**Analytical Framework and Study Plan Outline**

**The United States Bureau of Reclamation-Funded**

**John Day River Oregon**

**Research**

Prepared by

Nick Bouwes (editor)

Eco Logical Research

Analytical Framework Committee Members:

Peter Bayley

Mark Bowen

Don Butcher

Guillermo Giannico

Scott Heppell

Chris Jordan

Phil Larsen

Hiram Li

Michael Newsom

Jim Ruzycki

August 11, 2004

**Table of Contents**

[LIST OF FIGURES ii](#__RefHeading___Toc80112503)

[1.0 INTRODUCTION 1](#__RefHeading___Toc80112504)

[2.0 OVERVIEW OF THE ANALYTICAL FRAMEWORK
2](#__RefHeading___Toc80112505)

[3.0 IDENTIFYING FACTORS LIMITING SALMON AND STEELHEAD PRODUCTION IN THE
JOHN DAY RIVER BASIN 9](#__RefHeading___Toc80112506)

[4.0 Ongoing Research, Monitoring and Evaluation projects in the John
Day Basin 18](#__RefHeading___Toc80112507)

[**4.1 The Status and Effectiveness Monitoring Group**
18](#__RefHeading___Toc80112508)

[**4.1 The Status and Effectiveness Monitoring Group**
18](#__RefHeading___Toc80112509)

[**4.1.1 EMAP- Western Pilot Project** 18](#__RefHeading___Toc80112510)

[**4.1.2 PIBO Effectiveness Monitoring Program**
19](#__RefHeading___Toc80112511)

[**4.1.3 ODFW Habitat and Riparian Survey**
20](#__RefHeading___Toc80112512)

[**4.2 The Freshwater Production Group**
22](#__RefHeading___Toc80112513)

[**4.3 GIS Group** 24](#__RefHeading___Toc80112514)

[**4.4 Landscape Changes and Patterns Project**
27](#__RefHeading___Toc80112515)

[**4.5 John Day River Basin Airborne TIR Remote Sensing & Spatial Data
Analysis Project** 28](#__RefHeading___Toc80112516)

[**4.6 Assessment of Stream Bed Substrate Stability and Excess Sediment
Project** 29](#__RefHeading___Toc80112517)

[**4.6 John Day TMDL project** 31](#__RefHeading___Toc80112518)

[**4.7 Juvenile salmon and steelhead production project**
33](#__RefHeading___Toc80112519)

[**4.7.1 Study** 33](#study-1)

[**4.7.2 Study 2** 34](#study-2)

[**4.7.3 Study 3** 35](#study-3)

[**4.7.4 Framework for juvenile production project**
36](#framework-for-juvenile-production-project)

[**4.8 Push-up dam removal project** 36](#__RefHeading___Toc80112524)

[5.0 Project Synthesis 38](#__RefHeading___Toc80112525)

[**5.1 Exploratory research** 38](#__RefHeading___Toc80112526)

[**5.2 Identifying effective mitigation strategies**
44](#__RefHeading___Toc80112527)

[6.0 Literature Cited 47](#__RefHeading___Toc80112528)

[APPENDIX: ORIGINAL PROPOSALS 53](#__RefHeading___Toc80112529)

**List of Figures**[]{#__RefHeading___Toc80112503 .anchor}

[**Figure 1.** Hierarchical scales for spatial references and fish
populations. 4](#__RefHeading___Toc80112530)

[**Figure 2**. Development of the over-arching question using
exploratory research describe in this document
8](#__RefHeading___Toc80112531)

[**Figure 3**. Land use practices in the John Day Basin that can
potentially impact fish production. 14](#__RefHeading___Toc80112532)

[**Figure 4.** The relationships between riparian vegetation and stream
conditions. 16](#__RefHeading___Toc80112533)

[**Figure 5.** Longitudinal temperature patterns for the Middle Fork
John day at Mid-August discharges 17](#__RefHeading___Toc80112534)

[**Figure 6.** Conceptual framework for geospatial information to
coordinate research efforts in the John Day Basin
26](#__RefHeading___Toc80112535)

[**Figure 7.** A schematic of the different research projects in the
John Day River Basin 40](#__RefHeading___Toc80112536)

[**Figure 8.** A schematic of the different research projects in the
John Day River Basin 43](#__RefHeading___Toc80112537)

[**Figure 9.** A hypothetical example of how synthesis of the John Day
RME efforts may be used by the AFG to identify, design, and test
restoration approaches in John Day Basin
45](#__RefHeading___Toc80112538)

**1.0 INTRODUCTION**[]{#__RefHeading___Toc80112504 .anchor}

In 2000, the National Marine Fisheries Service (NMFS) issued a
Biological Opinion describing operations of the Federal Columbia River
Power System (Opinion). The Opinion included 199 Actions under a
Reasonable and Prudent Alternative (RPA) to avoid jeopardy. The Action
Agencies for the Opinion - the US Bureau of Reclamation (Reclamation),
the Bonneville Power Administration (BPA), and the US Corps of Engineers
(Corps)- are implementing habitat actions and a research, monitoring,
and evaluation (RME) program under the RPA to improve habitat and
migratory pathways in the Action Area of the Opinion.

The basic outline for this program is discussed in the Action Agencies
new Proposed Action for the draft 2004 FCRPS Biological Opinion. The
Action Agencies will implement action effectiveness research through
pilot studies in key basins where the research will contribute to the
overall goal of understanding how to meet the hydrosystem survival gap
most efficiently. The Action Agencies will concentrate on four types of
tributary actions in the Action Area: entrainment, instream flow,
channel structure, and riparian habitat. These actions affect the
primary limiting factors for salmonids in the Action Area: direct
mortality, water supply, food supply, temperature, sedimentation, and
cover. The action agencies will assess the limiting factors on a
periodic basis in those subbasins to ensure that the tributary actions
are addressing the correct factors.

The Action Agencies have initiated pilot studies in the John Day basin
which will continue to inform Reclamation's proposed conservation
measure for Mid-Columbia steelhead, and these studies will continue for
the duration of that conservation measure. The John Day pilot study is
important because (1) the John Day basin is represented by several
populations of the Mid-Columbia steelhead; (2) there is an opportunity
to build quickly on past research in the basin to develop answers to key
management questions; (3) past information suggests that focused
research should address water supply, temperature, and sediment
potential key limiting factors; (4) there is little influence of
hatchery fish in the basin; (5) the basin has key sites where fish traps
can be effectively located; and (6) the information from the research is
likely to be transferable to other ESUs.

The John Day RME program will focus on two anadromous fish species:
spring/summer chinook (*Oncorhynchus tshawytscha*) and (*Oncorhynchus
mykiss*). Ocean-going, anadromous, *O. mykiss* are referred to as
steelhead. Steelhead in the John Day River are part of the Mid-Columbia
Evolutionarily Significant Unit and were listed as threatened by NMFS in
1999 (64 FR 14517). The RME program described in this document will be
used to help identify environmental variables most influential to
freshwater production of these species, and effective mitigation efforts
to rebuild these populations. To aid in the coordination of the John Day
RME program, four workgroups have been established; the Freshwater
Production Group, the Habitat Monitoring Group, the GIS Group, and the
Analytical Framework Group (AFG).

The intention of the AFG is to provide a forum to discuss the various
research strategies in the basin, outline research needs, ensure
continuity between the different projects, reduce duplication of
efforts, and integrate research results, and develop appropriate
mitigation experiments. Most members of the AFG are currently involved
in research within the basin, and therefore are familiar with this
system. This collective knowledge is useful in outlining feasible
research programs. Also, while a comprehensive evaluation of factors
that are potentially limiting freshwater production of salmon and
steelhead will be conducted, this past experience can help identify
problems areas where research should focus in order to develop 'fast
track' mitigation strategies to provide immediate benefits to
populations in peril.

The AFG has begun to develop a framework to summarize and identify
research needs to determine the role of biotic and abiotic factors on
the freshwater production of salmon and steelhead. A set of questions
that potentially need to be addressed in order to design effective and
efficient mitigation programs has been developed. The goal of this
document is to first describe this framework and then summarize ongoing
and proposed studies in an attempt to coordinate research within the
basin and to identify additional research needs. This will provide a
central reference document that will allow researchers to have a
comprehensive understanding of the information that will be available
from the various research projects. Much of the data gathered from this
research will be archived in a GIS format and made accessible to all
researchers. Information sharing will stimulate more comprehensive and
creative studies, increase the cumulative understanding of ecological
processes, and increase the overall efficiency in identifying the proper
mitigation strategies most beneficial to these populations.

Another role of the AFG is to review and synthesize information from
this research. This synthesis will be used to design an Intensive
Watershed Study in which mitigation strategies will be implemented in an
experimental management approach. This effort will commence following
the 2004 field season.

This document focuses on issues raised by the AFG. Topics related to
status and effectiveness habitat monitoring are addressed by the Status
and Effectiveness Habitat Monitoring Group. Subbasin smolt production
estimates are dealt with by the Freshwater Production Group. Issues
related to archiving data in a geospatial data base are dealt with in
the GIS group. To provide the reader with some concepts of the issues in
these other workgroups, a short synopsis of those efforts are provided
below.

**2.0 OVERVIEW OF THE ANALYTICAL
FRAMEWORK**[]{#__RefHeading___Toc80112505 .anchor}

Historically, conceptual frameworks to aid in understanding of stream
processes and structure were based on time-invariant, longitudinal
concepts of the lotic system (Vannote et al. 1980) and seasonal
hydrological effects on river-floodplains at different scales (Junk et
al. 1989). Because streams are highly complex and dynamic in a nested
hierarchy, several stream ecologists have argued that ecological
processes in lotic systems can be conceptually organized in a
hierarchical framework (Frissell et al. 1987, Johnson et al. 1995,
Hunsaker and Levine 1995, Ward 1998). This hierarchical approach has
been more specifically applied to fish ecology in streams (Schlosser
1991, Schlosser and Angermeier 1995, Fausch et al. 2002). This approach
is also important for developing management actions because humans alter
the landscape at multiple scales, and thus the consequences from these
disturbances must be viewed in the appropriate context (Risser et al.
1999, Fausch et al. 2002). Fausch et al. (2002) have argued that
successful fish management and conservation programs require bridging
the gap in understanding between small and large scale processes, often
not considered by researchers. They propose five principles to help
generate useful information for the development of effective management
plans for stream fishes. First, research must be conducted at the
appropriate scales of the question of interest. Second, different
physical and ecological processes will be revealed at different
spatiotemporal scales, but processes may interact among scales. Third,
rare or unique features or events can have large effects on fish
populations. Fourth, anthropogenic habitat degradation can have impacts
in multiple directions, upstream and downstream. Finally, fisheries
ecologists must strive to make observations and test predictions at
similar scales in which managers operate. We have decided to heed this
advice and take a multiscale approach to assess the impact of
potentially limiting factors in the John Day basin. A spatially
hierarchical framework is useful in organizing this approach.

The range of factors we explore extend from the broadest scale of the
John Day basin and their impacts on salmon and steelhead populations and
subpopulations, to localized sites that affect individuals or small
groups of fish (Figure 1). Large scale processes set the template for
these small processes. To simplify discussion, we define three sets of
scales: (1) basin and subbasin, (2) small watershed and reaches, and (3)
habitat and microhabitat scales. The meaning of 'scale' here refers to
the spatial and temporal scales to which data are aggregated to address
the issue, and therefore reflects the minimum resolution to which
processes or mechanisms can be considered. The scale to which inferences
are attempted can be larger, such as a trend suggested by a series of
annual measurements.

**Figure 1.** Hierarchical scales for spatial definitions and
corresponding levels of organization for fish (dashed line indicates
nested component).[]{#__RefHeading___Toc80112530 .anchor}

\(1\) Information pertaining to basin/subbasin landscape and land use
patterns will be collected and may include variables such as: soil and
geology types, precipitation, hydrology, stream temperatures, air
temperatures, climatic factors (longer term), fire (size, frequency and
intensity), landslides, flood events, management activities (e.g.
mining, timber harvest, grazing, etc.), ownership boundaries, road
density, water use (points of use and return), diversions and barriers,
and culverts, and agricultural and urban development. These potential
important factors may be collected directly at this large scale (remote
sensing), or when collected on-site at smaller scales, need to be
summarized at the appropriate sub-basin or basin scale. This information
should include, where possible, historical and current conditions so
that population trends can be linked to changes in habitat condition
summarized at the appropriate temporal scales. Salmon and steelhead
information at these larger scales will mainly include basin and
subbasin estimates of spawner (redds) numbers and smolt production at
the population level over several year-classes or at an inferred
metapopulation level. Some studies conducted at these scales tend to be
descriptive in nature, but even qualitative contrasts can be assessed
given a meaningful response that can be measured. By definition, the
largest scale considered (basin) cannot be replicated or compared
spatially, but temporal changes at the basin and subbsain scales can and
should be pursued despite the statistical challenges. Long-term natural
or semi-managed experiments using consistently measured and aggregated
information, ideally incorporating an adaptive (experimental) management
approach, would provide clues to regulation of salmonid populations of
most direct relevance to fishery managers.

\(2\) At the intermediate scales of small watersheds and stream reaches,
relationships need to be identified and quantified between
characteristic sets of habitats that includes their geographic
relationship, and associated biological characteristics that affect fish
behavior, growth, and survival. It is at these scales that fishes carry
out important aspects of their life-history (Fausch et al. 2002).
However, larger scale processes must be used as the context to qualify
conditions in which these processes occur. In addition, larger scale
information may also be used as a template to help define reaches.
Habitat and land use information, appropriately summarized to the scale
of the response, may include: physical dimensions and instream habitat
characteristics (e.g., gradient, depth and area of pools, riffles,
structure and substrate), channel type, valley type, temperature,
oxygen, springs, riparian characteristics (e.g. vegetation type and
extent, density, canopy cover), primary and secondary production, water
use (points of use and return), diversions and barriers, and culverts,
grazing, and pollutants. Appropriate responses for salmon and steelhead
include: density, size structure, growth rate, behavioral patterns,
survival, recruitment, and production at the population or subpopulation
level for the age groups concerned. Typically one year would be an
appropriate temporal scale for small watersheds, although within-season
attributes, such as density or growth responses, may be more appropriate
at the reach scale.

\(3\) At the smallest, habitat and microhabitat scales, causal
mechanisms at the individual or local, subpopulation levels need to be
explored to help explain or give credibility to consistent larger scale
patterns and relationships, keeping in mind that phenomena at small
scales can be 'filtered out' or expressed in an unexpected manner at
larger scales. Questions at these scales often provide the option of
field, laboratory, or natural experiment approaches. A natural
experiment either requires a specific design of sampling at the habitat
level (or habitat combination, such as pool-riffle), or utilizes
information from one or more monitoring programs. Given the large number
of samples required, the latter is preferable economically, but requires
careful trade-offs between the needs of studies relating to different
questions and scales. Fish and habitat measures need to be taken at
these small scales whatever the ultimate scale over which those measures
are aggregated spatially and temporally, and many monitoring sites are
also needed to ground truth large-scale information from remote sensing.
Examples of small scale studies might include the response of salmon and
steelhead individuals or local populations to temperature, pool or
riffle characteristics, substrate type, and water velocity. Also,
primary and secondary production, intra- and interspecific interactions
(i.e. competition and predation), hydrogeomorphic habitat preferences,
physiological responses, feeding behavior, and spawning behavior may
either be of interest or need to be taken into account. Temporal scales
of one season or less would typically be most appropriate for these
small spatial scales. In some cases, especially with field experiments,
aggregating data over daily time periods is more appropriate.

The research in the JDA is a multiscale program in that questions are
being investigated at different scales, but does not presume that
processes or mechanisms are transferable in a predictable manner across
scales. A hierarchical scale concept is useful in directing our
approach, but actual relationships among scales are much more complex. A
major challenge is to find those processes that have some degree of
additively so that inferences and meaningful conclusions can be made at
larger scales. This is not just an academic issue. For example, strong
inference of an adverse effect of push-up dams at the habitat level (3)
on subpopulations may be evident, but be insignificant and overridden by
other processes at the subbasin scale (1) on the population. Therefore
management changes at the local scale should not be expected to have a
population-level benefit under this scenario. With such issues in mind,
researchers are encouraged to collaborate early in the program to
determine the feasibility and development of parallel questions that can
be addressed at two or more scales. Such discourse has already taken
place in the AFG.

The above discussion outlines the theoretical background for
investigating the influence of multiple factors on salmon and steelhead
behavior, growth, survival, and ultimately production over a wide range
of scales. At the beginning of a research program, review of past
literature and experience, existing theory, is needed to guide research
designs. Much of this review has occurred, and a set of studies have
been proposed and initiated to investigate this large scope of diverse
topics. By necessity, these studies are conducted by researchers from
several institutions and agencies. This diverse research is expected to
occur over the next several years. One of the main tasks of the AFG is
to coordinate these efforts, refine research designs, synthesize the
results of multiple studies, and put this information into the larger
context useful for the management of salmon and steelhead populations.

While specific studies in the JDA may lead insight into general
ecological processes, the ultimate goal of the collective research
program is more practical in nature; to identify effective mitigation
strategies for salmon and steelhead. Thus, the over-arching question
that this research as a whole is expected to address is: Can restoration
actions aid in the recovery of salmon and steelhead in the JDA?
Individual research projects in the JDA may address more specific
questions that are manageable on a study-by-study basis. The AFG,
however, must synthesize the information obtained from these studies to
refine this overarching question, and eventually develop specific
hypotheses addressing the impact of mitigation actions on fish
production that can be addressed at the relevant scale (e.g. watershed)
through an experimental management approach (Figure 2). Thus, relative
to the over-arching question, the research described in this document is
somewhat exploratory and will help: formulate more precise hypotheses;
design large-scale restoration actions in the form of an experiment to
test these hypotheses; and design effectiveness monitoring programs to
detect the effects of these actions. Researchers cognizant of the
over-arching question, study approaches and results occurring at
different scales may more effectively incorporate their research into a
greater context and thereby qualify their inferences more realistically
and develop more meaningful hypotheses for subsequent research.

**Figure 2**. Development of the over-arching question using exploratory
research describe in this document[]{#__RefHeading___Toc80112531
.anchor}. The goal is to use this research to refine the question and
design hypotheses that can be tested at the appropriate scale to
determine whether specific restoration actions can be used to recover
salmon and steelhead populations within the John Day Basin (modified
from Ford 2000).

**3.0 IDENTIFYING FACTORS LIMITING SALMON AND STEELHEAD PRODUCTION IN
THE JOHN DAY RIVER BASIN**[]{#__RefHeading___Toc80112506 .anchor}

The general intentions of the AFG are described above. The following
discussion focuses on how factors limiting salmon and steelhead
production in the JDA will be addressed. First, we identify questions
that if addressed could lead to considerable insight in the factors most
likely affecting fish production. We also provide some discussion on
some of the factors where past knowledge has suggested may be important
and worth pursing intensively to quickly develop related mitigation
strategies.

Based on experience and knowledge of factors affecting the survival of
growth of salmonids in the JDA and other basin, the AFG has developed
potential questions and examples that might be addressed by research. An
exhaustive list of important questions will help generate discussion and
develop research goals in the JDA. Questions of interest at each scale
include:

[Basin/subbasin scale]{.underline}

What is the freshwater productivity of the salmon and steelhead
population in the JDA Basin and subbasins?

-   What is the spawning success of salmon and steelhead?

-   What is the survival of eggs during incubation?

-   What is the survival during rearing stage of juvenile salmon and
    steelhead?

What are the major landscape patterns in the JDA basin and subbasins?

-   soil type

-   geology type

-   precipitation

-   topology/hydrology

-   air temperature

-   precipitation

-   stream temperatures

-   fire impacts

-   landslides

-   flood events

-   beaver ponds

What are the major land use patterns in the JDA basin and subbasins?

-   agriculture

-   grazing

-   forestry

-   mining

-   urbanization

-   road density

-   culverts/passage barriers

How do landscape/land use patterns relate to freshwater production of
fishes?

What are the major landscape/land uses that can be altered through
management activities?

[Watershed/reach scale]{.underline}

What is the local freshwater productivity of salmon and steelhead?

-   What is the spawning success of salmon and steelhead?

-   What is the survival of eggs during incubation?

-   What is the survival during rearing stage of juvenile salmon and
    steelhead?

What is the status of local habitat features?

-   physical dimensions and instream habitat characteristics

    -   gradient

    -   depth

    -   pool area

    -   riffles

    -   structure and substrate

-   channel type

-   valley type

-   temperature

-   oxygen

-   springs

-   riparian characteristics

    -   vegetation type and extent

    -   density

    -   canopy cover

-   water use (points of collection and return)

-   diversions and barriers

-   primary/secondary production

-   sediment input

-   salinity/toxins

What are the major habitat factors limiting local fish production?

-   Fine sediment loading

    -   loss of spawning gravel → reduced spawning success/egg survival

    -   loss of ground/surface water exchange → increased water
        temperature → unsuitable habitat leading to reduced growth and
        survival

    -   loss of habitat complexity for benthic invertebrates → decrease
        secondary production → reduced juvenile salmonid growth and
        survival

-   Riparian vegetation loss

    -   increase solar inputs → increased water temperature → unsuitable
        habitat leading to reduced growth and survival

    -   increase sedimentation → increased water temperature →
        unsuitable habitat leading to reduced growth and survival

    -   decrease ground/surface water exchange → increased water
        temperature → unsuitable habitat leading to reduced growth and
        survival

    -   decrease large woody debris input → reduced cover and substrate
        → decrease refugia and primary and secondary production

-   Passage barriers

    -   decreased or no movement downstream or between suitable habitat
        types → use of unsuitable habitat leading to reduced growth and
        survival

-   Water withdraws

    -   entrainment

    -   water return of warmer, lower quality water → unsuitable habitat
        leading to reduced growth and survival

-   Water temperatures → unsuitable habitat leading to reduced growth
    and survival

-   Salinity/toxins → unsuitable habitat leading to reduced growth and
    survival

What are the major biotic factors limiting local fish production?

-   Predation

    -   fish (e.g. adult trout)

-   Secondary production → inadequate production leading to reduced
    growth and survival

    -   nutrients/primary production

    -   substrate

    -   competition

What are the interactions between physical and biotic factors that limit
local fish production?

-   temperature and secondary production (food may be limiting because
    elevated stream temperature is too high but temperature still below
    maximum cardiac output)

-   water temperature and predation

-   elevated stream temperatures can increase disease virulence

-   sedimentation and secondary production

    -   loss of refugia

    -   loss of quality primary production

-   nutrients and secondary production

What are the interactions between basin/subbasin features with
watershed/reach habitat?

-   landscape/land use features and stream reach temperature

-   landscape/land use features and sediment load

-   landscape/land use features and riparian vegetation

-   landscape/land use features and ground/surface water exchange

What is the scale at which mitigation efforts need to occur in order to
have impact on salmonid production?

Attempts to answer these questions may provide insight into important
mechanisms regulating fish production. In addition, results from such
research will likely aid in developing effective mitigation strategies.
While several factors in the list above will regulate fish production,
many of these controlling factors are inherent properties of the JDA
Basin and are not subject to change through restoration actions, such as
climate and geology types. Development of effective mitigation
strategies should focus on mutable characteristics of the environment.
The greatest mitigation opportunities likely lie within the alteration
of current land use activities that have had large impacts on the John
Day Basin. Several land use activities have large impacts on watersheds
that have affected fish production. Broad categories of these activities
can be defined as agriculture, grazing, mining, forestry, and
urbanization. Below is a brief discussion of how these practices can
have negative impacts on fish survival and growth resulting in a
decrease in freshwater productivity of salmon and steelhead in the JDA.

Several aspects of agriculture can have impacts on stream habitat. In
the JDA, large agricultural crops include alfalfa, grass, and clover to
feed livestock. Irrigation occurs mainly in the upper mainstem John Day
from Picture Gorge to the Blue Mountain Hot Springs, in areas of the
Middle Fork, and in the lower areas of the North Fork (PEA 2003). There
are also considerable irrigation withdrawls in the lower mainstem from
Service Creek to Kimberly. In order to grow these crops, pumps and
diversions are used to provide irrigation. Over 300 pump stations and
permanent diversions are not screened to NOAAF standards in the John Day
Basin, resulting in entrainment of juvenile salmon and steelhead (PEA
2003). Push-up dams are temporary water diversions used to flood
irrigate land made by piling dirt, rock, sandbags, and rip-rap into 2-10
ft high dams. Construction of these dams generally requires the
in-stream use of heavy equipment, which results in disturbance of the
channel and bank habitat creating large sediment inputs. Push-up dams
require maintenance one to several times a year., It is estimated that
there are up to several hundred of these structures present in the JDA
basin (PEA 2003). Diversions, including push-up dams, can act as
barriers to juveniles searching for suitable habitats and to adults
migrating to natal spawning territories. Also, unused water returning to
the river is often much warmer and contains sediments, nutrients, and
pesticides that can decrease water quality. Reduction in the volume of
water in the main channel allows for a more rapid increase in stream
temperatures as well. In addition to the impacts of water withdraws, the
loss of perennial vegetation and yearly soil turnover increases sediment
load to the river. Sediments fill in spawning gravels and cobble
important for primary and secondary production. Stream sedimentation
also decreases subsurface/surface water exchange that can affect water
temperatures. Thus, relevant question concerning the impacts of
agriculture on fish production include: Are there alternative
agriculture practices that can reduce these negative impacts?; Are there
ways to mitigate for past agricultural impacts?

Cattle and sheep graze in several USFS and private lands throughout the
JDA Basin. Grazing has direct impacts to stream habitat. Erosion of
stream banks due to trampling and loss of riparian vegetation from
overgrazing increases sedimentation and channelization. In addition,
increases in stream temperature results from loss of riparian cover
increasing solar input and decreased ground/surface water exchange due
to soil compaction, loss of extensive roots systems from riparian
vegetation, and stream sedimentation. Soil compaction can also prevent
recruitment of vegetation and wetlands. Can grazing practices be altered
to decrease these impacts? Are there ways to mitigate for these effects?

Mining occurs throughout the JDA drainage. Most commercial and
recreational mining occurred historically; however, mining in the JDA
still occurs for gold and other precious metals (PEA 2003). Mining
occurs mainly on USFS lands on the Middle Fork and North Fork John Day
Rivers and their tributaries. A majority of the current mining activity
takes place on Granite Creek in the upper North Fork John Day (PEA
2003). In addition, rock and gravel extraction occurs throughout the JDA
Basin. Mining activities can increase in-river sedimentation, decrease
riparian vegetation, and add pollutants to the water leading to problems
described above. Can mining activities be reduced or altered to minimize
impacts? Can old mine sites be restored?

Timber harvest does not occur at the same intensity as in the past,
although this practice still occurs. Most timber harvest occurs mainly
in the upper portions of the basin. Loss of timber can result in the
destabilization of surface soils and increase sediment and nutrient
inputs to streams. This can have physical and biological consequences to
stream function. In addition, roads built to access timber are often
large sources of sediment input to streams. Long-term inputs of large
woody debris, which act as in-stream sediment traps, are often reduced
through timber harvest. Large woody debris is also important in
providing in-stream habitat and creating pools important to salmonids.
Riparian vegetation lost through timber harvest also allows for greater
solar input into surface water thereby creating warmer stream
temperatures. Deep extensive root systems are also lost reducing surface
water/ground water exchange that can lead to an increase in stream
temperatures. The impacts of forestry on stream function can have
considerable impacts on food web dynamics (Lowe et al. 1986, Newbold et
al. 1980). Are there alternative forestry practices that reduce impacts
on stream function in the JDA (e.g. increase riparian buffers,
alternative road construction)? Are there mitigation opportunities in
areas of past timber harvest?

The JDA Basin is over 20,000 km^2^ , with a total population of under
7,000. This is one of the most sparsely populated regions of Oregon. The
five largest cities are John Day (population 1,821), Prairie City
(population 1,080), Condon (population 759) Canyon City (population
669), and Mount Vernon (population 595) and are located in the Upper
John Day Subbasin (PEA 2002). Other towns include: Dayville (population
138) also in the Upper John Day Subbasin; Long Creek (population 228) in
the Middle Fork John Day Subbasin; Ukiah (population 255), Monument
(population 151) and Granite (population 24) are in the North Fork John
Day Subbasin (PEA 2002). Thus, urbanization occurs in a small area of
the JDA Basin and relative to several basins, little urban influence.
Nonetheless, urbanization could have point source impacts on salmonids
in the JDA basin. Areas of vegetated covered soils have been replaced by
non-permeable surfaces

**Figure 3**. Land use practices in the John Day Basin that can
potentially impact fish production.[]{#__RefHeading___Toc80112532
.anchor} Arrows point from the land use practices to habitat features
that could be affected that can ultimately impact fish production
directly or indirectly.

producing greater runoff that has gone through subsurface cooling. This
runoff can also carry pollutants (e.g. petroleum products) that can have
negative impacts on the survival of salmonid eggs and juvenile. Stream
channelization to reduce the effects of seasonal and flash flooding is
the result of human occupation of the landscape. The bulk of this was
done after the 1964 floods to convey the water quickly downstream.

Multiple land use practices have occurred in the JDA that could have
resulted in profound changes in the stream habitat important for the
freshwater life stages of steelhead and salmon (Figure 3). Many of these
land uses can be linked to changes in temperature (Figure 3). Change in
the thermal structure of the John Day River is thought to be very
important in limiting the production of coldwater fishes. The AFG has
agreed that research focused towards temperature impacts on fish
production is the highest priority, and thus, the role of temperature on
stream ecology is discussed in detail.

Stream temperature patterns result from the interaction of important
physical and ecological processes acting within the landscape (Ward
1985). Geomorphic conditions affect stream temperature through a variety
of ways. Stream temperatures can be moderated by groundwater inputs and
hyporheic exchange, the quantity of which may be influenced by the width
and composition of the alluvial floodplain (Stanford and Ward 1993).
Stream channel structure influences the extent of floodplain aquifer
recharge during seasonal floods, hyporheic exchange, hydraulic
conductivity, flow, retention time, heat gained by the stream from solar
radiation, and heat lost from the stream through evaporative processes.
Factors that disturb riparian vegetation can increase insolation and
stream temperatures (Beschta et al. 1987). Aspect and topographic
shading affect solar input to the streams. Vegetative structure and
condition will also affect rates of water infiltration and surface
runoff to streams, hydraulic conductivity via soil porosity and via
extensive rooting networks (Figure 4).

Stream temperatures can have direct impacts on salmonids through changes
in growth rates, the severity of stress imposed by environmental
toxicants (Schreck and Li 1991), the nature and intensity of intra- and
interspecific interactions (Reeves et al. 1987), and alter relationships
between immunocompetency of fishes and pathogens (Becker and Fugiyama
1978, Avatilion et al. 1980, Avatilion 1981). Lack of growth can lower
survival due to increased vulnerability to predation (Luecke et al.
1990, Miller et al. 1988), decreased migration and foraging capabilities
(Miller et al, 1988), and decreased fat storage needed for overwintering
(Reimers 1963, Cunjack 1987, 1988). The cumulative effects of
temperature on a population can be expressed through production
(survival and biomass) and is the population response of individual
growth and survival.

In the John Day River Basin, initial studies provide evidence that
stream temperatures may be a limiting factor for salmon and steelhead
spawning and rearing. Extensive temperature profiles reveal that in the
Middle Fork of the John Day, for example, in 1996, 28% of the stream,
temperatures were higher than optimal for salmonids, and in the
remaining areas temperatures were at lethal levels (Figure 5A&B). In
1995, temperatures ranged from near optimal to lethal during late summer
(Figure 5A). These results suggest that the thermal regime is
heterogeneous with extensive areas of unsuitable habitat.

> ![](media/image1.wmf){width="4.625in" height="3.7868055555555555in"}

**Figure 4.** The relationships between riparian vegetation and stream
conditions.[]{#__RefHeading___Toc80112533 .anchor}

Further evidence of temperature effects in the John Day come from
Torgersen et al. (1999) who found that adult spring chinook were able to
survive high stream temperatures by finding coldwater refugia. Salmon
carrying temperature-sensitive, radio tags were tracked to plumes of
coldwater 1-3°C cooler than the mainstream as detected by Forward
Looking Infrared (FLIR) imagery. These plumes were apparently connected
to groundwater inputs suggesting that the dynamics of water routing and
storage, particularly hyporheic water, was critical for salmon. Similar
behavior of using isolated thermal refugia has been noted for juvenile
salmonids in northeastern Oregon streams (Ebersole et al. 2003).

Because of the large influence of temperature on chinook and steelhead
biology (Schreck and Li 1991), and of the large anthropogenic habitat
changes in the John Day drainage that have likely altered stream
temperatures, we suspect that the survival and persistence of these
species may be dependent on our ability to alter this crucial factor.
Therefore, we have developed a research plan to help clarify the current
impacts of temperature on chinook and steelhead populations in the John
Day Basin and to develop mitigation actions to most efficiently
manipulate processes controlling stream temperatures and fish habitats.
It is important to acknowledge that temperature may not play a major
role in the productivity of salmon and steelhead; however, we believe
that, based on prior knowledge, studies evaluating this factor on the
onset may lead to time savings in developing mitigation strategies for
fish populations in peril.

![](media/image2.wmf){width="3.5in" height="2.0180555555555557in"}

![](media/image3.wmf){width="2.74375in" height="1.5277777777777777in"}

**Figure 5.** (A) Longitudinal temperature patterns for the Middle Fork
John day at Mid-August discharges[]{#__RefHeading___Toc80112534 .anchor}
130% (1996) and 150% (1995) of normal. (B) is the proportion of the
stream reaches in 1996 expressed in terms of generally accepted
physiological temperature categories for salmonids.

In addition to focusing a considerable amount of research to
understanding the role of temperature on salmonid production and factors
influencing temperature, the AFG has also decided that changes in
sediment input due to human activities leading to decreases in
production (Figure 3) should be evaluated in detail. Substrate
characteristics are often sensitive indicators of the effects of human
activities on streams (MacDonald et al., 1991). Streambed
characteristics are often cited as major controls on the species
composition of macroinvertebrate, periphyton, and fish assemblages in
streams (e.g., Hynes, 1972; Cummins, 1974; Platts et al., 1983). Along
with bedform (e.g., riffles and pools), substrate size is a primary
control on the hydraulic roughness and consequently the range of water
velocities in a stream channel. It also influences the size range of
interstices that provide living space and cover for macroinvertebrates,
salamanders, sculpins, and darters. Accumulations of fine substrate
particles fill the interstices of coarser bed materials, reducing
habitat space and its availability for benthic fish and
macroinvertebrates (Platts et al. 1983; Hawkins et al. 1983; Rinne
1988). In addition, these fine particles impede circulation of
oxygenated water into hyporheic habitats and salmonid eggs buried in
redds. Decreases in the mean substrate size and increases in streambed
fine sediments can destabilize stream channels (Wilcock 1988) and may
indicate increases in the rates of upland erosion and sediment supply
(Lisle 1982, Dietrich et al. 1989). In addition, large inputs of
sediment can lead to reduced channel complexity and frequency of pools
(Madej, 2001), which could alter the scale and relative magnitude of
hyporheic flow that depends upon streambed morphology (Kasahara and
Wondzell, 2003). Lack of exchange between surface and hyporheic waters
can result in elevated surface water temperatures.

**4.0 Ongoing Research, Monitoring and Evaluation projects in the John
Day Basin**[]{#__RefHeading___Toc80112507 .anchor}

Here we provide a short summary of the different research groups and
projects that are scheduled to occur over the next few years in the John
Day river basin. We address the general methods, objectives, questions,
and the scale that each project will focus. Further details of the
projects are provided in the following appendices. We then provide a
discussion of how the complement of the various research projects will
produce an outline of the processes that ultimately impact freshwater
production of salmon and steelhead in the basin.

**4.1 The Status and Effectiveness Habitat Monitoring
Group**[]{#__RefHeading___Toc80112508 .anchor}

As previous mentioned, the John Day River basin is one of three pilot
subbains in the Columbia River Basin where three novel RME programs will
be developed and tested: (i) subbasin-scale pilot status and trend
monitoring efforts for anadromous salmonids and their habitat, and
research investigating the ecological factors affecting salmonid
freshwater production, (ii) development of habitat restoration
activities to be tested in selected watersheds, and (iii) effectiveness
monitoring to evaluate the benefit of habitat restoration projects in
these selected watersheds. Therefore, the Status and Effectiveness
Habitat Monitoring Group will play an important role in
[]{#__RefHeading___Toc80112509 .anchor}the explicit development and
testing of the sampling designs, protocols and methodologies required
for generating habitat monitoring data of known spatio-temporal
resolution, accuracy and precision related to these three RME programs.
In addition, the group will insure that information gathered from the
monitoring programs will be archived in the GIS data dictionary (see
below). The group will also work with the AFG and Freshwater Production
Group to coordinate efforts, identify information needs, and synthesize
information for further RME activities. Three habitat monitoring
programs are currently implemented in the John Day Basin: ODEQ's EMAP-
Western Pilot Project, USFS's Pacfish/Infish Biological Opinions
Effectiveness Monitoring program (PIBO), ODFW's EMAP Habitat and
Riparian Survey. Below is a brief description of each program.

**4.1.1 EMAP- Western Pilot Project**[]{#__RefHeading___Toc80112510
.anchor}

The EMAP-Western Pilot Project is a partnership between the United
States Environmental Protection Agency and the Oregon Department of
Environmental Quality.  Project design and organization is under
direction of the USEPA, while field operations within John Day Basin are
managed by ODEQ's Laboratory Division\--Watershed Assessment Section. 
The EMAP program was created because conventional water quality surveys
were criticized regarding their inability to adequately assess
conditions of the nation's surface waters.  In response, the EMAP
program was designed by scientists within the USEPA to provide a
scientifically defensible method for assessing ecological integrity. 
EMAP differs from traditional water quality surveys by applying a more
holistic approach.  EMAP utilizes a suite of indicators spanning the
chemical, physical, and biological components of aquatic systems. The
goals of EMAP program nationally and in the John Day are to classify the
conditions of aquatic resources across larger scales or regions
(watersheds, basins, states, etc.).  The main objective is to identify
status and trends in ecological conditions across the study areas.

 

To draw larger scale inferences, EMAP relies on a probability based
survey design.  Sites are randomly selected across the scale of
interest, with each site representing a fraction of the total resource. 
In this way, the results of a single site represent a portion of a
larger population.  The strength of the EMAP program is in combining
results from single sites into a larger overall picture of ecological
integrity within a region. ODEQ measures several geomorphic and riparian
habitat variables in the John Day including flow, stream channel
profiles, slope, sediment composition, shade, vegetative layers-density
and complexity, and invasive plants (see Kaufmann et al. 1999 for more
details).

 

In addition, ODEQ monitors water chemistry including nutrients (C, P,
N), physical properties (pH, conductivity, temperature, etc.),
biological characteristics such as periphyton, macroinvertebrates,
aquatic vertebrates, and human disturbance at the watershed scale (GIS)
and reach scale.

**4.1.2 PIBO Effectiveness Monitoring
Program**[]{#__RefHeading___Toc80112511 .anchor}

The information for the PIBO Effectiveness monitoring program comes from
Kershner et al. (2004). The PIBO program monitors stream and riparian
habitat in the areas covered under the Biological Opinion for Bull trout
and Steelhead including the portions of the upper Columbia River basin
on USFS lands within INFISH and PACFISH, and BLM lands within PACFISH or
containing bull trout. At the landscape scale, the effectiveness
monitoring plan is intended to answer the question, "Are key biological
and physical attributes, processes, and functions of upslope, riparian,
and aquatic systems being degraded, maintained, or restored within the
geographic range of PIBO?" At the watershed scale, monitoring will be
used to assess the condition of individual watersheds and evaluate the
extent to which management practices are effective in maintaining or
restoring key ecological indicators.

PIBO is expected to sample approximately one-half of the potential
watersheds that have perennial streams and greater than 50 percent
Federal ownership above the sample reach over a 5 year period within the
geographic area. The same watersheds will be resampled over a subsequent
5-year period. This design is represented as a rotating panel that is
serially augmented and alternates over a given period (Urquhart and
others 1998). The subsample of reference and managed watersheds will be
randomly selected within the group. At full implementation (which began
in 2003), PIBO will be sampling 250 sub-watersheds per year or 1250
every 5 years within this area. An additional 50 sub-watersheds
(sentinel sites) will be sampled annually. In 2006, PIBO will begin
resampling reaches that were originally sampled in 2001. At this time,
PIBO will begin assessing changes in resource conditions given current
land management practices. In the John Day Basin, PIBO is expected to
sample between 75-150 sites.

The most downstream reach in the watershed is used to represent a
response reach wherever possible. This "integrator" reach is a minimum
of 20 times the bankfull width, but never less than 80 m. An integrator
reach is defined as never having a gradient greater than 3 percent. In
general, these reach types represent pool-riffle channels that generally
have the greatest sensitivity to increases in sediment supply and peak
flows (Montgomery and MacDonald 2002).

A combination of in-channel, riparian vegetation, and macroinvertebrate
characteristics are measured at each integrator reach. Twenty in-channel
variables were used to describe the physical nature of the stream
including: stream gradient, sinuosity, bank angle, undercut depth, bank
stability measurements, bankfull widths, channel cross-sections, wetted
widths, width-to-depth ratios, entrenchment ratio, and a modified Wolman
pebble (D50, D84, %\< 6 mm), pool-tail fines (\< 6 mm and \< 2mm), large
woody debris (LWD), conductivity, and alkalinity. Water temperatures are
measured with recording temperature loggers between July 16 and
September 2. In addition, six vegetation variables are used to described
riparian vegetation along the greenline and five riparian cross sections
within 10 m of stream, and twelve metrics are used to describe the
macroinvertebrate communities.

Photographs are taken facing upstream and downstream from the top and
bottom of each reach. Additional photographs are taken of channel and
vegetation cross-sections and representative views of pools, riffles,
marker location, and any unique characteristics occurring within the
reach. Locations are described for each photograph so that repeat
pictures can be taken from close to the same point. Beginning in 2003, a
site marker tag was installed at each reach. Marker tags were not placed
at reaches within wilderness areas; rather a distinct natural feature
was used as the site marker. The distance and compass bearing to the
beginning of the reach were recorded and a photo of the marker, in
perspective to the reach start, was also taken. After a reach is
established, a map program is used to create a topographic map of the
reach location. Any other pertinent details are included in the map or
added, such as private land boundaries, road numbers, trails, etc.

**4.1.3 ODFW Habitat and Riparian Survey**[]{#__RefHeading___Toc80112512
.anchor}

ODFW has proposed that the structure and methods employed by the Oregon
Plan for Salmon and Watersheds Monitoring Program be extended to the
John Day subbasin of the Columbia Plateau. This approach, successfully
implemented in Oregon's coastal watersheds, applies a rigorous, Tier-2
sampling design to answer key monitoring questions, provides integration
of sampling efforts, and has greatly improved coordination among state,
federal, and tribal governments, along with local watershed groups.

ODFW has begun to survey habitat information paired with the juvenile
snorkel surveys under the same sampling design. In each subbasin, ODFW,
in cooperation with co-managers and other interested parties, will
refine the sampling universe for habitat and juvenile surveys based on
current ODFW distribution maps. The sampling domain will be defined at
the upper ends of watersheds by perennial streams and at the lower end
by the capability of field crews to snorkel the sample reach. To balance
the needs of status (more random sites) and trend (more repeat sites)
monitoring, we will implement a rotating panel design in the Columbia
Plateau based on recommendations from the EPA EMAP Design Group. The 50
sites drawn on an annual basis for each subbasin will be assigned to the
rotating panel design as follows:

-   3 panels with different repeat intervals

-   17 of the sites will be sampled every year

-   16 sites will be allocated to a 4 year rotating panel (sites visited
    once every 4 years on a staggered basis)

-   17 sites will be new sites each year

With this sampling strategy, 50 sites will be drawn the first year and
33 new sites will be drawn in subsequent years because 17 of the
originally drawn sites will be repeated each year. ODFW experience on
coastal watersheds has demonstrated that a target sample size of 50
sites will meet the precision targets for habitat and juvenile sampling.
Over the first 3 years of the study, ODFW will evaluate the influence of
sample size on meeting/not-meeting/exceeding target precision levels and
make recommendations for adjusting the sample size accordingly.

Channel habitat and riparian surveys will be conducted as described by
Moore et al. (1997) with some modifications. Modifications include:
survey lengths of 500-1000 m and measurement of all habitat unit lengths
and widths (as opposed to estimation). Survey teams will collect field
data based on stream, reach, and channel unit characteristics. Each
field crew is comprised of two people with each member responsible for
specific tasks. The \"Estimator\" will focus on the identification of
channel unit characteristics. The \"Numerator\" will focus on the counts
and relative distribution of several unit attributes and will verify the
length and width estimates for a subset of units. The \"Estimator\" and
\"Numerator\" share the responsibility for describing reach
characteristics, riparian conditions, identifying habitat unit types,
and for quantifying the amount of large woody debris. The methods and
indicator variables collected with this protocol can be viewed at
<http://osu.orst.edu/Dept/ODFW/freshwater/inventory/pdffiles/habmethod.pdf>.

The variables described are indicators of habitat structure, sediment
supply and quality, riparian forest connectivity and health, and
in-stream habitat complexity. The specific attributes include but are
not constrained to:

> Density of woody debris pieces (\> 3 m length, \>0.15 m diameter)
>
> Density of woody debris volume (\> 3 m length, \>0.15 m diameter)
>
> Density of key woody debris pieces (\>10 m length, \>0.6 m diameter)
>
> Density of wood jams (groupings of more than 4 wood pieces)
>
> Density of deep pools (pools \>1 m in depth)
>
> Percent pool area
>
> Density of riparian conifers (\>0.5 m DBH) within 30 m of the stream
> channel
>
> Percent of channel shading (percent of 180 degrees)
>
> Percent of substrate area with fine sediments (\<2 mm) in riffle units
>
> Percent of substrate area with gravel (2-64 mm) in riffle units

While these attributes do not describe all of the conditions necessary
for high quality

salmonid habitat, they do describe important attributes of habitat
structure within and adjacent to the stream channel. The attributes are
also indicative of streamside and upland processes.

**4.2 The Freshwater Production Group**[]{#__RefHeading___Toc80112513
.anchor}

The Freshwater Production Group is charged with designing methods to
estimate smolt production in the different subbasins during the
outmigration periods for s/s Chinook and steelhead and for determining
juvenile and adult steelhead and Chinook abundance and distribution. The
Oregon Department of Fish and Wildlife (ODFW) is largely responsible for
estimating freshwater production, abundance, and distribution of
salmonids in the John Day subbasins.

Specifically, the objectives include:

1.  Monitor trends in abundance of juvenile trout and salmon and status
    and trends in stream and riparian habitats in the John Day River
    subbasin.

2.  Monitor status and trends in steelhead redd abundance in the John
    Day River subbasin.

3.  Estimate the number and distribution of spring chinook salmon redds
    and spawners in the John Day River subbasin.

4.  Estimate smolt-to-adult survival rates (SAR) and out-migrant
    abundance for spring chinook and summer steelhead and life history
    characteristics of steelhead above Rkm 298 (river mile 185) in the
    John Day River subbasin.

5.  Measure distribution of adult spring chinook holding habitat in the
    John Day River subbasin. Examine if temperature remains a limiting
    factor to freshwater habitat distribution.

Basin-wide distribution surveys for juvenile fish are conducted in the
same reaches surveyed for habitat by the ODFW EMAP approach. Snorkel
surveys are the predominant method to quantify the number of juvenile
*O. mykiss* and spring Chinook in these reaches. These surveys involve a
single upstream pass through each pool during daylight along a 1-km
survey reach. Counts of the number of juvenile and adult trout (*O.
mykiss and O. clarki*) and salmon (*O. tshawytscha*) are recorded for
each pool. Trout and salmon will be categorized as juvenile (1+ years or
greater), or adult based on size classes. If all pools in a reach have
poor visibilities then as many pools in the reach as possible will be
electrofished. Electrofishing data will be combined with snorkeling data
to determine the presence/absence of juvenile *O. mykiss* and spring
chinook. The presence/absence data will be analyzed to quantify the
percent of sites where juvenile *O. mykiss* and spring chinook are
present.

Status and trend monitoring for adult steelhead and Chinook are also
conducted to determine abundance and distribution of spawning adults.
Steelhead redd surveys are conducted annually based on standard ODFW
methods. Fifty sites are selected and are visited every two weeks
throughout the season to quantify the cumulative redd count at each
site. Each surveyor counts live fish and all redds are counted and
flagged. Population status is indexed through cumulative redd counts.
Hatchery: wild ratios are estimated by observing the occurrence of
adipose fin-clipped and unmarked live fish on spawning grounds. ODFW
managers also conduct annual, steelhead spawner surveys to compliment
trend analysis. Methods are similar to those described above except that
surveys are conducted on stream reaches selected over the past 50 years
to maximize trend data analysis. Spring Chinook spawner surveys are also
conducted annually by ODFW. Adult fish and redds are counted and
carcasses are sampled to determine sex, age, and reproductive success.
These surveys include index and census counts. All known spawning
habitat is surveyed for census counts and supplemented with randomly
chosen survey sites outside of known spawning habitat. Similar to
steelhead, index survey sites were established over the past 50 years to
maximize trend data analysis. Additional details of both juvenile and
adult survey techniques can be found in the ODFW FY2003 statements of
work.

This section summarizes the information found in the ODFW FY2003
Statement of Work for estimating freshwater production. Between the
completion of the life history and natural escapement study in 1984 and
the start of this project in 1998, spring chinook spawning surveys have
not provided adequate information to assess age structure,
progeny-to-parent production values, smolt-to-adult survival (SAR), or
natural spawning escapement. Further, only very limited information is
available for steelhead life history, escapement, and productivity
measures in the John Day subbasin. To meet the data needs to assess the
long-term effectiveness of habitat projects, and to differentiate
freshwater and ocean survival, sufficient annual estimates of spawner
escapement, age structure, SAR, egg-to-smolt survival, and freshwater
habitat use are essential. These needs are beginning to be addressed
through spawning ground surveys initiated for spring chinook salmon in
1998 and smolt PIT-tagging efforts initiated in 1999. Much of the
information described here will likely be used to compliment research
described in the Analytical Framework.

One objective of the study conducted by ODFW is to estimate
smolt-to-adult survival rates (SAR) and out-migrant abundance for spring
chinook and summer steelhead and life history characteristics of
steelhead (above Rkm 298) in the John Day River basin. Using methods
developed by Lindsay et al. (1986), ODFW will collect chinook smolts
using beach-seining techniques in the lower Mainstem and the lower North
Fork upstream from the mouth to Rkm 40. This mainstem river reach is
downstream of all known spawning and rearing areas and is designed to
sample the entire John Day River basin population during the smolt
migration period (Lindsay et al. 1986, Wilson et al. 2001). A minimum of
4,000 chinook smolts, captured in either seines or rotary screw traps,
will be PIT tagged. Estimates SAR for both species will rely on FCRPS
PIT-tag detection facilities at the Bonneville Dam to document returning
tagged adults. We will use the PTAGIS and DART data systems to store
PIT-tagged fish information.

To determine productivity (out-migrant abundance) of specific hydrologic
units for chinook (and management units for steelhead), ODFW will
estimate contributions of Upper Mainstem (beginning spring 2003), Middle
Fork (autumn 2003), and North Fork (2004) to total smolt productivity.
Rotary screw traps will be placed near the downstream extent of each of
the three hydrologic units to measure basin-specific smolt abundance.
Traps will be located below known chinook spawning areas. These same
traps will be used for steelhead and will be located near the downstream
extent of the steelhead management units defined by Chilcote (2001). The
number of emigrants from above the trap location will be estimated using
periodic, mark-recapture trap efficiencies (Thedinga et al. 1994). A
minimum of 500 smolts of each species in each basin will be PIT tagged
to verify their origin if recaptured in our downstream seining efforts.

Additional screw traps are expected to be operated on the South Fork
John Day River, and other undefined locations, by the Bureau of
Reclamation for Tier-3 studies of steelhead. ODFW will coordinate with
this effort to reduce trapping redundancy and share equipment and
efforts when appropriate. SARs have not been estimated for John Day
steelhead to help guide sample size requirements. Assuming a SAR similar
to spring chinook (\~1.2%, Lindsay et al. 1986) a goal of 5,500 smolts
will have to be PIT tagged to produce an adequate sample of 60 returning
adults. SAR will be determined for each year class using scale analyses
of collected juveniles. Populations will then be apportioned into the
varying life histories and summed across years for SAR.

To determine freshwater life history traits of juvenile chinook and
steelhead ODFW will subsample steelhead juveniles for age determination
and use the above trap efficiency and abundance estimate efforts for
migration timing in the John Day subbasin. In addition, ODFW plans to
evaluate the distribution of adult spring chinook holding habitat in the
John Day River subbasin. Examine if temperature remains a limiting
factor to freshwater habitat distribution.

To determine the freshwater habitat use by adult spring Chinook salmon
during critical warm-water periods, snorkel surveys have been conducted
in the Middle and North Fork subbasins. During summer months when water
temperatures are greatest (July and August), streams are surveyed
longitudinally to determine the presence/absence of adult Chinook. Water
temperatures are monitored using point measurements and with
thermistors. Thermistors are placed at the downstream extent (presumably
warmest experienced temperatures) of observed fish distributions. Adult
Chinook are counted, their residing habitat is qualitatively described,
thermal refugia are noted, and all pre-spawning mortalities (carcasses)
are counted and examined for age, sex, size, and fecundity.

**4.3 GIS Group**[]{#__RefHeading___Toc80112514 .anchor}

Identifying data needs is a critical subtask in the study design
described by the Analytical Framework group. The GIS group is
responsible for providing the information infrastructure that supports
the collecting and analyzing of data and the display of results. The
Empirical Method Road Map (Figure 1) illustrates the general data
management process the FCRPS RME Program is following. The data
dictionary is a data management tool that provides a comprehensive
conceptual framework based on the monitoring indicators and protocols
developed for collecting data. The John Day RME Data Management Pilot
Data Dictionary is largely based on (Hillman, 2004) and includes the
monitoring data which are presently being collected by various
organizations working in the John Day Basin. The Data Dictionary is then
used by the GIS group to develop a logical and physical design for the
Geodatabase (GDB) container that hosts the RME data. The Needs Analysis
examines the Data Dictionary to determine if existing data are adequate
for the proposed studies. If existing data are found wanting then
additional indicators and/or protocols may be introduced into the Data
Dictionary with subsequent enhancements made to the Geodatabase. To be
effective as a Columbia Basin wide information system, future
modifications to the Data Dictionary and Geodatabase design will
eventually require a formalized process with an established approving
committee.

**Figure 6.** Conceptual framework for geospatial information to
coordinate research efforts in the John Day
Basin[]{#__RefHeading___Toc80112535 .anchor}

**4.4 Landscape Changes and Patterns
Project**[]{#__RefHeading___Toc80112515 .anchor}

The ability to evaluate changes in landscapes is rapidly expanding with
recent technological advances of aerial and space borne remote sensing
(RS), global positioning system (GPS) satellites and precision
navigation and surveying, and management and analysis of geographic
information using geographic information systems (GIS). Exploring unique
linkage between these three tools and their related application to
Pacific salmon freshwater life history is the foundation of this
project.

While there are clear patterns in the correlations between land use and
land cover at a landscape scale, with salmon population trajectories,
these correlations are often too general for extrapolating mechanistic
connections between habitat type and condition, and salmon population
status for two reasons. First, most studies that attempt to relate gross
habitat attributes with population trends, use static geospatial data
layers, whereas population tends are evaluated over a times series.
Second, currently used geospatial data layers of land use and land cover
and classification of remote sensed imagery is not specific to Pacific
salmon habitat requirements.

This study will attempt to develop applications in the use of remote
sensed imagery classifications with the objectives that:

-   compare the ability of various types of remote sensed imagery to
    identify habitat features relevant to anadromous salmonids, and

-   track land use and land cover change over time.

The central questions to be answered by the study are:

1)  Can remote sensed data of different spatial and spectral resolutions
    be used in combination to generate high spatial resolution habitat
    classifications?

2)  Can pattern recognition or texture analysis be used to enhance
    classification of high spatial resolution/low spectral resolution
    remote sensed data?

3)  How much of field or ground surveyed information can be gathered
    using remote sensed data?

4)  What are the limitations of various remote sensed data layers with
    respect to habitat feature delineation?

5)  How much of remote sensed imagery classification process can be
    automated?

6)  Are riparian and wetland habitats accurately classified using
    LADNSAT ETM+ remote sensed data?

7)  Is it feasible to use change detection of LANDSAT ETM+ remote sensed
    data in habitat models?

8)  Does a time series of land use and land cover improve the fit of
    fish habitat models?

This work will be conducted over the whole basin of the John Day. In
addition, this study will be conducted over the whole basin extent in
the Grande Ronde (OR); Salmon (ID); Wenatchee (WA); Willamette (OR); and
Yakima (WA). Much of this will be based on the BOR's time series (1984,
1988, 1992, 1996, and 2000) of raw LANDSAT TM imagery. The study will
produce a series of geospatial datalayers containing the various
classified land use and land cover categories for each year in the
remote sensed imagery time series. Of interest to BOR Reclamation is a
description of the change in the following broad categories of land use
and land cover: agriculture, urban, logging, riparian vegetation,
wetland vegetation, and roads. In addition the researchers will review
existing efforts to classify land use and land cover in the United
States, such as U.S.Geological Survey (USGS) National Land Cover
Database; USGS Land Use and Land Cover Program, NationalGAP Analysis
Program; and the Northwest Habitat Institute Current and Historic
Wildlife-Habitat Types Program.

The use of Geographic Information Systems (GIS) and Remote Sensing (RS)
in spatial analysis provides the tool to manage, edit, and analyze
spatial and temporal patterns of multispectral remotely sensed data.
Land cover classification and spatial and temporal analysis will be
divided into three categories: land use and land cover classification;
change detection and outcome correlation through descriptions of spatial
and temporal variance; and translations across multiple spatial "scales"
The strength of the spatial relationship of spatial scale with habitat
structure will be validated with ground-truth observations of habitat
composition.

Project Investigators: Blake Feist and Miles Logsdon of NOAA Fisheries

**4.5 John Day River Basin Airborne TIR Remote Sensing & Spatial Data
Analysis Project**[]{#__RefHeading___Toc80112516 .anchor}

Although similar in methods to the above project, this project will
focus on temperature and fish survey information. Landscape scale
surveys within the Upper John Day River Basin were conducted from 1994
through 1998 by the Department of Fisheries and Wildlife at Oregon State
University. These studies include intensive habitat surveys, fish pit
tagging/tracking, and stream temperature analysis. The stream
temperature analysis consisted of both point location monitoring using
in-stream thermographs and spatially continuous temperature profiles
derived from airborne thermal infrared imagery. These extensive data
sets are currently archived at OSU and can provide a critical baseline
for future studies in the upper watershed.

In this study, past data sets will be assembled and analyzed in order to
provide a complete context for analyzing temperature affects on fish
habit quality in the Upper Middle Fork and South Fork John Day Rivers.
These data will provide a historic (10 year) perspective for fish
distributions, landscape features, and temperature patterns and are a
key component for designing sampling plans for the summers of 2003 and
2004. This portion of the project will include retrieving and
documenting the archived data sets, plotting temperature degree days
from fixed (point) monitoring sites, comparing spatial temperature
patterns from the TIR imagery, converting fish distribution profiles to
GIS data layers (per year), and identifying the location of in-stream
features (push-up dams/diversions/spring locations, etc.) that may
influence stream temperature patterns across multiple spatial scales.

Further, airborne TIR imagery will be collected on both the upper Middle
Fork and South Fork John Day Rivers during the summer of 2003 and 2004.
These data will provide complete picture current conditions including
sources of heating, temperature accumulation, cold-water refugia, and
spatial explicit thermal gradients. These data will allow a comparison
of temperature profiles in the upper Middle Fork that illustrate how
changes in watershed management (stream fencing, water buy backs and
allocations, etc.) may have influenced spatial temperature patterns and
local habitat quality over the past eight years. The project
deliverables would include spatially explicit longitudinal temperature
profiles, high resolution TIR and color video imagery at fine scale (\<
1 meter) features, and a report illustrating and analyzing temperature
patterns (i.e. tributary influences, source heating areas, and thermal
refugia). In addition, the imagery provides an opportunity to visually
display complex watershed processes related to human landscape and
riparian influences.

Project Investigators: Russel Faux at Watershed Sciences, M.Sc. Luis
Francisco Madriñán and Hiram Li at Oregon State University.

**4.6 Assessment of Stream Bed Substrate Stability and Excess Sediment
Project**[]{#__RefHeading___Toc80112517 .anchor}

Elevated water temperature and excess deposition of fine sediments are
thought to be major causes of biological impairment in streams in the
John Day Basin of Oregon, especially restricting the spatial and
temporal patterns of key salmonid species. Many of the John Day streams
and rivers are listed as water quality-limited for sediment and
temperature on the State-Federal 303(d) list of impaired waters.
Accordingly, the Oregon Department of Environmental Quality (ODEQ) must
develop Total Maximum Daily Loads (TMDLs) for these listed water bodies.
In addition, the NPCC (Northwest Power and Conservation Council) must
evaluate the effectiveness of habitat restoration and mitigation actions
that address these stressors.

The purpose of this project is to estimate the prevalence and evaluate
the impacts of excess fine sediments throughout the John Day Basin by
using an existing data set of 100+ recently sampled stream reaches and
an analytical approach that evaluates the relationship between sediment
supply and sediment transport as they are affected by natural factors
and human disturbances. Stressors identified in this proposed effort can
be directly incorporated in the Source Assessment of the upcoming John
Day and Deschutes subbasin sediment and temperature TMDLs (see below).

A field and analytical approach used by the USEPA and ODEQ to evaluate
the deviation of observed streambed particle size from that expected in
the absence of anthropogenic disturbances will be applied to the John
Day Basin. This approach to assess excess sediment in streams uses
channel and substrate data from stream surveys (e.g., EMAP and REMAP).
Current sediment size distributions are based on a systematic pebble
count. Expected size is based upon sediment transport theory and the
assumption of an equilibrium condition between long-term sediment supply
and transport in the absence of disturbance. Specifically, we use
quantitative measurements of channel dimensions, slope, bankfull flow
depth, large woody debris, residual pool depth and other measurements to
estimate mean bed shear stress at bankfull flows and the critical
substrate diameter that can be mobilized by those flows. Mean observed
particle sizes substantially larger than the critical (expected)
diameter may indicate a sediment-starved system, such as the proximal
downstream channel below a dam. Mean observed particle sizes much
smaller than that expected likely indicate excess sediment accumulation
due to elevated sediment supplies to the stream. Observations of human
disturbance, riparian characteristics and condition, bank condition,
etc. provide evidence of the causes of the excess sediment supply. The
protocol and the index are more quantitative, precise and accurate than
existing visual qualitative methods typically applied by resource
managers. Because the approach can be applied efficiently to a large
number of sites throughout a basin, it is easier to apply in a
basin-wide study than more labor-intensive approaches often applied in
research or engineering projects. The excess sedimentation index,
Relative Bed Stability (RBS) (Kaufmann et al. 1999), which is calculated
from data collected using EMAP-style habitat information, adds an
important component beyond that typically used by state programs in that
it takes into account the stream's capacity to transport bed material
rather than simply the observed particle sizes or sediment deposition.

The objectives of this study are to:

1\. [Estimate the proportion of the channel network with excess fine
sediments.]{.underline} Existing channel habitat data that ODEQ
collected as part of EMAP-type surveys and under the PIBO
(Pacfish/Infish Biological Opinion) conducted in the John Day Basin over
the past several years at more than 100 sites will be evaluated.

2\. [Estimate the relationship between an incidence of excess fine
sediments in the channel network and measures of human-related
disturbance.]{.underline} Characterization watershed and riparian
stressors at the sample sites will includes: grazing; timber harvest;
agricultural cropping, irrigation practices, and roads. Detailed
watershed disturbance metrics (including percent of watershed in
forested, clearcut, and partially cut land cover; watershed and riparian
road density, a grazing intensity index, and other metrics) that will be
used in initial analyses have already been calculated from map and air
photo analysis in combination with site visit data at 26 sites in the
John Day Basin. This analysis will be extended to the rest of the sites
with available data, and if resources permit, obtain the appropriate
watershed scale data.

3\. [Estimate sediment delivery at each sampling location.]{.underline}
A set of GIS-based modeling tools will be used estimate sediment
delivery at each sampling location. This approach uses topographic, soil
texture, and land cover data to estimate spatially explicit soil erosion
by applying the Revised Universal Soil Loss Equations (RUSLE) in a GIS
context. These results are combined with SEDMOD (Spatially Explicit
Delivery MODel \[Fraser, 1999\]) to estimate the average rate of
sediment delivery to the stream channel network within a watershed.

4\. [Map locations in the channel network expected to contain excess
fine sediments.]{.underline} **T**he RUSLE/SEDMOD approach will be used
in a predictive fashion, as follows. First, land cover classes that are
associated with human disturbances with be replaced by synthetic data
simulating likely land cover found in the absence of human activity.
Differences in estimated sediment supply to the stream network between
the two scenarios (actual minus undisturbed) would represent an estimate
of the *increase* in sediment supply due to human disturbance. Second,
associations between Relative Bed Stability (RBS) and modelled
perturbations in the sediment supply will be examined. RBS is expected
be more strongly \[negatively\] correlated with these *changes* in
sediment supply than with estimated total sediment supply under current
land use. We expect that undisturbed streams maintain a long-term
equilibrium between sediment supply and transport, with the result that
RBS would remain relatively uniform within an undisturbed stream network
even if sediment supply is spatially variable. Last, if RBS is strongly
related to estimated anthropogenic perturbations in sediment delivery to
stream channels for the EMAP sites, then a regression relationship could
be developed to use modeled values of excess sediment delivery to
predict and map locations within the stream network where decreased bed
stability (low RBS) and excess sediment deposition are likely to be
found.

The integration of the modeling approach with the sample survey results
should allow us to improve our ability to evaluate where in the channel
network excess sediments are supplied (associated with various human
disturbances), where excess sediments are deposited, and potentially,
where remedial actions are likely to have greatest potential effect.

Project investigators: Philip R. Kaufmann, Phil Larsen (U.S.EPA, NHEERL,
WED, Corvallis, OR.), John Faustini (OSU Dept of Fisheries & Wildlife,
Corvallis, OR)

**4.6 John Day TMDL project**[]{#__RefHeading___Toc80112518 .anchor}

Total maximum daily loads (TMDL) are target water quality standards. 
Standards typically contain threshold values for water quality
conditions such as pollutant concentration, pH, dissolved oxygen, or
temperature.  The temperature standard numeric criteria in the John Day
is based on salmonid life cycles as the most sensitive beneficial use of
Basin waters. In the John Day Basin, rivers exceed these thresholds for
temperature, pH, bacteria and other constituents. 

The objective of the TMDL in the John Day is to quantify the conditions
leading to high temperature.  Generally, the numeric criteria of the
standards cannot be met even under the best estimate of more natural
conditions.  In this case, the default target of the TMDL is the best
estimate of natural conditions. Accordingly, for temperature, the TMDL
process assesses the existing and estimated natural potential heat
loads.  From this, land use authorities are allocated a maximum
allowable heat load (best estimate of natural) and the amount of heat
reduction required to achieve this.  Further, these heat loads are
translated into more intuitive measurable targets such as percent
effective shade and channel width.

Specifically the objectives are:  

-   Comprehensive water quality assessment (for temperature) in the
    North, Middle and South Forks of the John Day River.

-   DO, pH and bacteria assessment on mainstem John Day River

-   Local sediment, bacteria and macroinvertebrate assessments (small
    parts of North Fork & upper mainstem)

-   GIS-based assessment Basin wide (DEM & DOQ assessment of solar
    influence)

-   Based on assessment and modeling, delineate human component of
    pollutant loading.

-   Allocation of pollutant loads (TMDL project includes identification
    of responsible management agencies and collaborative production of
    water quality management plan)

In order to implement this process, a calibrated model is needed that
will compute the following:

-   flow volume and velocity, wetted channel width and depth, and
    effective shade (daily solar radiant energy blocked by vegetation
    and topography)

-   temperature, temporally and spatially, based on all relevant heat
    transfer processes including evaporation, bed conduction,
    convection, mass transfer, short wave (direct and diffuse) and long
    wave radiation.

In addition to providing jurisdictionally allocated goals to address
water quality, model output allows rapid longitudinal viewing of where
heat loads are furthest from potential, and to what process the excess
heat is attributable.  Other studies will develop relationships between
reach temperature distributions and salmon and steelhead productivity so
that the TMDL can be used to evaluate how alternative habitat
restoration effort may affect stream temperatures and ultimately fish
productivity.

 

Monitoring and assessment of vegetation, hydrology, morphology and
meteorological conditions will provide input for temperature modeling
(one-dimensional thalwag characterization). The temperature model will
be calibrated spatially to airborne thermal infrared data and temporally
to instream temperature dataloggers. Based on historical information
including aerial photography, literature, local knowledge, and current
undisturbed conditions, system potential channel shape and vegetation
will be assessed. These estimated conditions will provide the basis for
simulation of a more natural shading and temperature. One key output
will be summer afternoon longitudinal temperature profiles. Temperature
will be simulated for a variety of flow scenarios as well. This
information will inform key questions:

-   What is controlling temperature in the Basin, and to what extent is
    this anthropogenic?

-   What is a more natural longitudinal temperature profile in the
    summer afternoon?

-   What is the summer diel temperature range and how much has it been
    increased through human activities? Where?

-   Can the seasonal time-frame of elevated temperatures be reduced?

The TMDL model will characterize reaches within a sub-basin. The rivers
that would be modeled are the perennial lengths of North Fork, Middle
Fork and South Fork and perhaps the mainstem or part of it. Tributary
inputs are accounted for.

Specific analytical methods can be found in *Analytical Methods for
Dynamic Open Channel Heat and Mass Transfer* (Boyd, Matthew and Kasper,
Brian, 2002, [www.heatsource.info](../www.heatsource.info)), and are
summarized in TMDLs (e.g., Klamath, Umatilla) that can be found on DEQ's
website: <http://www.deq.state.or.us/wq/TMDLs/TMDLs.htm>. Ground Level
monitoring methods include Rosgen Level II Inventory (Rosgen, 1996),
Wolman Pebble Counts (Wolman 1954); Solar Pathfinder^TM^, continuous
temperature monitoring (Watershed Assessment Mode of Operations Manual,
ODEQ, 2004 - http://www.deq.state.or.us/lab/qa/DEQ03-LAB-0036-SOP.pdf)

 

Project Investigators: Don Butcher, Paul Daniello, Brian Kasper at ODEQ

**4.7 Juvenile salmon and steelhead production
project**[]{#__RefHeading___Toc80112519 .anchor}

The production project is comprised of several components. The set of
studies provided here will be used to connect larger and same scale
landscape, land use, and habitat patterns to important salmon and
steelhead responses. The main objective of this project is to evaluate
whether habitat and temperature attributes can explain changes in fish
behavior such as densities and movement, growth and other physiological
conditions, survival, and ultimately production. The components of this
project can be organized by concepts laid out in Hughes and Grand (2000)
bioenergetic/ideal free distribution model.

# 

# **4.7.1 Study** **1**

Previous studies indicate that the subbasins in the John Day River have
a heterogeneous and relatively wide distribution of temperatures
throughout the basin. Differences in reach temperatures allow for the
comparison of fish abundance over several temperature regimes. The first
approach used to address this objective will be to correlate reach
temperatures and habitat characteristics to reach estimates of fish
abundance.

A distribution of reach late summer temperatures throughout the upper
John Day River basin will be determined through two approaches. First,
using information gathered in the Spatial Data Analysis project,
summer-afternoon spatial temperature patterns will be observed using
existing and 2004 paired TIR and true color imagery for the North Fork,
Middle Fork, South Fork and mainstem, from mouths to headwaters. Second,
using the TIR information as a template, temporal temperature patterns
will be characterized using in-stream recorders (thermistors) placed
throughout the length of the mainstem and the North, Middle and South
Forks and at the mouths of all major tributaries feeding these rivers
(tributaries that are likely to modify the receiving stream
temperature). These longitudinal temperature profiles will be used to
define reaches.

Snorkel surveys will then be conducted in these reaches to estimate fish
densities as described by Li et al. (1994). This information will be
used to construct a distribution of reach juvenile chinook and steelhead
densities throughout the subbasins. As supplemental environmental
information that could potentially be used in further analyses, a
modified Hankin-Reeves type habitat surveys (modified to be consistent
with the habitat metrics to be measured in the first type of survey)
will also be conducted over the same reaches as the snorkel surveys.

A regression approach could be used to evaluate whether a relationship
exists between average (over a defined period) maximum reach
temperatures and reach density of juvenile salmon and steelhead.
Degree-days (e.g. daily maximum temperatures summed over a defined
period), which may provide a better integration of reach temperatures
over time, should also be considered as a predictor to reach fish
abundance. Positive spatial correlations, where sites tend to be more
similar to closer sites than further sites, may be present in the
juvenile density information. Comparison between models that include a
spatial covariance parameter and models that do not may provide
information to the degree of mixing between reaches.

In addition to assessing the ability of temperature to explain the
variation in juvenile densities, alternative explanations should also be
considered. Because habitat surveys will be conducted in conjunction
with fish surveys, habitat characteristics can also be used as predictor
variables. Model comparison techniques (i.e. AIC scores) could be used
to determine if one or more habitat descriptors are necessary when
estimating the abundance of juveniles in a reach.

The question this study addresses is: Can temperature and habitat
characteristics predict the carrying capacity of juvenile salmon and
steelhead of a stream reach?

# 

# **4.7.2 Study 2**

Correlative studies, like the one just described, can provide evidence
supporting a mechanistic relationship between cause and effect; however,
they are not definitive and can be misleading if the relationship is
spurious. Thus, other studies are necessary to help define these
mechanistic relationships. An experiment has the power to provide strong
contrast while at the same time reducing variability and controlling
multiple factors that often vexes large-scale correlative approaches.

If temperature is governing the juvenile salmon and steelhead abundance
(i.e. density) in pools through active selection by individuals, then
manipulation of densities in pool over different thermal regimes may
elicit differential behavioral responses. These responses to pool
density of differing thermal structure will give insight into the
importance of temperature in habitat selection and density dependent
intraspecific interactions. This problem will be approached by
experimentally adding and removing fish in pools with different thermal
regimes and monitoring immigration and emigration rates following these
manipulations.

# **4.7.3 Study 3** 

Ultimately, the response desired from habitat mitigation in the John Day
Basin is an increase in population growth rates of target species.
However, given the tremendous distances traveled by anadromous species
and the range of environments encountered, isolating the signal from
changes in spawning and rearing habitat by only evaluating population
growth rates will likely be impossible. The most informative population
response relative to early life stages is freshwater productivity. Here
we define freshwater productivity as the number or biomass of smolts per
female. This measure of productivity can be further divided to growth
and survival over different life stages in the spawning and rearing
habitat.

A difference in this study from those previously described is that
changes in density and growth through time and space must be evaluated
to address questions about productivity. In this study Passive
Integrated Transponder (PIT) tags will be used to uniquely identify
individual fish and follow them through time and space attempting to
document their thermal experiences and relating them to growth and
survival. This information will provide insights into the influence of
temperatures on freshwater productivity.

In this study, small watersheds will be selected over different thermal
strata. Juvenile steelhead will be captured with seines in each of these
watersheds and PIT tagged. Size and weights of the fish will be measured
and recorded. Fishes will be recaptured as they migrate downstream to
overwinter using screw traps. Size, weight will be measured and recorded
along with a PIT tag identification of captured fish. In addition, a
non-invasive fat determination will be made using a commercially
available meter that measures conductance. The Ponderal Index will be
used to measure condition and an external inspection will be made of the
body and gills for lesions and parasites. From this information growth
will be estimated prior to overwintering. Rearing survival will also be
estimated base on screw trap efficiencies. An attempt will be made to
recapture salmonids returning for their second year of freshwater
rearing. We expect that those that survived had higher fat content after
the summer growth season.

The following year a new cohort will be tagged using the same
techniques. Fish from both cohorts are recaptured, again in screw traps
on the onset of the downstream fall migration. The same information is
recorded for recapture PIT-tagged fish. The first cohort continues their
migration down to John Day and Bonneville dams. The bypass systems in
these dams are equipped with PIT tag detectors. Using
Cormack-Jolly-Seber mark-recapture methodology, survival from first
release to John Day dam can be estimated.

Using the longitudinal temperature profiles from *Study 1* we will
attempt to estimate the thermal experience of an individual based on the
reach they occupy. In order to define their thermal experience, an
estimate of fish movement and site fidelity will be necessary. We will
use radio telemetry to gain insight into the migratory behavior of fish.
Growth, fat content, overwinter survival, and survival to John Day dam
will then be correlated to the thermal regime experience by individuals.
The question that will be address is: Does thermal experience closer to
optimal temperatures result in improved growth and, survival, and
eventually production than those fish experiencing less suitable
conditions?

In addition to PIT tags, radio tags will be used to track movement of
individuals. The Hughes and Grand model would predict greater movement
from individuals further from optimal habitat, unless densities are high
enough in optimal habitat to reduce movement.

# **4.7.4 Framework for juvenile production project**

A set of expected results of *Study 1, 2* and *3* will be based a model
framework based on the approach of Hughes and Grand (2000). In 1970,
Fretwell and Lucas introduced the concept of Ideal Free Distribution
(IFD), which states that in more saturated environments, individuals
will distribute themselves in habitats that are intrinsically different
such that their fitness is similar. Because growth rates and
survivorship are often correlated to fitness they are often used as
surrogate. The IFD assumes that an organism has perfect knowledge of the
system and is free to move from patch to patch. The result of
intraspecific resource competition forces individuals to move from lower
quality to higher quality patches. At equilibrium the average per capita
resource consumption, and ultimately growth, survival, and fitness is
the same for all habitats.

Physiological models have also been used to estimate patch use, where
organisms select for patches based on optimal physical properties
controlling physiological processes and food availability (Elliot 1982).
This is an especially important consideration for ectotherms such as
fish, where temperature controls metabolic activity. While the IFD
suffers from exclusion of this property, physiological models do not
include density dependent interactions. Hughes and Grand (2000) included
physiological component of the IFD to better describe habitat
utilization of fish. Their model included 3 important considerations:
temperature, food availability and relative competitiveness based on
size. When factors such as temperature were largely limiting habitat
utilization their model produced similar predictions as physiological
models. When density dependent factors were limiting then their model
produced similar predictions as the IFD. Thus, at intermediate levels of
these factors their model produced different results than both types of
models.

This model will be used as a framework to the proposed studies that will
integrate temperature effects on physiology through a bioenergetics
model and the IFD model to describe the density of juvenile salmon and
steelhead in various stream reaches. Assuming food availability will be
assumed equal amongst all patches, the model would suggest that fish
will be moving to patches of higher quality defined by density and
thermal structure. Growth and survival are expected to be similar across
patches within their sphere of knowledge.

# 

Project investigators: Hiram Li, Guillermo Guannico

**4.8 Push-up dam removal project**[]{#__RefHeading___Toc80112524
.anchor}

The impact of push-dams on salmon and steelhead movement, access to
thermally advantageous habitats, and ultimately survival will be
addressed in this study. Results from this study will determine the
effectiveness of push-up dam removal in increasing freshwater
production. Critical components to the feasibility of this experiment
are the location and accessibility to push-up dams. The outcome of what
push-up dams can be manipulated will determined the fate of this
project.

The main questions addressed by this study are:

1.  Will push-up dams impede migration of juvenile redband trout
    (*Oncorhynchus mykiss)* to juvenile rearing grounds?

2.  Will flat panel stantion dams be an improvement over push-up dams in
    passing juvenile redband trout upstream?

3.  Will push-up dams impede movement to physiologically more suitable
    habitat upstream during the base-flow period of August?

4.  How do flat panel stantion dams compare to unimpeded locations with
    respect to transit time?

*Site Selection*

Four push-up dams are located in the lower 5 mi. of the South Fork John
Day (SFJD) Basin. They are scheduled for replacement in 2005. Previous
snorkeling surveys (1984, 85, 98 Li unpublished data) indicate that
these sites were not used by redband trout during the base flow period.
Therefore question 3 cannot be answered at this site.

There are four fish bearing sub-basins in the SFJD: Black Canyon, Wind
Creek, Deer Creek, and Murderers Creek. Black Canyon is in a wilderness
area. Wind Creek is on private property. Deer Creek drains USFS lands
and Murderers Creek is controlled by the Tri-Agency group of ODFW, USFS,
and BLM. Deer and Murderers Creek are or have been gauged and have
Hankin & Reeves (1988) habitat surveys conducted within them. Push-up
dams exist with Murderers Creek but the Tri-Agency Management Group must
give us permission to conduct experiments within the system.

*Study Design*

Questions 1 and 2 will be conducted at the lower SFJD. The issues here
are of the timing of the movements up and downstream in relation to the
raising and lowering of the push-up dams. The second issue is to
determine whether or not trout overwinter *in situ* or moved downstream
SFJD. Trout will be radio-tagged and PIT-Tagged in Black Canyon, Deer
Creek and Murderers Creek. Radio-tagged fishes in the sub-basins seemed
to over winter *in situ.* Although origin is known, the number of
PIT-tagged fish that left the SFJD will be unknown. The sampling period
for radio-tracking will be every two weeks. During this sampling period
mobile PIT-tag detection will be attempted.

Any trout successfully passed upstream by the replacement dams may be
better than the current system, especially as best management plans
(BMP) controlling push-up dam construction using anniversary dates is
not practical. Movement patterns are not only controlled by photoperiod
and scotoperiod, but by water temperature and discharge. Determining a
fail-safe adjusted time to allow dam construction would be difficult to
predict yearly and difficult to enforce. Using radio-tracking, the
transit time upstream through the push-up dams can be estimated.
Radio-tags would be supplemented with PIT-tags, under the assumption
that fish caught within the same group would travel to the same
location. Even if this was untrue, fish may not be detected until later
upstream. There is also the possibility of detecting fish PIT-tagged the
previous year.

Questions 3 and 4 will be tested experimentally in Murderers and Deer
Creek. Fish will be tracked above and below push-up dams in 2004.
Movement will then be monitored under flatten or breach push-up dams in
2005 in Murderers Creek (small breaches will simulate fish gap in flat
panel station dams). The will be done in Black Canyon and Wind Creek.
Deer Creek naturally desiccates during the year and there are no
artificial barriers inhibiting dispersal. Both Murderers Creek and Deer
Creek are warmwater sites (above 20^o^C); whereas, Black Canyon and Wind
Creek are coldwater sites (below 20^o^C). The contrasts are these:
Warmwater system with barriers (Murderers Creek), Warmwater system
without Barriers (Deer Creek). Coldwater systems with barriers (Black
Canyon and Wind Creek. We hypothesize that redband trout in Black Canyon
and Wind Creek will move little (small home ranges); whereas fishes in
Murderers Creek and Deer Creek will try to redistribute.

Project investigators: Hiram Li

**5.0 Project Synthesis**[]{#__RefHeading___Toc80112525 .anchor}

**5.1 Exploratory research**[]{#__RefHeading___Toc80112526 .anchor}

The general purpose of the research described above is to determine the
biotic and abiotic factors in the John Day River governing spring/summer
chinook and steelhead production. Through this exploratory process it is
anticipated that effective mitigation strategies will be identified for
the John Day River Basin. As mentioned above we believe a hierarchical
understanding of processes in the John Day will most efficiently
organize this effort. Thus, research must identify mechanistic
relationships between fish and their habitat and community and how
larger scale processes provide the template for such relationships.

An overview of the various research projects in the John Day basin is
provided in Figure 6. The figure tries to capture the multiple scales
(from larger to smaller going left to right) that the various research
projects will operate. Arrows linking octagons (landscape or habitat
features) to other scales or measures (bold text) represent processes
and relationships. Projects and workgroups (ovals) are arranged over the
processes they will evaluate. Rectangles are specific features of
reaches that will be given greater consideration. Although information
exchange is expected between all projects, arrows connecting different
ovals represent information that is required from one group to the
other. For example, the Spatial Data Analysis Project will require reach
production estimates from the Juvenile Salmon and Steelhead Production
Project to link large scale features to production.

Establishing how temperature and other habitat features relate to
observed densities (housed under behavior) is addressed in *Study 1* of
the Juvenile Salmon and Steelhead Production Project. Whether the
results of *Study 1* are due to density dependent interactions between
juvenile anadromous salmonids mediated through temperature are addressed
at a local level through addition and removal experiments in *Study 2*.
These relationships will be expanded to the watershed/reach scale
through PIT-tag and radio telemetry in *Study 3,* where movement
patterns will be observed within the context of alternative theoretical
distributions. Relationships between factors such as reach condition
(habitat and temperature) and condition factors, growth, survival, and
ultimately juvenile production will also be established in *Study 3.*
Thus, the relationship of habitat and temperature on behavior (movement
and density), growth, survival, and ultimately production will be
address in the Juvenile Salmon and Steelhead Production Project (Figure
6).

The Push-up Dam Removal Project will attempt to evaluate the benefits
that removal of push-up dams will have on fish access to optimal
habitats and resulting survival differences. Results from the Production
Project will provide the context for mechanistic relationships that are
operating under this manipulation (Figure 6).

The TMDL Project will explain the structure of reach temperatures as a
function of riparian habitat and geomorphic characteristics. Thus,
changes in these characteristics as a response to mitigation strategies
can be used to project changes in reach temperature loading. Used in
conjunction with the Juvenile Salmon and Steelhead Production Project,
it may be possible to predict how changes in reach temperature loading
as a result of mitigation may impact juvenile behavior growth and
survival (Figure 6).

The Assessment of Stream Bed Substrate Stability and Excess Sediment
Project will function much like the TMDL project, in that reach
sediments loads as a function of alternative landscape patterns will be
evaluated. This information may be coupled with the TMDL project to
evaluate how sediment loads relate to temperature loading. This project
may also be linked to the Juvenile Salmon and Steelhead Production
Project either through impacts on temperature or comparisons in local
population behavioral, growth and survival responses to various sediment
loads (Figure 6).

While we need to establish these smaller scale processes we must also
evaluate how larger scale processes relate to smaller scale processes.
Two studies have been designed to address how basin and subbasin
features can be used to delineate units of study (i.e. reaches). Also,
how large scale processes form the template for smaller scale process
will also be established. The Landscape Change and Patterns Project will
evaluate how changes through time in landscape and land use patterns are
important to anadromous salmonid habitat using remote sensing
information. The Spatial Data Analysis project will address how these
characteristics relate to reach scale habitat and temperature
information and how this relates to estimates of juvenile production
(Figure 6).

**Figure 7.** A schematic of the different research projects in the John
Day River Basin[]{#__RefHeading___Toc80112536 .anchor} generally
arranged from large scale (left) to small sale (right). Arrows
originating through octagons (landscape or habitat features) and linking
ovals (project or workgroups) to other scales or measures, represent
processes. Projects and workgroups are arranged by the processes they
will evaluate. Rectangles are specific features of reaches that will be
given greater consideration. Arrows connecting different ovals
represents information exchange.

Because ODFW is collecting subbasin estimates of smolt production for
both anadromous species, comparison between subbasin land use and
landscape patterns can be made to production estimates. Subbasin smolt
production estimates can also be used as independent data to validate
the predicted cumulative reach estimates of production based on
temperature and/or habitat developed in the Juvenile Salmon and
Steelhead Production Project (Figure 6).

The Smolt Monitoring and Status and Effectiveness Monitoring groups will
provide intensive on the ground sampling of smolt abundance and habitat
condition. This information can be used to ground truth remote sensing
data. Also, this will provide a temporal view of responses of habitat to
changes in large scale features and mitigation efforts. Because there
will be overlap between the information collected in these groups and
the Juvenile Salmon and Steelhead Production Project, an exchange of
labor and information is expected. All georeferenced information
collected at the basin/subbasin and watershed/reach scale will be stored
in a central GIS data base managed by the GIS Group (Figure 6).

Several techniques will be used to evaluate relationships between biotic
and abiotic variables at the multiple scales. For example, correlative
approaches could be used to evaluate the relationship between landscape
scale variables and habitat variables at the watershed/reach level.
Information theoretic approaches have been advocated recently as a means
to identify the most parsimonious models (models that explain the
greatest amount of variability with the least amount of variables)
between response and explanatory variables (Burnham and Anderson 2002,
Hilborn and Mangel 2000). One approach to this method is create the most
global model considered and select simpler models on the basis of
Akaikie Information Criteria (AIC) scores. For example, watershed/reach
temperatures may be a function of basin/subbasin level characteristics.
Fish production by reach may be a function of temperature loading and/or
other reach habitat features. As a general conceptual model to these
relationships the following global models can be created and all
possible model subsets can be quickly be evaluated using AIC scores.

> temperature~reach~ = *f* (soil type, geology type, precipitation,
> hydrology, air temperature, climate, fire size, fire frequency fire
> intensity, landslides, flood events, mining sites, timber harvest,
> grazing intensity, ownership boundaries, road density, water use,
> water return, diversions and barriers, and culverts, agriculture,
> urban development)~subbasin~

steelhead freshwater production~reach~ = *f* (temperature, gradient,
pool depth, pool area, riffles area, large woody debris, substrate,
channel type, valley type, oxygen, springs, veg type, veg extent, veg
density, canopy cover, primary production, secondary production, water
use, water return, diversions, barriers, culverts, grazing,
pollutants)~reach~

Links between landscape patterns and fish production can be explored
through this process. The above models are only conceptual examples. In
reality, the analytical methods used in these exploratory analyses are
much more complicated as they need to consider spatial and temporal
structure, autocorrelations, nested models, interactions, etc.

An alternative approach is to construct analytical or simulation models
that explicitly state mechanistic relationships, often based on previous
research, and are calibrated and validated to empirical information.
Sensitivity analyses can be used to provide insight into influential
variables. In addition, these models can be used to simulate alternative
states. The TMDL model described in this document will use this approach
to estimate temperature load in a stream reach based on various habitat
variables. The TMDL model will then evaluate hypothetical changes in
habitat variables (e.g. due to restoration or land use) impacts on
temperature loads.

How the above example could be evaluated in the current research scheme
in the John Day is illustrated in Figure 7. Assuming temperature has
been demonstrated to be the major limiting factor in the John Day; using
the relationship between reach temperatures and productivity from
Juvenile Salmon and Steelhead Production Project, and the relationship
between habitat characteristics and temperature from the TMDL Project,
we will have the ability to relate changes in habitat or impacts of
mitigation strategies on juvenile production. Further, using the
relationships between landscapes and reach habitat characteristics from
the Spatial Data Analysis Project, evaluations between large scale
processes and reach estimates of juvenile production may possible
through the relationships just described or through an independent set
of relationships based on production estimates from the Juvenile Salmon
and Steelhead Production Project. This information will be stored into
the Geodatabase and may be useful to other researchers.

By reviewing the current projects in the region, it is hoped that
researchers will collaborate to improve current research, avoid
duplication of efforts, provide exchange in information, and help
fulfill the needs of other projects. For example, the Spatial Data
Analysis Project and the Landscape Change and Patterns Project may have
a fair amount of overlap, and thus some of the labor invested in
duplicate efforts can be freed for other analyses. As another example,
how reaches are defined and where research is conducted for both the
TMDL model and the Juvenile Salmon and Steelhead Production Project may
be crucial for these two projects to be compatible and to provide the
link described above.

By comparing the initial set of questions to the questions addressed
under the proposed research, questions that have yet to be addressed can
be identified. For example, very little research is being conducted at
the small scale needed to provide causal mechanisms to observed reach
patterns. The conclusion of the Juvenile Salmon and Steelhead Production
Project may be that temperature appears to be limiting production. This
may be true under current conditions, but it may also be possible that
metabolic activity due to high temperatures, resulting in decrease
growth and survival only occurs under the current food availability.
Increases in production may allow higher growth because these higher
temperatures may actually result in greater metabolic output.

**Figure 8.** A schematic of the different research projects in the John
Day River Basin[]{#__RefHeading___Toc80112537 .anchor} generally
arranged from large scale (left) to small sale (right). Arrows
originating through octagons (landscape or habitat features) and linking
ovals (project or workgroups) to other scales or measures, represent
processes. Projects and workgroups are arranged by the processes they
will evaluate. Rectangles are specific features of reaches that will be
given greater consideration. Arrows connecting different ovals
represents information exchange.

The goal of the Analytical Frame workgroup is not ensure all questions
listed earlier in the document are researched. Rather, to address
questions that appear most relevant based on existing knowledge. The
purpose of identifying an exhaustive list of questions is keep
researchers open to alternative hypotheses that may need to be examined
if current research cannot determine limiting factors in freshwater
production of salmon and steelhead that are subject to change through
mitigation. Using the above example, if temperature is determined to be
at the optimal temperature in several areas to maximize growth and
temperature, then perhaps freshwater production is limited by survival
in the egg life-stage (e.g. due to sedimentation), not in the juvenile
freshwater life-stage. Therefore, during synthesis of the research in
the John Day Basin it will be necessary for the AFG to review an
exhaustive list of questions.

**5.2 Identifying effective mitigation
strategies**[]{#__RefHeading___Toc80112527 .anchor}

As stated throughout the document, the main goal of the AFG is to
identify effective mitigation strategies to increase salmonid production
in the John Day Basin. This will require intensive RME efforts to
identify limiting factors, which we have described previously. This will
establish status, trends, and causal mechanisms of salmonids and their
habitat at various spatial resolutions. The AFG is responsible for
synthesizing the RME effort and designing an experimental restoration
project at the appropriate spatial and temporal scale to increase
freshwater production. The methods used to conduct this synthesis will
depend on the data form, availability, and relevance and it thus
expected to evolve during the synthesis process. An example how this
synthesis is envisioned is described in Figure 8.

Recall that effective mitigation strategies will have to focus on
mutable characteristics of the landscape, namely human induced changes.
The five land uses described in Figure 3 will be evaluated by research
occurring at the basin/subbasin scale. Assume the Landscape Change and
Pattern Analysis Project identifies agriculture as a land use activity
that has higher correlated, temporally and spatially, to habitat
patterns important to steelhead (Figure 8). Say, of the multiple impacts
that agriculture can have on stream function the Assessment of Stream
Bed Substrate Stability and Excess Sediment Project, indicates that
excessive sedimentation is most important (Figure 8). The TMDL project
may find that excessive sedimentation has lead to reduced
surface/subsurface water exchange resulting in increase temperatures.
Increase in temperatures may be shown to be limiting fish growth,
survival and production by the Juvenile Salmon and Steelhead Production
Project (Figure 8). By modeling alternative sediment loads to the stream
bed, the TMDL model may suggest that reduction of sediments in the
stream bed may increase water exchange and decrease temperatures. The
decrease in temperatures may result in an increase in fish production.

**Figure 9.** A hypothetical example of how synthesis of the John Day
RME efforts may be used by the AFG to identify, design, and test
restoration approaches in John Day Basin[]{#__RefHeading___Toc80112538
.anchor}. This figure builds off of Figure 3 as example of how various
research projects may identify the factors at multiple scales may lead
to decreases in fish production. This information is then used to design
a watershed study as depicted in Figure 3.

Through this synthesis of the available information, an experimental
restoration project to reduce sediments in some watersheds while using
other non-manipulated watersheds as controls is conducted (Figure 8). An
intensive effectiveness monitoring program (based on lessons learned
from the status and trends monitoring now occurring) and other research
projects are used to evaluate the impacts of this restoration project.
Results of this large-scale experiment may demonstrate that reduction of
fine sediments may have a large positive impact on salmon production
and, therefore, a basin-wide strategy to improve agricultural practices
should be implemented to aid in the recovery of steelhead in the John
Day. Alternatively, no changes may have occurred as a result of the
removal of fine sediments in the manipulated watersheds in which case
the cycle is repeated based on further research and the increase in
knowledge acquired from this large-scale experiment (Figure 8).

This document is the first to describe how an intensive RME effort will
be implemented in the John Day Basin. The AFG will be responsible to
design, guide and synthesize this information. The process by which
science will be used to design mitigation strategies in the John Day is
expected to evolve as more information becomes available. This document
will be updated on an annual basis to reflect this learning process.
This document will serve as reference and a context for scientists and
managers to house their goals.

**6.0 Literature Cited**[]{#__RefHeading___Toc80112528 .anchor}

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**APPENDIX**

**ORIGINAL PROPOSALS**[]{#__RefHeading___Toc80112529 .anchor}

**[Landscape Change and Patterns Project]{.underline}**

**Section C - Description/Specifications/Work Statement**

I. Introduction/Purpose

The Columbia River basin of the Pacific Northwest has experienced a
significant decline in various populations of Pacific salmon
(*Oncorhynchus* spp.). Many of these declines have been so severe that
some populations have come under protection from the Endangered Species
Act (ESA). These declines are due, in part, to degradation of
terrestrial habitats that are required by Pacific salmon to complete
their freshwater life history stages.

The purpose of this contract is to conduct research which directly
addresses the role of current and future applications of remotely sensed
data and geospatial analysis techniques in monitoring and decision
support of activities which affect the quality and quantity of Pacific
salmon habitat in the Columbia River basin.

II\. Background

The research and management community responsible for understanding the
complex spatial and temporal relationship between social, economic, and
natural resources of this region rely upon the rapidly expanding
technologies of aerial and space borne remote sensing (RS), global
positioning system (GPS) satellites and precision navigation and
surveying, and management and analysis of geographic information using
geographic information systems (GIS). Exploring unique linkage between
these three tools and their related application to Pacific salmon
freshwater life history is the foundation of this contract.

The interaction of any species to its environment is constrained by both
natural and anthropogenic processes at various spatial and temporal
scales. The expected variation in both habitat quality and quantity for
Pacific salmon within the Columbia River basin is also an issue of
spatial and temporal scales. Local (or fine) scale habitat linkages are
fairly well understood, however, broad (or coarse) scale, landscape
habitat linkages are more poorly understood. Human use of the land
surface is reflected in the land cover and land use patterns imposed at
the landscape scale. While there are clear patterns in the correlations
between land use and land cover at a landscape scale, with salmon
population trajectories, these correlations are often too general for
extrapolating mechanistic connections between habitat type and
condition, and salmon population status.

This inability to make mechanistic connections is a result of two
limitations. First, most studies that attempt to relate gross habitat
attributes with population trends, use static geospatial data layers.
Clearly, a time series of land use and land cover change is a better
choice to correlate habitat conditions over time, with salmon population
trends. Second, to date, there has never been a classification of remote
sensed imagery that was specific to Pacific salmon habitat requirements.
Researchers have always used existing geospatial data layers of land use
and land cover, that were never intended for use with these types of
analyses.

Reclamation feels that remote sensing offers a unique (and feasible)
approach to the problems of understanding the Pacific salmon interaction
with the environment across multiple scales. Resource managers
responsible for the recovery of Pacific salmon need better information
about habitat requirements in order to assess the condition of
watersheds eligible for restoration and conservation. Scientists at the
Northwest Fisheries Science Center (DoCNOAA- NMFS) have developed a
landscape scale model for predicting which habitats in a given subbasin
are most likely to support greater densities of Pacific salmon (Pess et
al. 2002; Feist et al. 2003; Steel et al. In Review). This is a useful
tool for resource managers involved with recovery planning activities.
However, this model is limited by the spatial resolution of the input
habitat geospatial data layers.

Because of the enormous spatial extent occupied by Pacific salmon in the
Columbia River basin, resource managers find it difficult to adequately
use field surveys to inventory fine scale habitat attributes. These
surveys are extremely costly and time consuming, precluding the
feasibility of executing such surveys over large geographic areas. Many
resource managers have resorted to using broad scale, landscape habitat
attributes obtained from geospatial data layers as a proxy for ground
surveys. However, there is a poor understanding of the connection
between local and landscape scale habitat attributes, with respect to
anadromous salmonids.

III\. Work Requirements

The Contractor shall conduct a study to develop applications in the use
of remote sensed imagery classifications that:

-   compare the ability of various types of remote sensed imagery to
    identify habitat features relevant to anadromous salmonids, and

-   track land use and land cover change over time.

The central questions to be answered by the study are:

> 1\) Can remote sensed data of different spatial and spectral
> resolutions be used in combination to generate high spatial resolution
> habitat classifications?
>
> 2\) Can pattern recognition or texture analysis be used to enhance
> classification of high spatial resolution/low spectral resolution
> remote sensed data?
>
> 3\) How much of field or ground surveyed information can be gathered
> using remote sensed data?
>
> 4\) What are the limitations of various remote sensed data layers with
> respect to habitat feature delineation?
>
> 5\) How much of remote sensed imagery classification process can be
> automated?
>
> 6\) Are riparian and wetland habitats accurately classified using
> LADNSAT ETM+ remote sensed data?
>
> 7\) Is it feasible to use change detection of LANDSAT ETM+ remote
> sensed data in habitat models?
>
> 8\) Does a time series of land use and land cover improve the fit of
> fish habitat models?

The Contractor shall address two spatial extents in the context of the
research questions listed above. First at the "whole basin extent",
within each of the six subbasins of the Columbia River basin - Grande
Ronde (OR); John Day (OR); Salmon (ID); Wenatchee (WA); Willamette (OR);
and Yakima (WA) -- the Contractor shall focus on the questions related
to land use and land cover classification and change detection.

Extent 1: Reclamation already has a time series (1984, 1988, 1992, 1996,
and 2000) of raw LANDSAT TM imagery which be provided to the Contractor.
The Contractor shall produce a series of geospatial datalayers
containing the various classified land use and land cover categories for
each year in the remote sensed imagery time series; along with a
manuscript submitted to peer-reviewed scientific journals descriptive of
that resulting dataset and the procedures and protocols which were used
in its creation.

Reclamation is interested in having the Contractor describe the change
in the follow broad categories of land use and land cover:

-   Agriculture

-   Urban

-   Logging

-   Riparian vegetation

-   Wetland vegetation

-   Roads

Extent 2: The second spatial extent of interest to Reclamation is the
upper Salmon River subbasin within the Salmon River basin, Idaho, in the
Pacific Northwest of the United States. Reclamation has a LANDSAT ETM
scene, as well as IKONOS 1m panchromatic and 4m multispectral images.
The Contractor shall produce a final product that is a geospatial data
layer(s) containing various land use and land cover categories, as well
as manuscripts submitted to peer reviewed scientific journals addressing
the preparation of these data, a description of the composition and
configuration of the resulting land use and land cover data, and an
assessment of the data application to fish habitat models. The initial
classifications are:

-   Logging extents,

-   Riparian vegetation,

-   Wetland vegetation

-   Roads,

-   Push-up dams,

-   Salmon redds or nests,

-   In stream habitat variables:

    -   Pools, riffles, glides

    -   Stream channel width

    -   Log jams and large woody debris

    -   Substrate type

    -   Channel incision (as a result of loss of beaver habitat, grazing
        \[trampling, compaction, and devegetation\],and climate change)

To accomplish these goals, the Contractor shall ensure that:

-   all Geospatial data layers share a common projection and coordinate
    system (i.e., UTM),

-   all Geospatial data layers are maintained in one of the three
    standard ESRI formats for GIS data (ARC/INFO coverage or grid,
    ArcGIS Geodatabase, or ArcView shapefile or grid), and

-   all Geospatial data layers include FGDC compliant metadata.

The Contractor shall review existing efforts to classify land use and
land cover in the United States, such as U.S.Geological Survey (USGS)
National Land Cover Database; USGS Land Use and Land Cover Program,
NationalGAP Analysis Program; and the Northwest Habitat Institute
Current and Historic Wildlife-Habitat Types Program.

IV\. Required Approach to the Work

The use of Geographic Information Systems (GIS) and Remote Sensing (RS)
in spatial analysis provides the tool to manage, edit, and analyse
spatial and temporal patterns in these data. Mapping the configuration
of the landscape at a given time has become a task best addressed
through the classification of multispectral remotely sensed data. The
image processing goal is to group the variation in the surface material
reflection at different wavelengths of solar energy into recognizable
categories of land cover. Changes in the composition and configuration
of these mapped data layers serve as structural evidence of physical,
biological, and chemical processes that function in the landscape. As an
integrated and interdisciplinary analysis tool, GIS, RS, and Spatial
Data Analysis combine as a useful technique for understanding ecosystem
dynamics and their link to habitat sustainability.

The Contractor shall focus on three types of land cover classification
and spatial and temporal analysis through the proposed work:

[A. Land use and Land cover classification]{.underline}: The Contractor
shall begin with a method used to identify general surfaces material
based upon the guided clustering or hybrid image classification approach
(Richards1993, Lillesand and Kiefer, 1999) that applies both
unsupervised (automatically generated) and supervised (manually
generated) clustering algorithms to produce a final classification. This
shall be expanded by applying a discrete Normalized Difference
Vegetation Index (NDVI) (Burgan 1993) band ratio grouping to selected
spectral clusters and a normalized elevation value prior to assigning
the characteristic to each land cover class. This Hybrid classification
procedure is a valuable tool where high variability in the spectral
characteristics of a given land cover type can be anticipated. However,
this requirement in no way restricts the Contractor from applying
different classification to the resulting spectral clusters to ensure a
range of uses to the resulting data.

[B. Change detection and outcome correlation]{.underline}: This general
category describes the analysis of correlation and covariance between
changes in spatial pattern metric between independent time steps within
a dataset for a given study area. The desired result here is to convey a
quantitative measure for the changing shape and configuration of the
phenomenon. Simple spatial analysis tools found in most commercial
geographic information systems easily perform the analysis of variance,
correlation, covariance, and semi-variance. One of the most important
preprocessing steps to ensure the meaningfulness of these types of
analyses is to ensure a cell-to-cell georegistration. While correlation
and covariance may illustrate changing relationships between themes over
time, changes in the spatial variance can illustrate changes in spatial
structure of a single theme (Cressie, 1991) over time. Differing
measures of spatial structure can be obtained from available GIS
procedures or public domain spatial analysis software such as FRAGSTATS
ver. 2.0. (McGarigal and Marks 1994), the R Package (Casgrain and
Legendre 2001), and ADE-4 (Thioulouse et al. 1997). The aim of
quantifying the spatial/temporal pattern is to better understand not
only the variety in composition, but also the configuration, of the
changing elements within an analysis region. Describing the region\'s
spatial structure in this way is sometimes referred to as physiognomy or
pattern analysis (Dunning et al. 1992, Turner 1989). In general, indices
or metrics describe both the variety and abundance of elements or
spatial objects (composition), or the shape and relative placement of
those objects (configuration) for the region as a whole. These indices
together are descriptive of the spatial structure, and are not
statistical inferences for spatial process (see Ripley, 1988 or Cressie,
1991).

[C. Translations across multiple spatial "scales"]{.underline}: As the
correlation of measurements of a phenomena increases or decreases over
space, the phenomena can be described by its "self similarity" or
"auto-correlation." Relating the shape of either the spatial
semi-variogram or a metric of spatial auto-correlation for each class of
land cover at each time step with ground-truth observations of habitat
composition will allow the Contractor to investigate the strength of the
spatial relationship of spatial scale with habitat structure. This
approach may offer one tool in determining the "spatial scale" for
sampling and future survey analysis.

V. Tasks, Schedule and Required Deliverables

The work shall be divided into five tasks and is scheduled over a
project period of twenty four (24) months from the date of contract
award.

*Task (1), Raw Image Data Inventory and Management*: This task shall
focus on the preparation, georegistration, any necessary spatial and
spectral correction, inventory, and management of the collection of
remotely sensed satellite image data from Reclamation. Metadata for
these data shall be assembled, assessed for quality where possible, and
then cataloged when used in the application. The Contractor shall make
an assessment, in conjunction with the NOAA staff, of the quality and
relevance of the data. *Schedule*: Beginning in at project start and
continuing for 6 months. Documentation delivered in 9 month following
project start.

*Task (2), Land Use and Land Cover Classification*: This task shall
produce an adaptive classified land use and land cover data set for the
time series of imagery provided by Reclamation. Included in this task is
the documentation of the procedure and protocols used in the final
classification.

*Schedule*: Beginning in the third month of the project and continuing
for 12 months. Documentation and manuscript submission shall be complete
three month later, in the 18th month of the project.

*Task (3), Land Use and Land Cover Change Analysis*: This task shall
produce a descriptive narrative and mapped characterization of the
change in land use and landcover at an appropriate resolution for both
the whole basin extent and the Upper Salmon river basin extent. This
task shall result in a submitted manuscript to a peer review journal.

*Schedule*: Beginning in 9th month of the project and continuing for
nine month. The submitted manuscript, descriptive narrative and map
products shall be delivered three months later in the 21st month of the
project.

*Task (4), Landscape Assessment*: This task shall extend the descriptive
land use and land cover change data into a spatially explicit pattern
analysis relating landscape metric with habitat change. The Contractor
shall assess the meaningfulness of metrics for use in habitat models and
applications to management decisions. This task shall also include a
submitted manuscript to a peer-review journal.

*Schedule*: Beginning in the 12th month of the project and continuing
for 9 months. The submitted manuscript shall be delivered at the end of
the project period (month 24).

*Task (5), Project Administration*: This task includes project task
coordination, submission of semi-annual progress reports, preparation of
all final documentation, and manuscript submission. Semi-annual progress
reports and a final project summary document consisting of progress
reports, documentation for all work completed, and draft manuscripts,
shall be provided.

*Schedule*: Beginning in at the start of the project and continuing
throughout the life of the project. Semi-annual progress reports
including for each project task, the staffing activities, task
completion targets, and major activities shall be provided on a 6 month
interval follow the start of the project.

**Proposal: Assessment of Stream Bed Substrate Stability and Excess
Sediment in Streams in the John Day Basin of Oregon**

Philip R. Kaufmann, Phil Larsen (U.S.EPA, NHEERL, WED, Corvallis, OR.)

John Faustini (OSU Dept of Fisheries & Wildlife, Corvallis, OR)

**PROBLEM STATEMENT AND SUMMARY:**

Elevated water temperature and excess deposition of fine sediments are
thought to be major causes of biological impairment in streams in the
John Day Basin of Oregon, especially restricting the spatial and
temporal patterns of key salmonid species. Many of the John Day streams
and rivers are listed as water quality-limited for sediment and
temperature on the State-Federal 303(d) list of impaired waters.
Accordingly, the Oregon Department of Environmental Quality (ODEQ) must
develop Total Maximum Daily Loads (TMDLs) for these listed water bodies.
In addition, the NPCC (Northwest Power and Conservation Council) must
evaluate the effectiveness of habitat restoration and mitigation actions
that address these stressors.

We propose to estimate the prevalence and evaluate the impacts of excess
fine sediments throughout the John Day Basin by using an existing data
set of 100+ recently sampled stream reaches and an analytical approach
that evaluates the relationship between sediment supply and sediment
transport as they are affected by natural factors and human
disturbances. (See Background Section for a description of the method).
Stressors identified in our proposed efforts can be directly
incorporated in the ASource Assessment@ of the upcoming John Day and
Deschutes subbasin sediment and temperature TMDLs.

Our proposed approach consists of four elements, the first two in Stage
1 of the Budget and Timeframe; the second two in Stage 2:

1\. **Estimate the proportion of the channel network with excess fine
sediments.** We will evaluate existing channel habitat data that ODEQ
collected as part of EMAP-type surveys conducted in the John Day Basin
over the past several years at more than 100 sites. The data are readily
amenable to the types of analyses described in the Background section.
We will also evaluate the extent to which data collected under PIBO
(Pacfish/Infish Biological Opinion) are compatible with our estimation
procedures and will incorporate their data to the extent feasible. We
will also coordinate with ODFW to modify their protocols so that we can
make these estimates with the ongoing habitat surveys planned to start
in 2004. ![](media/image5.wmf){width="2.682638888888889in"
height="1.8430555555555554in"}

2\. **Estimate the relationship between an incidence of excess fine
sediments in the channel network and measures of human-related
disturbance.** We will characterize watershed and riparian disturbance
at the sample sites. The list of potential stressors includes, but is
not limited to: 1) grazing; 2) timber harvest; 3) agricultural cropping,
4) irrigation practices, and 5) roads. We will begin this analysis using
a subset of approximately 26 sites in the John Day Basin for which
detailed watershed disturbance metrics (including percent of watershed
in forested, clearcut, and partially cut land cover; watershed and
riparian road density, a grazing intensity index, and other metrics)
have already been calculated from map and air photo analysis in
combination with site visit data. We will extend this analysis to the
rest of the sites with available data, and if resources permit, obtain
the appropriate watershed scale data.

3\. **Estimate sediment delivery at each sampling location.** We will
apply a set of GIS-based modeling tools developed by the EPA Landscape
Research Group in Las Vegas to estimate sediment delivery at each
sampling location. This approach uses topographic, soil texture, and
land cover data to estimate spatially explicit soil erosion by applying
the Revised Universal Soil Loss Equations (RUSLE) in a GIS context.
These results are combined with SEDMOD (Spatially Explicit Delivery
MODel \[Fraser, 1999\]) to estimate the average rate of sediment
delivery to the stream channel network within a watershed.

4\. **Map locations in the channel network expected to contain excess
fine sediments.** We will explore the possibility of using the
RUSLE/SEDMOD approach in a more predictive fashion, as follows. First,
we will substitute synthetic land cover data that represent
Aundisturbed@ conditions by replacing cover classes that are associated
with human disturbances with land cover types likely in the absence of
human activity. Differences in estimated sediment supply to the stream
network between the two scenarios (Aactual@ minus Aundisturbed@) would
represent an estimate of the *increase* in sediment supply due to human
disturbance. Second, we will examine associations between RBS and
modelled perturbations in the sediment supply. We hypothesize that RBS
will be more strongly \[negatively\] correlated with these *changes* in
sediment supply than with estimated total sediment supply under current
land use. We expect that undisturbed streams maintain a long-term
equilibrium between sediment supply and transport, with the result that
RBS would remain relatively uniform within an undisturbed stream network
even if sediment supply is spatially variable. Last, if RBS is strongly
related to estimated anthropogenic perturbations in sediment delivery to
stream channels for the EMAP sites, then a regression relationship could
be developed to use modeled values of excess sediment delivery to
predict and map locations within the stream network where decreased bed
stability (low RBS) and excess sediment deposition are likely to be
found.

The integration of the modeling approach with the sample survey results
should allow us to improve our ability to evaluate where in the channel
network excess sediments are supplied (associated with various human
disturbances), where excess sediments are deposited, and potentially,
where remedial actions are likely to have greatest potential effect.

**Budget and Time frame:**

Stage 1 (July 2004-April 2005):

Products:

Manuscript examining natural and anthropogenic controls on channel form
and sediment.

Database for modelling current and estimated alteration of sediment
supply rates.

Stage 2 (Jan 2005 - Sept 2005).

Products:

Map of estimated current erosion and sediment supply rates in John Day
Basin

Map of estimated anthropogenic alteration of sediment supply rates in
John Day Basin

Map of anthropogenic sediment alteration in stream network of John Day
Basin

**BACKGROUND:**

Streambed characteristics are often cited as major controls on the
species composition of macroinvertebrate, periphyton, and fish
assemblages in streams (e.g., Hynes, 1972; Cummins, 1974; Platts et al.,
1983). Along with bedform (e.g., riffles and pools), substrate size is a
primary control on the hydraulic roughness and consequently the range of
water velocities in a stream channel. It also influences the size range
of interstices that provide living space and cover for
macroinvertebrates, salamanders, sculpins, and darters. Accumulations of
fine substrate particles fill the interstices of coarser bed materials,
reducing habitat space and its availability for benthic fish and
macroinvertebrates (Platts et al. 1983; Hawkins et al. 1983; Rinne
1988). In addition, these fine particles impede circulation of
oxygenated water into hyporheic habitats. Substrate characteristics are
often sensitive indicators of the effects of human activities on streams
(MacDonald et al., 1991). Decreases in the mean substrate size and
increases in stream bed fine sediments can destabilize stream channels
(Wilcock 1988) and may indicate increases in the rates of upland erosion
and sediment supply (Lisle 1982 Dietrich et al. 1989). In addition,
large inputs of sediment can lead to reduced channel complexity and
frequency of pools (Madej, 2001), which could alter the scale and
relative magnitude of hyporheic flow that depends upon streambed
morphology (Kasahara and Wondzell, 2003),

Although many human activities directly or indirectly alter stream
substrates, streambed particle sizes also vary naturally in streams with
different sizes, slopes, and surficial geology (Leopold et al. 1964;
Morisawa 1968). The size composition of a streambed depends on the rates
of supply of various sediment sizes to the stream and the rate at which
the flow takes them downstream (Mackin, 1948). Sediment supply to
streams is influenced by topography, precipitation, and land cover, but
the source of sediments is the basin soil and geology, and supplies are
greater where these materials are inherently more erodible. Once
sediments reach a channel and become part of the stream bed, their
transport is largely a function of channel slope and discharge during
floods. (In turn, flood discharge is largely dependent upon drainage
area, precipitation intensity, and basin topography, vegetation and
soils..) For streams that have the same rate of sediment input from
watershed erosion, steeper streams tend to have coarser substrates than
those with lower gradient, and larger streams (because they tend to be
deeper) have coarser substrates than small ones flowing at the same
slope. However, this transport capability can be greatly altered by the
presence of such features as large woody debris and complexities in
channel shape (sinuosity, pools, width/depth ratio, etc.). The
combination of these factors determines the depth and velocity of
streamflow and the shear stress (erosive force) that it exerts on the
streambed. By comparing the actual particle sizes observed in a stream
with a calculation of the sizes of particles that can be mobilized by
that stream, we can evaluate the streambed stability. Furthermore, we
can evaluate whether low values of bed stability are due to accumulation
of fine sediments (Aexcess fining@) as opposed to an increase in
discharge (hence, an increase in transport capacity), and may examine
watershed data to infer whether the sediment supply to the stream may be
augmented by upslope erosion from anthropogenic and natural
disturbances.

We propose to apply a field and analytical approach used by the USEPA
and ODEQ to evaluate the deviation of observed streambed particle size
from that expected in the absence of anthropogenic disturbances. This
approach to assess excess sediment in streams uses channel and substrate
data from stream surveys (e.g., EMAP and REMAP). Current sediment size
distributions are based on a systematic Apebble count.@ Expected size is
based upon sediment transport theory and the assumption of an
equilibrium condition between long-term sediment supply and transport in
the absence of disturbance. Specifically, we use quantitative
measurements of channel dimensions, slope, bankfull flow depth, large
woody debris, residual pool depth and other measurements to estimate
mean bed shear stress at bankfull flows and the critical substrate
diameter that can be mobilized by those flows. Mean observed particle
sizes substantially larger than the critical (expected) diameter may
indicate a sediment-starved system,such as the proximal downstream
channel below a dam. Mean observed particle sizes much smaller than that
expected likely indicate excess sediment accumulation due to elevated
sediment supplies to the stream. Observations of human disturbance,
riparian characteristics and condition, bank condition etc. provide
evidence of the causes of the excess sediment supply. The protocol and
the index are more quantitative, precise and accurate than existing
visual qualitative methods typically applied by resource managers.
Because the approach can be applied efficiently to a large number of
sites throughout a basin, it is easier to apply in a basinwide study
than more labor-intensive approaches often applied in research or
engineering projects. The excess sedimentation index, RBS (Kaufmann et
al. 1999), which is calculated from data collected using EMAP-style
habitat information, adds an important component beyond that typically
used by state programs in that it takes into account the stream=s
capacity to transport bed material rather than simply the observed
particle sizes or sediment deposition.

**QUANTIFYING CHANNEL RESPONSE TO ALTERED SEDIMENT INPUTS**

***Relative Bed Stability (RBS)*** is calculated as the ratio of
observed substrate diameter divided by the calculated Acritical@ or
mobile diameter (Dingman 1984). RBS is the inverse of the substrate
Afining@ measure calculated by Buffington and Montgomery (1999a,b), and
is conceptually similar to the ARiffle Stability Index@ of Kappesser
(2002) and the bed stability ratio discussed by Dietrich et al. (1989).

***Bed Substrate Size**:* When evaluating the stability of whole
streambeds (vs. individual bed particles), observed substrate is
typically represented by the median surface particle diameter (e.g.,
D~50~) or the geometric mean diameter (D~gm~). To characterize the
actual substrate particle size distribution in a stream channel, EMAP
follows widely accepted procedures. The EMAP field protocols (Kaufmann
and Robison, 1998) like those of most practitioners (e.g., Platts et
al., 1983; Bauer and Burton, 1993) employ a systematic Apebble count,\"
as described by Wolman (1954), to quantify the substrate size
distribution.

***Critical Substrate Size:*** For calculating critical (mobile)
substrate diameter in a natural stream, it is necessary to estimate
average streambed tractive force, or shear stress, for some common
reference flow conditions likely to mobilize the streambed. Bankfull
discharge is typically chosen for this purpose, though it is more
appropriate for gravel-bed streams than for Alive-bed@ streams such as
naturally sand-bedded streams that transport bedload at lower flows. The
EMAP approach for estimating the critical substrate particle diameter in
a stream is based on sediment transport theory (e.g., Simons and
Senturk, 1977), which allows an estimate of the average streambed shear
stress or erosive tractive force on the bed during bankfull flow. Stream
channels can be very complex, exhibiting a wide range in local bed shear
stress due to small-scale spatial variation in slope, depth, and
roughness within a channel reach (Lyle et al., 2000). In developing this
approach, EMAP researchers (Kaufmann et al., 1999; Kaufmann and Larsen,
in review) used physical habitat measurements collected in synoptic
surveys (Kaufmann and Robison 1998) to estimate the channel
characteristics affecting bed shear stress at bankfull flows. These
field measurements include bankfull channel dimensions, slope, channel
complexity, and large woody debris. Using the channel and substrate data
described in the two preceeding paragraphs, EMAP researchers modified
the Dingman (1984) RBS calculation to accomodate losses in shear stress
resulting from large woody debris and channel complexity (Kaufmann et
al. 1999). The reductions in shear stress, and therefore critical
diameter, caused by these roughness elements allow fine particles to be
more stable in a stream of a given slope and depth.

***Interpretation of RBS Values:*** We hypothesize that, given a natural
disturbance regime, sediment supply in watersheds not altered by human
disturbances will be in approximate long-term dynamic equilibrium with
transport. For streams with sediment transport limited by competence
(critical shear stress), rather than total capacity (stream power), the
mean of RBS values in these relatively unaltered streams should tend
toward a value of 1.0 and may have slight surface coarsening due to low
hillslope erosion rates (Dietrich et al. 1989). Alternatively, and more
generally, RBS for streams draining watersheds relatively undisturbed by
humans should tend towards some value (not necessarily 1.0) that is
characteristic of the region or of specific classes of streams within a
region, depending upon their natural lithology, soils, topography,
climate, and vegetation. RBS values in EMAP sample streams range between
approximately 0.0001 and 1000. A high positive value of RBS (e.g.,
100-1000) indicates an extremely stable, immovable stream substrate like
that in an armored canal, a tailwater reach below a dam, or other
situations where the sediment supply is low, relative to the hydraulic
competence of the stream to transport bedload sediments downstream
(Dietrich et al., 1989). Very small RBS values (e.g., .01-.0001)
describe a channel composed of substrates that are frequently moved by
even small to moderate discharges.

In watersheds where sediment supplies are augmented relative to a
stream=s bedload transport competence, we expect to see evidence of
excess fine sediments, or Atextural fining@ (Dietrich et al., 1989).
Very small RBS values (e.g., .01-.0001) describe a channel composed of
sediment that is can be transported by a wide range of flows and hence
moves frequently, indicating excessive amounts of fine particles
compared with expected values in comparable undisturbed watersheds. Such
evidence of textural fining of the streambed (RBS\<\<1) typically occurs
when land use activities increase hillslope erosion (Lisle 1982;
Dietrich et al. 1989; Lisle and Hilton 1992). We further expect that,
for streams draining basins of equal erodibility, RBS values should
decrease in proportion to increases in sediment supply above that
provided by the natural land disturbance regime. To the extent that
human land use increases sediment supply by land erosion within regions
of relatively uniform erodibility, RBS of streams in surveys should be
inversely related to basin and riparian land use intensity and extent.
We have demonstrated this association of lower RBS with land use
disturbances in several regions (Kaufmann et al, 1999, Kaufmann and
Larsen, in review) Finally, the more erodible the basin lithology within
a geoclimatic region, the steeper we expect the decline in RBS with
progressive disturbance to be. As demonstrated for streams in the
Pacific Coastal region by Kaufmann and Larsen (in review), this means
that we expect any given amount of land use disturbance to augment
sediment supplies to a greater degree in basins underlain by erodible
rocks than in basins underlain by more resistant rock.

***Channel Morphology Responses***

In addition to textural responses such as streambed fining, channels may
response to changes in sediment supply through changes in channel
morphology. In particular, large inputs of sediment (increased sediment
supply) can cause increases in width-depth ratio or decreases in channel
complexity and the depth and frequency of pools (Madej, 2001). Such
responses would have important implications for channel shading and for
hyporheic flow, which is largely driven by streambed morphology
(Kasahara and Wondzell, 2003), and hence also would have important
implications for stream temperature, which is profoundly influenced by
both shading and hyporheic flow (White et al., 1987; Fortner and White,
1988). Relevant morphological characteristics are quantified in EMAP
data by several residual pool and thalweg depth metrics derived from the
thalweg depth profile. We will evaluate whether the streams in the
Deschutes/John Day dataset exhibit morphological responses to altered
sediment supply from human activities by testing whether channel width,
incision, constraint, residual pool depth or the coefficient of
variation in thalweg depth are associated with variations in human
disturbance or with predicted increases in sediment supply due to human
activities.

**DATA SOURCES**

The work we propose will focus on data collected within the arid
Deschutes/John Day subbasin, located in central Oregon. The
Deschutes/John Day subbasin is a focus area of the Western EMAP program,
so physical habitat, biological, and GIS data have been collected at
over 100 stream sampling sites in the basin (Fig. 1). EMAP data
collection efforts for this area occurred over the past several years,
and were completed in the summer of 2003. All the physical habitat data
and much of the biological data collected during these efforts have been
processed and included in the U.S. EPA EMAP database, SWIM (Surface
Water Information Management). In addition to the measurements of stream
channel characteristics used to calculate substrate metrics and RBS, the
EMAP field data contain systematic observations of riparian vegetation
and the presence or absence of 11 categories of human disturbance
(Kaufmann and Robison, 1998; Kaufmann et al., 1999).

For all the sample sites, watershed boundaries have been delineated and
a suite of landscape metrics have been computed using digital elevation
data, satellite imagery, and existing GIS data layers. These landscape
metrics include several measures of anthropogenic disturbance including
road density based on TIGER digital line files (Bureau of the
Census,1992) and land cover information based on classified Thematic
Mapper imagery from the National Land Cover Database (NLCD)
(http://landcover.usgs.gov/natllandcover.asp). In addition, at
approximately 26 sites in the John Day basin, more detailed disturbance
metrics developed from map and air photo analysis in combination with
site visit information are also available. These more detailed
assessments include road metrics derived from digital road coverages
updated using recent USFS fire road maps (including road density in the
entire watershed and within a 30 m riparian buffer, as well as number of
road-stream crossings in the watershed), a grazing intensity index, and
land cover information derived from analysis of two sets of 1:40,000
scale aerial photos (color infrared imagery from the early 1990s and
black-and-white imagery from 2000). The land cover information includes
percent cover metrics for the watershed as a whole as well as the
riparian network (30 m buffer), including forested, clearcut, and
partial cut cover classes for assessing timber harvest impacts.

**CHARACTERIZING HUMAN DISTURBANCE AND CHANNEL RESPONSE**

We will use the data sources described above to quantify human
disturbance (stressors) at the watershed scale for all EMAP sample sites
and at the watershed and riparian scale (within a 30-m riparian buffer)
for the subset of approximately 26 sites for which more detailed land
cover and disturbance data are available. Potential stressors we will
quantify using these data include, but are not limited to, grazing;
timber harvest, agricultural cropping, and roads. We will use
nonparametric statistical methods (e.g., principal components analysis
and Spearman rank-order correlation statistic) to explore and test
hypothesized associations between landscape/riparian stressors and
channel response (i.e., RBS and excess fine sediments, as well as
channel morphology metrics such as residual pool depth and variability
of thalweg depth).

**MODELING NATURAL AND ANTHROPOGENIC CONTROLS ON SEDIMENT SUPPLY**

We propose to apply a set of GIS-based modeling tools developed by the
EPA Landscape Research Group in Las Vegas (Van Remortel and Heggem,
2003) to estimate sediment delivery to stream channels at each of the
100+ sampled reach locations. This approach applies the Revised
Universal Soil Loss Equation (RUSLE; Renard et al., 1997) in a GIS
context to estimate spatially varying soil erosion rates across the
landscape (Van Remortel,et al., 2001). The RUSLE is an empirical formula
that estimates soil erosion caused by raindrop impact and surface runoff
(sheet and rill erosion) based on rainfall amount and intensity
(30-minute maximum intensity with a 10-yr recurrence interval); an
empirical soil erodibility factor determined by soil texture; topography
as represented by slope length, steepness and shape; and a land cover
factor that accounts for vegetation and agricultural practices. In the
implementation developed by the Las Vegas lab (Van Remortel and Heggem,
2003), the software programs are bundled with the necessary gridded data
sets to run the RUSLE computations, including 30-m digital elevation
model (DEM) data (although higher resolution data can be used if
availableCe.g., 10 m DEM), soil texture data from the STATSGO database
(USDA-NRCS, 1994), spatially distributed rainfall erosivity (R-factor)
data derived from precipitation intensity estimated using the PRISM
model (Daly et al., 1994; Daly and Taylor, 2002), and NLCD land cover
data.

Output from the RUSLE module is used as input to another model, SEDMOD
(Spatially Explicit Delivery MODel \[Fraser, 1999\]), which also uses
much of the same input data. SEDMOD estimates sediment deposition that
occurs during overland flow on hillslopes to calculate a spatially
explicit sediment delivery ratio (SDR) that varies with drainage area,
slope, ground cover and other factors. The SDR, computed on a
cell-by-cell basis, is the estimated fraction of eroded sediment
delivered to the next downslope cell and, ultimately, to stream
channels. In combination with the RUSLE estimates of spatially varying
erosion rates, the SDR is used to estimate a basin average sediment
delivery rate to the stream channel network. In addition, although the
model only outputs basin average summary metrics, it also computes
sediment delivery values along the drainage network which can be saved
to an output file. These data can be used to map spatially varying
sediment delivery rates to the channel and to estimate sediment supply
at the basin Apour point@ (i.e., at the location of the sampled stream
reach).

We propose to use the RUSLE and SEDMOD models to estimate the
basin-average sediment supply rate and the total sediment delivery rate
at the basin outlet for the watersheds associated with each of the EMAP
sample sites in the Deschutes/John Day dataset. These estimated sediment
delivery rates incorporate human disturbance effects (albeit somewhat
crudely) through their dependence on human-influenced land cover data.
If our hypothesis that RBS values should be depressed (and abundance of
fine sediments increased) in streams where human disturbance has
augmented sediment delivery to stream channels is correct, then we would
expect to see lower RBS values at EMAP sample sites located in basins
that have high estimated sediment delivery rates due to land use
impacts.

We also would explore the possibility of using the RUSLE/SEDMOD approach
in a more predictive fashion, in two ways. First, although the model in
its current form does not allow substitution of another dataset for the
supplied NLCD data, it would be possible to substitute a synthetic land
cover data that represent Aundisturbed@ conditions by replacing cover
classes that are associated with human disturbances (e.g., clearcuts,
croplands, pasture) with classes that represent land cover types that
would likely exist in the absence of human activity. Differences in
estimated sediment supply to the stream network between the two
scenarios (Aactual@ minus Aundisturbed@) would represent an estimate of
the *increase* in sediment supply due to human disturbance. We
hypothesize that RBS will be more strongly \[negatively\] correlated
with these *changes* in sediment supply than with estimated total
sediment supply under current land use. That is, RBS should respond to
*perturbations* in sediment supply rather than to spatial variations in
sediment delivery. This expectation is a consequence of the assumption
that undisturbed streams maintain a long-term equilibrium between
sediment supply and transport. That is, they adjust their transport
capacity (through adjustments in slope, channel morphology, and bed
texture) to natural spatial variations in sediment supply, maintaining a
balance between sediment supply and transport capacity. Hence, RBS would
be expected to remain relatively uniform within an undisturbed stream
network even if sediment supply is spatially variable.

Secondly, if RBS is strongly related to estimated anthropogenic
perturbations in sediment delivery to stream channels for the EMAP
sites, then a regression relationship could be developed to use modeled
values of excess sediment delivery to predict and map locations within
the stream network where decreased bed stability (low RBS) and excess
sediment deposition are likely to be found.

**REFERENCES CITED**

Bauer, S.B., and T.A. Burton. 1993. Monitoring Protocols to Evaluate
Water Quality Effects of Grazing Management on Western Rangeland
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X, Seattle, WA. 166 p.

Buffington, J.M. and D.R. Montgomery. 1999a. Effects of hydraulic
roughness on surface textures of gravel-bed rivers. *Water. Resour. Res.
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Buffington, J.M. and D.R. Montgomery. 1999b. Effects of sediment supply
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Bureau of the Census. 1992. TIGER/Line Files, Census of Population and
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Cummins, K.W. 1974. Structure and function of stream ecosystems.
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Daly, C., R.P. Neilson, and D.L. Phillips. 1994. A
statistical‑topographic model for mapping climatological precipitation
over mountainous terrain. Journal of Applied Meteorology, 33: 140‑158.

Daly, C., and G.H. Taylor. 2002. Development of new spatial grids of R
factor and 10-yr EI20 for the conterminous United States. Internal EPA
report, NERL-LV. Spatial Climate Analysis Service, Oregon State
University, Corvallis, Oregon.

Dietrich, W.E., J.W. Kirchner, H. Ikeda, and F. Iseya. 1989. Sediment
supply and the development of the coarse surface layer in gravel bed
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Dingman, S.L. 1984. Fluvial Hydrology. W.H. Freeman, New York. 383 p.

Fortner, S.L., and D.S. White. 1988. Interstitial water patterns: a
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Fraser, R.H., 1999. SEDMOD: A GIS_Based Delivery Model for Diffuse
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Forestry and Environmental Studies, Yale University, New Haven, CT.

Hawkins, C.P., M.L. Murphy, and N.J. Anderson. 1983. Density of fish and
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Hynes, H.B.N. 1972. Ecology of Running Waters. Univ. of Toronto Press,
Canada. 555p.

Kappesser, G.B. 2002. A riffle stability index to evaluate sediment
loading to streams. J. Am. Water Resour. Assoc. 38(4):1069-1081.

Kasahara, T., and S.M. Wondzell. 2003. Geomorphic controls on hyporheic
exchange flow in mountain streams. Water. Resour. Res. 39(1), 1005,
doi:10.1029/2002WR001386.

Kaufmann, P.R. and D.P. Larsen. (In review). Sedimentation in Pacific
Northwest Coastal Streams \-- Evidence from Regional Surveys of Bed
Substrate Size and Stability.

Kaufmann, P.R., P. Levine, E.G. Robison, C.Seeliger, and D.Peck. (1999)
Quantifying physical habitat in wadeable streams EPA 620/R-99/003.
Environmental Monitoring and Assessment Program (EMAP), U.S.
Environmental Protection Agency, Washington, DC. 102 pp + Appendices.

Kaufmann, P.R. and E.G. Robison. 1998. Physical Habitat Assessment. pp
6-1 to 6-38 [In]{.underline}: D.J. Klemm and J.M. Lazorchak, eds.,
Environmental Monitoring and Assessment Program 1994 Pilot Field
Operations Manual for Streams. EPA/620/R-94/004. Environ. Monit. Syst.
Lab., Office of Research and Develop., U.S. Envir. Protection Agency,
Cincinnati, Ohio.

Leopold, , L.B. M.G. Wolman, and J.P. Miller. 1964. Fluvial processes in
geomorphology. W.H. Freeman and Co., San. Fran. CA, USA. 522 p.

Lisle, T.E. 1982. Effects of aggradation and degradation on riffle-pool
morphology in natural gravel channels, northwestern California. Water.
Resour. Res. 18(6):1643-1651.

Lisle, T.E. and S. Hilton. 1992. The volume of fine sediment in pools:
an index of sediment supply in gravel-bed streams. Water Res. Bull.
28(2):371-383.

Lisle, T.E., J.M. Nelson, J. Pitlick, M.A. Madej, and B.L. Barkett.
2000. Variability of bed mobility in natural, gravel-bed channels and
adjustments to sediment load at local and reach scales. *Water Resourc.
Res.* 36(12):3743-3755.

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to Evaluate Effects of Forestry Activities on Streams in the Pacific
Northwest and Alaska. WPA 910/9-91-001. U.S. Environmental Protection
Agency, Region X, Seattle, Washington. 166 p.

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59:463-512.

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**[TMDL Project]{.underline}**

**Project Name**

John Day River Basin TMDL

**Project Investigators**

ODEQ staff (currently Don Butcher, Paul Daniello, Brian Kasper, other HQ
& lab staff)

**Work Products**

-   Water quality goals for John Day Basin (to address pH, temperature,
    DO, sediment, macroinvertebrates & bacteria) major rivers and
    streams. Goals will likely be expressed in terms of riparian
    condition improvement, e.g., enhanced vegetation.

-   Water quality management plan to implement above goals

**Budget and Schedule by Work Product**

-   Budget: This is an inter-organizational effort including local
    management agencies. ODEQ budget is approximately 3 FTE for 3 years,
    plus lab analyses & equipment, transportation.

-   Schedule (***[attachment 1]{.underline}***)

**Study Objectives**

-   Comprehensive water quality assessment (for temperature) in the
    North, Middle and South Forks of the John Day River.

-   DO, pH and bacteria assessment on mainstem John Day River

-   Local sediment, bacteria and macroinvertebrate assessments (small
    parts of North Fork & upper mainstem)

-   GIS-based assessment Basin wide (DEM & DOQ assessment of solar
    influence)

-   Based on assessment and modeling, delineate human component of
    pollutant loading.

-   Allocation of pollutant loads (TMDL project includes identification
    of responsible management agencies and collaborative production of
    water quality management plan)

**Study Sites** (Except as noted, study areas are the North, Middle and
South Fork of the the John Day Basin. Sample sites will be
longitudinally distributed along the mainstems of these forks, and
temperature and flow will be monitored at their major tributaries as
well)

-   ***[Attachment 2 identifies the planned number of sample sites per
    area for 2004]{.underline}*** (note: some monitoring has been
    completed as of the date of this draft. All monitoring is planned to
    be completed in 2004)

**Site Selection Methodology**

1.  waterbodies with identified water quality impairment (ODEQ 303d
    list)

2.  longitudinal distribution

3.  determine representative number of sites (judgement)

4.  determine representative locations (local variance, appropriate site
    characteristics for parameter, e.g., morphology in areas without
    human structures)

5.  identify site access

**Sampling Regime**

Mostly status monitoring, though there are 5 longterm quarterly water
quality stations in the Basin that will be utilized.

**What is sampled**

(***[attachment 3]{.underline}***)

**How is it sampled - on the ground (some will be supplemented by GIS
methods)**

> Grab Samples (standard methods)
>
> Dataloggers

-   climate -- Vemco^TM^, Unidatalogger Vemco^TM^, public/private
    weather stations

-   water temperature- Vemco^TM^

-   DO, pH - Hydrolab^TM^

> Vegetation (site ID: species, structure; solar pathfinder)
>
> Morphology and substrate (Rosgen Level II transect, available EMAP,
> pebble count)
>
> Flow, velocity, wetted width and depth (portable flow meter, wading
> rod and tape)

**Proposed Analysis**

-   Longitudinal 1-D shade, flow, wetted width and temperature
    simulation, likley using Heat Source
    ([www.heatsource.info](../www.heatsource.info)).

-   Modeling of other water quality parameters, likely using Qual2K.

-   Linkage of macroinvertebrate distribution to temperature & sediment.

**Reporting Plan**

TMDL document, available on-line

***Attachment 1:***

![](media/image6.wmf){width="6.397916666666666in"
height="3.792361111111111in"}

***Attachment 2:***

***Note -- additonal sites/activities have been completed (temperature
and flow) in the North Fork and Middle Fork.***

***John Day Basin 2004 Monitoring for TMDL --12/3/03 DRAFT***

+----------+-------------------+--------+---------------+------------+
| **303(d) | **Parameter**     | *      | **Where**     | **When**   |
| list**   |                   | *Who** |               |            |
+----------+-------------------+--------+---------------+------------+
| pH, DO   | Hydrolab (pH, DO, | Lab    | UJD (5)       | 1          |
|          | temp)             |        |               | wee        |
|          |                   |        | LJD (4)       | k(Jul-Aug) |
|          |                   |        |               |            |
|          |                   |        | Utley (1)     |            |
+----------+-------------------+--------+---------------+------------+
| B        | Grab Sample       | Lab    | UJD (5)       | 2X at      |
| acteria, | (Bacteria,        |        |               | Hydrolab   |
| pH, DO   | Nutrients, field  |        | LJD (4)       | sites      |
|          | parameters,       |        |               |            |
|          | flow.)            |        | Utley (1)     |            |
+----------+-------------------+--------+---------------+------------+
| Bacteria | Bacteria, flow    | Lab    | UJD(10)       | 3X         |
+----------+-------------------+--------+---------------+------------+
| Temp     | T                 | Lab,   | SFJD          | Done       |
|          | emperature(Vemco) | R      |               |            |
|          |                   | egion, | MFJD          | Done       |
|          |                   | Other  |               |            |
|          |                   | ag     | NFJD          | Done       |
|          |                   | encies |               |            |
|          |                   |        | UJD           | None       |
|          |                   |        |               |            |
|          |                   |        | LJD           | None       |
+----------+-------------------+--------+---------------+------------+
|          | Flow and          | Lab,   | SFJD (10)     | 1 event    |
|          | representative    | R      |               | (Jul/Aug)  |
|          | width & depth     | egion, | MFJD (3)      |            |
|          |                   | Other  |               |            |
|          |                   | ag     | NFJD(3)       |            |
|          |                   | encies |               |            |
+----------+-------------------+--------+---------------+------------+
|          | Vegetation/shade  | Lab    | SFJD (12)     | 1 event    |
|          |                   |        |               | (July-     |
|          | -   1 site per    |        | MFJD (15)     | mid-Sep)   |
|          |     5-10 miles.   |        |               |            |
|          |                   |        | NFJD (20)     |            |
|          | -   ID, solar     |        |               |            |
|          |     pathfinder,   |        |               |            |
|          |     and           |        |               |            |
|          |     vegetation    |        |               |            |
|          |     height)       |        |               |            |
+----------+-------------------+--------+---------------+------------+
|          | Mor               | R      | SFJD (12)     | 1 event    |
|          | phology/substrate | egion, |               | (Aug-Oct)  |
|          |                   | Other  | MFJD (15)     |            |
|          | -   1 sample per  | ag     |               |            |
|          |     5-10 miles    | encies | NFJD (20)     |            |
+----------+-------------------+--------+---------------+------------+
|          | Continuous air    | Lab    | SFJD (2)      | Season     |
|          | temperature,      |        |               |            |
|          | humidity          |        | MFJD (0)      |            |
|          |                   |        |               |            |
|          | -   TNC/SWCD      |        | NFJD (4)      |            |
|          |     currently has |        |               |            |
|          |     2 on MFJD     |        |               |            |
+----------+-------------------+--------+---------------+------------+
| Bio      | Biocriteria       |        |               |            |
| criteria | Analysis (linkage |        |               |            |
|          | with sed/temp)    |        |               |            |
+----------+-------------------+--------+---------------+------------+

UJD -- Upper John Day

LJD -- Lower John Day

Upper/Lower boundary is at North Fork - Mainstem confluence

***Attachment 3:***

***Variables Monitored***

***Site Specific***

> **In-Stream**

-   Recording thermistors

-   DO, pH, bacteria, nutrients, macroinvertebrates, TSS, turbidity,
    substrate particle size/distribution

> **Channel**

-   Bankfull Cross-Section: Width (also via remote sensing), Depth, Side
    Slope

-   Sinuosity (also via remote sensing)

-   Entrenchment

-   Aspect (also via remote sensing)

> **Vegetation**

-   Height, Map Pattern, Canopy Density, Percent Effective Shade

> **Hydraulics**

-   Gradient (also via DEM)

-   Streambed Roughness, Percent Bedrock/Boulder

-   Discharge and Velocity

-   Wetted Width & Depth

> **Weather**

-   Wind Speed

-   Humidity

-   Air Temperature

-   Cloud Cover

***GIS***

> **Remote Sensing**

-   Thermal Infrared Radiometry (TIR)

-   Sub-meter/pixel color orthoimagery

> **Digital Elevation Model**

-   Stream Elevation Profile

-   Shade Angles (near and far)

-   Gradient

**[Juvenile Salmon and Steelhead Production Project]{.underline}**

Note: This proposal has changed from the original submitted proposal
that follows.

> Background:
>
> *The Watershed, Stream Temperatures, and Salmonid Productivity*
>
> Elevated stream temperatures are thought to limit the carrying
> capacities of the Columbia River Plateau. We propose that we can index
> the carrying capacity of threatened and endangered salmonids by
> monitoring stream temperatures. Stream temperatures reflect many
> different ecological processes acting in concert (e.g., flow,
> insolation) and are strongly correlated with salmonid production
> (survival and growth). Moreover, we suggest that salmonids will move
> to those habitats that offer the best opportunities for growth and
> survival in accordance with the Ideal Free Distribution (IFD) concept
> (e.g., more food and cover and less metabolic demands).
>
> Pilot data from the John Day Basin suggest that redband trout
> (*Oncorhynchus mykiss)* from stream reaches at 23 ^o^C are less
> physically fit than those rearing at 14 ^o^C. If we can demonstrate
> that physical fitness and therefore production is related to
> temperature, the next step will be to assess the amount of stream
> habitat in optimal, suitable, marginal and unsuitable temperature
> states. Fishes in optimal and suitable stream reaches should be found
> at greater densities and in better physical condition (as indexed by
> percent body fat) than fishes from marginal and unsuitable reaches.
> They should have greater overwinter survival, and migrate past
> Bonneville Dam in larger numbers. Alternative hypotheses will be
> developed and tested as well.
>
> We suspected that the survival and persistence of threatened and
> endangered salmonid fishes was dependent on our understanding of the
> processes controlling stream temperatures and fish habitats. Factors
> that disturb upstream riparian vegetation can increase insolation and
> stream temperatures (Hewlett and Fortson 1982, Beschta et al. 1987,
> Beschta and Taylor 1988). We found that adult spring chinook
> (*Oncorhynchus tshawytscha*) were able to survive high stream
> temperatures by finding coldwater refugia in temperature refugia.
> Salmon carrying temperature-sensitive, radio tags were tracked to
> plumes of coldwater 1-3^o^C cooler than the mainstream as detected by
> Forward Looking Infrared (FLIR) imagery (Torgersen et al. 1999). These
> plumes were apparently connected to groundwater inputs and we
> hypothesized that the dynamics of water routing and storage,
> particularly hyporheic water, was critical for salmon.
>
> Stream temperature patterns result from the interaction of important
> physical and ecological processes acting within the landscape (Ward
> 1985). Geomorphic conditions affect stream temperature through a
> variety of ways. Solar input to the streams is affected by aspect and
> topographic shading. Stream temperatures can be moderated by
> groundwater inputs and hyporheic exchange, the quantity of which may
> be influenced by the width and composition of the alluvial floodplain
> (Stanford and Ward 1993). Stream channel structure influences the
> extent of floodplain aquifer recharge during seasonal floods,
> hyporheic exchange, hydraulic conductivity, flow, retention time, heat
> gained by the stream from solar radiation, and heat lost from the
> stream through evaporative processes. Riparian structure, both above
> and below ground, affects temperature in multiple ways; the most
> obvious is that the extent of vegetative canopy limits solar radiation
> to the stream. However, vegetative structure and condition will also
> affect rates of water infiltration and surface runoff to streams,
> hydraulic conductivity via soil porosity, and hydraulic connectivity
> to the stream channel via extensive rooting networks (Fig 1).
>
> ![](media/image1.wmf){width="4.625in" height="3.7868055555555555in"}
>
> Figure 1 The relations between riparian vegetation and stream
> conditions
>
> Temperature has a direct effect on organismal, population, community
> and ecosystem processes. It acts as both controlling and directive
> factors on metabolism and therefore biological productivity (Fry
> 1947). It will effect the severity of stress imposed by environmental
> toxicants (Schreck and Li 1991), change the nature and intensity of
> interspecific interactions (Reeves et al. 1987), and alter
> relationships between immunocompetency of fishes and pathogens (See
> Figure 2 below. Also see Becker and Fugiyama 1978, Avatilion et al.
> 1980, Avatilion 1981).
>
> Figure 2. Influences of insolation, riparian vegetation, and
> temperature on fish assemblages.
>
> ![](media/image7.wmf)*Monitoring fishes by measuring stream
> temperatures, applying bioenergetic measurements, and measuring
> carrying capacity using the Ideal Free Distribution.*
>
> The distribution of stream temperatures may be an excellent index of
> carrying capacity and the distribution of fishes within the stream
> (Figure 3). Habitat quality can be defined by physiological tolerances
> of salmonids to stream temperature; therefore the proportions and
> quantities of stream reaches should be a reasonable indicator.
> Salmonids, in general are limited to cold water, having an upper
> incipient lethal temperature around 26^o^C (Wurtsbaugh and Davis 197
> ). However, recent studies by by Gamperl et al. (*In Press)* and
> Rodnick et al. (*In Press),* found that some populations of redband
> trout (*O. mykiss*) in the Great Basin have evolved for warmer
> temperatures and have greater metabolic power above 26^o^C and that
> may hold for the redband trout of the John Day Basin. However,
> physiological tolerances are only part of the story. Empirical
> evidence strongly suggests that temperature and the quality and
> quantity of its prey limits redband trout density and distribution in
> the John Day drainage of Oregon (Li et al. 1994, Tate et al 1994).
> Q~10~ for salmonids is roughly 2, which means that for every 10^o^C
> metabolism doubles. This means that salmonids at 20^o^C will have to
> assimilate roughly twice as many calories to grow as much as a fish at
> 10^o^C.
>
> These are the implications suggested by Hughes and Grand (2000) where
> they suggest modifying Fretwell and Lucas (1970 ) concept of the Ideal
> Free Distribution (IDF) by adding a physiological component will
> better describe carrying capacity of habitat patches. As originally
> presented, the IDF conceived that resources per capita in relationship
> to the available resources governed limits to carrying capacities of
> habitat. Hughes and Grant (2000) showed that it is the net
> profitability of a patch which determined its quality and is
> determined by two components: prey inputs (resources/capita) and
> metabolic overhead (physiological costs). This concept can be adapted
> for monitoring at several scales. This can reveal details governing
> growth (e.g., patterns of activity, lack of cover, differences in food
> availability such as lack of terrestrial input, increased metabolic
> costs due to [severity of migration]{.underline}, reduced home range,
> predator intimidation causing reduction in foraging time, etc.).

![](media/image8.wmf){width="3.5in"
height="2.0181102362204726in"}![](media/image9.wmf){width="3.25in"
height="1.4984251968503937in"}

> Figure 3. (A) Longitudinal temperature patterns for the Middle Fork
> John day at Mid-August discharges 130% (1996) and 150% (1995) of
> normal. (B) is the proportion of the stream reaches in 1996 expressed
> in terms of generally accepted physiological temperature categories
> for salmonids.
>
> At the riverscape level, we can measure growth (the difference between
> energy input and metabolism) patterns along the longitudinal
> temperature profile. Actually for young-of-the-year, this resolves
> down to one measurement of fat content at the end of the growing
> season, as differences among sizes of emergent fry are relatively
> small. At the level of patches, habitat quality can be determined
> using bioenergetic models such as that derived by Bowen (1996). Lack
> of growth can lead to decreased probability of survival due to lack of
> fat to cope with cold, winter temperatures (Reimers 1963, Cunjack
> 1987, 1988, Rodnick, personal communication). Getting an index of
> production (survival and biomass) is the population analog of
> individual growth and the cumulative effect of individual growth.

### Application of Research

The application of this research is to determine how different types of
water management strategies affect the productivity of threatened and
endangered anadromous salmonids in arid, high desert, salmonid streams
of the Columbia Basin.

### Objectives

There are three major objectives:

1.  Determine whether or not longitudinal profiles of stream
    temperatures are a good index of a stream's carrying capacity for
    anadromous salmonids.

2.  Validate this technique by examining the relationship between stream
    temperature and the following variables: (a) fish density, (b)
    physiological characteristics of individual fish, (c) individual
    growth rates, (d) survival rates through the Columbia River dams,
    and (e) freshwater production of salmonids.

3.  Use this approach to determine how irrigation barriers and other
    water management techniques affect the freshwater production of
    salmonids.

### Methods

**Stream Temperature Profiles**

We will use remotely gathered images using forward looking infrared
videography gathered from

Airborne remote sensing using the methods of Torgersen et al. (1999).

**Fish densities:**

Fish densities will be gathered using the survey techniques of Li et al.
(1994).

**Fish physiological status:**

The test is as follows:

> 1\. Simple bioenergetic models of metabolic expenditures for trout
> (weight based adjusted) inhabiting reaches of different temperatures
> are calculated. All other things being equal (e.g., prey input), fish
> should grow less well at marginal temperatures (19-23^o^C).
>
> 2\. We will weigh, measure, and record percent fat of each individual
> captured. The fat determination will use a commercially available
> meter that measures conductance and is non invasive. The Ponderal
> Index will be used to measure condition and an external inspection
> will be made of the body and gills for lesions and parasites.
>
> **Growth, survival and Production:**
>
> 1\. Fishes will be tagged with Passive Integrated Transponders,
> weighted and measured. Their locations will be geo-referenced and
> located according to stream temperature.
>
> 2\. Densities of fishes at stream reaches of different temperatures
> will be gathered. All things being equal, salmonids will have lower
> densities at higher temperatures (previous study strongly suggests
> that this is the case).
>
> 3\. Fishes will be recaptured as they migrate downstream to over
> winter using screw traps (estimates of growth and survival of
> individual fish will be conducted).
>
> 4\. We shall recapture salmonids returning for their second year of
> freshwater rearing. Our hypothesis is that those that survive had
> higher fat content after the summer growth season.
>
> 5\. The following year a new cohort is tagged. Fish from both cohorts
> are recaptured on the onset of the downstream fall migration. Physical
> data are recorded, survival noted.
>
> 8\. The cycle repeats except that the first cohort is migrating
> through the dams. The dams ave PIT tag readers. Our hypothesis is that
> fish rearing at higher temperatures have much less success.
>
> 9\. We will compare the individual based population model(s) to the
> GIS based model wherein we assume that growth and survival will be the
> ocean is proportional to the amount of optimal habitat.
>
> **Validation of the Concept of Temperature as An Index of Carrying
> Capacity Using Concepts of bioenergetics and the Ideal Free
> Distribution.**
>
> If temperature is a good index of the carrying carrying capacity then:

1.  We should see higher relative densities of salmonids in stream
    reaches of suitable and optimal temperatures.

2.  Movement of fishes should follow the Ideal Free Distribution; fish
    will move to habitats that maximize survival and growth.

3.  Growth is the net result of prey intake less assimilation and
    metabolic losses and.metabolic energy losses are directly correlated
    with stream temperatures. All other things being equal, optimal
    temperatures favor growth.

4.  Growth can be indexed by percent fat/fish

5.  Fatter fish will have greater over wintering and pass Bonneville Dam
    in greater numbers.

> Figure 4. The Ideal Free Distribution of fishes in relation to the
> profitability of the habitat site as expressed in percent of fat
> accrued by individuals. Note that as habitat quality diminishes either
> because of less food resources per capita or because of greater energy
> expenditures, habitat becomes saturated due density-dependent
> response. As the best quality habitat (A) becomes saturated, a
> crossing-over point is reached where the remaining habitat is equal to
> habitat (B) and movement to (A) and (B) is equal and so on. K~i~ on
> the X axis denotes carrying capacities for patch i where I = a, b, c,
> respectively.
>
> Therefore the salmonid carrying capacity of a stream is related to the
> amount of stream in optimal and suitable habitats because:

1.  Salmonids in marginal habitats may have very low productivity
    because of low growth and survival

2.  Salmonids in warmer sections of stream may encounter greater numbers
    of warmwater fish competitors for food.

3.  Salmonids in warmer sections of stream may encounter more predators
    and experience higher mortality.

> Then stream temperatures can be used to assess status of the habitats
> for salmonids (Tier 1). And changes in the proportion and absolute
> amount of stream reaches in optimal and suitable habitats can be used
> to monitor effectiveness of a stream restoration activity (Tier 2).
>
> *Push-up dams*
>
> Prime land for grazing or hay-alfalfa operations in northeastern
> Oregon are located in wider alluvial valleys because the deposition of
> silt generally makes soil conditions better. Streams in these alluvial
> valleys naturally had less riparian shading than the narrower, steeper
> valleys of the canyons. They also had high meander length and gravel
> bars were common. Water tables were high and wetlands were an
> important component of the riparian zone. Sedges through their massive
> root structure created channels from the riparian zone to the stream.
> In small first order streams, roots of sedges from both banks can
> actually meet under the middle of the stream. As 40% of the root mass
> at any one time is dying, the porosity of the wet and dry wetlands
> increase and water infiltration is high (Fig. 5). These features
> increased the connectivity of the riparian zone to the stream and
> released coolwater downstream. Where riparian vegetation existed, the
> canopy of willows, alder, aspen and cottonwood covered the stream and
> served several purposes. It reduced insolation, increased trophic
> input of wood and leaves for boring and shredding aquatic insects, and
> provided inputs of terrestrial invertebrates for the fish to feed.
> Downed trees acted as habitat forming structures. These valleys
> attracted beavers. Beavers created porous dams which increased
> retention time of water, decreased nutrient spirals, increased carbon
> turnover, enhanced the capacity of the water table and wetlands, and
> encouraged overtopping flows into the flood plain during spring
> runoff.
>
> Many of these features do not favor grazing nor alfalfa-hay
> operations. Wetlands can spread hoof-and-mouth disease, and flooding
> can interfere with the timing of ranch activities. Ditching and
> draining of wetlands increased useable acreage at a time conducive to
> ranchers. Wetlands are often regarded and filled and the gallery of
> riparian forest is diminished for a host of reasons, but overgrazing
> has been implicated in many situations. Water tables dropped because
> cows and farm machinery increase soil bulk density. Precipitation runs
> off rather than soaks into the soil. Farmers and ranchers channelized
> streams to prevent flooding or reduce its effect; and this also
> diminished water table recharge. Water tables fell because over
> grazing can lead to stream incision which also lowers the water table.
> This may partly explain why ranchers and farmers need dams, to divert
> water for irrigation.
>
> ![](media/image1.wmf)
>
> Figure 5. Infiltration rates (cm hour^-1^) for grazed and exclosed dry
> meadows along the Middle Fork John Day River, Oregon. Data are based
> on the mean and standard error of 3 sites for each community and
> treatment.
>
> Push-up dams must be viewed as part of this suite of agricultural
> practices that represent a syndrome on the land and riverscape. This
> syndrome, draws off water from the stream during summer base flow,
> rather than during during spring runoff, when water is cold and
> plentiful. The consequence is higher stream temperatures downstream
> because the width to depth ratio increases while flow diminishes all
> of which increases the effect of insolation. Upstream ponding can
> increase stream temperatures as the "forebay" is usually much less
> complex than that of beaver ponds and a wide, open, treeless expanse
> can act as a solar collector. Unlike beaver dams that are
> semipermiable, push-up dams probably block the movement of fishes.
> Because water behind the dam is warmer, it can support warm water
> predators such as the introduced smallmouth bass and the northern
> pikeminnow (Buchanan and Hooton 1981), and locally enhance the number
> of putative warm water competitors such as the redside shiner.
>
> Technologically, new dam designs may be able to reduce or eliminate
> the physical aspects of impeding fish movement, by increasing
> permeability; but, other aspects that degrade habitat for salmonids
> may still be active, such as encouraging cool and warm water predators
> and warm water competitors to increase their populations within a
> system.

     

### Progress/Results

2.1 Statement of Work (Task). This contract implements two projects:

> **Project 1:** Watershed analysis: geology, geomorphology, land use
> and stream pool temperature profiles
>
> Task 1: Identify watersheds for comparative study (Tier 1 analysis
> with ground-truthing)
>
> Task 2: Develop a set of hypotheses about the relationships between
> existing land uses and stream temperatures, and develop a methodology
> or model for evaluating these relationships.
>
> Task 3: Verify these relationships through empirical measurements in
> accordance with the RME guidelines.
>
> Task 4: Document findings
>
> **Project 2:** Demonstrate that redband productivity is not the same
> in the presence of push-up dams, lay-flat stanchions, infiltration
> galleries, and no diversion structure.
>
> Task 1: Identify the study sites for the diversion alternatives.
>
> Task 2: Develop and implement a pre-project monitoring proposal that
> will partition survival and production for the diversion alternatives.
>
> Task 3: Develop and implement an identical post-project monitoring
> plan.
>
> Task 4: Compare pre-project and post-project survival and production
> for the alternative diversion structure options.
>
> Task 5: Document findings.

2.2 Needed Servicing Agency Skills:

It is essential that the Servicing Agency has extensive research
experience in the John Day Basin, including published papers on fish and
fish habitat.

It is also essential that the Servicing Agency has identified key
research people who have the expertise to carry out the research
identified in the statement of work.

The Servicing Agency must be skilled and experienced in dealing with
people and organizing and facilitating meetings in the John Day Basin.

2.3 Documentation Required. The Servicing Agency will document the
following:

> 2.3.1 A detailed Project Plan with project milestones.

2.3.2 Brief semi-annual reports on tasks undertaken, percentage of tasks
completed, and any issues affecting completion, priorities or progress
in achieving project milestones.

2.3.3 Draft and final reports documenting in detail, with appropriate
tables, figures, and text, each of the tasks above.

2.4 Deliverables

> 2.4.1 A detailed project plan.

2.4.2 Semi-annual status reports shall be submitted to Reclamation's
Interagency Acquisition Technical Representative (IATR).

2.4.3 Final written report and other appurtenant documents shall be
provided in both paper (ten copies: nine bound and one unbound) and in
an electronic version.

2.4.4 Acquired and/or processed RME information including geospatial and
tabular databases, spreadsheets, imagery, or other digital formats.

# 

**[John Day River Basin Airborne TIR Remote Sensing & Spatial Data
Analysis]{.underline}**

The proposal was pasted in its entirety in the document.

**[Push-up Dam Removal Project]{.underline}**

The proposal was pasted in its entirety in the document with slight
modifications.

Literature Cited

Bowen, M.D. 1996. Habitat use and selection by a stream resident
salmonid in a regulated river: tests of four bioenergetic optimization
hypotheses. Utah State University. Dissertation. Logan, UT.

Fretwell, S.D. 1972. Populations in a seasonal environment. Princeton
Univ. Press, Princeton, NJ.

Hughes, N.F. and T.C. Grand. 2000. Physiological ecology meets the
ideal-free distribution: predicting the distribution of size-structured
fish populations across temperature gradients. Environmental Biology of
Fishes 59: 285-298.

National Marine Fisheries Service. 1999. Endangered and threatened
species: threatened status for two ESUs of steelhead in Washington and
Oregon. Final Rule. Federal Register Volume 64: 14517-14528.

National Marine Fisheries Service. 2000. Biological Opinion.
Reinitiation of consultation on operation of the Federal Columbia River
Power System including the Juvenile Fish Transportation Program and 19
Bureau of Reclamation Projects in the Columbia Basin. NMFS NW Region,
Portland OR. On the web:
<http://www.nwr.noaa.gov/1hydrop/hydroweb/docs/Final/2000Biop.html>

PEA, Programmatic Environmental Assessment. 2002. Mid-Columbia steelhead
ESU. Implementation of Action 149 of NMFS 2000 FCRPS BiOp in three John
Day subbasins. Barnes and Associates and US Bureau of Reclamation. PNW
Region Boise, ID.