Intrusion
into the redd is higher with smaller particle sizes
and these particles have a higher potential to
reduce survival. Larger intruding particles can
create a seal or a clogged layer within the gravel
preventing fry from emerging from the redd.
Relation between embryo survival and particle
size has been investigated in lab studies;
however, the degree to which these studies
simulate the conditions found in the egg pocket
of a natural redd is unknown.
Rearing Habitat
The capacity of a stream to support salmonid
fish populations depends on the spawning and
incubation success, the quality and quantity of
suitable habitat, abundance and composition of
food, and interactions with other fish and
predators. Environmental factors can affect the
distribution and abundance of juvenile salmonids
at various scales. Temperature, productivity,
suitable space, and water quality can regulate
fish populations at a reach or stream system
scale. Fish respond to velocity, depth,
substrate, cover, competition and predation at a
habitat unit or micro-habitat scale. Temperature,
dissolved oxygen, turbidity, and nutrients are
important water chemistry factors that regulate
the distribution of salmonids. These factors for
the most part are addressed in state water
quality standards or programs and are not
discussed further.
14
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Aquatic Habitat Indicators
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Salmonid Habitat Requirements and Land use effects
Space suitable for use by salmonids is a
function of streamflow, channel morphology,
gradient, and various forms of instream or
riparian cover. Space requirements are related
to sufficient depth and quality of water flowing at
appropriate velocities. The addition of cover -
extra depth, preferred substrates, woody debris,
etc. - increases the complexity of the space.
The amount of space needed by fish increases
with age and size class. Physical space in a
stream is reduced over time as dikes and levees
are built to contain flood flows, roads are built in
the riparian zone, and streams are ditched or
moved to one side of the valley floor.
Given adequate flow in a stream, velocity is
probably the next most important factor in
determining the amount of suitable space for
rearing salmonids. If the velocities are
unsuitable, no fish will be present. Natural
streams contain a diversity of velocities and
depths. The velocities required and used by
juvenile salmonids vary with size of fish and
sometimes with species. Some juvenile
salmonids, as they grow, select sites in streams
with increasingly faster velocities, presumably to
gain access to more abundant food. Preferred
depth of water is subject to needs for suitable
velocities, access to food, and security from
predators. The relation between water depth
and fish numbers depends on the mixture offish
species and sizes, amount of cover, and size of
stream. Fish abundance likely rises with
increasing depth up to a point.
Substrates are important habitats for incubating
embryos and aquatic invertebrates that provide
much of the food for salmonids; substrates also
provide cover for fish in summer and winter.
Juvenile salmonids will hide in the interstitial
spaces of stream substrates, particularly in
winter, when the spaces are accessible. The
summer or winter carrying capacity of the
stream for fish declines when fine sediments fill
the interstitial spaces. For example, it has been
observed that steelhead and Chinook salmon
migrate downstream in fall and winter until areas
with larger substrate are encountered. In
summer, clean substrates contribute to carrying
capacity by providing habitat for invertebrates
that fish utilize as prey. In winter, the substrate
is more important as a source of cover.
Cover is an important, but difficult to define,
aspect of salmonid habitats in streams.
Features that provide cover include water depth,
water turbulence, large-particle substrates,
overhanging or undercut banks, overhanging
vegetation, woody debris, and aquatic
vegetation. Cover provides security from
predation for fish and allows them to occupy
portions of streams they might not use
otherwise. Fish abundance in streams has been
correlated with the abundance and quality of
cover in studies of cutthroat trout, steelhead,
and Chinook salmon. Large woody debris is an
important form of cover linked to abundance of
juvenile coho salmon and steelhead.
Alteration of Salmonid Habitats by
Land-Use Practices
Modification of aquatic habitats generally affects
one or more of six fundamental components of
stream ecosystems: channel structure,
hydrology, sediment input, environmental
factors, riparian forests, and exogenous material
(Table 1). Actions that change channel structure,
hydrology, or sediment delivery essentially alter
the physical habitat that can be occupied by
anadromous salmonids. Environmental factors
change either the physical environment or water
chemistry, which either directly affect the
physiology of salmonids or indirectly influence
their food resources. Riparian forests influence
numerous processes such as flood routing,
sediment trapping, nutrient uptake, energy
inputs, wood, shade, stream temperature, and
root strength. Exogenous materials, including
dissolved chemicals, particulate material, and
exotic organisms, represent factors commonly
not part of the evolutionary history of the aquatic
ecosystems. Responses to these introduced
materials can be severe and can persist as long
as the material remains in the ecosystem.
Conversion of lowland forests, coastal tide
lands, floodplains, and headwater forests, as
well as alteration of water quality have affected
anadromous salmonids and aquatic ecosystems
throughout the Pacific Northwest. Much of the
habitat of lower main rivers is no longer in forest
lands but instead is in areas zoned for
agriculture, urban, and industrial development.
Many of these lands have been converted from
coniferous forests to grasslands, meadows,
deciduous forests, or paved surfaces. As a
consequence of settlement, many historical
lowland or floodplain forests have been
eliminated, and recent society has little memory
15
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Aquatic Habitat Indicators
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Salmonid Habitat Requirements and Land use effects
of the conditions of those riparian forests and
the roles that they played. Riparian forests in
lower valley floodplains, particularly secondary
channels and off-channel ponds, were
particularly critical for the survival of rearing
salmon during winter floods and provided
cold-water refuges during warmer periods of the
year.
Assessment of habitat loss is limited to a few
case studies. Comparison of current conditions
of the upper Willamette River with maps
constructed by the cadastral land survey of the
1850s reveals extensive simplification. Sections
of the river, originally braided and containing
side channels and floodplain lakes, are now
single channels with little or no lateral
connections. Lowland streams and rivers have
been simplified and channelized so extensively
that it is rare to find reaches that resemble
natural channels and floodplain forests.
Land-use practices differ in their impacts and on
the portions of the landscape and river
drainages that are altered. Forested lands make
up 46% of the land cover of Washington,
Oregon, and Idaho, and the federal government
manages or supervises ~60% of the forest
lands. Rangelands account for 32% of the land
base, and croplands and pasture make up
another 20%. Only 2% of the Pacific Northwest
is represented by urban or developed lands.
Habitat Loss Associated with Forest
Management
Forest practices,e.g., timber harvest, yarding,
road building, alter many processes of
watersheds and aquatic ecosystems. These
interactions have been evaluated and
synthesized in several major symposia, reports,
and books. These works provide detailed
reviews of the effects of forest practices on
aquatic ecosystems; the following summary
highlights some of the major changes related to
habitat alteration in forest lands.
Historical Habitat Change
When commercial logging began in the mid-19th
century rivers served as the early routes for
transportation. Splash dams were constructed
to generate sufficient flows for moving the logs
down stream channels. During relatively low
flow conditions, a slurry of water and logs was
suddenly released, destroying riparian zones
and aquatic communities as it moved
downstream. Structurally complex habitats
within these streams were channelized and
cleared to facilitate transportation. Splash
damming and log drives from the 1870s through
the 1920s altered streams and rivers to such an
extent that they have not yet fully healed.
The history of logging on both public and private
lands in the Pacific Northwest left a legacy of
altered habitats that will require considerable
time for recovery, and the return to historical
conditions will probably never occur on a large
proportion of the forested landscape. Stream
surveys by federal agencies have shown that
habitat is in fair to poor condition (BLM 1991,
FEMAT 1993, Hessburg 1993, Thomas et al.
1993). The BLM estimated that 64% of the
riparian areas on their lands in Oregon and
Washington and 45% of their riparian areas in
Idaho did not meet the objectives of their
management policies (BLM 1991). FEMAT
(1993) concluded that "aquatic ecosystems in
the range of the northern spotted owl exhibit
signs of degradation and ecological stress....
Although several factors are responsible for
declines of anadromous fish populations, habitat
loss and modification are major determinants of
their current status."
One of the few quantitative studies of habitat
change was based on a survey of pools in
Pacific Northwest streams, conducted by the
USFWS from 1934 to 1946. The Pacific
Northwest Research Station of the USFS and its
cooperators resurveyed the same streams 50
years later to determine changes in channel
conditions. Frequencies of very large pools in
658 km of stream in 13 basins in Washington
and Oregon decreased by an average of 58%.
On the basis of habitat surveys from 1934 to
1946, Mclntosh et al. (1994) concluded that the
frequency of large pools in watersheds with
forest management in eastern Oregon and
Washington declined by an average of 31%,
while pools in unmanaged basins increased by
200%. These changes have occurred since
1934, which followed more than 80 years of
extensive habitat alteration in all of the surveyed
basins. Loss of large-pool habitat has been
caused by various forest management-related
factors, including the removal of large wood and
large boulders, an increase in the amount of fine
16
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Aquatic Habitat Indicators
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Salmonid Habitat Requirements and Land use effects
sediment (sand and gravel) deposited in pool
bottoms, and in some instances, by
channelization (FEMAT 1993).
A study of streams in old growth forests, forests
with moderate harvest (<50% harvested within
the last 40 years), and forests with intensive
harvest (>50% harvested within the last 40
years) in western Washington documented
significant changes in pool habitat and amounts
of large wood. Pool areas and depths were
significantly lower in streams in old-growth
forests than in harvested basins, and pools >1 m
in depth were almost eliminated in harvested
basins. A reduction in the abundance of large
pieces of wood was also related to logging.
Channel Structure
One of the most profound changes in habitat
related to forest practices is alteration of channel
structure. Channel structure can be affected
directly by sedimentation, mass failure, changes
in rooting and vegetative cover, and direct
channel modification by heavy equipment.
Channels can respond differently to physical
change depending on geology, climate,
sediment loading, vegetation, slope, and basin
position. Decreased heterogeneity of channel
units and loss of pool habitat are common
responses to forest practices in the Pacific
Northwest.
The 1970s marked the first well-documented
recognition of the role of wood in stream
ecosystems. Numerous studies have
demonstrated that clearcutting, often in
combination with stream clean-up, have
dramatically reduced the volumes and types of
wood in streams throughout the region.
Removal of mature trees along streams reduces
natural loading rates for centuries. Loss of wood
from channels directly influences the distribution
and abundance offish populations and is one of
the longest lasting effects of forest harvest on
anadromous salmonids.
Floodplains are fundamental and often
overlooked components of stream channels and
alluvial valleys. Secondary channels provide
important refugia in moderate to high-gradient
streams during floods. Seasonally flooded
channels and riverine ponds support a major
component of the populations of coho salmon
and other fish species during winter months
(Peterson 1982, Peterson and Reid 1984, Brown
and Hartman 1988). Loss of floodplain habitats
in both montane and lowland riparian forests has
been one of the most pervasive and unregulated
forms of habitat loss in the Pacific Northwest
(NRC1996).
Habitat Loss Associated with Agriculture
and Livestock Grazing
Agricultural lands (including croplands and
pastures) make up ~20% of the land base of the
region, and rangelands account for >30% of the
land. In combination, lands used for production
of crops or livestock account for ~50% of the
northwestern states. These lands are located in
the lower portions of the river basins where
stream gradients are low and valleys are formed
primarily by alluvial deposition. Agricultural and
rangelands usually contain more species of fish
than steeper headwater streams in forests and
often some of the more productive aquatic
habitat within the basin. These lands also
contain the mainstem reaches essential for the
migration of anadromous salmonids.
Land-use practices on agricultural and range
lands have greatly reduced the availability and
quality of salmonid habitat. Agricultural lands
generally occur in lowland valleys that
historically contained the majority of floodplains
and wetlands within the region. Most of these
aquatic habitats were eliminated by
channelization, draining, road building, and filling
operations prior to World War II. Fishery
biologists have no quantitative measures of the
degree to which the elimination of lowland
aquatic systems affected salmon, but recent
evidence indicates that these were some of the
most productive habitats within the landscape.
Studies of the effects of livestock grazing on
aquatic ecosystems and salmonids generally
have observed responses consistent with
studies of habitat relationships on forest lands.
Where riparian vegetation is heavily grazed and
channel structure is changed, populations of
some fish species decline, the balance of
species is altered, and stream flows are
negatively affected.
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Aquatic Habitat Indicators
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Salmonid Habitat Requirements and Land use effects
Habitat Loss Associated with
Urbanization
Urban lands make up only 2% of the land base
of the Pacific Northwest. They, however, exert a
disproportionate influence on salmonid
production, because urban areas are frequently
located in important salmonid migration corridors
and wintering sites. In spite of their relatively
small area, >70% of the population of the region
lives in cities and towns (76%, 70%, 57%, 93%
for Washington, Oregon, Idaho, and California,
respectively [American Almanac: Statistical
Abstracts of the United States 1994]). The urban
sector primarily dictates regional resource
management, though constraints on land use
are borne almost entirely by the rural sector.
Increases in the proportion of the urban
population will only create greater conflicts
between interests of the general public, private
landowners, and natural resource agencies that
manage the majority of the land base.
Though total urban area may be small, cities
and towns are located at critical positions on
major rivers, tributary junctions, and estuaries.
The confluences of major rivers in the Pacific
Northwest, e.g. the Willamette and Columbia
rivers, Puget Sound, and its tributaries, are
centers of major regional metropolitan. Aquatic
habitats in urban areas are more highly altered
than in any other land-use type in the Pacific
Northwest, and the proportion of the streams
within the urban areas that are degraded is
greater than the proportion of highly altered
streams on agricultural, range, or forested lands.
Most urban areas are located on historical
wetlands, but drainage requirements for
residences and urban centers have eliminated
~90% of these productive aquatic habitats in
some drainage systems. Water quality and
habitat conditions in these critical migration
pathways within river networks potentially
restrict movement of salmonid smolts from their
natal streams, survival in winter rearing areas, or
return of adult salmon to the headwaters. In
addition, habitat degradation and direct effects
on invertebrate communities reduce food
supplies for fish assemblages. Loss of
wetlands, tidal sloughs, and estuaries in heavily
urbanized or industrialized river basins have
been extensive. In some areas of Puget Sound,
over 95% of estuarine and coastal wetland
habitats have been eliminated since the 19th
century. Though forest practices and, to a
lesser degree, agricultural practices have drawn
intense scrutiny resulting in more protective
land-use regulations, urbanization and industrial
development tend to cause the most extensive
alteration of aquatic ecosystems. Future
population increases in the Pacific Northwest will
expand the spatial extent of this source of
habitat loss.
18
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reduced primary and secondary productivity, increase
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mainstem and floodplain rearing habitats, reduced pri
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978), Noggle (1978), Bisson and Bilby (1982), Berg s
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behavioral avoidance and breakdown of social
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artman (1983), Hughes and Davis(1986), Beschta et
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Aquatic Habitat Indicators
SECTION 4
A Landscape context for habitat indicators
4. A LANDSCAPE CONTEXT FOR HABITAT INDICATORS
Temporal and Spatial Scales
Pacific Northwest stream communities respond
to environmental variability in different ways at
different scales of time and space. Gaining an
understanding of these biological and physical
habitat-shaping processes is, therefore, a matter
of understanding temporal and spatial scale.
Assessments conducted at one scale cannot
reliably evaluate the effects of processes that
are most important at other scales, and may in
fact produce misleading results (Wiens 1981).
Spatial scales for habitat studies are often
dictated more by resource constraints than by
sound study design. Results from studies at a
few local plots in various habitats that are then
generalized to the broader realm can lead to the
application of a correct insight to the wrong
situation (Wiens 1981, Conquest and Ralph
1998) A solution to this potential confusion is to
understand how the physical processes that
produce the patterns in populations and habitats
vary as a function of scale. Recent advances in
the physical sciences help considerably in
providing the perspective tools to aid our
understanding of patterns and processes
operating at the landscape and watershed scale.
Hierarchical Context
Variability in Pacific Northwest freshwater and
estuarine ecosystems mirrors interactions of
processes that operate at multiple scales.
Recognizing the existence and importance of
these scales and sorting out their interactions
helps make sense of this variability. Hierarchy
theory advances the idea that ecosystem
processes and functions operating at different
scales form a nested interdependent system
where one level influences other levels above
and below it. Understanding one level in a
system is greatly informed by those levels
immediately above and below it, but much less
so by those levels a long way from it (Greenland
1998). In reality, there is a continual shifting of
aquatic habitat conditions (over space and time)
that reflects the fact that controlling processes
are highly variable across the landscape. The
rate, pattern, duration and magnitude of
changes to these controlling processes are
occasionally reset by high impact events (pulse
disturbances), which helps explain why we see
opposing areas of habitat abundance and
scarcity (Greenland 1998). These features are
expected as part of the natural character of
watersheds. Press disturbances (more frequent,
less dispersed or chronic occurrences) are more
often associated with human activities and also
drive the quality and quantity of aquatic habitats,
although often at smaller scales. Salmon and
trout populations native to the Pacific Northwest
streams have adapted over the millennia to
these variable conditions and, until recently,
have been able to maintain large, diverse and
distinct runs within the larger populations of the
various species. The cumulative effects of
watershed processes accelerated by human
activities can impose persistent, widespread
declines in habitat quality throughout the historic
range of salmon and trout.
Control Factors and Scale
How can these fundamental principles be used
to stratify assessment information and to help
distinguish between landscape scale factors
(ultimate controls) and local scale factors
(proximate controls) that affect the
characteristics of watersheds and streams?
What are the principle factors that could be used
to stratify our focus? How can we use these
principles as we try to identify and apply a suite
of appropriate variables (factors, parameters)
that reflect meaningful habitat changes and
relate to processes affected by human
activities?
22
-------
Aquatic Habitat Indicators
SECTION 4
A Landscape context for habitat indicators
Ultimate controls, such as climate, geology
(landform) and vegetation (land cover), refer to
factors that operate over large areas, are stable
over long time periods (hundreds to thousands
of years), and act to shape the overall character
and attainable conditions within drainage
networks. Proximate controls are a function of
ultimate factors and refer to local conditions of
geology, landform and biotic processes
operating over smaller areas (e.g. reach scales)
and over shorter time spans (decades to years).
These factors include such physical processes
as precipitation patterns, discharge,
temperature, localized hill-slope erosion and
mass slope failures, channel migration,
sediment input and routing, and associated
biological processes. All of these proximate
factors are influenced as well by an equally
diverse mix of human activities (Naiman et al.
1992, Figures).
Long
Ultimate
Time
Climate
Geology
Vegetation
Mass Wasting
Sediment Input / Routing
Organic Debris^
Competition
Predation
Proximate
Short
Small
Spatial
Scale
Large
Figure 3. The role of ultimate vs. proximate factors in determining watershed and stream
characteristics (Naiman et al. 1992).
Classification Systems
Objectives of Classification
The term "classification" suggests that sets of
characteristics and observations can be
organized into meaningful groups based on
measures of similarity or difference. Experience
suggests that each stream type possesses a set
of inherent and presumably predictable
attributes (e.g. channel pattern, dimensions and
profile, bio-geo-chemical signature, resistance
and response to change, and biotic productivity),
which reflect the expressions of local climate,
geology, landform and disturbance regimes.
Basin characteristics (size, climate, geology)
help define flow (water and sediment)
characteristics which in turn help shape channel
characteristics within some broadly predictable
ranges (Rosgen 1996, Orsborn 1990).
Understanding these inherent relationships is
the key to identifying the appropriate factors for
the assessment of the status and trends of
aquatic systems, including the communities of
organisms they support. Understanding how
various geologic and climatic processes interact
within a watershed gives a more thorough
picture of the natural conditions (actual and
potential) as well as of the direction and
23
-------
Aquatic Habitat Indicators
SECTION 4
A Landscape context for habitat indicators
magnitude of possible changes triggered by
natural or human disturbances.
Early efforts were made to develop a more
systematic approach for understanding the
natural variability found in stream channels, their
riparian zones, and floodplains. These systems
tried to identify those common characteristics
which when compared among streams allowed
for some assessment of relative stream "health"
(Naiman et al. 1992). These efforts have lead to
an evolving legacy of stream channel
classification systems, most of which are based
on the assumption that patterns in channel
morphology can be used to simplify the wide
array of stream conditions encountered. Many
of the systems developed were driven by the
desire to associate key habitat types with certain
fish life stages. Much effort has been expended
on data collection and comparison in an attempt
to find commonalties and patterns across the
broad range of stream types and sometimes
without the benefit of a logical basis to limit the
confusion of inherent differences. Organization
of stream types is possible, once it is recognized
that the stream is a product of the landscape
and that landscapes sharing common climatic
and geologic features likely produce streams of
a similar character. A common geo-climatic
setting will impart certain common
characteristics of instream habitat features. This
setting does not, however, explain the range
within certain stream characteristics, particularly
those often associated with what we interpret as
"biotic health". Factors which operate at a more
local level also influence the habitat features and
ultimately the biotic health of the system.
One view of aquatic classification is to nest
stream and watersheds within a broader
landscape scale using the concept of
ecoregions, an area with relative homogeneity in
the characteristics and components that
constitute an ecosystem (Omernik and Bailey
1997). At the ecoregion scale, ranges of
expected values for habitat quality indicators can
be developed empirically from data representing
reference conditions. The reference conditions
should allow us to understand better the range
in expression of several variables and - by
inference - reflect the actual potential stream
habitats within a particular basin context.
As discussed previously, we recognize that this
approach has several immediate limitations.
First, there is little agreement currently on what
constitutes reference areas to cover the
ecoregions identified at the Level III scale.
Identification and use of reference areas is an
ongoing effort at the state and regional level.
Secondly, the currently available databases
generally are not sufficiently robust to provide
statistically reliable values. Third, there are
some ecoregions or regional areas, such as
grass/shrub lands, where land management has
been so pervasive as to eliminate entirely the
potential for reference conditions. Regardless of
these current limitations, we believe it is useful
to outline an approach and then initiate the
search for appropriate data sets or encourage
the collection of appropriate data. In the interim,
we will need to depend on the published data
sets available and use them with appropriate
caution.
Derivation of Habitat Indicator
Variables and Stream Classification
The challenge of selecting appropriate habitat
indicators is one of determining from what level
on this continuum of controlling factors should
habitat variables be derived. Variables drawn
from processes associated with ultimate controls
lack the resolution to allow for meaningful
comparison of stream habitat over time and
space. Variables associated with proximate
controls vary enough in space and time to allow
tracking of changes in habitat quality, but the
dynamic nature of these processes does not
allow for meaningful comparisons between
streams and within the same stream over time.
To assure comparable stream conditions, the
framework of ultimate controls must be
incorporated into the analysis when data
comparisons are made.
In order to factor in the wide range of processes
inherent in both ultimate and proximate controls,
ecologists, hydrologists and geographers have
developed a number of classification systems (
Table 2). These systems can be placed on a
scale ranging from micro-habitat features, such
as individual pools, to regional features, such as
geologic provinces. A defensible classification
system will incorporate the entire spectrum of
processes influencing stream features and
recognize the tiered/nested nature of landscape
and aquatic features.
24
-------
Aquatic Habitat Indicators
SECTION 4
A Landscape context for habitat indicators
Table 2. Summary of contemporary spatial scale classifications.
Classification
System
Bisson etal. 1982
Frissell etal. 1986
Maxwell etal 1995
Montgomery &
Buffington 1997
Omernik & Bailey
1997
Paustian 1992
Rosgen 1996
Seaberet al. 1987
Spatial Scales Addressed by the Classification System
Ecoregion
X
X
River Basin
X
X
X
Watershed
X
X
X
X
X
Sub-watershed
X
X
X
X
X
X
Valley Segment
X
X
X
X
X
Stream Reach
X
X
X
X
X
Habitat Unit
X
X
Aquatic/Landscape Classification
Systems
Frissell et al. (1986) were among the first to
describe a spatially-nested hierarchical system
for channel classification consisting of stream
system, segment system, reach system, pool-
riffle system, and microhabitat systems. This
approach emphasizes the watershed-dependent
nature of river systems and the importance of
physical habitat in controlling biotic organization
within a regional bio-geo-climatic framework.
Watershed characteristics reflect the geologic
and climatic history of the drainage basin.
Stream system places the entire drainage
network in a watershed context. Segment
systems are portions of streams bounded by
such major discontinuities as tributaries or
changes in underlying bedrock. Within
segments, reach systems are defined by breaks
in characteristics such as channel slope, bank
material, floodplain characteristics, substrate
character, and riparian canopy cover. Pool-riffle
systems are characterized by breaks in bed
topography and water surface slope, depth, and
velocity pattern. Micro-habitat systems are
components of pool-riffle systems similar in such
morphologic features as substrate type, water
depth and velocity (see also Bisson et al. 1987,
Hawkins etal. 1993).
Frissell's original nested hierarchy scheme has
been expanded to include forces which operate
on a more regional basis (ultimate controls) than
individual stream systems. Each ecoregion is in
turn potentially subdivided into river basins and
watersheds. However, it should be recognized
that hydrologic boundaries do not neatly fit
within the boundaries drawn around similar
terrestrial landscapes. Figure 4 is an illustration
of a simple hierarchical system that shows
watersheds nested within the ecoregion setting.
Various other hierarchical schemes are possible
and appropriate depending on the purpose for
the hierarchical framework.
The geomorphic stream classification system
(Rosgen 1986) classifies stream channel
systems at the broad scale by their pattern,
profile and channel dimensions. At the stream
reach level, it has been useful in evaluating
suitability of proposed fish habitat structures,
livestock grazing systems, and stream
restoration projects. Montgomery and
Buffington (1993) describe a process-based
classification system to delineate streams as
sediment source, transport, and response
(deposition). In Alaska a functional system was
developed for use on the Tongas National
Forest (Paustin et al. 1992), which has been
widely accepted and is being used to define
appropriate forestland management approaches
and the overall design of the aquatic monitoring
program. The hierarchical framework of aquatic
ecological units described by Maxwell et al.
(1995) is a comprehensive system that
integrates surface water systems, geoclimatic
settings, and ground water systems and spans
the spatial hierarchy from ecoregion to river
reach scale. The highest recognized level in the
landscape hierarchy is a broad physiographic
area termed 'ecoregion'.
A Hierarchical Approach for Habitat
Indicators
The illustration in Figure 4 shows a hierarchical
system that integrates the ultimate controls that
25
-------
Aquatic Habitat Indicators
SECTION 4
A Landscape context for habitat indicators
operate at the landscape scale (ecoregions) with
the proximate controls that operate at the stream
channel and stream reach level. Other
intermediate levels in the hierarchical system
integrate these factors at different geographic
scales. We have eliminated the segment level,
since this hierarchical level is somewhat
arbitrary and not used consistently.
The hierarchical system offers a number of
advantages, including:
1. classification at higher levels narrows the set
of variables needed at lower levels;
2. it allows for integration of data from diverse
sources and of different levels of resolution;
3. it allows the scientist or manager to select
the level of resolution most appropriate for
their objectives;
4. and, it allows the distinction between
inherent differences and those associated
with the imprint of human activities, thus
aiding in the interpretation of observations.
Ecoregions
Geology and climate are ultimately responsible
for setting the stage on which factors that
operate at more local scales and shorter time
frames act to shape channel conditions. For
habitat variables, it is, therefore, appropriate to
select a top tier, the ecoregion, that is stratified
primarily on these factors. The ecoregion
delineation not only provides a framework for a
landscape hierarchical scheme (Omernik 1995),
but ecoregions have also been used as the
initial basis for classifying streams (Whittier et al.
1988); the authors use geology, vegetation and
climate as the basis for their initial stream
stratification. Ecoregions are further delineated
based on soils, land use, wildlife, and hydrology.
Ecoregions have been used successfully to
stratify the landscape for description of aquatic
biological communities. Fish assemblage
patterns corresponded well to ecoregions in
three statewide assessments (Hughes et al.
1990). Ecoregions have been recognized as the
initial stratification level for some statewide
monitoring and bioassessment programs
(Hughes et. al. 1994, Hughes 1995).
Eco region
River Basin
Subbasin
W atershed
Steram System
Stream Segm ent
Stream Reach
ChannelUnit
Figure 4. Hierarchical scheme of landscape and stream network.
River Systems, Watershed, Sub-
watershed
These levels have been grouped together here
for the purpose of common discussion. They all
display clear hydrographic boundaries with
increasing similarities in geologic and
topographic features as one moves downscale
within the hierarchical framework.
Distinguishing features include relative basin
area and position in the drainage network.
These levels correspond to the fourth and fifth
"field" of the Hydrologic Unit Code system
26
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Aquatic Habitat Indicators
SECTION 4
A Landscape context for habitat indicators
(Seaber et al. 1987) commonly used by many
state and federal agencies. Basins within a
given "field" vary in size by an order of
magnitude (e.g., 5th field HUC can be 10 km.
sq. - 100 km. sq. in area), so simple
comparisons of one 5th field watershed to
another should be done with caution.
Stratification based on lithology and topography
would seem to offer greater opportunity to
compare similar basins.
Stream System
The stream system incorporates features of the
lowest level of the hierarchical system, i.e. those
features which directly define biotic health.
Assessment at the stream system level is
usually necessary to address cumulative effects
(Frissel et al. 1986) but requires information of
sufficient rigor and resolution to be useful.
Stream systems are of similar geologic structure
within any given area and operate on a time
scale of tens to hundreds of years, responding
to major geologic events and trends. Channel
features such as pattern are usually similar
within any given stream system, while features
such as slope may display a predictable pattern
or range.
Stream Reach
Stream reach is probably the most critical level
of the hierarchy with respect to habitat variables.
This is due to the fact that the stream reach
exists at the crossroads where both ultimate
controls and, for the first time in the hierarchy,
proximate controls are evident. For example,
geology and landform dictate stream gradient,
but the influence of organic debris can influence
the character of a defining habitat component
such as plunge pools. As such, the features that
delineate the stream reach are critical variables
when defining and comparing habitat quality.
The stream reach is the level most commonly
associated with assessment of biologic integrity.
This level also displays the influence of the
major "inputs" to the stream of water, sediment,
and wood. It is, perhaps, the least physically
discrete unit in the hierarchy and has been the
subject of the most confusion with respect to
terminology. Common geomorphic parameters,
such as channel pattern, profile, entrenchment,
stream and valley width, channel materials, and
vegetation, define stream reach (Maxwell et al.
1995). Reaches operate on a scale of tens to
hundreds of years, and stream reach is the
highest level in the scheme which can display
the influence of stream biota (i.e. wood formed
pools).
Channel Unit
Channel units represent specific habitat units
(pools, riffles, and glides) and can be quite
uniform with respect to their morphologic and
hydraulic condition. Channel units are assessed
in the context of their stream reach and are often
used as a diagnostic tool for assessing apparent
status and trends in the overall quality of aquatic
habitat. They are less useful in determining
cause and effect relationships, since they often
are the cumulative outcome of events that
happened upstream even years before. For
example, pool filling by gravel wedges could
result from slope failures decades before.
Channel units operate on very short time scales
of years and respond readily to natural and
human caused changes associated with
sediment and discharge input processes.
Stratification at the Stream Reach
Level
Ideally, aquatic indicator variables are those
which are most biologically relevant,
quantitative, and repeatable. The variables
must reflect the various inputs (water, sediment,
and wood) that influence all levels of the aquatic
hierarchical scheme. The stream reach and
stream segment levels appear to be most logical
level to derive suitable indicator variables
(Frissel et al. 1986, Rosgen 1996, Montgomery
and Buffington 1993). The level below stream
reach, the channel unit, inherently displays
significant variability over short periods of time
and space, which limits its potential utility in
organizing habitat variables. The stream reach
scale integrates (smoothes out) the variability
inherent at the finer scale and provides a
grouping level of the stream that can be used for
comparison of stream reaches over time or
between stream reaches.
The common set of defining features for stream
classification systems at the Stream Reach
scale are channel gradient and confinement
27
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Aquatic Habitat Indicators
SECTION 4
A Landscape context for habitat indicators
(Rosgen 1996, Montgomery and Buffington
1993). The third variable, which commonly
defines a stream reach, is some measure of
stream power such as bankfull width. Bankfull
width, along with the associated discharge
regime, serves as a consistent morphological
index that relates to channel formation and
maintenance. The Channel Type Users Guide
for southeast Alaska (Paustian et al. 1992) is
channel classification system that uses all three
criteria (bankfull width gradient, and
confinement) along with incision depth as the
principal criteria to define stream reach.
Stream Gradient
Stream gradient is the change in water surface
elevation over a given distance expressed as a
percentage. Gradient is directly related to both
bed-material load and grain size and is inversely
related to discharge (Schumm 1977). In
practice, gradient is usually first determined
approximated from topographic maps and then
field verified with reliable techniques. Error in
either technique is greatest in low gradient
(<3%) channels. Longitudinal profiles using
engineer survey equipment is the most accurate
means of determining channel gradient.
Gradient classes are useful in grouping streams
with a similar response to flow and sediment
inputs. The following gradient classes illustrate
some grouping of channels but are sensitive to
lower gradient streams (see Montgomery &
Buffington 1993, Rosgen 1996). Twenty percent
is selected as the upper level due to the
dominance of terrestrial, rather than fluvial,
processes that define the morphologic
characteristics of these steep channels.
Figure 5. Gradient classes for channel grouping.
Stream Confinement
Determination of stream confinement is the
subject of considerable confusion. This is
unfortunate, since the ability of a stream to move
laterally is always of prime concern to land
managers and biologists. Most definitions of
stream confinement refer to the ratio of the
active channel (i.e. the bankfull width) to the
valley bottom or floodplain width (Ralph et al.
1992, Moore et al. 1993, and Rosgen 1996).
Much of the confusion relates to interpretation of
valley bottom or floodplain width. Some
classification systems utilize the width of some
defined event such as the 100 year flood, while
others employ total valley width regardless of
whether the valley floor is a historic remnant
isolated from the current day channel.
An appropriate definition identifies confinement
as the ratio of the bankfull width to the width of
the modern floodplain. The modern floodplain
may be synonymous with the 100 year
floodplain or channel migration zone.
Determination of bankfull width requires some
careful observation and field calibration with
known flow - stage information.
Commonly used confinement classes include:
• U-unconstrained: Floodplain width > 4 times
bankfull width.
• M-moderately constrained: Floodplain width
2-4 times bankfull width.
• C-constrained: Floodplain width < 2 times
bankfull width.
Bankfull Width
Bankfull width is used as a surrogate for bankfull
discharge. Bankfull discharge can be described
as that flow (Q) volume which transports the
largest portion of the annual sediment load,
including bedload, over a period of years
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Aquatic Habitat Indicators
SECTION 4
A Landscape context for habitat indicators
(Wolman and Miller 1960). It is that flow which
mobilizes the majority of the bed material as well
as developing and maintaining the form of the
channel (Olsen et al. 1997). It is a critical
discharge, as channel forming forces do not
increase proportionately at flows greater than
bankfull due to over-bank dissipation of energy.
Bankfull flows generally correspond to the 1.5 to
2 year recurrence flow event (Bray 1982).
Measurement of bankfull width is a repeatable
variable but often difficult to identify in non-
entrenched channels.
Summary
Landscape scale factors (ultimate controls) and
local scale factors (proximate controls) influence
the expression of stream habitats. The
landscape scale factors, such as climate,
geology, and vegetation operate over large
areas, are stable over long time periods
(hundreds to thousands of years) and act to
shape the overall character and attainable
conditions within drainage networks. Local
scale factors are a function of ultimate factors
and refer to local conditions of geology, landform
and biotic processes that operate over smaller
areas (e.g. reach scales) and over shorter time
spans (decades to years). A hierarchical
classification system that integrates both
landscape scale factors and local scale factors
provides the organizational framework
necessary to address the spatial variability
inherent in aquatic habitats.
Ecoregions provide a first-tier of organization
which are stratified on the basis of ultimate
factors - climate, geology, and vegetation. At
the ecoregion scale, the ranges of expected
values for habitat quality indicators can be
developed empirically from data representing
reference conditions. The reference conditions
allow us to better understand the range of
values that reflect the actual potential stream
habitats within a particular basin context.
The hierarchical stream system, tiered within
ecoregions, provides a way to organize the local
scale factors which influence the stream
condition. The stream reach and stream
segment levels of the stream network are the
most logical level from which to derive suitable
indicator variables. The level below stream
reach, the channel unit, inherently displays
significant variability over short periods of time
and space, which limits its potential utility in
organizing habitat variables. The stream reach
scale integrates (smoothes out) the variability
inherent at the finer scale and provides a
grouping level of the stream that can be used for
the comparison of a stream reaches overtime or
between stream reaches.
The common set of defining features for stream
classification systems at the Stream Reach
scale are channel gradient, channel
confinement, and bankfull width. Bankfull width,
along with the associated discharge regime,
serves as a consistent morphological index that
relates to channel formation and maintenance.
Bankfull width provides a measure of stream
power. Drainage basin area is a closely related
hydrologic variable that has proven to be useful
in explaining the variability in geomorphic
channel characteristics and habitat variables.
Ecoregions and stream classification systems
provide a framework for organizing habitat
components, habitat variables, and narrative as
well as numerical indicators. The Level III
Ecoregions may provide a sufficient first iteration
for categorizing watersheds in order to evaluate
potential reference conditions for many habitat
variables. Further sub-division of Ecoregion
organization may be useful in providing a more
homogeneous organization of watersheds but
may also be a daunting task given the limited
amount of data on reference condition. A
meaningful organization of stream networks
ultimately depends on the identification of
geomorphically similar stream reaches.
Fundamental factors in organizing stream
reaches are stream gradient, confinement, and
stream power (bankfull width or basin area).
Classification systems that incorporate these
factors should be useful in developing a spatial
framework for habitat indicators.
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Aquatic Habitat Indicators
SECTION 5
An Approach to Habitat Quality Indicators
*
5. AN APPROACH TO HABITAT QUALITY INDICATORS
A framework for developing habitat quality
indicators will address the challenges that we
summarized above, namely accounting for
natural variability, legacy effects of past land
uses and natural disturbance patterns,
improving measurement methods, and
addressing the lack of habitat data from
undisturbed areas to serve as reference
conditions. A fundamental issue relates to how
the indicator is used within the context of the
water quality management program. Different
approaches to the application of indicators in
environmental and natural resource programs
have been discussed in the literature and
provide a useful context for thinking about
approaches to the use of aquatic habitat
indicators.
Types of Indicators
Cairns et al. (1993) proposed organizing
indicators into three general types: compliance
indicators, diagnostic indicators, and early
warning indicators. Compliance indicators are
those chosen to judge the attainment and
maintenance of ecosystem objectives.
Traditional water quality criteria generally fit
within this category. Criteria for toxic chemicals
or heavy metals, for example, are established at
some threshold of effect intended to protect the
aquatic biota. In many cases, the most useful
parameters in judging compliance with a
specified objective are not the best for
determining why objectives are not being met.
Diagnostic indicators are those parameters and
processes that provide insight into the cause of
noncompliance. Early warning indicators are
those that assist in maintaining the desired
condition by detecting impending deterioration
before substantial impact occurs. Water
temperature serves as an example of a
compliance indicator, while shade and overhead
canopy can be considered to be diagnostic
indicators. Early warning indicators for
temperature are land management measures
such as the percentage of timber harvest in the
riparian zone or number of road miles adjacent
to the channel.
Closely related to early warning indicators is the
concept of leading edge variables. Leading
edge variables refer to an approach of
watershed management that detects problems
with ecological processes before they result in
irretrievable damage. Conceptually, one should
be able to detect changes to the hydrologic
regime or sediment regime at the watershed
scale before the cumulative effects of upslope
activities reach a damaging condition for
instream resources. An example of leading
edge indicators is the hydrologic analyses of
anticipated change in peak flows due to
clearcutting and the extension of road networks
in forested areas or due to the increase in
impervious surfaces in urban areas. Leading
edge variables are an important concept to
assist in preventing damage to streams at the
watershed to river basin scale. However, these
concepts are at an early stage of development,
and there is no general understanding of what
they are or how they might be applied.
No single set of variables fulfills all of the
objectives for the different types of indicators.
Aquatic habitat indicators likely best fit the
description of diagnostic indicators. Aquatic
habitat measures do not function as early
warning indicators, since they are measured in-
stream after the land management activity has
occurred and integrate the effect of both natural
disturbances and impacts due to the legacy of
management actions over time (i.e. cumulative
effects). Potential early warning indicators of
habitat damage are measured upslope of the
stream channel or upstream as cumulative
inputs. Effective early warning indicators will
address the management activities in the
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An Approach to Habitat Quality Indicators
watershed such as road density, riparian
condition related to shade and large wood
recruitment, or sediment sources.
Aquatic habitat variables can be used to assess
the quality of the habitat in meeting the needs of
beneficial uses. However, because of the high
variability in habitat measurement and the lack
of a ready connection to source assessment, it
appears that habitat variables are best used as
diagnostic indicators rather than as compliance
measures. The habitat measurement should be
used to detect when the environmental condition
is outside the expected range supportive of the
beneficial use. The reason for such deviation
should then be further evaluated by investigating
the historical, current, and potentially natural
causes of low habitat integrity. A complete
monitoring and management program which is
effective in protecting beneficial uses will need
to address the entire management system from
evaluation of on-slope activities to the evaluation
of watershed and instream processes and
functions. Habitat indicators by themselves can
only be expected to fulfill one facet of the role of
environmental indicators.
Input vs. Output Approaches to
Ecosystem Management
Related to the functional types of indicators is
the conceptual model for resource management
used to approach problem definition and
resolution. The current water quality model for
landscape scale management relies primarily on
the output-oriented strategy (Montgomery 1995).
Output management responds to ecosystem
conditions and defines limits to acceptable
resource damage. This style of management is
considered reactive rather than preventative,
since land use activities are modified only after
degradation has occurred to levels beyond
which further degradation is considered
unacceptable. Input management implies a
preventative approach based on modifying land
use practice to reduce or preclude adverse
environmental impacts. The shift in emphasis
under the input-oriented approach is toward
changing management upslope of the problem
before it occurs.
The nonpoint source management program
within the CWA can accommodate both the
input and output-oriented strategies. Traditional
nonpoint source programs have emphasized the
reactive mode by developing and implementing
a system of BMP's after significant cumulative
damage has occurred. This is in part a function
of the lag effect between the legacy of land
management activities and the passage of
environmental laws. This has also led to some
extent to the current backlog of streams listed as
303(d) waters and the need to focus state and
federal agency resources on reducing pollutant
input to these water bodies through
development of TMDL's.
Using Indicators in ESA Review
The NMFS and USFWS use indicators to
evaluate the effect of land management
activities for conferencing, consultations, and
permits under the ESA. Since the purpose is to
evaluate the effects of proposed actions on
listed species, the decision documents ( NMFS
1996, USFWS 1998) address the pathways and
indicators of management effects. The
pathways include water quality, habitat access,
habitat elements, channel condition and
dynamics, hydrology, and watershed effects.
These pathways and their associated indicators,
therefore, address the watershed process and
input variables (e.g. road density and
disturbance history) as well as outcome
variables (e.g. substrate quality, LWD frequency,
and W:D ratio). The indicators in the matrix
represent a mix of diagnostic, early warning
indicators, and outcome variables appropriate to
the purpose of the document. These purposes
have corollaries in the CWA, but there are also
differences due to the different regulatory
framework between the two laws. ESA requires
the federal regulatory agencies to address
habitat protection for endangered species from a
very conservative approach. This influences the
interpretation of the literature and the selection
of default numerical targets.
Suggested Approach for Habitat
Quality Indicators under the CWA
The purpose and organizational framework for
habitat indicators may differ in a subtle, but
important, manner from their use under the ESA.
We have identified two purposes for habitat
indicators within the CWA. One objective is to
assess the status and condition of the habitat
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An Approach to Habitat Quality Indicators
which supports the beneficial use. The second
is to evaluate the adequacy of BMP's within the
framework of the nonpoint source feedback
loop. Because physical habitat features are
indeed outcome variables, they function best as
an index of the habitat's ability to support the
beneficial use and less efficiently as a way to
judge the adequacy of the management
practices.
Habitat features (as outcome variables) reflect
the cumulative effect of all the influences
upstream of the assessment reach and,
therefore, act as an integrator of the cumulative
and interactive effects of upstream processes;
these effects can be both attributed to natural
sources and management actions, both past
and present. The ability to detect the "signal" of
management effects within the context of natural
disturbance and legacy effects depends on the
site-specific conditions and the efficiency of the
study design. For this reason, nonpoint source
monitoring programs have always recognized
(but not fully actualized) the need for
implementation and effectiveness monitoring
which incorporates the assessment of input
variables.
There are two CWA programs where an
emphasis on the habitat condition as an
outcome variable is clearly needed. One is the
establishment of water quality criteria which
provides the environmental endpoint desired or
expected. The second, and closely related,
program is to establish targets for stream
segments forTMDL's.
We suggest that the strategy for the use of
habitat indicators for CWA purposes should
incorporate the following elements:
• An emphasis on the use of habitat variables
as diagnostic indicators rather than as
compliance criteria.
• Establishing indicators within a spatial
framework that accounts for variability in
landscape patterns and channel type to
specify numerical criteria.
• An emphasis on the quantitative
measurement of aquatic habitat indicators to
achieve needed precision and repeatability.
• An interagency recognition of the need to
identify reference conditions within the
ecoregion framework.
• Recognition that, as we learn more,
adjustments should be made to the suite of
indicators themselves, and the interpretation
of what they tell us about the aquatic
resources.
The diversity of landscapes and the high natural
variability of habitat characteristics preclude the
ability to readily identify numerical habitat criteria
at regional scales. Habitat indicators must
reflect the diversity in habitat quality across the
landscape; hence, the need for landscape and
stream stratification systems. Within a stream
type, the indicator needs to reflect the variability
that occurs under a natural setting. The
indicator needs to be measured in a reliable and
repeatable manner that expresses both the
central tendency and the spread of the data.
Habitat indicators are best used within the
framework of the nonpoint source feedback loop
(see Introduction section) as diagnostic tools of
water resource integrity rather than as
compliance endpoints. Habitat quality integrates
cumulative effects in the watershed from both
natural disturbance and from cultural activities.
The interpretation of habitat quality for a given
stream reach requires consideration of a number
of potential sources and watershed processes.
Some example scenarios for evaluating the
outcome of habitat quality studies are listed
below.
Scenarios for Interpretation of
Diagnostic Indicators
Three possible situations are briefly presented
below to illustrate common problems and
remedies. It is important to stress that knowing
what indicators are appropriate depends upon
careful assessment and an understanding of
what drives the expression of factors important
to aquatic habitats. Typically a suite of
parameter or factors will contribute relevant
information to understanding the nature and
significance of the problem that limits the habitat
capacity rather than a single indicator.
1) The indicators are applied correctly, but the
expected value for a given parameter is
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An Approach to Habitat Quality Indicators
inappropriate at the scale of watershed
organization or for the stream classes under
consideration. In this case, the land
manager or water quality agency can
conduct a watershed/basin specific
evaluation and suggest more appropriate
watershed values. Quality control
procedures including scientific peer review
would need to be in place to assure the
acceptance of the revised indicator value.
2) Anthropogenic impacts, either historic or
ongoing, have altered the watershed
processes. In this case, the landowner
needs to evaluate alternative practices
including passive and active means of
restoration (See Kaufmann et al. 1997).
3) Natural disturbance events have recently
altered the stream condition. In this case,
human activities should be evaluated with
respect to their contribution to the effect of
the event as well as the stress that will be
placed on the resource in the future.
Assessment Scale
Another important consideration is the scale at
which the evaluation is made. Stream habitat
variables are measured at the habitat unit scale
- that is, at the scale of pool, riffle, and glides.
However, the appropriate scale for evaluating
changes to habitat is likely at the next unit of
organization, namely at the reach scale. The
reach scale describes a uniform section of
stream with respect to channel morphology
(gradient, confinement, width and depth).
Variability in habitat measures is expected to
decrease as one moves upward in scale, i.e.
from individual habitat units toward groups of
habitat units aggregated at the reach scale.
Individual channel habitats can be highly
variable in comparison to the expected range of
condition, but the spread of the data around the
mean or median should decrease as the
channel habitat units are aggregated.
Evaluating information by geomorphically similar
reaches facilitates comparison between
managed and unmanaged or reference reaches.
Within a watershed context, habitat indicators
can be used to identify stream reaches or sub-
watersheds outside the expected range. These
areas should then be investigated further for
causal linkages to watershed activities.
Narrative and Numeric Criteria
Water quality standards provide for specification
of narrative and numeric criteria. Numeric
criteria are generally specified when the
quantitative relationship between the pollutant
and the beneficial use are well established in the
scientific literature and the criteria are applicable
across large geographic areas such as at a
state, ecoregion, or river basin scale.
Environmental endpoints for water quality
criteria are specified no further than the narrative
stage when the pollutant-beneficial use
relationship is highly variable across the
landscape as well as dependant on site-specific
factors and, therefore, requires local scale
adjustment before numeric targets can be
established. Narrative criteria could be used to
describe the process for developing the numeric
criteria at the local scale.
The NMFS/USFWS matrix uses the terminology
of pathway to identify the process by which a
management action can have an impact on
aquatic biota. Where feasible default numerical
criteria are specified that indicate the proper
functioning of this pathway. The specification of
the pathway is a corollary to the concept of
narrative criteria within the CWA. The use of
default numeric criteria in the matrix is a
corollary to numeric criteria established at the
national or statewide level under the CWA. Both
approaches provide for a process that identifies
site-specific numeric criteria more applicable at
a local scale. The fact that this option is rarely
exercised is an area of contention between the
regulatory and regulated community.
The following sections of this document expand
on the suggested approach. In Section 5, we
evaluate the existing recommendations of
habitat variables as useable for aquatic habitat
indicators within the context of CWA water
quality programs. Section 6 describes the
landscape and stream network considerations
for establishing habitat variables. Section 7
describes the context for assessment and
monitoring of habitat variables. Section 8
discusses application of habitat indicators to
CWA programs.
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SECTION 6
Evaluation of Potential Aquatic Habitat Indicators
6. EVALUATION OF POTENTIAL AQUATIC HABITAT
INDICATORS
Indicators in Relation to Clean Water
Act Objectives
Habitat variables have been developed to meet
various purposes including assessment of
fisheries production, determining limiting factors,
identifying the effects of land management, and
evaluating habitat improvement activities. Two
major interrelated objectives for habitat
assessment are evident in CWA programs. The
first objective is to determine whether
designated beneficial uses are attainable and
assess the current status of the beneficial uses
in a waterbody. The second objective is to
evaluate the effect of pollutant sources on a
beneficial use and assess the need for change
in pollution controls for point sources or change
in management practices for nonpoint source
activities. Meeting these two major monitoring
themes will dictate the different criteria for the
selection of habitat indicators.
The first objective, assessing the status of the
beneficial use, identifies the indicator as having
an intrinsic importance itself; the indicator is the
environmental endpoint. Macroinvertebrate and
fish communities are measured directly to
assess the status of beneficial uses identified in
the water quality standards. A criticism of using
aquatic biota as a monitoring indicator is the
same one raised in the discussion of habitat
measures. The variability in the biotic
community can be so high that its direct practical
use as an indicator in detecting response to
environmental stress is low. With certain types
of stressors, the reality is that by the time an
effect shows up it is too late for effective
management or mitigation (Kelly and Harwell
1990).
The second objective encompasses a major
emphasis of water quality programs in providing
feedback to regulatory and management
programs. In nonpoint source programs,
monitoring is categorized under implementation
and effectiveness objectives. Implementation
monitoring addresses whether the BMP's were
installed according to plans or regulations, while
effectiveness monitoring is more comprehensive
in attempting to determine if the management
practices were effective in protecting the
beneficial uses (MacDonald et al. 1991). A
desirable characteristic of an early warning
indicator is rapid responses to the environmental
stress. A related trait is that the indicator has a
high fidelity in characterizing an effect from
disturbance. Strong evidence of a causal
relationship between the stressor and a relevant
response to the beneficial use is required.
To accomplish either objective in the CWA,
habitat indicators need to meet certain
expectations for measurement reliability.
Expectations of high quality assurance and
quality control should be similar to those
described for other physical and chemical
variables. Signal-to-noise ratio is a particularly
important consideration for indicators in a highly
variable environment. The sensitivity and,
therefore, the utility of the indicator is dependent
on detecting the signal of human effects from
the background noise in the measurement
system. Kelly and Harwell (1990) provide a
thorough review of these characteristics of
environmental indicators. The following four
criteria summarize the major considerations we
believe are important in selecting habitat
indicators.
1. Relevant to the Environmental/Biotic
Endpoint
The qualitative relationship between in-stream
habitat variables and their effect on salmonid
populations is well established as described
earlier in Section 3. Salmonid fish and other
aquatic biota are sensitive to the quality and
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Evaluation of Potential Aquatic Habitat Indicators
quantity of physical habitat that can be altered
by human activities.
2. Applicable to the Landscape and Stream
Network
The importance of habitat features in supporting
salmonid populations varies across the Pacific
Northwest as climate, geology, and landform
interact. Large woody debris plays a major role
in the evolution of channel habitat characteristics
and hiding cover in a forest ecosystem. This
contrasts to the development of habitat
characteristics (pools and riffles) within meadow
and grass/shrub ecosystems where large woody
debris is a minor or absent element of physical
structure. Grouping streams within a
hierarchical stream network is necessary to
assure that the variables and the range of
magnitude of the variable are appropriate to the
stream reach, stream segment, or watershed
under consideration.
3. Responsive to Human-Caused Stressors
Human actions can cause effects on aquatic
ecosystems either as individual or cumulative
actions. The linkages between nonpoint source
activities and habitat elements are generally
understood. Habitat variables generally will not
satisfy the objective of rapid response desired in
providing feedback for adaptive management.
For this reason, many professionals believe that
effectiveness monitoring should focus on
upslope processes associated with specific
projects (Reid and Furniss 1998).
Habitat variables measure cumulative changes
over time and space; this is an important
consideration in meeting CWA goals. To a large
degree, cumulative effects are the issue driving
both the increased listings of threatened and
endangered species and the increase in TMDL
listings. The accumulation of localized or small
habitat modifications, which can go unnoticed
and unregulated, results in regional and global
change in fisheries populations (Burns 1991).
These cumulative effects cannot be addressed
by the close focus on site-specific application of
BMP's. For this reason, evaluation of human
impacts on water resources will likely need to
address both on-slope evaluation of inputs to the
aquatic system as well as the response
variables measured instream.
4. Measurement Reliability
Every environmental indicator needs to satisfy
the data quality objectives of accuracy,
precision, and repeatability. These data quality
objectives must be balanced against the real-
world tradeoffs related to the ease of monitoring,
cost, and required expertise. In providing this
balance, the ability to meet the desired
monitoring objective is a critical factor often
overlooked for the sake of expediency.
Habitat Indicators Currently in Use
Various agency programs currently use a
number of variables to measure habitat quality.
Some of these habitat variables can either be
redundant or be measured at different levels of
intensity. In addition, other variables are
collected during stream surveys to aid in data
interpretation or stream classification. A
compilation of habitat variables for which a
numeric value has been suggested is provided
in Appendix C for background information.
To get a sense of the variables commonly
evaluated, we have included the variables from
three sources in this discussion. First, there is
a list of habitat variables compiled by Spence et
al. (1996). They inventoried the existing
monitoring programs in Washington, Oregon,
and Idaho and compiled variables applicable to
salmonid conservation. The applicable subset
of physical habitat variables from this inventory
are listed in Table 3. The placement into
functional categories is somewhat arbitrary, but
their inventory helps in identifying similar and
redundant variables. This data is collected by
agencies in the Pacific Northwest for a variety of
environmental, fisheries, and land management
programs.
The second and third lists of habitat variables
comes from two documents that have been
important to the management on federal lands.
The document referred to by the acronym
'PACFISH' (USFS 1995) described the Riparian
Management Objectives (RMO) for pool
frequency, water temperature, large woody
debris, bank stability, lower bank angle, and
width/depth ratio (Table 4). The RMO's
establish instream and streamside-habitat
conditions intended to define good habitat for
anadromous fish at the landscape scale. The
RMO's serve as indicators against which
35
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Evaluation of Potential Aquatic Habitat Indicators
attainment, or progress toward attainment, of the
overall program goals can be measured. The
interim values were developed using stream
inventory data within the geographic extent of
the anadomous fish species. The objectives
were described as "interim" since the RMO's
could be modified to reflect conditions in a
specific watershed or stream reach based on
local geology, topography, climate, and potential
vegetation.
The National Marine Fisheries Service's matrix
document (NMFS 1996) lists "pathways and
indicators" for evaluating management actions
under ESA (Table 5). The document was
developed to address management actions on
federal lands in relation to the Northwest Forest
Plan, the Recovery Plan for Snake River
Salmon, and consultation on the Land Resource
Management Plan for eight national forests in
Idaho and Oregon. The matrix is explicit that the
numerical values are considered default values
to be adjusted for local conditions. Under
circumstances where the default values do not
apply, the analyst is to provide documentation
for development and use of locally and
biologically appropriate values.
Regardless of the caveats made regarding the
ability to modify the default values, the users of
these documents have voiced several concerns
that generally focus on: 1) problems in applying
a limited set of criteria across a highly variable
landscape which are not stratified as to scale, 2)
not accounting for the effect of natural
disturbance on the habitat variables, and 3) the
problems associated with lack of known
precision and accuracy of habitat measures.
Stream ecologists also are concerned that
setting instream criteria focuses managers on
the wrong kinds of stream restoration practices,
such as adding LWD or creating pools artificially.
Table 3. Habitat variables used in monitoring programs in the Pacific Northwest.
Channel Features
Velocity / depth
Channel shape
Channel type
Width/depth ratio
Stream / valley type
Gradient
Sinuosity
Discharge
Depths and widths
Large woody debris
Residual pool depth
Floodplain width
Thalweg profile
Stream Substrate
Percent Fines (fine sediment)
Embeddedness
Bottom substrate
Substrate Size
Fish Habitat Descriptors
Fish cover
Pool / riffle ratio
Pool character
Winter refugia
Habitat units / (habitat type)
Streambank
Bank stability
Bank vegetation
Bank character
Bank height
Bank incision
Bank undercut
Bank erosion
Riparian Area
Canopy cover
Canopy closure (densiometer)
Riparian buffer
Stream disturbance
Insolation
Riparian vegetation structure
Aspect
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Table 4. Selected habitat criteria used in federal programs in the western United States.
USFS & USBLM. 1995. PACFISH. Decision Notice/Decision Record, Findings of No Significant Impact Environmental
Assessment, for the interim strategies for managing anadromous fish-producing watersheds in eastern Oregon and
Washington, Idaho, and portions of California.
Habitat Feature
Interim Objectives
Pool Frequency
(all systems)
Large Woody Debris
(forested systems)
Bank Stability
(non-forested systems)
Width/Depth Ratio
(all systems)
Wetted width 10 20 25 50 75 100
Pools per mile 96 56 47 26 23 18
East of Cascade Crest in Oregon, Washington, Idaho:
> 20 pieces per mile; > 12 inch diameter; > 35 foot length
> 80 percent stable
< 10, mean wetted width divided by mean depth
125 150 200
14 12 9
National Marine Fisheries Service. 1996. Making endangered species act determinations of effect for individual or grouped
actions at the watershed scale.
Indicator
Properly Functioning
Sediment / Turbidity
Substrate
Large Woody Debris
Pool Frequency
Width/Depth Ratio
Streambank Condition
< 12% fines (<0.85mm) in gravel, turbdity low
Dominate substrate is gravel or cobble (interstitial spaces clear),
or embeddedness < 20%
Coast : > 80 pieces/mile > 24" diameter > 50 ft. length;
Eastside : > 20 pieces/mile > 12" diameter > 35 ft. length;
and adequate sources of woody debris recruitment in riparian areas
channel width 5 10 15 20 25 50 75
Spools/mile 184 96 70 56 47 26 23
> 90% stable; i.e., on average, less than 10% of banks are actively eroding
100
18
Note: See documents for complete description of criteria and the context in which they are to
be used.
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Evaluation of Potential Aquatic Habitat Indicators
Table 5: Summary of pathways and habitat indicators for ESA determinations (modified from
NMFS1996).
Pathway
1. Water Quality
2 Habitat Access
3 Habitat Elements
4. Channel Condition &
Dynamics
5. Flow & Hydrology
6. Watershed
Conditions
Narrative Statement
• Chemical contamination
• Nutrients
• Physical barriers
• Dominant substrate size
• LWD recruitment
• Pool frequency & LWD
recruitment standards
• Pool quality (depth,
cover, sediment filling)
• Off-channel habitat
• Refugia
• Actively eroding banks
• Floodplain connectivity
• Change in peak/base
flows
• Increase in drainage
networks
• Road location (no valley
bottom roads)
• Disturbance history
(unstable areas, refugia,
riparian areas)
• Riparian reserves
(shade, LWD recruitment,
connectivity)
Numerical Indicator
• Temperature
• % Fines
• Percent
embeddedness
• LWD frequency
• Pool frequency
• Pool depth
• Width/Depth ratio
• Percent stable
banks
• Road Density
• Equivalent clearcut
area.
• Percent Late
successional old
growth
• Intact refugia for
sensitive aquatic
species
• Riparian
vegetation, %
similarity
Properly Functioning
Value for
Numerical Indicator
50-57 F
< 20 % embeddedness
Coast: > 80 pieces/mile
East-side: > 20 pieces/mile
Table: pools/mile specified
by channel width.
Pools > 1 meter depth
<10
> 90% stable
< 2 miles/sq. mile
< 15% EGA
> 15% retention of late
successional old growth
> 80% intact
> 50% potential natural
community composition
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Sorting Potential Narrative and
Numerical Indicators
As described in the previous section, there are a
number of variables to consider as habitat
indicators. Some confusion arises because of
the various objectives, methods, and terms that
have been used to describe habitat variables.
A reminder regarding terminology may be
useful. Habitat component refers to an element
of the habitat where an organism occurs
(Armantrout 1998) and is considered generally
synonymous with stream attribute and pathway.
A habitat variable is a quantifiable measurement
of a habitat component (synonymous with
parameter). Water quality criteria, as used in
the CWA, refers to the elements of state
standards, expressed as numerical quantities or
narrative statements, that represent the quality
of water needed to support a particular
beneficial use (USEPA 1994c). The term
'habitat indicator' is used in this document to
emphasize its application for assessing the
condition of the habitat rather than the more
regulatory connotation usually associated with
the term 'criteria'.
As described at the beginning of this section,
there are four primary considerations in deciding
whether an indicator should be used as a habitat
indicator. A decision process for sorting through
potential habitat components and variables is
shown in Figure 6.
1. Relevance to Biota. The first criterion
evaluates whether the habitat component is
relevant to the biota, in this case salmonids. At
a broad level the components that comprise
salmonid habitat are well known and can be
readily described qualitatively. This would result
in a list of candidate narrative criteria. Habitat
Components for narrative criteria may include:
• Flow regime
• Habitat space
• Channel structure
• Substrate quality
• Streambank condition
• Riparian condition
• Temperature regime
• Water quality constituents
• Habitat access
These components are generally synonymous
with the pathways listed in the NMFS matrix. In
addition, the NMFS matrix includes input
variables and watershed components used to
further evaluate management actions.
Relevant to
Biota
k.
i
r
Responsive
to Impacts
i
f
Applicable to
Landscape
k.
i
r
Biological
Effect
Quantified
Candidate ^ ("Applicable ^) f Applicable ^
Narrative Habitat in Target
Criteria J ^ Variables J ^ Landscape J
^
Acceptable
Data Quality
i
r
Candidate
Numeric
Criteria
Figure 6. Decision diagram for selecting habitat variables.
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2. Responsive to Management. The second
criterion evaluates whether the variable is
responsive to the types of impacts caused by
management activities. Often the outcome of
management activities - as manifested instream
- are similar to those associated with natural
disturbance events and are, therefore, not
readily distinguished from natural causes. The
distinction between human causes and natural
causes is made through careful monitoring
design (e.g. upstream vs. downstream of
pollutant sources) or via the study of processes
in natural systems and their comparison to the
alteration of response and recovery rates in
managed systems. For example, measuring
residual pool depth does not distinguish
between the source of sediment, but comparing
residual pool depths to undisturbed watersheds
of a similar channel type provides an indication
of whether human activities have altered the
sediment regime enough to decrease pool
depth. In contrast, annual fluctuations in flow
rate can largely reflect natural climatic cycles,
which in turn can overwhelm our ability to detect
the additive effect from human influences.
Therefore, it follows that residual pool depth is a
useful habitat variable, whereas variation in
annual discharge alone may have little utility as
a stand alone indicator unless evaluated in the
context of a carefully designed analysis that
looks at more detailed flow statistics The
predominant land use within a basin can
substantially affect the choice of variables. For
example, in an urban context where the
influence of impervious surfaces highly alters
seasonal instream flows, storm flow peaks
increase in frequency, duration and magnitude.
3. Appropriate to the Landscape. Channel
forming processes within similar landscapes
form recognizable patterns in fisheries habitat.
Therefore, it is appropriate to identify habitat
variables grouped by similarities in the
landscape. Variables that measure habitat
space such as pool frequency, W:D ratio, and
residual pool depth can be useful across many
types of landscapes - forested, grassland, and
cropland streams. However, the habitat forming
processes vary by landscape, and this will
influence the selection of habitat variables. An
obvious example is the importance of large
woody debris in forested ecosystems in contrast
to streams located in grass/, shrublands and
desert ecosystems.
4. Linkage to Beneficial Use. The final two
criteria address the question of whether it is
feasible and technically defensible to establish
numeric criteria for a habitat component. The
first issue is whether sufficient information exists
to quantify the linkage between habitat and the
beneficial use.
The traditional way quantifying the biological
effect is by using test organisms in a laboratory
setting and studying the acute dose response
relationship. Even with the controlled
experimental approach, there is a wide
variability in the response of test organisms and
different reported toxicity values. Chronic
exposure or multiple toxicant tests (synergy) are
seldom part of the protocol.
The response of salmonids to declining habitat
conditions is not readily replicated in the lab but
can be documented through field studies with
some difficulty. Transfer of this information to
other stream systems in quantitative terms is
difficult if not infeasible. Field studies confirm
the pathways of effects and the biological
response in terms of declining fish distribution or
populations. The quantification of habitat effects
is best accomplished through the comparison of
habitat conditions to least disturbed or reference
condition watersheds. An exception to this
general observation is the use of laboratory
studies in evaluating the effect of fine sediment
on egg to fry survival. However, even with this
variable, some significant questions arise in
regards to the transferability of observed effects
to field conditions.
5. Quantifiable as Numeric Criteria. If
significant natural resource policy decisions are
going to be based on monitoring data, there
must be confidence that the data is reliable and
the interpretations sound. The final criterion in
selecting numeric criteria addresses the issue of
the measurability of habitat variables, that is, the
ability to achieve desireable levels of accuracy
and precision. Two primary considerations
influence the potential usefulness of a habitat
parameter. One is the signal-to-noise ratio
which is a function of the natural variability and
the sample error associated with the monitoring
protocol. The second consideration is the
accuracy, precision, and repeatability associated
with a specific monitoring technique. Many of
the habitat variables in current use (Table 3) are
measured at various levels of intensity from
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qualitative surveys to quantitative measure-
ments. Data that results from these methods
have different data quality characteristics and
are generally not comparable. Some quanti-
tative habitat protocols are so time-consuming
that agencies have opted to rely on ocular
estimates.
Potential Habitat Components and
Habitat Variables
In the previous sections, we identified habitat
variables commonly used in monitoring and land
management programs. These variables
address a mix of purposes - watershed input
variables, outcome variables, pathways of
habitat effects, and associated explanatory
variables used to establish status and trends in
aquatic resource conditions.
How might these potential variables be applied
as narrative and numeric water quality criteria?
To answer this question, the variables are sorted
by habitat component in Table 6 to facilitate
comparison to the evaluation criteria illustrated
in Figure 6. The column headings for Table 6
are explained below.
Narrative Criteria. Narrative criteria might be
appropriately developed at the Habitat
Component level of organization. Habitat
components represent the major elements of the
aquatic habitat necessary to support salmonid
species of fish - adequate flows, habitat space,
substrate quality, streambank and riparian
condition, water column chemistry, habitat
access and connectivity. Incorporating narrative
criteria into state water quality standards would
be a major step in the right direction of
recognizing the importance of habitat within
water quality programs.
Pathways. The second column in the table,
Pathway Elements, are generally addressed
under the CWA as elements of pollution control
programs rather than as environmental
endpoints. The pathways of effect are regulated
via state BMP's, standards, and guides in land
management plans or as pollution abatement
measures in TMDL implementation plans.
Pathways of effects are generally addressed in
state water quality standards by way of
reference to approved management practices
for specific nonpoint source activities.
Habitat Variables. The Habitat Variables listed
in the table are outcome variables that are likely
candidates as aquatic habitat indicators. The
last column in the table shows some of the
associated explanatory variables needed to
interpret outcome habitat variables.
In the next section, the rationale for evaluating
the candidate habitat variables as aquatic
habitat indicators is presented. The emphasis of
this discussion will be on the last two sorting
criteria, quantifiable biological effect and data
quality, since these two criteria generally
determine whether it is technically feasible to
specify numeric criteria.
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Table 6: Habitat components, pathways of effects, and potential habitat variables.
Habitat Component
1. Flow Regime
2. Habitat Space &
Channel Structure
3. Substrate Quality
4. Streambank &
Riparian Condition
5. Water Column
Chemistry
6. Habitat Access
7. Watershed
Condition &
Connectivity
Pathway Elements
• Peak flow
• Low flow
• Rapid fluctuations
• Increase in drainage
networks
• Off-channel habitat
• Flow modification
• Surface erosion
• Mass wasting
• Streambank erosion
• Pool filling
• Streambank
disturbance
• Channel
modification
• LWD recruitment
• Vegetative rooting/
bank stability
• Shading
• Nutrient modification
• Various pathways
associated with
nonpoint source
pollution activities.
• Physical Barriers
• Road density
• Disturbance history
• Riparian reserves
• Floodplain
connectivity
Habitat Variables
• velocity, depth,
wetted perimeter,
useable habitat
space.
• Pool frequency
• Residual pool depth
• Pool/riffle ratio
• W:D ratio
• LWD frequency
• Area of suitable
spawning & rearing
habitat
• Percent surface fines
• Fines at depth
• Embeddedness
• Substrate composition
• Bank Stability
• Undercut banks
• Overhanging vegetation
• Greenline vegetation
• Canopy cover
• Temperature
• Dissolved oxygen
• Turbidity & suspended
sediment
• Nutrients
• Toxics
Associated
Explanatory Variables
Discharge
Geomorphology
Stream & valley types
Reach characteristics
• gradient
• bankfull width
• channel
confinement
• sinuosity
• Rock type & soils
• Physiography
• Stream type
• Rock type & soils
• Stream type
• Riparian community
composition
Soils & geology
Geochemistry
Landscape patterns
Discharge
• Ecoregion
• Land use
• Soils & geology
• Hydrology
• Mass wasting &
erosion potential
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Sorting Potential Aquatic Habitat
Indicators
The Habitat Components listed in Table 6 are
relevant to aquatic biota and salmonid fishes,
have been related in some manner to
management effects, and therefore, would be
useful to consider as narrative criteria in state
water quality standards.
The next step is to identify which habitat
variables are likely candidates as quantitative
indicators. The potential habitat variables need
to pass the final litmus tests of applicability
within landscapes, whether the biological effect
has been quantified, and lastly, whether the
habitat variable can be measured with
acceptable data quality.
A best-professional-judgement approach is used
to evaluate potential variables. This step is
highly subjective, since other evaluators using a
similar logic path may arrive at different
conclusions. Also, there is the continually
evolving state of science. Better monitoring
tools or evidence of improved data quality over
current methods can readily change the results
of this evaluation. At a minimum, evaluations of
habitat indicators should consider the suggested
criteria and document their assumptions and
logic processes.
Flow Regime
Alteration of flow regimes is considered a
significant factor in the decline of fish
populations in the Northwest. Changes in
discharge regime have altered migration
patterns, changed sediment deposition and
scour, contributed to mortality of eggs and fry,
and reduced available habitat space.
Many studies have documented the increases in
annual water yield and peak discharge
(frequency, magnitude and duration) associated
with timber harvest (Burton 1997). Since most
of the studies were conducted in small,
experimental watersheds, the evidence for water
quantity change has been less conclusive in
larger watersheds. Timber harvest and road
building can increase peak flows of streams in
several ways: alteration of snowmelt patterns,
interception of subsurface flows by the road
network, and alteration of evapotranspiration
patterns. However, the long-term effect, good or
bad, of peak flows on channel stability and
aquatic habitat is an issue that is not yet
resolved (Troendle and Stednick 1999).
The effect of low flows on fish community habitat
has also been documented. How much
streamflow is required to protect aquatic
resources has been examined from the
perspective of instream fish habitat, (Orth 1987),
channel maintenance flows (Rosgen et al.
1986), and riparian zone influence and valley
maintenance flows (Hill et al. 1991). Over
appropriation for water withdrawals from surface
and groundwater sources have seriously
reduced fish habitat in many streams throughout
the Pacific Northwest, especially in the drier
interior basins of Washington, Oregon and
Idaho. The instream flow incremental
methodology has been used for some time to
evaluate the effects of decreasing streamflow on
usable quantities of physical habitat
space.(Bovee 1982). Micro-habitat preferences
have been described for a number of salmonid
species using velocity, depth, and substrate size
(Bjornn and Reiser 1991).
We can visualize that minimum stream flow can
be addressed in a narrative statement format,
since the effects of altered low flows on fishery
habitat are fairly well understood. The effects of
peak flows on channels and aquatic habitats are
less resolved, especially with respect to
predicting the magnitude of effect and channel
response or making a narrative or numeric
criteria untenable. However, the outcome of
hydrologic watershed alteration would be
manifested as changes to the habitat space and
channel structure of the stream. For this reason,
potentially useful habitat variables that are
responsive to flow alteration are those that
measure channel morphology as described in
the section below.
Habitat Space and Channel Structure
For our purposes, we have divided the channel
components into two parts - channel dimension
and channel structure variables.
Channel Dimension
Habitat space can be visualized as the
interaction of three dimensions of the channel -
length, width, and depth. Length and width
measures potential habitat space directly
proportional to the size of the watershed and
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magnitude of the flow regime. Channel depth
provides the third dimension important to aquatic
habitat. The volume of water (flow expressed at
"Q") moving through a channel at any given time
(velocity "V" expressed at cubic feet per second
or cfs) is affected by these channel dimensions
(width and depth) as Q = W x D x V. Channel
gradient affects velocity. As the channel
narrows (width decreases) at a given location,
the velocity and depth increase. As the channel
widens, velocity falls and depth decreases. As
flow increases, velocities at the channel margin
also increase shear stress which controls the
sediment transport capacity of the stream at
high flow events.
Stream channel bankfull width is a function of
streamflow occurrence and magnitude, size and
type of transported sediment, and bed and bank
materials of the channel (Rosgen 1996).
Bankfull channel widths generally increase
downstream as the square root of discharge
(Leopold et al. 1964) and, therefore, serve as an
element of stream classification systems.
Channel width can be modified by human
disturbance - diking and channelization,
changes in riparian vegetation, and changes in
flow and sediment regime due to watershed
alterations. The bankfull cross-sectional shape
corresponds to changes in the magnitude and
frequency of bankfull discharge. The bankfull
dimensions can be altered by management
activities in the watershed such as water
diversion, clear cutting, vegetative conversion,
and over-grazing. Channels can become over-
widened, which reduces habitat (depth, velocity)
especially during summer low flow periods.
Over-grazing from livestock in the riparian zone
reduces vegetation and damages stream banks,
which leads to an altered channel form
characterized as wider and shallower than
normal (Elmore and Beschta 1987, Platts 1991).
Stream channel response to cattle exclosures
have been variable, but in many studies a
reduction in bankfull dimensions (indicating a
recovery of width/depth ratio) has been
observed a decade or more after cattle were
excluded (Magilligan and McDowell 1997).
Width:Depth ratio integrates cross-sectional
shape into one variable. In Rosgen stream
classification (Rosgen 1996), W:D ratios are
associated with stream types based on empirical
measures of a large number of streams. The
stream types are categorized by fairly broad
break points in W:D ratios (less than or greater
than 12 and greater than 40). These broad
categories demonstrate the high natural
variability even within a stream type, which
suggests the difficulty in attempting to establish
a regional numerical value for W:D ratios even if
stratified by stream type.
The other concern with stream width and W:D
ratios is the methodology used to measure these
variables. At a stream inventory level, bankfull
width is estimated by using field characteristics
such as sediment surfaces and vegetative
breaks to identify the elevation of the active
floodplain surface. The definitions of bankfull
width are vague and the actual selection of
bankfull width is subjective (Johnson and Heil
1996), thereby leading to highly variable
interpretation of bankfull level. Some field
methods measure only wetted width, which tells
very little about the channel characteristics of
the measured stream. When bankfull is
measured at monumented cross sections,
subjectivity is decreased and the precision of the
method improves substantially (Harrelson et al.
1994). Nelson et al. (1992) rated precision and
accuracy of the W:D measurement as good with
an average confidence interval of 7% of the
mean.
Given the variability in natural channel
dimensions, the variability in channel type
response (i.e., some channel types increase in
widths, while other types are resistant to bank
erosion), and the subjective nature of identifying
bankfull, we would not suggest the use of
bankfull width or W:D ratio as a numeric habitat
indicator alone. The bankfull dimension is useful
as one measure of a suite of variables to
characterize channel dimensions, but this should
be used at the site-specific or reach-specific
level and be measured at monumented cross-
sections to assure precision and repeatability
(see Harrelson et. al. 1994, Olson-Rutz and
Marlow 1992, for methods and interpretation).
In comparison, stream depth, measured as
residual pool depth, is a less ambiguous
measure of habitat space and structure that may
be useful as a habitat indicator as discussed in
the next section.
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Pools and Large Woody Debris
A high frequency of quality pools is required to
support salmonid populations in streams and
rivers. Adult fish utilize pools as resting areas
during migration and for hiding cover during
spawning, and pools are important habitats for
juvenile rearing. The combination of depth and
cover primarily determine the quality of the
pools. Cover elements are generally evaluated
using subjective ratings of overhanging bank;
overhanging vegetation; and the presence of
wood, roots, and large substrate. Deep pools
also provide better hiding cover.
Salmonid species in forested ecosystems have
evolved in streams where large woody debris
plays a major role in forming habitats, providing
cover, influencing sediment processes, stream
energy, and nutrient cycling.
Human disturbances strongly influence pool
indicators. Reduction in pool frequency and
depth occurs through cumulative activities in the
watershed by altering channel morphology,
changing discharge and sediment equilibrium,
modifying the active channel, and decreasing or
eliminating riparian vegetation (Section 3, Table
1). Large woody debris size, frequency, and
loading potential have been altered by historic
activities that actively removed wood from
channels or decreased input from riparian forest
stands. Residual pool depth integrates the
effect of several management alterations - pool
filling from excessive sedimentation, decrease in
channel obstructions, and changes in channel
dimensions and bed stability.
The effects of human disturbance, however, on
these channel features may not be detected due
to the lag-time in effects and the insensitivity of
the monitoring methods In general, pool
frequency, pool depth, and LWD frequency are
not sensitive to disturbance over the short-term
(with the exception of direct channel
modifications). There is a long lag-time between
activities on the landscape and the response in
the channel, both in response to detrimental
effects of management and in response to
restoration actions. Stream channels, where
large wood was removed and where adjacent
riparian forests have been harvested, will require
decades (or centuries) to return to natural
loading rates.
Several studies have evaluated the value of
using habitat unit classification (e.g. pool vs.
riffles) to monitor trends over time. Poole et al.
(1997) found that the subjectivity of habitat unit
classification seriously compromised the
repeatability and precision of the method. Pools
and riffles are not separated by distinct
boundaries; this lack of clearly defined
boundaries contributes to observer bias.
Aggregating sub-categories of habitat units into
fewer broader categories (such as with the
REMAP variable, Percent Slow in Section 7)
improves precision; however, it reduces the
sensitivity of the method to land use impacts,
because even larger shifts in channel
morphology are needed to observe a response
in the data. Again, linking residual pool depth
measurements with thalweg profiles and bed
particle size characterization may help resolve
some of these problems, but the interpretation of
the cause-effect relationship can remain elusive
unless tied to a whole watershed assessment of
sediment input sources (Madej and Ozaki 1996)
Visual assignment of habitat unit classification
alone lacks the sensitivity and precision required
to document incremental changes due to
management effects in stream channels at the
reach scale. Habitat units may not be sensitive
enough to land use effects at this scale and
multiple crew observer error introduces a high
source of variability (Poole et al. 1997).
Transforming the data into pool-to-riffle ratios
further reduces the sensitivity of the data.
Expressing the data in habitat units per length
(pools per mile) retains the original
measurement scale of the data.
In contrast, analyses conducted at the regional
scale have been successful in detecting land-
use patterns, because sample sizes were
sufficient to overcome the large variance
associated with habitat unit classification
(Mclntosh et al. 1995, Ralph et al. 1994, Poole
etal. 1997).
Residual pool depth is a quantitative measure
less subject to observer error than other
measures of stream dimension and is
independent of streamflow at time of
measurement (Lisle 1987). The residual pool
depth is measured as the difference between
the maximum pool depth and the pool crest
outlet depth. Although pool depth varies along
the stream profile, the average residual pool
depth for a stream channel type is sensitive to
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land management alterations (Ralph et al. 1994,
Mclntosh et al. 1995, Woodsmith and Buffington
1995).
LWD frequency is influenced by the
methodology - the size definition of LWD, the
position of the wood influencing the channel,
and the procedure for counting pieces in a log
jams. However, when LWD is operationally
defined, it can be measured with some
precision. Ralph et al. (1994) concluded that
LWD volume and position are easily measured
and are objective and repeatable. Additionally,
they appear sensitive to even moderate land use
practices. Stratifying the data by channel
gradient and basin area reduced the variation
imposed by larger scale factors.
LWD frequency can be expected to be highly
variable in natural stream systems, since
recruitment occurs through periodic disturbance
such as high winds, floods, and mass wasting
events. Regardless, these random events
generally result in higher LWD loading and
higher LWD volumes in natural systems over the
long term in comparison to altered streams.
Pool frequency, residual pool depth, and large
woody debris are three habitat structure
variables relevant to aquatic biota and can be
used to discern management effects over larger
geographical scales. These variables measure
cumulative effects of management and so are
not expected to be responsive to changes in
management over shorter time frames.
Observer bias hampers the precision and
repeatability of pool frequency, however. The
subjective nature of pool frequency measures
could be more objective if thalweg profiles were
combined with ocular habitat typing.
Pool frequency, residual pool depth, and large
woody debris are variables that could logically
be specified as numeric indicators, if they are
stratified by landscape and channel types,
specifically basin size and gradient.
Reid and Furnis (1998) summarize some
thoughts counter to the rationale described
above. It is instructive to be aware of these
concerns about using physical channel features.
These issues include the channel response
time, interpretation of cause, addressing the
ecosystem health objective, background
variability, and cost effectiveness. Measures of
channel form (e.g., pool frequency and width-
depth ratio) exhibit a lengthy lag time in
response to disturbance, while channel form
responds slowly to management-related
changes in driving variables such as changes in
water, large wood, and sediment. Interpretation
of the cause is not feasible, since channels
respond in the same way to multiple stressors.
Channels can widen due to an increase in
sediment load, alteration of riparian vegetation,
an increase in runoff, and for other reasons.
Application of single set of variables over broad
areas is likely to be ineffective, because
ecosystem health is being impaired by vastly
different suite of influences in different
geographic areas. Lastly, a healthy lotic
ecosystem requires that different parts of the
channel system exhibit very different in-channel
conditions over time; this variation is an
essential characteristic of naturally functioning
aquatic ecosystems. For these reasons, Reid
and Furnis (1998) suggest that monitoring
strategies should focus on upslope and riparian
condition indicators rather than on instream
channel and habitat measures.
Substrate Quality
Sediment is one the most pervasive pollutants
identified as an issue in Pacific Northwest
streams, yet little consensus exists among
scientists on how to quantify the effects of
sedimentation on aquatic ecosystems.
Substrate material is also an essential
component of salmonid habitats, including
spawning substrate, cover for juveniles, and the
media that supports the primary and secondary
production of the bacteria, algae and insects that
support aquatic communities. Again, different
land uses seem to have somewhat predictable
outcomes on the input and routing of sediment
into streams, which varies depending upon the
terrain characteristics of the landscape on which
they occur. Sediment in transport is
operationally divided into suspended sediment
and bedload sediment. Suspended sediment
consists of the finer grained particles, namely silt
and clay size particles. Sand sized and greater
material moved along the stream bottom
comprise bedload. Suspended sediment is a
water column pollutant that has traditionally
been addressed in state water quality standards
as a narrative criteria or as a turbidity standard.
Sediment deposited in critical aquatic habitats,
such as salmonid spawning and rearing areas,
is treated here as an issue of fine substrate
quality (< 0. 85 mm, particularly because it can
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affect intergravel dissolved oxygen concen-
trations. Another size fraction < 6.35 mm has
been of concern because of its tendency to
infiltrate into gravel nests and prevent oxygen
uptake and alevin emergence (Bjornn and
Reiser 1991).
Establishing quantitative criteria for deposited
fine sediment remains an illusive target for
several reasons. No general agreement exists
in the scientific literature on a numerical target
although several numerical values have been
suggested and are in common use as default
criteria. Secondly, practical and technical
limitations prevent direct comparability between
field measurements and the numerical value
obtained in laboratory studies. A large body of
literature illustrates that fine sediments are
detrimental to salmonid populations through
alteration of the habitat and direct effects on egg
survival and developing embryos (Havis et al
1993, Bjornn and Reiser 1991). However,
questions about the adequacy of field methods
and laboratory studies for setting numerical
criteria remain. Laboratory studies that
established thresholds for fine sediment do not
adequately reflect conditions faced by embryos
or emerging alevins (Everest et al. 1987,
Chapman 1988) due to the difficulty of
replicating conditions found in the egg pocket of
natural redds. Field studies of redds confirm the
concern about adequately representing the
sediment composition actually encountered by
eggs and young fry in these studies (Thurow
and King 1991).
In a review of this issue, Spence et al. (1996)
identified two recommendations for setting
specific sediment targets for spawning habitat in
the literature. Rhodes et al. (1994) concluded
that survival to emergence for Chinook salmon in
the Snake River Basin is probably substantially
reduced when fine sediment concentrations in
spawning gravel exceed 20%. Peterson et al.
(1992) proposed a target of 11% fine sediments
in spawning gravels for low-to-moderate
gradient streams in Washington with the caveat
that this criteria not be applied across geologic
boundaries and secondly that exceeding the
criteria should initiate a review of potential
causes. Spence et al. (1996) made no specific
recommendations for targets in rearing habitats
because of a lack of available information in the
literature. An important precaution implied in
these papers is that locally developed criteria
should not be generalized for use outside of the
area in which they were intended.
A related issue that is a cause for caution in
using values for fine sediment is data
comparability between methods. A number of
methods with various levels of monitoring
intensity report values as "percent fines".
Stream inventory procedures use a diversity of
methods such as visual observation, sampling
grids, and Wolman pebble counts to estimate
percent fines. Wolman pebble counts are
biased against detecting substrate particles <
0.85 mm in diameter (Wolman 1954). More
quantitative methods use systematic sampling of
surface fines, cobble embeddedness, or core
sampling (fines at depth) to measure percent
fines. Various levels of precision, accuracy, and
repeatability are associated with each method
and level of sampling intensity. Yet, all of these
methods only indirectly measure the problem
factors that would affect egg-to-emergent
survival of salmon embryos. Workers in
northern California (Randy Klein pers. comm.)
are measuring gravel permeability near known
redd sites and calibrating these sequential
readings to egg-to-emergent survival. These
field trials are also linking measurements of
turbidity to storm events. More such field tests
are needed to develop and refine reliable
methods in order to capture this important
sediment parameter. Resolution of these issues
requires an interagency effort to develop
standardized methods and agreement on their
application and interpretation. Recent work by
L. Reid in northern California (personal
communication) to evaluate linkages between
turbidity and fish survival shows promise in that
it suggests a detectable correlation between
land disturbance (road building and logging,
traffic volumes on gravel roads, etc.) and
elevated turbidity levels as well as fish survival.
At the very least, these methods might prove a
useful tool to document the effectiveness of fine
sediment abatement techniques applied within a
basin.
Given the uncertainty in the measurement of fine
sediment and in quantitatively describing its
effect on salmonids and other aquatic
organisms, we do not believe it is appropriate to
specify a numeric habitat indicator. Fine
sediment has a demonstrated effect on aquatic
resources and should be included in state
standards as a narrative criteria, as is already
done in many cases. It may be feasible to fine
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tune the narrative criteria to provide a greater
degree of specificity than is currently described.
State, federal, and tribal agencies should pool
their efforts to develop appropriate measures.
Another aspect of sediment involves the input of
large volumes of both coarse and fine sediment
associated with bank failures, bank erosion, and
the hill-slope process of mass wasting (mass
slope failures, shallow rapid landslides, soil
creep, etc.). When the rate, magnitude, and
pattern of these processes are disrupted through
land management (timber harvest, road building,
mining, residential construction), the volume of
sediment entering a stream channel can quickly
overwhelm its capacity to convey the material.
Large increases in sediment input volumes have
been shown to alter substantially habitat
features (pools and riffles) and can create highly
unstable spawning areas subject to gravel scour
and fill events when seasonal peak flows
approach bankfull discharge. When coincident
with spawning sites selected by adult fish, these
events can reduce the overall success of
spawning, which in turn can reduce the overall
recruitment for an entire year's population
(Frissell, in preparation 1999, Orsborn and
Ralph 1994). In some areas, redd scour and fill
related mortality can be a significant factor
limiting overall stock recovery, and yet, this is
largely unaccounted for in current assessments.
Timely management solutions to these problems
are limited.
At a much larger scale, EPA is currently
applying an assessment technique (Fitzgerald et
al. 1998) to address watershed level sediment
input sources. This method is the basis for
several ongoing TMDL's that attempt to quantify
both background and management induced
sediment sources and volumes. A sediment
reduction target is then established that focuses
management actions towards preventing further
inputs and reducing chronic sources (such as
road surface sources).
Streambank and Riparian Condition
Bank Stability
The stability of the streambank and associated
riparian vegetation are important characteristics
that contribute to aquatic habitats. These factors
are more important in some areas than others
and are directly related to land use, such as
cattle trampling of range-land stream banks
(Bauer and Burton 1993). Streambanks with a
protective vegetative root structure develop
undercut banks which are important hiding areas
for juvenile and adult fish. Woody and
herbaceous riparian species of plants have deep
fibrous roots that resist erosion and hold the
bank together. The plant mass above ground
resists the force of water and provides a
protective layer that prevents lateral bank
erosion. Overhanging vegetation provides
cover, shade, organic material for stream
energy, and vegetative structure for terrestrial
and emerging aquatic insects.
Naturally stable banks result from the bank
material (rock or clay content) and/or the riparian
vegetative community associated with the
streambank. Natural low gradient river systems
exhibit bank erosion at low rates in dynamic
equilibrium such that banks are eroded in one
location and rebuilt in another to retain the
overall cross-sectional dimensions over the long
term. This is especially evident where one sees
lateral movement of a river meander or bend.
The objectives for stable banks are to prevent
streambank erosion processes from delivering
fine sediments to critical spawning and rearing
habitats, to create conditions favorable to the
development of undercut banks, to protect deep-
rooted vegetation in order to add to stability and
provide shade, and to maintain channel
dimensions favorable to fish habitat
development (McCullough 1999). Banks can be
destabilized by livestock grazing through
vegetative removal and bank trampling which
results in bank calving, by road building along
stream channels, and by logging riparian
vegetation that eliminates the root strength and
physically disrupts the soil surface.
Bank stability is intended to portray the absence
of processes that result in bank erosion. The
majority of bank stability methods involve a
subjective rating of some combination of
vegetative cover, bank material, and evidence of
slumping or sloughing (Platts et al. 1987, Bauer
& Burton 1993, Shuet-Hames et al. 1994).
McCullough (1999) describes a modification of
earlier systems that is more objective because
measured data or categorical observations are
recorded in the field for each factor. Bank
stability is assessed by measuring bank angle
and height, bank material composition, and bank
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vegetative cover for both the upper and lower
bank. The measured bank angle, percentage of
stream bank covered by stable rock material,
and percentage of vegetative cover are
converted to a value based on a scoring system.
The system reduces some of the inherent
subjectivity associated with earlier systems by
measuring and recording the bank angle and by
closely defining categories for the other factors.
This method (McCullough 1999) should improve
accuracy and precision over previous methods,
but, has not been tested to date in other
systems and by other observers. The field
observations are converted to interpretive
information by using a scoring system. This
method may prove to be advantageous in
reducing observer error; however, the method
needs to be tested in other stream systems, in
response to other kinds of stressors, and
evaluated for precision and repeatability before
its general applicability to water quality programs
is demonstrated.
CRITFC proposed a standard of 90% bank
stability for managed watersheds (CRITFC
1995). The 90% bank stability criterion is
considered an anticipated average minimum
performance level possible under various
geomorphic conditions which will provide
favorable biological conditions over time
(McCullough 1999). In a review of the literature,
Spence et al. (1996) noted that there is no or
little quantitative information to support regional
target values for bank stability. Given the great
diversity in stream types and the associated
differences in inherent bank stability, it may be
more appropriate to use bank stability as one of
the monitoring characteristics that should be
evaluated as part of an overall habitat quality
survey.
Given the subjective nature of bank stability
measurement and the uncertainty about setting
appropriate targets, we suggest that bank
stability be evaluated, if at all, in relation to
specific stream types within a landscape setting.
Intensive channel survey methods that utilize
monumented cross-sections, as described in
Harrelson et al. (1994), may provide the best
means of quantitatively evaluating bank change
over the long term. Cross-section methods
evaluate a single point on the stream bank such
that multiple cross-sections are needed to
survey even a small portion of the stream length.
Hence, field rating methods have
understandably been the method of choice for
evaluating management practices.
Water Column Chemistry, Habitat
Access & Watershed Condition
These habitat components are recognized as
important factors in the aquatic ecosystem which
are necessary to support beneficial uses. The
habitat elements are listed in Table 6 to provide
consistency with the Services matrix documents.
Habitat Access, Watershed Condition, and
Connectivity components are topics that may be
appropriate as narrative statements in water
quality standards, but these topics are outside
the scope of this paper.
Water quality chemistry has been the primary
focus of state and federal water quality
programs with a long history of scientific inquiry
and discussion regarding appropriate criteria.
Some chemical parameters are more reflective
of specific land use effects than others. The
states and EPA engage in a periodic review, the
Triennial Review, to evaluate the need to revise
the water quality criteria.
One issue that crosses over between "water
chemistry" measures and habitat quality is the
effect of suspended sediment on habitat quality.
State agencies have adopted various narrative
criteria and, in some cases, numeric criteria for
turbidity, a surrogate measure of suspended
sediment effects. With the increase in TMDL
listings, the interest in identifying targets for
suspended sediment has increased. A logical
method to address these targets are dose-
response models, which evaluate the effects of
target fish communities to suspended sediment.
Dose-response models have been developed to
evaluate the biological response to suspended
sediment concentration and duration using
meta-analysis of a large number of studies
(Newcombe 1994, and Newcombe and Jensen
1996). The effect of suspended sediment
pollution is integrated into a Scale of Severity
(SEV) of ill effects. The scale of effects includes
behavioral effects (e.g. avoidance), sublethal
effects such as feeding rates and minor
physiological stress, and lethal and sublethal
effects.
The SEV rating incorporates the effect of habitat
damage. Habitat damage is characterized in
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biological and physical terms. Biological signals
of habitat damage include underutilization of
stream habitat, abandonment of traditional
spawning habitat, as well as displacement and
avoidance of habitat. Physical changes included
in the SEV scores are degradation of spawning
habitat, damage to habitat, and loss of habitat
(Newcombe and Jensen 1996).
Six SEV empirical equations were developed
from the published data to model the fish
response to suspended sediment dose, the
product of sediment concentration and duration
of exposure. The models address various life
stages and include juvenile and adult salmonids,
eggs and larvae of salmonids, as well as non-
salmonids. These models provide the ability to
target a life stage in response to a specific
suspended sediment pollution event, and they
appear to provide a very useful method of
integrating the concentration and duration into
an analysis tool. The method provides a means
of developing TMDL targets for suspended
sediment concentrations for specific water
bodies and sensitive life stages. The article by
Newcombe and Jensen (1996) summarizes the
previous efforts and refines the dose-response
model.
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ASSESSMENT AND MONITORING
The Silver Bullet: "While the motivation to find
tools that are relatively simple to implement, that
can be used directly and consistently by field
personnel, and are sensitive enough to provide
a direct measure of impact is understandable,
there is no a priori reason to expect that any
monitoring protocol can necessarily possess all
of these attributes. In other words we can not
assume that a silver bullet exists to solve our
problems." Kondolf(1997).
Introduction
The critical question for evaluating habitat that
needs to be addressed is what is our ability to
detect ecologically significant change with a
given set of monitoring methods? Although no
silver bullet exists, there are established
systematic approaches to environmental
monitoring applicable to the task of habitat
measurement (MacDonald 1994, MacDonald et.
al. 1991, USEPA 1997). This systematic
approach involves the development of
monitoring design, the selection of appropriate
variables and methods, quality assurance (QA)
and quality control (QC), and data interpretation.
These considerations are important because
water quality programs require a high degree of
confidence in the resulting conclusions. The
outcomes of evaluating pollution control
measures and establishing targets for TMDL's,
for example, have significant ecological,
economic, and social implications.
This section focuses specifically on the issues
related to data quality. The other elements of
monitoring design have been addressed in more
detail in other documents and statistical texts
(Ward et al. 1990, Gilbert 1987, Sokal and Rohlf
1987, Helsel and Hirsch 1995, Snedecor and
Cochran 1980). Habitat indicators are
measured using a variety of methods for varying
purposes. There are no accepted standard
methods for habitat protocols comparable to the
standard methods for water quality parameters.
Habitat variables are monitored with a mix of
measured and observed types of data leading to
difficulties in data comparability. It is important
to understand and resolve these data quality
issues, if habitat indicators are to be used to
measure progress in meeting water quality
objectives.
Systematic procedures have been established
for controlling data quality associated with water
quality monitoring. Since water quality
professionals should be familiar with these
concepts, we address data quality issues for
habitat variables by comparison and contrast to
these procedures. Standard methods address
the analytical laboratory procedures,
standardized procedures for collection and
handling of water quality samples, and
established QA/QC procedures. This
comparison focuses on the estimation of
precision and accuracy, since this issue is
fundamental to detecting ecologically significant
change.
Monitoring Design
For water quality programs, we earlier identified
two primary sets of objectives for habitat
variables.
1) Assess the aquatic environment's status in
terms of supporting the "beneficial uses", i.e.
fish communities.
2) Assess the effectiveness of BMP's or
nonpoint source pollution controls.
These purposes require different monitoring
designs, a different mix of indicators (input
variables, watershed characteristics, outcome
variables), and a different degree of
quantification. Monitoring design issues for
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water quality and habitat studies have been
addressed in MacDonald et al. (1991);
Conquest, Ralph, and Naiman (1994); and
Hubert (1997). In a recent article entitled
"Statistical design and analysis considerations
for monitoring and assessment', Conquest and
Ralph (1998) present guidance on how to
develop statistically reliable monitoring designs
based on assessment objectives, and from
there, how to proceed to proper data acquisition,
information management and data analysis.
Some general characteristics of good monitoring
design described in these documents include:
1) clearly articulated goals and objectives,
2) selection of variables and protocols based
on the needs defined by those objectives,
3) standard monitoring procedures,
4) field methods training program and
integrated quality control,
5) QA/QC procedures as described above,
6) statistical design, and
7) data management.
Nonpoint source monitoring has primarily
focused on BMP evaluation in order to reduce
pollutant discharge, though somewhat in
isolation from the watershed processes that
control its expression. Much of the guidance on
nonpoint source monitoring has, therefore,
focused on this objective - either in examining
the utility of variables in implementation and
effectiveness monitoring or on the statistical
design of these studies. The objective of
evaluating habitat status in supporting beneficial
uses has been addressed to a lesser degree.
Therefore, we address the monitoring design of
BMP effectiveness studies first and consider
designs for habitat status as a subset or special
case of the first type of studies.
Effectiveness of BMP's - Objectives
Three types of monitoring are commonly
described as relating to the monitoring success
of nonpoint source controls or restoration
activities: implementation monitoring,
effectiveness monitoring, and validation
monitoring (MacDonald et al. 1991, Kershner
1997). Validation monitoring is a research level
of monitoring that addresses cause and effect
relationships of watershed processes or fish
population response to habitat manipulation.
These types of studies require long-term
commitment of resources and manipulation of
watersheds over long term periods, such as the
Rural Clean Water Program experimental
watersheds (USEPA 1992).
Implementation Monitoring asks did managers
implement BMP's or restoration activities in
accordance to guidelines and regulations
designed to reduce unintended environmental
impacts? Implementation monitoring during the
activity can lead to mid-course corrections.
Implementation monitoring at the end of the
project provides necessary feedback to
determine whether guidelines and regulations
were met. Implementation monitoring can be as
simple as counting the number of structures
installed and evaluating if the structures were
installed as designed. The actual monitoring
activity can be limited to visual inspections, field
notes, and photographs.
Effectiveness Monitoring asks were BMP's or
restoration activities effective in attaining the
desired condition and in meeting the restoration
objectives? This kind of monitoring is more
complex than implementation monitoring,
because we need to determine if the desired
outcome of the BMP's were attained. The
answer to this question cannot be ascertained
until the interaction of management practices
and natural disturbance regimes can be
considered (e.g. after several cycles of high
stream flows). It has been common for stream
restoration projects, such as artificial placement
of Large Woody Debris, to be deemed effective
under low flow cycles then to unravel during
years of higher flows.
Effectiveness of BMP's - Study Design
Statistical design for BMP effectiveness studies
are based on experimental units, treated versus
non-treated stream reaches. In an idealized
simple experiment, the experimental units would
be randomly selected and assigned some
treatment, while another set would be left
untreated as controls. These experimental units
are considered representative samples of the
larger population about which inference will be
made. Repeated measurements generate the
data used to describe the sampled populations.
Most water quality studies do not readily fit this
idealized statistical design. The experimental
units cannot be randomly assigned, since the
treatments occur across large, rarely uniform,
watershed areas. Many extraneous factors
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affect the experimental units that often cannot
be accounted for in the data gathering or
statistical treatment. The experiment
necessarily occurs over a long time period as
BMP's are implemented, and therefore, the
seasonal and annual variations also are
dominant factors affecting the results.
Nonpoint source studies have generally targeted
water quality variables rather than habitat
variables in assessing BMP effectiveness.
Three monitoring designs common to water
quality studies are paired watershed,
upstream/downstream, and before/after
(Grabow et al. 1999). A paired watershed
design (Clausen and Spooner 1993) comprises
two watersheds (control and treatment) of
similar location, land use, and two time periods
of study (calibration and treatment). The goal is
to establish a relationship between the control
and treatment watersheds to evaluate the effect
of changed land management in one of the
watersheds. An upstream/downstream
(before/after) design (Spooner et al. 1985) also
requires calibration and treatment periods;
however, unlike the paired watershed design,
only one watershed is monitored with sampling
stations positioned upstream and downstream of
the treatment area. With a before/after
monitoring design, water quality data from one
downstream station is collected for a period of
time before and after BMP implementation.
Habitat /Beneficial Use Status- Study
Design
Studies that address the objective of habitat
status will primarily take the form of comparison
between "managed" streams, those that are
influenced by human activities, to those stream
segments that are reference streams. Because
of the difficulty in obtaining data for comparable
reference streams, stream segments that
represent some gradient of "least disturbed" or
"proper functioning" have been used for
comparison in biological monitoring programs.
However, there are recognized difficulties in
using streams that have had some degree of
management as a reference condition (Hughes
1995). A primary consideration in monitoring
design is to compare similar stream reaches as
stratified by landscape and stream network
characteristics as described in Section 6.
Data Quality Objectives
Data quality objectives are integrated into EPA
water quality monitoring programs as described
in quality assurance documents (USEPA 1994a
and 1994b). The abbreviated description of
QA/QC methods is taken from the EPA
publication, Monitoring Guidance for
Determining the Effectiveness of Nonpoint
Source Controls (USEPA 1997). The document
specifically addresses water quality monitoring
but does provide data quality concepts
transferable to habitat monitoring.
What is quality assurance and quality
control?
Quality Assurance is an integrated system of
activities used to verify that the quality control
system is operating within acceptable limits.
Quality Control is a system of technical
procedures and activities implemented to
produce measurements of requisite quality. QC
procedures include the collection and analysis of
replicate samples and the evaluation of the
degree to which the samples represent the true
environmental condition. QA procedures are
more operational in nature and address the
selection of qualified personnel, training,
development of data quality objectives, and
maintenance of complete records. For water
quality monitoring, specification of QA/QC
procedures and the development of Quality
Assurance Project Plan are required of all EPA
funded projects.
The EPA documents (USEPA 1994b,
USEPA1997b) describe an iterative planning
procedure, the Data Quality Objectives Planning
Process, to develop a monitoring program. The
objective of this process is to determine the
qualitative and quantitative data needs for the
project. The process, intended to improve the
effectiveness and defensibility of data, is
documented in a Quality Assurance Project
Plan. The Project Plan identifies the resulting
monitoring design and identifies data quality
objectives for the project. The data quality is
expressed in terms of precision, accuracy,
comparability, representativeness, and
completeness.
The difference between precision and accuracy
is illustrated in Figure 7. Accuracy can be
thought of as being on target - that is, the
samples are clustered around the bull's eye.
Precision is represented by the closely placed
marks on the target; the individual samples
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repeatedly come up with a similar result, even if
it is not the correct one. These are simplistic
illustrations, as other complex outcomes are
possible; yet, they should convey the basic
conceptual differences between precision and
accuracy.
High accuracy, low precision
High precision, low accuracy
High accuracy and high precision
Figure 7. Illustration of precision and accuracy.
Precision is a measure of the mutual
agreement among individual measurements of
the same property. Precision is expressed as
the coefficient of variation (CV), also referred to
as the percent relative standard deviation
(USEPA1997).
CV = (s/x)*100.
where s = sample standard deviation
x = the arithmetic mean
CV= Coefficient of Variation
Precision measures the reproducibility of the
measurement method; it answers the question:
how close is the result when the same quantity
is measured repeatedly? For water quality
studies, precision is estimated by evaluating a
series of replicate samples. The replicates,
usually duplicate samples, are taken from a
stream using the same exact field procedure
and submitted to the laboratory for analysis.
When the results from the duplicate samples are
similar in value, the Coefficient of Variation is
low, for example in the 5 to 15 percent range.
Various potential sources of error influence the
precision of water quality sampling, e.g.failure to
mix the samples adequately, random
contamination of the sample container,
analytical error, etc.
For habitat variables, measuring precision is not
as straightforward as with water quality samples.
The replicate sample is accomplished by
repetition of the sampling method by field crews
- either the same field crew at different times or
by a different crew at the same location. As with
water quality samples, the estimation of
precision can be influenced by a number of
factors which contribute to sampling error, e.g.
differences between observers or slight
differences in selection of the monitoring
location, like the placement of a transect across
the channel. It is also feasible for the actual
value of the variable to change in a short time
between repeated visits to the site.
The precision of habitat variables has been
evaluated in other ways than the Coefficient of
Variation. The mean Percent Agreement (PA)
among observers has been used as an estimate
of precision when measuring habitat types -
that is, pool vs. riffles. Mean PA is defined as
the consensus score divided by the number of
observers (Roper and Scarnecchia 1995). A
modified method uses an expression called the
Adjusted Percent Agreement (APA) to estimate
precision (Poole et al. 1997). The APA
characterizes how much better (or worse) than
randomness the observed agreement is as a
percentage of the distance between
randomness and complete agreement. Refer to
the paper by Poole et al (1997) for details on
how to calculate this expression.
Accuracy is the degree of agreement of a
measurement with an accepted reference or true
value. To estimate accuracy in water quality
sampling a known concentration, a "spike
sample", is added to the stream or lake sample
in the field. The field procedure of spiking is
used to gain an understanding of whether the
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ambient water chemistry has an influence on
recovery of the known spike concentration.
Percent recovery is calculated as the difference
between the known concentration and the result
of the spiked sample. The Average Percent
Recovery from completing a series of such
spiked samples is calculated as an expression
of accuracy.
Percent Recovery = A-B/C *100
Where: A = spiked sample result
B = sample result
C = spike added
For habitat variables, the actual or true value
can never be known with complete confidence,
since we do not have the same easy ability to
create the known value as with water quality
samples. Accuracy of habitat variables can only
be readily determined by comparing one method
of measure, considered more accurate, to the
test protocol being evaluated. For example, one
may compare the value for gradient obtained
from a clinometer (a less accurate method) to
gradient measured with a Total Station
Engineering Level that more accurately
measures distance and change in elevation.
Both methods are estimates of the "true value"
and are subject to sources of error, but the Total
Station value can be considered the standard
against which the other field method is
evaluated.
Estimating the accuracy of field measurements
is technically difficult or infeasible. However,
accuracy as a data quality objective may not be
as critical as precision and repeatability to the
monitoring purpose. This statement may seem
counterintuitive, since we are always interested
in high data quality - that is, data with known
precision and accuracy. However, consider that,
if the objective in habitat evaluations is to
compare one site to another (e.g. a study reach
to a reference reach), then repeatability and
comparability are of utmost importance. This
assumes that the method is accurate (or
inaccurate) in a consistent direction.
Comparison of habitat measures with known
precision will answer the question of whether the
study reach is different from the reference reach
even if the accuracy is unknown. Contrast this
situation to comparison of habitat measures to a
specified numeric target - a compliance
objective. In this situation, accuracy becomes
as critical as precision, since we are now
interested in knowing that we have measured
the study reach in a manner that provides direct
comparison to a target value - that is, how far is
the study reach value from the bull's eye or
criterion value.
The other data quality measures are more
qualitative but are, nonetheless, an important
consideration in monitoring procedures.
Comparability is the confidence with which one
data set can be compared to another.
Comparability is particularly a problem with
categorical habitat variables due to the variation
in methods, monitoring crews, and associated
training. Representiveness relates to the
degree to which the samples are typical of the
measured population. This condition depends
on the ability of the procedure to select samples
with a minimal bias from the target population.
Completeness is defined as the amount of valid
data obtained from a measurement system
compared to the amount that was expected.
Samples can fail to be collected, or their
information value can be compromised in
countless ways - failure to use Write-in-the-
Rain paper, a cassette tape dropped in a pool,
field personnel and notebooks that disappeared
in a hole in the ice, an automatic sampler lost in
a flood event, etc. (And they all have happened
to the authors).
Use of Physical Habitat Variables in
Monitoring
Habitat variables have a role in monitoring
design for both the water quality objectives
described above - habitat status in supporting
beneficial uses and effectiveness monitoring. In
addition to habitat variables, cause and effect
studies of nonpoint source activities need to
address the pathway elements (such as listed in
Table 5, Section 5). The studies can look at a
variety of physical factors related to soils,
vegetation, hydrology and the ways that
nonpoint sources ultimately alter the watershed
and channel processes. These studies and their
associated variables encompass a potentially
wide spectrum of the natural resource field -
hydrology, geology, soils, geomorphology,
riparian, and wetlands, etc. Published
monitoring guidelines have addressed
application to specific sources: forestry
(MacDonald et al. 1991, Dissmeyer 1994),
range/and grazing (Bauer and Burton 1993), and
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agriculture (USEPA 1992). The EPA monitoring
guidance document (USEPA 1997 in Appendix
A) lists fifty-four monitoring guidance documents
for nonpoint source activities.
Measurement of Habitat Variables
Habitat variables are monitored using different
scales of measure which influence the flexibility
in interpreting the data. Four measurement
scales are commonly used when collecting
scientific data: nominal, ordinal, interval, and
ratio scales (from Poole et al. 1997J. The
nominal scale is used when items are classified.
This scale assigns names to categories, but the
names alone tell us nothing about the
relationship between objects, except that objects
in the same category are more similar to one
another in some respect than objects in different
categories. "Pool," "riffle", and "cascade" are
categories without inherent rank and are,
therefore, nominal measures. The ordinal scale
is a scale of order or rank. Categories can be
placed in ascending or descending order, but
the magnitude of change when moving from one
category to another is not constant. "Sand,
"Pebble," and "Cobble" are ordinal
measurements of particle size. The interval
scale specifies rank and quantifies the
magnitude of change between any two
measures; any zero point on the scale is
arbitrarily located. Temperature measured in C
(zero is the point at which water freezes) or F
(zero is 32 below the point at which water
freezes) are interval measurements. Finally, the
ratio scale is an interval scale with an absolute
zero. Stream width and pool depth measured in
linear units such as inches or cm are ratio
measurements. These scales are described in
order of ascending flexibility with respect to
statistical techniques - the nominal scale is the
least flexible and the ratio scale is the most. A
greater variety of arithmetic operations and
statistical techniques is available for data
collected at more flexible scales (Schuster and
Zuurling 1986). Generally speaking, using the
nominal scale for data that could be recorded
using other measurement scales can
unnecessarily limit the statistical tools available
for analyzing the data and, therefore, limit the
utility of the data set.
Categorical data (nominal and ordinal scale) can
provide useful information but has shortcomings
associated with inherent observer bias. Habitat
unit classification (pool, riffle, glides, etc.) has
been used to quantify aquatic habitat in order to
monitor the response of individual streams to
human activities. Poole et al. (1997) found that
habitat unit classification data collected in this
manner was not useful for this purpose because:
1) observer bias seriously compromised
repeatability, precision, and transferability of the
information; 2) important ecological change was
not always manifested as changes in habitat
frequency; and, 3) classification data are
nominal which can intrinsically limit their
amenability to statistical analysis.
Habitat components have been measured by a
variety of different methods based on different
scales of measure. These variables are not
comparable with respect to data quality
objectives, although the variable name may
imply that the same habitat component is being
measured. For example, the variable "percent
fines sediment" has been measured based on a
variety of monitoring protocols: ocular estimates
by an observer looking across an entire transect
and making a mental average; ocular estimates
of specific sub-samples along a transect using a
view box; tallies of percent fines based on
observations of percent fines from a grid placed
on the stream bed; placement of substrate
particles into descriptive size classes such as
sand, gravel, cobble based on ocular means;
and, via a diversity of modifications of the
Wolman pebble count method. The "percent
fines sediment' values obtained from these
different procedures can be quite different. Little
specific information exists on the precision of
these various methods, and so, the degree of
reproducibility and comparability is mostly
unknown. This example illustrates the current
confusion in habitat monitoring and the difficulty
of applying these measures to water quality
programs until the method as well as method
precision and accuracy are defined. One
program that has systematically evaluated
precision of habitat parameters is the EPA
Regional Ecosystem Monitoring and
Assessment Program. Estimates of precision
for the habitat variables collected during this
program are described in the next section.
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Case Study of Precision of Physical
Habitat Variables
A project that is part of US EPA's Regional
Environmental Monitoring and Assessment
Program (REMAP) has examined the issue of
precision of measures of physical habitat in
wadeable streams (Kaufmann et al. in progress).
The study evaluated the precision and
repeatability of a number of habitat variables
collected using visual, semi-quantitative, and
quantitative procedures. Data was collected in
several hundred streams in Oregon, the Mid-
Atlantic States, and the Midwest. For this report,
we have only summarized the precision
estimates from streams in Oregon.
The REMAP study is interested in comparing
streams from a broad regional context.
Estimates of precision are specific to the
REMAP objectives and protocols, but they do
provide a good example of how the scale of
measurement affects the precision of the result.
We selected a sub-set of variables (metrics)
from this paper that measure the habitat
components described in the previous section.
The description of variables are simplified to
illustrate the topic of precision. The reader
should refer to the EPA publication (Kaufmann
et al. 1998) for information on specific field
methods and variable selection to answer any
questions regarding transferability and
comparability to their monitoring methods.
Precision was estimated as the standard
deviation of replicates, as the Coefficient of
Variation (CV), and as the Signal to Noise ratio.
The lower the value of the standard deviation of
replicates the more precise is the measurement.
These values are reported in the units of
measure, and so, they do not readily convey the
magnitude of precision. The Coefficient of
Variation is expressed as a percentage of the
mean and, therefore, provides a common
method of expressing the degree of variation.
The lower the CV the greater is the precision.
The CV is sensitive to the magnitude of the
mean (the CV increases as the value of the
mean decreases regardless of the actual
precision of the measurement) and can, thus, be
misleading. The third expression of precision is
the Signal to Noise ratio (S/N). The higher the
value the more precise the metric is and the
greater is the ability to discern differences
between streams. S/N values for this study
above 10 are considered precise for most uses,
7-10 are relatively precise, 3-7 are moderately
precise, 1-3 are relatively imprecise, and less
than 1 are imprecise.
Precision of variables described as visual
(qualitative), semi-quantitative, and quantitative
is compared in Table 7. Percent Pool habitat is
a visual estimate that is flow-dependent and,
therefore, exhibits low precision. Precision of
this observation increases when habitat types
are aggregated and only reported as Percent
Slow (i.e. all pools and glides combined). Note
the S:N ratio increases from 2.1 for Percent
Pools to 7.5 for Percent Slow habitat. Mean
Residual Depth is a quantitative measure based
on average residual depth for a reach using the
thalweg profile. We would expect the precision
to be higher for repeated measures of residual
depth from the same pool, though this statistic is
not shown in this data set. The LWD Frequency
methods used in REMAP is a semi-quantitative
method; the logs are visually placed into size
classes and tallied. The substrate metrics such
as Percent Fines + Sands variable used is a
semi-quantitative procedure, since the substrate
particles are placed visually into size classes.
The sample size used in the procedure consists
of 55 particles. If the sample size were
increased to 100 particles, the CV would be
expected decrease.
Percent Tree Canopy Present has a high
precision, because the classification that
observers are asked to evaluate is simple and
clear (i.e., either there is a tree canopy or there
is not). Proportion Overhanging Vegetation and
Proportion Undercut Banks are based on visual
estimates, which are relatively imprecise.
Canopy Density, measured with a densiometer,
increases the repeatability to a high level of
precision.
In summary, quantitative channel morphology
and riparian canopy measurements are
considered precise when applied to clearly
defined and less flow dependent features.
Semi-quantitative measurements are
intermediate in precision. Visual estimates of
riparian canopy cover and areal fish habitat
cover exhibit low to moderate precision.
Commonly used measures, such as riffle/pool
and width/depth ratios, as well as qualitative
visual assessments tend to be affected by flow
and, therefore, are imprecise.
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Table 7. Precision Estimates for selected quantitative and semi-quantitative variables from
REMAP studies in Oregon (Kaufmann et. al. 1988).
Habitat Variable
(reach scale)
Habitat Space
% Pool Habitat (Visual)
% Slow (Pools + Glides,
Visual)
Mean Residual Depth
(quantitative, cm)
LWD Frequency
(Semi-quantitative, %)
Substrate Quality
Percent Fines + Sand
(Semi-quantitative)
Streambank &
Riparian Condition
Percent Tree Canopy
(Qualitative)
Undercut Banks
(Semi-quantitative)
Overhanging Vegetation
(Semi-quantitative)
Canopy Density
(Quantitative)
Standard Deviation
of Replicates*
16
12
2.2
0.4
11
8.0
0.038
0.069
5.8
Grand Mean
33
52
11.6
30.5 %
92
0.068
0.19
71 .6 %
Coefficient
of Variation*
48%
23%
19%
n.a.
36%
8.7
56%
36%
8.1
Signal/Noise
Ratio
2.1
7.5
9.0
7.0
7.1
10
6.2
5.1
15
Detecting Differences
Precision and accuracy issues directly affect the
potential application of habitat measurements
used in CWA programs. If the monitoring
method is too imprecise to detect differences
considered ecologically significant, then these
habitat variables will not be useful in managing
water quality. The interaction of three primary
factors - sample size, variability, and the size of
the detection difference (Figure 8) - influences
the ability to detect differences. Variability
includes the natural variability of the measured
habitat component plus the variability (sampling
error) associated with the monitoring method.
Sample Size
Variability
Size of Detectable Difference
Figure 8. Detecting differences - The triangle of factors.
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In order to detect a statistically significant
difference among populations, the size of
detectable difference must be substantial
enough such that the difference is not subsumed
by variation in the data. Use of an imprecise
method imparts additional variance into a data
set. Data resulting from a methodology with
absolute precision would have no variance,
while a less precise method would result in data
with some variance attributed solely to the
measurement procedure. This additional
variance can distort conclusions by decreasing
the 'power1 of the test.
The power of a statistical test is a measure of
that test's ability to detect differences between
populations. A test with less power will require a
larger sample size and, therefore, greater
sampling effort than a test with more power in
order to detect the same differences among
populations. The magnitude of the difference in
central tendency (the mean or median) among
populations, the sample variance in the data set
(including error attributed to the method) and the
sample size all affect whether a significant
difference will be detected among populations.
Since the use of precise methodologies lowers
the variance in the resulting data by eliminating
sample error variance, a monitoring protocol that
uses more precise methods will be able to
detect change in the stream more readily than a
protocol that uses less precise methods.
Further, if the variance imparted by the
methodology is large enough to mask the
difference between the populations, that
methodology will likely never detect difference
between the populations of interest. Using the
most precise methods available increases the
sensitivity and, therefore, the utility of the
monitoring protocol. Applying sufficiently
imprecise methodologies renders the resulting
data of little or no use toward meeting a
monitoring program's goals.
The information on precision from Table 7
illustrates the influence of methods on detecting
differences. The CV provides a measure of the
ability to detect differences between populations
or between the sampled population and a
habitat target value. Percent Pool Habitat, a
visual estimate, has a CV of 48%. If our target
value is to have a stream with 50% pools, we
could not expect to detect a difference from the
criteria until the pool frequency was 48% away
from the criterion - roughly 25% pools. The
measure of the habitat target is too imprecise to
be useful, since a change of this magnitude
would be damaging to the beneficial use. Our
ability to detect differences improves with the
Percent Slow metric; with a CV of 23%, we
should be able to distinguish streams from the
50% target when Pool Frequencies are 38% or
less.
Utility of Existing Habitat
Assessment Methods
A recent survey of habitat assessment methods
by American Fisheries Society and USFWS
identified 52 method documents in use by state,
provincial, and federal governments (Bain,
Hughes, and Arend 1999). Thirty-one of these
methods were aimed at assessing streams and
rivers. Most methods assessed the channel
dimensions, substrate quality, water movement,
riparian zone, fish cover, and stream size as
common characteristics. Different approaches
are used in these methods to define how much
habitat needs to be measured and how study
areas are located. Application of the results
beyond the site-specific scale is limited by
sampling design considerations. No evaluation
of the comparability of these measurement
methods was described in this report.
The Rocky Mountain Research Station recently
assessed the efficacy of a standardized habitat
inventory protocol for EPA (Peterson and
Wollrab 1999). The R1/R4 fish and fish habitat
inventory procedure (Overton et al. 1997) is a
well-documented habitat monitoring protocol
used throughout the Intermountain West. As
with other habitat methods listed in the survey
above, the survey protocols have evolved over
time with an increased emphasis on
standardization. However, the results of the
analysis revealed several problems with
application of the procedures. Standardized
sampling methods were not consistently applied
across Forest Service districts or within districts
over time. These inconsistencies impede the
detection of change and limit the validity of
comparisons overtime and space. The analysis
found the procedures to be subjective, biased,
and inadequate for estimating fish populations
and characterizing fish habitat. Monitoring
protocols that use these procedures will likely
fail to detect significant changes or could
indicate false changes in fish habitat. The
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authors recommend that the inventory
procedures be replaced by a more rigorous
decision analysis system applied to a specific
management question.
If this analysis of the R1/R4 inventory
procedures (Peterson and Wollrab 1999) is
representative of the existing habitat protocols,
then there is good reason to question the utility
of inventory procedures for use in water quality
programs. The fisheries and aquatic ecology
community needs to address the shortcomings
of these methods and help review and develop
more robust procedures.
Summary
A systematic approach to monitoring addresses
monitoring design, selection of variables and
measurement methods, and quality
assurance/quality control procedures. Quality
assurance procedures established for water
quality monitoring provide a framework that can
be applied to the measurement of habitat
variables. The water quality monitoring
framework consists of established Standard
Methods for analytical analyses, Standard
Operating Procedures for field methods, and
QA/QC procedures. Currently no accepted
parallel systematic framework exists for assuring
the data quality for habitat monitoring. However,
a number of state and federal have programs
that address several of these components, and
the experience from these programs could be
brought together to build this framework.
Using habitat variables under the CWA as
diagnostic indicators, water quality criteria, or
environmental targets for TMDL's requires the
establishment of data quality objectives. The
detection of ecologically significant differences
requires data with known levels of precision and
accuracy. Measured quantitative data should be
used where feasible to overcome the observer
bias inherent in qualitative methods.
Quantitative methods for measuring habitat are
becoming more accessible and faster with the
use of Total Station Survey equipment and GPS
survey technology (Fisher and Toepfer 1998).
Quantitative channel measurements that are
standard procedures in hydrology and
geomorphology (Harrelson et al. 1994, Rosgen
1996) should be considered as ways to increase
quantitative measurement of habitat quality.
The Tongass National Forest channel condition
assessment protocol for channel morphology,
large woody debris, and grain size distribution
(Kuntzsch et al. 1998) provides an example of
the use of these quantitative methods. The
trade off between the costs of quantitative
methods and the expected benefits in detecting
change will also need to be considered.
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Application of Aquatic Habitat Indicators to CWA Programs
8. APPLICATION OF AQUATIC HABITAT INDICATORS TO
CWA PROGRAMS
In the previous sections of this paper, we
described the rationale, technical basis, and
potential limitations of using aquatic habitat
indicators in the CWA. The Executive Summary
contains a synopsis of the key conclusions from
this review and recommendations for future
action. In this section, we describe how the
current situation might be applied to water
quality standards and TMDLs.
Application to Water Quality
Standards
The current Water Quality Standards in EPA
Region 10 states (Alaska, Idaho, Washington
and Oregon) and certain tribes contain narrative
and numeric criteria designed to protect
"beneficial uses" of water that include cold water
biota, salmonid fish communities, and their
habitats. We briefly review the requirements for
water quality standards as well as current state
criteria and, then, suggest some alternative
approaches to water quality criteria relative to
aquatic habitats.
The discussion of water quality standards will be
brief; the reader is referred to the recent
Advanced Notice of Public Rulemaking on Water
Quality Standards (Federal Register Vol. 3, No.
129 published Tuesday, July 7, 1998) for more
details. Water quality criteria are levels of
individual pollutants, water quality
characteristics, or descriptions of conditions of a
water body that, if met, will generally protect the
designated use of the water. Narrative criteria
can include physical criteria such as habitat
characteristics and flow regimes. Section 303
(a-c) the CWA requires all states or tribes with
water quality program authority to evaluate the
need for water quality criteria in order to protect
a designated use and then to adopt appropriate
water quality criteria to protect existing and
designated uses. Narrative criteria are
descriptions of conditions necessary for the
water body to attain its 'designated use', such as
spawning and rearing habitat supportive of
healthy populations of salmon and trout.
Narrative criteria may address generic
conditions such as surface waters shall be 'be
free from' hazardous materials, toxic
substances, excess nutrients, and oxygen-
demanding materials. Narrative criteria may
also describe the process for developing a
numeric criteria given certain conditions.
All Region 10 states include numeric water
quality criteria for certain water column
variables, namely dissolved oxygen, total
dissolved gas, temperature, pH, turbidity,
ammonia, residual chlorine, and toxic
substances. The states show a wide diversity in
content, however, relative to protection of
aquatic habitats (Table 8). Generally, there are
policy statements regarding the full protection of
existing and designated uses of water, specific
use designations applicable to cold water
salmonid fish, salmonid spawning, as well as
biological criteria and biomonitoring. States
have used their antidegradation authority and its
requirements to protect existing uses as a basis
for incorporating additional requirements for
physical habitat into CWA Section 401
certifications. For example, the state of
Washington specified a minimum instream flow
requirement for the Elkhorn hydroelectric project
(in PUD No. 1, Jefferson County vs. Wa. Dept.
of Ecology [511US700], 1994).
Our conclusion upon reviewing the existing
standards is that narrative criteria for salmonid
habitat could be substantially strengthened by
more fully describing the mix of conditions
generally known to constitute suitable habitat.
For spawning habitat, these might include, for
example, "...maintenance of in-stream flow
conditions and suitably-sized gravel substrate
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Application of Aquatic Habitat Indicators to CWA Programs
for support of spawning at known historic
locations". These criteria could further specify
characteristics of stream bottom sediments (bed
particle sizes, % fines) as determined by a
specific method (e.g. pebble counts using
methods of Wolman 1954), as defined for
particular spawning locations (which could be
fixed using global positioning systems), and as
overlain onto spawning ground information
(determined by consulting timing and location
records of current and historic spawning ground
surveys and mapped at the 1:24,000 or 1:12,000
scale). These locations could then serve as a
focal point for additional evaluation of water
quality, peak discharge event recording, or bed
scour and fill events and their significance to egg
to emergence survival of the progeny from a
given salmon stock. Assessment of sediment
input sources from hillslope failures, and the
effect these have on spawning ground
characteristics and salmon success could then
be evaluated.
The narrative criteria could also describe the
process for development of site-specific or
ecoregional numeric criteria. Numeric criteria
could be tiered to these narrative statements as
more specific information becomes available for
individual ecoregions or river basins and
watersheds nested within these areas. Several
of the state standards already provide the
framework for this approach. For example, the
statements regarding reference condition and
site-specific criteria address two of the critical
elements to the approach that we have
discussed.
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Table 8. Compilation of State Standards in Region 10 with reference to protection of habitat
quality.
Idaho
Idaho Water Quality
Standards
IDAPA 16.01 .02
(compiled through
3/1999)
State Standards with Reference to Aquatic Habitats
Definition
12. Biological Monitoring or Biomonitoring. The use of a biological entity as a
detector and its response as a measure to determine environmental conditions.
Toxicity tests and biological surveys, including habitat monitoring, are common
biomonitoring methods. (8-24-94)
35. Existing Beneficial Use Or Existing Use. Those beneficial uses actually attained
in waters on or after November 28, 1 975, whether or not they are designated for
those waters in Idaho Department of Health and Welfare Rules, IDAPA 16.01.02,
"Water Quality Standards and Wastewater Treatment Requirements". (8-24-94)
40. Full Protection, Full Support, or Full Maintenance of Designated Beneficial
Uses of Water. Compliance with those levels of water quality criteria listed in
Sections 200, 250, 275 (if applicable), and 299 or with the reference streams or
conditions approved by the Director in consultation with the appropriate basin
advisory group. (3-20-97)
84. Reference Stream Or Condition. A water body which represents the minimum
conditions necessary to fully support the applicable designated beneficial uses as
further specified in these rules, or natural conditions with few impacts from human
activities and which are representative of the highest level of support attainable in
the basin. In highly mineralized areas or in the absence of such reference streams
or water bodies, the Director, in consultation with the basin advisory group and the
technical advisors to it, may define appropriate hypothetical reference conditions or
may use monitoring data specific to the site in question to determine conditions in
which the beneficial uses are fully supported. (3-20-97)
050. ADMINISTRATIVE POLICY.
02. Protection Of Waters Of The State. (7-1-93)
a. Wherever attainable, surface waters of the state shall be protected for beneficial
uses which for surface waters includes all recreational use in and on the water
surface and the preservation and propagation of desirable species of aquatic biota;
(8-24-94)
c. In all cases, existing beneficial uses of the waters of the state will be protected.
(7-1-93)
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Aquatic Habitat Indicators
SECTION 8
Application of Aquatic Habitat Indicators to CWA Programs
Idaho Water Quality
Standards
(Continued)
053. BENEFICIAL USE SUPPORT STATUS.
In determining whether a water body fully supports designated and existing
beneficial uses, the Department shall determine whether all of the applicable water
quality standards are being achieved, including any criteria developed pursuant to
these rules, and whether a healthy, balanced biological community is present.
The Department shall utilize biological and aquatic habitat parameters listed below
in the "Water body Assessment Guidance," Idaho Department of Health and
Welfare, Division of Environmental Quality, 1996, as a guide to assist in the
assessment of beneficial use status. These parameters are not to be considered or
treated as individual water quality criteria or otherwise interpreted or applied as
water quality standards. (3-20-97).
01. Aquatic Habitat Parameters. These parameters may include, but are not
limited to, stream width, stream depth, stream shade, measurements of sediment
impacts, bank stability, water flows, and other physical characteristics of the stream
that affect habitat for fish, macroinvertebrates or other aquatic life; and (3-20-97).
02. Biological Parameters. These parameters may include, but are not limited to,
evaluation of aquatic macroinvertebrates including Ephemeroptera, Plecoptera and
Trichoptera (EPT), Hilsenhoff Biotic Index, measures of functional feeding groups,
and the variety and number of fish or other aquatic life to determine biological
community diversity and functionality. (3-20-97)
100. SURFACE WATER USE CLASSIFICATIONS.
The designated beneficial uses for which the surface waters of the state are to be
protected include: (8-24-94)
c. Salmonid spawning: waters which provide or could provide a habitat for active
self-propagating populations of salmonid fishes. (7-1-93)
275. SITE-SPECIFIC SURFACE WATER QUALITY CRITERIA.
01. Procedures For Establishing Site-specific Water Quality Criteria.
{In summary, this section provides for development of criteria based on site-
specific analyses conducted in a scientifically justifiable manner.}
Washington
State Standards with Reference to Aquatic Habitats
Washington Water
Quality Standards
18 AAC70
(as amended,1999)
Definitions
"Biological assessment" is an evaluation of the biological condition of a water
body using surveys of aquatic community structure and function and other direct
measurements of resident biota in surface waters.
"Wildlife habitat" means waters of the state used by, or that directly or indirectly
provide food support to, fish, other aquatic life, and wildlife for any life history stage
or activity. {Note: list of code citations not included.}
General water use and criteria classes. WAC 173-201A-030
{Note: Fish and shellfish - Salmonid migration, rearing, spawning, and harvesting -
are listed as characteristic uses depending on Class designation. No habitat
related criteria are listed.}
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Aquatic Habitat Indicators
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Application of Aquatic Habitat Indicators to CWA Programs
Oregon
State Standards with Reference to Aquatic Habitats
Oregon Water Quality
Standards
Oregon Administrative
Rules OAR-340-41.
1999
Definitions
(32) "Aquatic Species" means any plants or animals which live at least part of their
life cycle in waters of the State.
(33) "Biological Criteria" means numerical values or narrative expressions that
describe the biological integrity of aquatic communities inhabiting waters of a given
designated aquatic life use.
(36) "Resident Biological Community" means aquatic life expected to exist in a
particular habitat when water quality standards for a specific ecoregion, basin, or
water body are met. This shall be established by accepted biomonitoring
techniques.
(37) "Without Detrimental Changes in the Resident Biological Community" means
no loss of ecological integrity when compared to natural conditions at an
appropriate reference site or region.
(38) "Ecological Integrity" means the summation of chemical, physical and
biological integrity capable of supporting and maintaining a balanced, integrated,
adaptive community of organisms having a species composition, diversity, and
functional organization comparable to that of the natural habitat of the region.
(39) "Appropriate Reference Site or Region" means a site on the same water body,
or within the same basin or ecoregion that has similar habitat conditions, and
represents the water quality and biological community attainable within the areas of
concern.
(40) "Critical Habitat" means those areas which support rare, threatened or
endangered species, or serve as sensitive spawning and rearing areas for aquatic
life.
Biological Criteria:
Waters of the state shall be of sufficient quality to support aquatic species without
detrimental changes in the resident biological communities. 340-041-0027
Standard applicable to all basins: The creation of tastes or odors or toxic or
other conditions that are deleterious to fish or other aquatic life or affect the
potability of drinking water or the palatability of fish or shellfish shall not be allowed;
Intergravel Dissolved Oxygen:
A) For water bodies identified by the Department as providing salmonid spawning,
during the periods from spawning until fry emergence from the gravels, the
following criteria apply:
(B) For water bodies identified by the Department as providing salmonid spawning
during the period from spawning until fry emergence from the gravels, the spatial
median intergravel dissolved oxygen concentration shall not fall below 6.0 mg/l;
(C) A spatial median of 8.0 mg/l intergravel dissolved oxygen level shall be used to
identify areas where the recognized beneficial use of salmonid spawning, egg
incubation and fry emergence from the egg and from the gravels may be impaired
and therefore require action by the Department.
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Aquatic Habitat Indicators
SECTION 8
Application of Aquatic Habitat Indicators to CWA Programs
Alaska
State Standards with Reference to Aquatic Habitats
Alaska Water Quality
Standards
18 AAC70
(as amended through
May 27, 1999)
Definitions
(19) "designated uses" means those uses specified in 18 AAC 70.020 as protected
use classes for each waterbody or segment, regardless of whether those uses are
being attained;
(24) "existing uses" means those uses actually attained in a waterbody on or after
November 28, 1975;
(52) "sediment" means solid material of organic or mineral origin that is
transported by, suspended in, or deposited from water; "sediment" includes
chemical and
biochemical precipitates and organic material, such as humus;
Sediment Standards - 70.020(b)
(C) Growth and Propagation of Fish, Shellfish, Other Aquatic Life, and Wildlife
The percent accumulation of fine sediment in the range of 0.1 mm to 4.0 mm in the
gravel bed of waters used by anadromous or resident fish for spawning may not be
increased more than 5% by weight above natural conditions (as shown from grain
size accumulation graph). In no case may the 0.1 mm to 4.0 mm fine sediment
range in those gravel beds exceed a maximum of 30% by weight (as shown from
grain size accumulation graph). (See notes 3 and 4). In all other surface waters no
sediment loads (suspended or deposited) that can cause adverse effects on
aquatic animal or plant life, their reproduction or habitat may be present.
Intergravel Dissolved Oxygen Standard - 70.020(b)
D.O. must be greater than 7 mg/l in waters used by anadromous and resident fish.
In no case may D.O. be less than 5 mg/l to a depth of 20 cm in the interstitial
waters of gravel used by anadromous or resident fish for spawning (See note 2).
For waters not used by anadromous or resident fish, D.O. must be greater than or
equal to 5 mg/l. In no case may D.O. be greater than 17 mg/l. The concentration of
D.O. may not exceed 110% of saturation at any point of sample collection.
. SITE-SPECIFIC CRITERIA. 70.235
The department will, in its discretion, establish a site-specific water quality criterion
that modifies a water quality criterion set out in 18 AAC 70.020(b)
{Note: This section describes the process for determining site-specific criteria.}
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Aquatic Habitat Indicators
SECTION 8
Application of Aquatic Habitat Indicators to CWA Programs
Example of Approach to Habitat
Indicators
Two examples, described in Appendix A and B,
illustrate the approach to developing numerical
indicators from empirical data collected in
reference areas. One example is based on
habitat indices developed as part of the Tongass
Land and Resource Management Plan. Three
habitat indices (pool area, pieces of large woody
debris, and bankfull width-to-depth ratio) were
derived from existing watershed-scale stream
inventory data for the Tongass National Forest.
The data are presented as the 25th, 50th, and
75th percentiles of the data. Refer to Appendix B
for a description of these habitat indicators.
The second example comes from data in the
Salmon River Basin located in Northern Rocky
Mountain Ecoregion in central Idaho. The U.S.
Forest Service Intermountain Research Station
collected data within this ecoregion to
characterize streams under natural conditions.
The data collection area focused on the high
rugged mountains of central Idaho where there
is little human disturbance. We selected this
data set for two reasons: first, there is high
assurance that natural forces (fire, wind, and
flood, and mass wasting events) are responsible
for the variation in habitat condition; and second,
the data was collected under written monitoring
protocols with careful attention to observer
training and quality control. This data set is
used to illustrate an example of narrative and
numeric criteria.
There are many possible formats for habitat
water quality criteria. Narrative criteria should
designate the importance of the habitat at the
Habitat Component level as discussed in
Section 5. The narrative criteria should further
identify the habitat indicators that will be
measured to evaluate attainment of the criterion
where feasible. We have used the phrase
"based on the range of conditions observed in
reference streams of a comparable stream
system" to convey the concept that the target
condition is obtained from streams of a similar
geomorphology in an undisturbed condition.
Numeric criteria can then be tiered to the
narrative statement as information becomes
available on a ecoregional basis. This
addresses the usual objection of a lack of
information on a statewide basis. The numeric
criteria refer to data sets compiled from
reference areas of a comparable landscape
setting and stream system. The example
language uses the phrase "as stratified by basin
area, parent geology, or other geomorphic
characteristic" to recognize the need for
stratification by landscape and stream network
characteristics. The actual stratification as listed
in the table, then, relies on an analysis of the
data in a manner that best explains the variation
due to ecoregional characteristics. We have
designated the third quartile of the data
distribution to act as a red flag to trigger further
evaluation with regards to the reason that a
stream might fall below this range.
Narrative criteria example
Maintain or restore the physical integrity of the
aquatic system necessary to support habitat for
salmonid spawning and rearing. Indicators of
physical habitat integrity include large woody
debris frequency, pool frequency, residual pool
depth, and percent surface fines. Numeric
habitat indicators will be developed by
ecoregional area based on the range of
conditions observed in reference streams of a
comparable stream system as this information
becomes available.
Numeric Criteria example
Large woody debris frequency, pool frequency,
and residual pool depth should occur within the
third quartile of the data distribution for reference
streams in the ecoregion as stratified by basin
area, parent geology, or other geomorphic
characteristics as determined by stream
quantitative stream surveys, see the example in
Figure 9. Comparison to numeric criteria is
based on the summary of data by stream reach.
Where data falls outside of the expected range,
the cause for such deviation shall be
determined.
67
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Aquatic Habitat Indicators
SECTION 8
Application of Aquatic Habitat Indicators to CWA Programs
Large woody debris/mile in different basin areas
N
IQR
Median
25%
75%
0-25
31
170.6
136.1
67.8
238.4
25-50
33
100
83.4
47.1
147.1
50-75
17
44
49.8
38.6
82.6
75-100
10
55.4
62.2
41.9
97.3
100-150
13
42.8
79.1
50.2
92.9
150-360
12
14.5
25.8
18.8
33.3
Pool frequency in Rosgen channel types
N
IQR
Median
25%
75%
All
124
24.0
20.7
12.6
36.6
A
4
23.3
60.2
46.7
70
B
92
23.4
20.4
11.7
35.1
C
28
18.5
19.6
16.7
35.2
Residual pool depth and basin area
N
IQR
Median
25%
75%
0-25
2342
0.25
0.35
0.25
0.5
25-50
1075
0.24
0.4
0.3
0.54
50-75
94
0.29
0.45
0.35
0.64
75-100
66
0.3
0.54
0.4
0.7
100-125
181
0.35
0.5
0.35
0.7
100-150
44
0.68
0.5
0.33
1
150-360
49
0.5
1.3
1
1.5
Percent fines of different geology and channel types
N
IQR
Median
25%
75%
All
8459
20
15
10
30
PlutAII
5733
20
15
10
30
PlutA
263
10
10
5
15
PlutB
3673
10
15
10
20
PlutC
1797
35
25
15
50
Vole All
2726
30
20
10
40
Vole A
11
22.5
40
22.5
45
VolcB
2385
35
20
10
45
VolcC
330
7
10
8
15
Figure 9. Percentiles of LWD/mile, pool frequency, residual pool depth, and percent fines from
the Salmon River Basin natural conditions database.
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Aquatic Habitat Indicators
SECTION 8
Application of Aquatic Habitat Indicators to CWA Programs
Application to TMDL Targets
An integral step in developing a TMDL is to
establish the water quality target for the pollutant
load analysis. The emphasis on quantitative
targets, regardless of the technical limitations on
establishing such numeric targets, is a
controversial issue that has not yet been
resolved. This apparent conflict occurs because
the legal mandate clashes with practical,
technical and scientific limitations. As currently
understood, development of a TMDL requires
pollutant load estimates, load allocation, and
specification of numeric targets. The logical
approach for developing numeric habitat targets
as described in the example above for numeric
criteria should also apply to the development of
TMDL targets. However, incorporating the
caveats and technical limitations of this
approach into TMDLs may be difficult because
of the nature of the regulatory framework for
water quality limited streams. We have
emphasized that habitat indicators should be
used as diagnostic indicators rather than as
compliance indicators. An appropriate use,
therefore, is to incorporate the habitat
components into the TMDL as a monitoring and
evaluation tool to be used in an adaptive
management framework.
The key difficulty in establishing numeric targets,
even as diagnostic indicators, is the expected
lack of information on reference areas on which
to base the TMDL target condition. There is
obviously no ready solution for the lack of
reference conditions, so the TMDL analyst will
have to exert some creativity in looking for
suitable information. The information search
should not be restricted within the watershed or
river basin. As discussed in the landscape
section, habitat conditions should be based on
(but not restricted to) the broader base of
reference streams within the ecoregion. In
addition, often isolated tracts of land that have
experienced little development can provide
some comparable reference data.
69
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Aquatic Habitat Indicators Literature Cited
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APPENDICES
78
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Aquatic Habitat Indicators Appendix A
APPENDIX A: EXAMPLE OF AQUATIC HABITAT INDICATORS IN THE ROCKY
MOUNTAIN ECOREGION
Introduction
The Pacific Northwest is characterized by a diversity of landscapes due to the natural variation in
climate, geology, and topography. The patterns of vegetation and the distribution offish and wildlife
populations are directly related to this diversity. Several geographic frameworks have been
established to better understand these regional patterns and aid in natural resource management. A
geographic framework provides a logical basis for characterizing the range of ecosystem conditions
that are realistically attainable, relative to regional patterns of cultural and physical constraints
(Omernik and Gallant 1986). Stream systems are a product of landscapes that share common
climatic and geologic features. Stream reference conditions within similar landscapes provides a
measure of natural conditions in which fish and other aquatic life have evolved. The ecoregion
framework provides a method of cataloging stream systems by similar broad scale characteristics of
geology, climate, and physiography. Stream networks nested within these broad scale landscapes
can be further grouped based on local channel characteristics such as gradient, stream size, and
confinement.
The Ecoregion classification scheme presented by Omernik (1995) is a useful framework for
delineating landscape by geology, climate, and vegetation characteristics. Ecoregions may be further
stratified by these landscape features and by watershed delineation to create nested hierarchical
frameworks. Hydrologic Units, described by USGS, is a commonly used system for organizing
watersheds using a nested hierarchical system. Stratifying watersheds within ecoregions provides a
method to compare stream systems across similar landscapes as well as between streams with
similar geomorphic features. Cataloging streams of similar types and characteristics allows
managers to better understand the potential capacity of a stream and the effects of activities that
have altered that capacity.
The Natural Conditions Database of Salmon River Basin
The U.S. Forest Service Intermountain Region Research Station, U.S. Dept. of Agriculture, surveyed
stream characteristics in the Salmon River basin, Idaho, that are representative of reference
conditions in this ecoregion. The database and description of stream characteristics represent
stream conditions shaped by natural forces in the absence of human disturbance. It is assumed that
these streams have channel dimensions, form, and patterns of systems influenced only by natural
disturbance regimes (such as fire, flood, drought) and that the frequency distributions for the selected
habitat type variables approximate the spatial and temporal variability for the Salmon River basin
(Overton et al. 1995). Data collection procedures were targeted at four landscape scales -
watershed, channel reach type, habitat type, and meso-habitat (meso-habitat refers to attributes of
the habitat type; bank characteristics, large woody debris). Objectives were to collect information on
habitat attributes that were considered both ecologically significant to fish and affected by land
management disturbance. The reader should consult the USFS document for a detailed presentation
of information from this database. For this example, we have focused on a subset of habitat
parameters within a smaller geographic area.
Upper Middle Fork Salmon River
The Upper Middle Fork Salmon drainage is a fourth level HUC located within the Salmon River basin
(third level HUC ) in central Idaho, Figure 10. The Salmon River basin contains large areas of
roadless that provide an opportunity to evaluate aquatic habitat that is influenced primarily by natural
disturbances. The area is characteristic of the high elevation mountain forests located within the
79
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Aquatic Habitat Indicators Appendix A
Northern Rocky Mountain Ecoregion, a Level III ecoregion, described by Omernik (1995). Landscape
characteristics of the Salmon River basin are summarized in the USFS publication (Overton 1995).
"The Salmon River drains a large, mostly forested basin in central Idaho. The Salmon River
country is characterized by high rugged mountains. It's topography is typical of many
dendritic drainages with tributaries forming steep v-shaped canyons. Dendritic drainage
networks are characteristic of soils with a homogeneous resistance to erosion. Many
tributaries have cut steep rock canyons with meadows at the head water areas. The whole
Salmon River Basin is an extensive area of forested mountains, sagebrush covered lower
slopes, and deeply incised river canyons. Volcanic and plutonic geologies make up the most
of the Salmon River basin."
Weathering of rock, grain size, amount of moisture, and vegetation play an important role in finding
which soils form and how a stream will develop and behave. There are two major, distinct geologies
found in the Salmon River drainage: the Idaho Batholith, a composite mass of granitic plutons, and
the Challis Volcanics (Overton 1995). The Idaho Batholith's is a plutonic, intrusive geology comprised
of granitic and dioritic subclasses, that are unstable and decompose rapidly. The Challis Volcanics is
extrusive, and comprised of basalt/andesite and rhyolite. Ryolite erodes similiarly to granitics, where
basalts/andesites erode faster than granitics.
To compare similar stream reaches we grouped the habitat variables (response variables) according
to the major factors that influence their magnitude. Habitat is characterized by measures of large
woody debris, pool frequency, residual pool depth, percent fines, and percent bank stability. These
habitat measures are grouped by three major landscape and stream network factors that exert a
major influence on their outcome - channel gradient, basin size, and geology.
80
-------
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Aquatic Habitat Indicators
APPENDIX A
Large Woody Debris
Large woody debris in forested streams is one of most important contributors of habitat and cover for fish
populations. Large woody debris can influence channel meandering, bank and substrate stability, and
variability in channel width. Large woody debris is a function of stream size, with smaller streams
containing more wood than larger streams (Bilby and Ward 1989). These relationships are observed in
the Upper Middle Fork Salmon basin; more large woody debris occurs in smaller basins, Figure 11.
Variability of data is represented by box and whisker plots. The lower and upper 25 percent of the data is
represented by the top and bottom of the box, the median is the central line within the box. The whiskers
extending from the box represent the 10th and 90th percentile and points exceeding whiskers are outliers.
Inter quartile range (IQR) and quartile values are provided in the table below the figure.
400
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Figure 11. Box Plot of large woody debris/mile in different size basin areas, in unmanaged
streams in the Upper Middle Fork Salmon River basin, Idaho.
82
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Aquatic Habitat Indicators
APPENDIX A
Pool Frequency and Depth
Pools provide important habitat throughout all salmonid life stages. Pool spacing in forest channels of
mountain drainage basins is controlled by large woody debris loading and channel type, slope, and width
(Montgomery et al. 1995). The spacing of pool features is proportional to stream width, and inversely
related to channel slope (Rosgen 1996). The influence can be noted in comparing pool frequency to
channel type (Figure 12) and basin size (Figure 13). Steeper Type A channels exhibited higher pool
frequency than the lower gradient Type C channels. Pool frequency was inversely related to basin size
(stream size) in the Upper Middle Fork Salmon, Figure 13.
The residual pool depth is a measure of stream depth that is independent from stream discharge and
therefore provides a useful comparable measure of available habitat. Residual pool depth increased in
larger systems (larger basin and channel size), Figure 14. Larger streams produce, fewer, but larger
pools than smaller streams.
140
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100 -
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0 -
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A B
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92
23.4
20.4
11.7
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18.5
19.6
16.7
35.2
Figure 12. Box plot of pool frequency in Rosgen channel types, in unmanaged streams in the
Upper Middle Fork Salmon River basin, Idaho.
83
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Aquatic Habitat Indicators
APPENDIX A
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Aquatic Habitat Indicators
APPENDIX A
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Figure 14. Box plot of residual pool depth and basin area, in unmanaged streams in the Upper
Middle Fork Salmon River Basin, Idaho.
85
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Aquatic Habitat Indicators
APPENDIX A
Surface Fines
Surface fines are defined as those particles less than 6 mm in size (silt/sand). Sediment of this size is
generally transported during peak flows and settles out on the pool bottoms and low gradient riffles. Fine
sediment can fill pools, reduce spatial variability, reduce egg to fry survival in a salmonid redd.
Observation of percent fines is highly variable (Figure 15), which is likely due to a combination of natural
variability and sampling error. The box plots show some interesting relationships between geology and
channel type. Percent fines increases in lower gradient channels(A to C) in plutonic geology, and
decreases in volcanic geology (A to C). Reference lines and arrows have been added to Figure 15 to
emphasize this trend.
100
so -
60 -
40 -
20 -
o -
Plutonic All Plutonic A Plutonic B Plutonic C Volcanic All Volcanic A Volcanic B Volcanic C
Geology and Channel Type
N
IQR
Median
25%
75%
All
8459
20
15
10
30
Plut All
5733
20
15
10
30
Plut A
263
10
10
5
15
PlutB
3673
10
15
10
20
PlutC
1797
35
25
15
50
Vole All
2726
30
20
10
40
Vole A
11
22.5
40
22.5
45
VolcB
2385
35
20
10
45
VolcC
330
7
10
8
15
Figure 15. Box plot of descriptive statistics of percent fines of different geology and channel
types, in unmanaged streams in the Upper Middle Fork Salmon River basin, Idaho.
86
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Aquatic Habitat Indicators
APPENDIX A
Bank Stability
Stable banks support riparian vegetation that provide shade, cover, and nutrient loading for salmonids.
Loss of bank stability reduces bank undercut and increases sediment loading. Bank stability can be
altered by natural or human caused events that change sediment load, vegetation type and density, and
channel stability. Percent bank stability was high in all samples of the unmanaged basin, Figure 16, with
the mean higher than 80% for each sample.
120
100 -
£
!a
80 -
60 -
I 40 ^
20 -
0 -
All
Plutonic All Plutonic A Plutonic B Plutonic CVolcanic AHVolcanic A Volcanic B Volcanic C
Geology and Channel Type
N
IQR
Median
25%
75%
All
9125
25
99.4
75
100
Plut All
5477
22.2
98.2
77.8
100
Plut A
227
0
100
100
100
PlutB
3346
16.7
100
83.3
100
PlutC
1905
35.0
89.4
65.1
100
Vole All
3647
29.9
100
70.1
100
Vole A
15
0
100
100
100
VolcB
3121
32.1
96.3
67.9
100
VolcC
511
16.5
100
83.5
100
Figure 16. Box plot of percent bank stability of different geology and channel types, in
unmanaged streams in the Upper Middle Fork Salmon River Basin, Idaho.
87
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Aquatic Habitat Indicators APPENDIX A
Summary
Data from the Middle Fork Salmon River illustrate the degree of variability that occurs in reference
watersheds. However, grouping of stream reaches by landscape and geomorphic factors was useful in
accounting for some of this variability. As basin and channel size increase; pool frequency and large
wood debris frequency decrease. Residual pool depth increases with an increase in basin size. Percent
surface fines was highly variable, but, grouping by geology and Rosgen stream type appeared to show
some utility.
Literature Cited
Bilby, R. E. and Ward, J. W. 1989. Changes in characteristics and function of woody debris with
increasing size of streams in Western Washington. Transactions of the American Fisheries
Society. 118:368-378.
Montgomery, D. R.; Buffington, J. M., and Smith, R. D. 1995. Pool spacing in forest channels. Water
Resources Research. 31:1097-1105.
Omernik, J. M. 1995. Ecoregions: A spatial framework for environmental management. In: Davis, W.S.
and T.P. Simon, editors. Biological assessment and criteria: Tools for water resource
planning and decision making. Lewis Publishers, London.
Omernik, J. M. and Gallant, A. L. 1986. Ecoregions of the Pacific Northwest. Environmental Research
Laboratory. Corvallis, OR. EPA/600/3-86/033.
Overton, C. K.; Mclntyre, J. D.; Armstrong, R.; Whitwell, S. L., and Duncan, K. A. 1995. User's guide to
fish habitat: Descriptions that represent natural conditions in the Salmon river basin, Idaho
General. USDA Forest Service, Intermountain Research Station, Technical Report INT-
GTR-322.
Rosgen, D. 1996. Applied River Morphology. Pagosa Spings, Colorado: Wildland Hydrology.
88
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Aquatic Habitat Indicators APPENDIX B
APPENDIX B: SELECTED FISH HABITAT INDICATORS FROM THE TONGASS
NATIONAL FOREST, ALASKA REGION
Introduction
The development of quantifiable fish habitat indices for the Tongass National Forest was initiated as part
of the Congressionally mandated Anadromous Fish Habitat Assessment in 1994 (AFHA 1995). The
AFHA effort identified key attributes of healthy aquatic systems in southeast Alaska; large woody debris,
off-channel flood-plain habitat, substrate composition, channel morphology, sediment sources and
delivery rate, and salmonid abundance and aquatic community diversity. Three habitat indices (pool
area, pieces of large woody debris, and bank full width-to-depth ratio) related to these key attributes, were
derived from existing watershed scale, stream inventory data for the Tongass. These indices have been
adopted as interim fish habitat objectives in the revised Tongass Land and Resource Management Plan
standards and guidelines "to evaluate the relative health or condition of riparian and aquatic habitat" of
Forest watersheds (TLMP 1997).
Hierarchical Framework
The Alaska Region has implemented the general frameworks for aquatic and terrestrial ecological units
described in Maxwell et al 1995. Landscape stratification at the subsection level of ecological hierarchy
provides a basis for stratifying watersheds with similar geoclimatic settings (similar climatic, geology,
physiographic patterns) (Figure 17).. Aquatic ecological units within the Riverine System are classified by
Stream Process and Channel Types (Paustian et al 1992). These units are equivalent to valley segment
and stream reach units in the national framework. These geomorphic ally based stream classes reflect
dominant aquatic ecosystem processes and correlate with important aquatic habitat attributes.
Description/Selection of Habitat Indicators
The pool, large wood, and channel width-depth parameters were selected from a Tongass N.F. - wide
stream inventory data base, because these specific indices were judged to have defined measurement
standards that were consistently applied by inventory crews across the "million acre forest" (AFHA 1995).
This initial set of habitat indicator data were compiled from watersheds that were in a pristine or
undisturbed state at the time of the stream surveys. This data set was too small to stratify by broad scale
ecological units, so data were pooled for the entire Alexander Archipelago Section (USDA 1993).
Individual habitat indicators, however, are categorized by stream process group or channel type
ecological units (Figure 18, 19 and 20). This approach reduces the overall variability in reference
conditions between stream segments being compared, by grouping habitat data for streams with a
common range of size and gradients and which are influenced by similar dominant geomorphic
processes.
89
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Aquatic Habitat Indicators APPENDIX B
The Tongass Fish Habitat Objectives are intended to be a first generation diagnostic tool for assessment
of stream habitat condition and improvement needs. Each of the indices relate to key processes and
habitat features that are directly or indirectly control fish habitat capability. Pool area reflects the balance
between sediment inputs and transport rates in a stream over time. Pools provide critical year around
rearing habitat and winter refuges for juvenile salmonids. Pool habitat also provides cover for adult
spawners and optimum spawning areas at pool tail-outs. Large woody debris is another major factor
influencing freshwater habitat diversity in southeast Alaska streams. Woody debris is strongly correlated
to pool formation, and provides cover and food sources for many aquatic organisms. Recruitment and
depletion of large woody debris is influenced by natural events such as floods, wind storms and
landslides, as well as, riparian timber harvest activities. Channel width-to-depth ratio is a general
indicator of stream stability for alluvial channels. Streams with consistently high width-to-depth values are
indicative of high sediment loads and channels that are susceptible to stream bed aggradation. These
conditions can limit aquatic habitat capability especially in systems having low amounts of pool forming
large woody debris.
The Tongass habitat objectives are not designed to be used as specific attainment goals. The AFHA
(1995) report recommends that these indices be used within the framework of watershed analysis to:
• Assess relative ecological capacities and disturbance regimes within an overall watershed context.
• Identify stream segments that are potentially most susceptible to management or natural
disturbances.
• Identify areas with exceptional habitat conditions.
• Identify opportunities for habitat protection, improvement and rehabilitation.
Emphasis for habitat rehabilitation should be directed toward stream systems with low numbers or pool,
small amounts of large woody debris and channels exhibiting high width-to-depth ratios. Professional
judgement is critical component to evaluate whether assessment results actually reflect conditions
outside the range of reference conditions, and whether active habitat management or reliance on natural
recovery processes are the most appropriate coarse of action in a given watershed setting.
Summary of Habitat Objectives
Box and whisker plots with table of descriptive statistics are shown in Figure 18, 19, and 20. Box and
whisker plots show median, and upper and lower quartile. A table of sample count and percentile values
has been added to each Figure.
90
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Aquatic Habitat Indicators APPENDIX B
Summary and Recommendations
The interim fish habitat objectives for the Tongass National Forest should be characterized as an initial
step toward development of objective, quantifiable indicators offish habitat condition and general stream
health. These objectives are an important component of ecological based standards for riparian and
watershed management in the Alaska Region.
Analysis of the current Tongass stream habitat data base and the associated fish habitat objectives
indicate that refinements are needed to improve future utility of these management tools. Limited sample
sizes, uneven geographic distribution of samples and lack of fully standardized measurement procedures
are major deficiencies (Coghill 1996). The AFHA (1995) report made several recommendations on how
to move forward toward the goal of developing more robust stream habitat objectives:
• Standardized data-collection and data-management procedures.
• Fill data gaps with respect to samples within aquatic ecological units and broad geographic areas.
• Establish a network of reference streams to monitor changes in habitat indeces over time.
• Modify and expand upon these initial habitat indicators.
The Alaska Region is implementing a long-term strategy for improving basic aquatic habitat data and
habitat indicators for the Tongass and Chugach Forests based on the above recommendations. A
Regional Aquatic Ecosystem Management Handbook (in-press) outlines procedures that will improve the
precision and reduce observer bias in collection of stream habitat data. Tightened measurement for
pools, for example, include hydraulic control criteria, and minimum pool size and residual depth criteria.
The new regional protocol has also adopts more consistent, streamlined measurement procedures for
large woody debris.
Table 9 compares the interim and revised habitat indices that will be derived from survey and monitoring
data collected using the new stream survey protocol. The revised fish habitat indicators will be based on
metrics that are independent of stream discharge to help reduce measurement error.
91
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Aquatic Habitat Indicators
APPENDIX B
Table 9. Comparisons of Interim (AFHA 1995) and revised (in-press) Fish Habitat Indicators for
the Tongass National Forest.
Interim Fish Habitat Indicators 1995
pool area (%)
large woody debris (# pieces/1 000 m^
bankfull width-depth ratio
Revised Alaska Region Habitat Indicators
pools (frequency/unit length of channel)
pools (frequency/unit channel width)
max. residual pool depth
large woody debris (# pieces/unit length)
key pieces of wood (# pieces/unit length)
bankfull width-depth ratio
stream bed substrate (D50/D84)
Finally, a network of stream reference reaches are being established as part of the Tongass Forest Plan
monitoring and evaluation strategy. Measuring trends at permanent reference reaches eliminates
between-stream variance when determining changes in stream habitat conditions over time in managed
watersheds. Use of control sites in unmanaged watersheds will help determined if measured changes
can be attributed to management activities.
References
Coghill, K. 1996. Unpublished report: An evaluation of the statistical power of existing stream survey dat
on the Tongass National Forest, with recommendations for an improved monitoring program. PNW
Research Station, Juneau, AK. 9p.
Maxwell, J.R., C.J. Edwards, M.E. Jensen, S.J. Paustian, H. Parrott, and D.M. Hill. 1995. A hierarchical
framework of aquatic ecological units in North America (Nearctic Zone). Gen. Tech. Rep. NC-176. USDA
Forest Service, North Central Forest Experiment Station. 72p.
Paustian, S.J., editor. 1992. A channel type users guide for the Tongass National Forest, southeast
Alaska. USDA Forest Service, Alaska Region. R10 Technical Report, 26. 179p.
Report to Congress: Anadromous fish habitat assessment (AFHA) 1995. USDA Forest Service, Alaska
Region. R10-MB-279.
Land and resource management plan: Tongass National Forest (TLMP) 1997. USDA Forest Service,
Alaska Region. R10-MB-338dd.
92
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Aquatic Habitat Indicators
APPENDIX B
Admiralty Island
Subsections and Watersheds
SAV - South Admiralty Volcanics
HGC - Hood-Gambler Carbonates
MHL - Mitchell Hasselborg Lowlands
TB - Thayer Batholith
GPV - Glass Peninsula Volcanics
NAR - North Admiralty Range
NAL - North Admiralty Lowlands
Alaska
North
Coast SubreQion
Figure 17. Landscape stratification at the subsection level of ecological hierarchy.
93
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Aquatic Habitat Indicators
APPENDIX B
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30
20
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FP
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LC
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MM
FP3
FP4
FP5
MM1
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37
8
12
19
15
15
17
5
13
7
25th
27
14
8
11
20
20
35
47
28
2
50th
49
26
20
22
35
53
47
51
40
22
75th
61
40
27
39
52
76
59
60
52
39
FP3 FP5 LC MM1
FP4 HC MC MM2
Channel Type/Process Gp.
Figure 18. Quartile ranges and interim pool area (%) objectives by process group and channel
type, Tongass National Forest pool indices.
en
^ bu
0) (N
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Channel Type-Process Gp.
Figure 19. Quartile ranges and interim large woody debris (# pieces/1,000 m2) by process group
and channel type, Tongass National Forest large woody debris indices.
94
-------
Aquatic Habitat Indicators
APPENDIX B
Bankfull width to depth
(dimensionless ratio)
-* M o *>. tn a* •**
DOOOOOOO
1
Median
Q1
•
•
\- \-
h 1-
• "^
P.G./
C.T.
FP3
FP4
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MM2
N
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8
16
30
9
17
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13
25
45
12
24
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18
35
70
18
33
FP3 FP5 MM2
FP4 MM1
Channel Type
Figure 20. Quartile ranges and interim stream width-to-depth ratio indices by process group and
channel type, Tongass National Forest width-to-depth indices.
95
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Aquatic Habitat Indicators APPENDIX C
APPENDIX C: SUMMARY OF RECOMMENDATIONS FOR SALMONID HABITAT
QUALITY
State and federal agencies or other organizations have examined the habitat requirements and habitat
stressors and have made varying recommendations for minimal conditions or observations on the habitat
needs.
The table lists papers that have included a recommendation for numerical values for salmonid habitat
quality. The summary addresses variables that are commonly evaluated in habitat inventory and
assessment. This includes Large Woody Debris, Substrate/Fine Sediments, Pool Occurrence and
Quality, Channel Dimension, Turbidity, and Temperature. Vegetation characteristics related to shade and
overhead cover have not been addressed.
96
-------
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Carlson, A.; M. Chapel; A. Colborn; D. Craig; T. Flaherty; C. Marshall; D
Pratt; M. Reynolds; S. Tanguay; W. Thompson, and S. Underwood. Old
Forest and Riparian Habitat Planning Project. Tahoe Nat. Forest; 1991.
-
X
X
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urbidity/
ediment
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X
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Peterson, N. P; A. Hendry, and T. P. Quinn. Assessment of cumulative
effects on salmonid habitat: some suggested parameters and target
conditions. Timber Fish and Wildlife, TFW-F3-92-001 ; 1992.
0)
X
o"
Platts, W. S. et. al. Preliminary status report on bull trout in California, Idar
Montana, Nevada, Oregon, and Washington. Don Chapman Consultants
Inc.; 1993.
CD
X
Raleigh, R. F.; T. Hickman; R. C. Solomon, and P. C. Nelson. Habitat
suitability information: Rainbow trout. U.S. Fish and Wildlife Services
FWS/OBS-82/10.60; 1984.
^
X
X
(/) ,
Rhodes, J. J. et. al. A coarse screening process for evaluation of the effec
of land management activites on salmon spawning.... Columbia River Inte
Tribal Fish Commision, Technical Report 94-4; 1994.
(N
X
•c
Spence, B. C.et. al. An ecosystem approach to salmonid conservation, Pa
II: Planning elements and monitoring strategies. DRAFT. Management
Technology, TR-501 -96-6057; 1996 May.
CO
X
SI
in
The Independent Scientific Group. Return to the river, restoration of
salmonid fishes in the Columbia river ecosystem. Columbia River Basin F
and Wildlife program of the Northwest Power Planning Council. 1996.
?
X
X
X
X
USFA & USBLM. (PACFISH). 1995 Feb.
in
X
X
X
T-
USFS & USBLM. Eastside Draft Environmental Impact Statement, Volume
Interior Columbia Basin Ecosystem Management Project; 1996.
CD
X
X
X
>• 0
Washington Forest Practices Board. Board Manual: Standard Methodolog
for Conducting Watershed Analysis, Under Chapter 222-22 WAC. 1994 N
£
-------
Aquatic Habitat Indicators Appendix D
APPENDIX D: BIBLIOGRAPHY
The annotated bibliography is on the Environmental Protection Agency Region 10
Internet web page at:
http://www.epa.gov/r1 oearth
99
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