AN ABSTRACT OF THE THESIS OF
Jens C. Lovtang for the degree of Master of Science in Fisheries Science presented on
March 17, 2005
Title: Distribution, Habitat Use and Growth of Juvenile Chinook Salmon in the Metolius
River Basin, Oregon.
Abstract ap roved:
Redacted for privacy
Hiram W. Li
Chinook salmon (Oncorhynchus tshawytscha) have been absent from their
historic spawning and rearing grounds in the Metolius River Basin in central Oregon
since 1968, when fish passage was terminated at the Pelton Round Butte Hydroelectric
Project on the Deschutes River. Plans have been developed to reestablish passage of
anadromous fish through the Project. However, only anecdotal evidence exists on the
historic distribution of spring Chinook juveniles in the Basin. A recent approach to
characterizing habitat quality for anadromous fishes in the Basin was the development of
HabRate (Burke et al. In Press), which presented a relative quality rating of habitat based
upon published fish-habitat relationships at the stream reach spatial scale. The present
study was initiated to test the predictions of HabRate for summer rearing juvenile
Chinook salmon in the Metolius Basin. Chinook salmon fry were released in the winters
of 2002 and 2003, and their densities and sizes were quantified via snorkeling and fish
collection in six unique study reaches in the upper Metolius River Basin. Each of these
stream reaches varied in terms of temperature, habitat availability, invertebrate drift
availability, and fish community composition.
My observations were not consistent with the qualitative predictions of HabRate.
Moreover, habitat utilization was not consistent among study reaches. Similar to other
qualitative habitat rating models (e.g. Habitat Suitability Indices (Raleigh et al. 1986) and
Instream Flow Incremental Methodology (Bovee 1982)), HabRate's predictions rely
solely on physical habitat characteristics, with the assumption that habitat will be used
consistently among stream reaches (i.e. a pooi in one reach is of equal importance as a
pooi in another reach). My results suggest that the unique ecological setting of each
study reach provides the context for understanding the patterns of growth, habitat use,
and diurnal activity of juvenile Chinook salmon. The inclusion of ecological components,
such as food availability, the bioenergetic constraints of temperature, and the risk of
predation can make these models more biologically realistic.
Growth of juvenile Chinook salmon among study reaches had a curvilinear
relationship to water temperature, and was also positively related to the drift density of
invertebrate biomass. In three collection seasons (fall 2002, spring 2003 and fall 2003)
41 to 69% of the variations in fork lengths were explained by a multiple regression model
including temperature and invertebrate drift. Based on these findings, I present a
conceptual growth capacity model based on the tenets of bioenergetics as a basis for
understanding the relative quality of the habitat among stream reaches for juvenile
Chinook salmon.
Fish community composition can help to explain observed patterns in habitat
utilization and die! activity patterns. In the study reaches that had a greater presence of
adult trout (potential predators), observations of juvenile Chinook salmon in mid-channel
habitat were infrequent to non-existent during the day and abundances were higher in all
habitat types at night. In the study reaches with colder water temperatures, observed
juvenile Chinook salmon densities were higher at night. I suggest that habitat selection
and diurnal activity patterns in some study reaches are reflective of strategies taken by the
fish to minimize risks of predation.
©Copyright by Jens C. Lovtang
March 17, 2005
All Rights Reserved
Distribution, Habitat Use, and Growth of Juvenile Chinook Salmon
in the Metolius River Basin, Oregon.
by
Jens C. Lovtang
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Science
Presented March 17, 2005
Commencement June 2005
Masters of Science thesis of Jens C. Lovtang presented on March 17, 2005.
Redacted for privacy
Major Professor, representing Fisheries Science
Redacted for privacy
Head of the Department of Fisheries and Wildlife
Redacted for privacy
Dean of the Graduate School
I understand that my thesis will become part of the permanent collection of Oregon State
University libraries. My signature below authorizes release of my thesis to any reader
upon request.
Redacted for privacy
Jens C. Lovtang, A4hor
ACKNOWLEDGEMENTS
First and foremost, I would like to thank Portland General Electric and their
partners the confederated Tribes of the Warm Springs Reservation of Oregon for funding
this project. I would particularly like to thank Don RatliffofPGE, who encouraged me
to pursue graduate education and patiently worked with me on multiple drafts of my
proposal before we had one that was acceptable.
I would like to extend special thanks to Hiram Li for serving as my major
professor and mentor. He took me on as a graduate student almost by accident, when I
was in need of a sponsor. I have enjoyed the many hours of "free-association" thinking
that have taken place in his office, and look forward to continued collaboration. The
process of writing was a struggle for me, and I thank you for your patience. I would also
like to thank my graduate committee members Guillermo Giannico and Paul Murtaugh.
Many people have directly and indirectly helped to make this project a success.
Mike Riehle was my first supervisor when I moved to Central Oregon in 1996, and I
thank him for provided a guiding influence over the years. Jack Palmer and the crew at
the ODFW Round Butte Hatchery provided the Chinook fry for this study, and Eric
Schulz and Rich Madden of PGE helped with fry releases. Jim Stemberg faithfully
tended the hatch boxes on Spring Creek in the winter of 2002. I also wish to thank
Metolius Basin land owners Mark and Toni Foster, Taj Livingstone, Irwin Holzman, and
the Samuel Johnson Foundation for graciously allowing me access to their property.
No research is conducted without the collaboration of others. Jeremy Romer
served as my field assistant for both years of the study, and I am forever indebted to him
for his hard work, his sense of humor (Snorkel-oo! Snorkel-oo!), and his sincere
friendship. Additional help in data collection efforts was provided by Scott Cotter, Peter
Lickwar, Mike Riehie, Nate Dachtler, Brad Nye and members of the Deschutes Basin
Land Trust, Dan Sobota, Lindsay Carison - Frady, Jeremiah Osborne-Gowey, Charles
Frady, Alex Farrand, Randy Colvin, Shami Premdas, Tom Tattam, John Dollhausen,
Jennifer Bizjak, and Renee Ripley. Toni Foster and the kids from Black Butte School
helped with fry releases.
I especially would like to thank my family for their love and support. Even
though we are separated by many miles, we are, as Dad says, "interconnectedly
independent". Without you, there is no me. Mom, Dad, and Kari - thank you. I also
look forward to many years of discovery and wonder with my daughters Linnea and
Kate. I get to experience the joys of vicariously exploring the world through your eyes.
Finally, I would like to thank my wife Sara for all of her love and support through
this entire endeavor. When I went back to school at OSU in 2000, we had just gotten
married, and life was pretty simple (in retrospect, that is). Now, after more than five
years of graduate school, we are trying to establish careers, own a mortgage and a dog,
and have the added adventures of raising two girls. No matter what happens at the office
or in the field, I always know that it will always be okay when I get home. Thank you for
being my best friend, and I look forward to spending the rest of our lives together.
TABLE OF CONTENTS
Page
INTRODUCTION
1
STUDY AREA
10
METHODS
12
Approach
12
Study Reaches and Sites
13
Fry Releases
16
Habitat Inventory
17
Stream Discharge
19
Water Temperature
19
Seasonal Snorkel Surveys
20
Juvenile Chinook Size and Condition
21
Invertebrate Drift
21
Data Analyses
23
RESULTS....
29
Habitat Inventory
29
Stream Discharge
31
Water Temperature
33
Densities and Habitat Utilization
35
Night vs. Day Snorkeling
41
Fish Communities
42
Juvenile Chinook Size and Condition
43
Invertebrate Drift
48
Size and Condition vs. Invertebrate Drift and Water Temperature
53
Comparisons to HabRate
57
TABLE OF CONTENTS (Continued)
Page
DISCUSSION
58
BIBLIOGRAPHY
69
APPENDIX A: Smolt Production Estimates
75
APPENDIX B: Microhabitat Patch Utilization
85
APPENDIX C: Snorkel Observations
88
APPENDIX D: Fish Conmiunities
100
LIST OF FIGURES
Figure
rage
1.
Conceptual model of the Ideal Free Distribution
8
2.
Location Map of the Pelton Round Butte Project, Lake Billy
Chinook, and the Metolius Basin Study Area, Oregon, U.S.A
11
3.
Map of the Metolius River Basin study area
15
4.
Representative sketch map of a study site in the Metolius Basin
18
5.
Daily maximum water temperatures in six study reaches in the
Upper Metolius Basin, May to October, 2002
34
Daily maximum water temperatures in six study reaches in the
Upper Metolius Basin, May to October, 2003
34
Box-and-whisker plots ofjuvenile Chinook salmon fork length for
a) fall 2002, b) spring 2003, c) fall 2003, and d) cumulative percent
rank in six study reaches in the Metolius Basin.
44
Box-and-whisker plots of condition factors from juvenile Chinook
salmon collected in a) fall 2002, b) spring 2003, c) fall 2003 and
d) All seasons in the Metolius Basin
46
Box-and-whisker plots of Drift Density (counts) of invertebrates in
six study reaches in the Metolius Basin, a) fall 2002, b) spring 2003,
c) fall 2003, and d) all seasons combined
49
Box-and-whisker plots of drift density (biomass) of invertebrates in
six study reaches in the Metolius Basin, a) fall 2002, b) spring 2003,
fall 2003, and d) all seasons combined
51
Polynomial regression display of juvenile Chinook salmon fork lengths
versus cumulative daily maximum temperature units (MTUs) in
a) fall 2002, b) Spring 2003, and c) Fall 2003
55
Regression display ofjuvenile Chinook salmon fork lengths
versus average invertebrate drift density biomass in a) fall 2002,
b) spring 2003, and c) fall 2003
56
The Scope for Growth (Redrawn from Brett et al. 1969) for juvenile
Chinook salmon in the Metolius Basin
61
6.
7.
8.
9.
10.
11.
12.
13.
LIST OF TABLES
Page
Table
Physical attributes of study reaches in the upper Metolius Basin
14
Chinook salmon fry released into the Metolius River Basin
in 2002 and 2003
16
Response and explanatory variables used in multiple regression
analysis of fish measurements vs. invertebrate drift and temperature...
28
Summary of available main channel and side channel habitat
surveyed in six study reaches in the Metolius River Basin
30
Comparison of seasonal stream discharge measurements (m3/sec)
for study reaches in the Metolius River Basin.
32
Cumulative daily maximum temperature units (MTU's) for
each season for study reaches in the Metolius Basin
33
Comparisons of densities of juvenile Chinook salmon in pools and
riffles among study reaches in the Metolius basin in 2002 and 2003
sample periods
36
Minimum, maximum, and mean densities (fish / m2) ofjuvenile
Chinook salmon in pool and riffle habitat in six study reaches
in the Metolius Basin
37
Habitat subunit electivity indices for juvenile Chinook salmon in
riffle dominated stream reaches in the Metolius Basin
40
Habitat subunit electivity indices for juvenile Chinook salmon in
pool/riffle stream reaches in the Metolius Basin
40
Night vs. day snorkeling survey counts of juvenile Chinook salmon
in sites in the Metolius basin in 2002 and 2003
41
Summary of fish species observed in six study reaches in the
Metolius Basin, 2002 and 2003 combined
42
Juvenile Chinook salmon collection sample sizes, fork lengths (mm),
and Bonferroni's multiple range tests results in 2002 and 2003
collection periods
45
LIST OF TABLES (Continued)
Table
Page
Juvenile Chinook salmon sample sizes, condition factors (K), and
Bonferroni's multiple range tests results in 2002 and 2003
collection periods.
47
Number of invertebrate drift samples, count drift density (number of
invertebrates drifting / m3 of stream / second), and Tukey's HSD comparisons from six study reaches in the Metolius Basin in 2002 and 2003.. 50
Number of invertebrate drift samples, biomass drift density (grams of
invertebrates drifting / m3 of stream / second), and Tukey's HSD comparisons from six study reaches in the Metolius Basin in 2002 and 2003.. 52
Significance results of multiple regression analyses ofjuvenile Chinook
fork lengths and conditions versus invertebrate drift density and water
temperatures
53
Comparison of HABRATE summer rearing ratings, estimated
smolt production, and corresponding ranking and ratings of
sampled streams reaches in the Metolius River Basin
57
LIST OF APPENDIX FIGURES
Figure
Cl.
CS.
ClO.
Dl.
Page
Day and night counts ofjuvenile Chinook salmon in the
Lake Creek study reach, 2002 and 2003
89
Day and night densities ofjuvenile Chinook salmon in the
Lake Creek study reach 2002 and 2003
89
Day and night counts of juvenile Chinook salmon in the
Metolius Readwaters study reach, 2002 and 2003
90
Day and night densities ofjuvenile Chinook salmon in the
Metolius Headwaters study reach, 2002 and 2003
90
Day and night counts ofjuvenile Chinook salmon in the
Canyon Creek study reach, 2002 and 2003
91
Day and night densities of juvenile Chinook salmon in the
Canyon Creek study reach, 2002 and 2003
91
Day and night counts ofjuvenile Chinook salmon in the
Metolius Mainstem study reach, 2002 and 2003
92
Day and night densities of juvenile Chinook salmon in the
Metolius Mainstem study reach, 2002 and 2003
92
Daytime numbers and densities ofjuvenile Chinook salmon
in the Spring Creek study reach, 2002 and 2003
93
Daytime numbers and densities of juvenile Chinook salmon
in the Heising Spring study reach, 2002 and 2003
93
Fish Communities in the Metolius Headwaters study reach in day
and night snorkel surveys 2002 and 2003
101
Fish Communities in the Metolius Mainstem study reach in day
and night snorkel surveys 2002 and 2003
102
Fish Communities in the Lake Creek study reach in day
and night snorkel surveys 2002 and 2003
103
Fish Communities in the Canyon Creek study reach in day
and night snorkel surveys 2002 and 2003
104
LIST OF APPENDIX FIGURES (Continued)
Figure
D5.
Page
Fish Communities in the Spring Creek and Heising Spring study
reaches in day snorkel surveys 2002 and 2003
105
LIST OF APPENDIX TABLES
Page
Table
Al.
AS.
Bi.
B2.
Cl.
Similarity code assigmnents of streams in the Metolius River Basin....
75
Habitat in all streams in the Metolius Basin potentially available to
anadromous fish
76
Maximum fall juvenile Chinook salmon density estimates (JCS/m2)
for habitats in sampled stream sections in the Metolius River Basin
78
Chinook smolt production estimates for the six study reaches
in the Metolius River Basin
79
Juvenile Chinook salmon smolt population estimates for pooi, riffle,
and side channel habitats in all streams available to anadromous fish
in the Metolius River Basin, based on maximum fall density estimates.
.
81
Habitat occupation based on the presence or absence of juvenile
Chinook salmon (JCS) and other community fishes by formative microhabitat patch types from all observations within the Metolius Basin. ...
86
Habitat occupation based on the presence or absence of juvenile
Chinook salmon (JCS) and other community fishes by associated microhabitat patch types from all observations within the Metolius Basin
86
Raw numbers ofjuvenile Chinook salmon observed in habitat
subunits during spring snorkel surveys in the Metolius River
Basin, 2002 and 2003
93
Densities of juvenile Chinook salmon (fish / m2) observed in all
habitat subunits during spring snorkel surveys in the
Metolius River Basin, 2002 and 2003
94
Raw numbers ofjuvenile Chinook salmon observed in all
habitat subunits during summer snorkel surveys in the
Metolius River Basin, 2002 and 2003
95
Densities of juvenile Chinook salmon (fish / m2) observed in all
habitat subunits during summer snorkel surveys in the
Metolius River Basin, 2002 and 2003
96
LIST OF APPENDIX TABLES (Continued)
Page
Table
Raw numbers ofjuvenile Chinook salmon observed in all
habitat subunits during fall snorkel surveys in the
Metolius River Basin, 2002 and 2003
97
Densities of juvenile Chinook salmon (fish / m2) observed in all
habitat subunits during fall snorkel surveys in the Metolius River
Basin, 2002 and 2003
98
Distribution, Habitat Use, and Growth of Juvenile Spring Chinook Salmon
in the Metolius River Basin, Oregon
INTRODUCTION
Chinook salmon were historically one of the most abundant and commercially
important species of fish on the western coast of North America. The largest of the
Pacific salmon, Chinook historically ranged from the Ventura River system in southern
California north to Kotzebue Sound, Alaska (Healey 1991). Several factors have
contributed to the decline of Chinook salmon populations in the Pacific Northwest,
including overharvest, degradation of spawning and rearing habitat, and the construction
of hydroelectric dams that blocked access to spawning and rearing grounds (Nehison et
al. 1991,Myersetal. 1998).
The Metolius River and its tributaries were historically the main spawning area
for stream-type (sensu Healey 1991) spring Chinook salmon in the middle Deschutes
River Basin (Nehison 1995). Chinook salmon were blocked from these historic
spawning and rearing areas when fish passage was terminated at the Pelton Round Butte
Hydroelectric Project (PRB Project) in 1968. In conjunction with federal relicensing
efforts for the PRB Project, Portland General Electric (PGE) and the Confederated Tribes
of the Warm Springs Reservation of Oregon (Tribes) developed a plan for reestablishing
passage of anadromous fish species, with the goal of establishing naturally spawning runs
of anadromous spring Chinook salmon, Sockeye salmon (0. ncr/ca), and steelhead (0.
mykiss) (PGE and Tribes 2004).
2
One of the uncertainties to be addressed as part of reintroduction efforts was the
productive potential of the habitats in the areas in which the fish are to be reintroduced.
Although Chinook salmon are native to the Metolius River Basin, only anecdotal
evidence exists about their historic population sizes and distribution. A key component
of reintroduction plans is annual releases of hatchery-origin Chinook fry into the waters
of the Metolius Basin (PGE and Tribes 2004). Knowledge of the relative quality of the
available habitat will allow for distribution of the fry in areas that will provide the best
chance for growth, survival, and successful smoltification.
A recent approach to characterizing habitat quality in the middle Deschutes Basin
for anadromous fish was the development of a qualitative rating model termed HabRate
(Burke et al. In Press). HabRate creates a relative quality rating (poor, fair or good) for
each stream reach potentially available to anadromous fish based on reach-level habitat
characteristics for three phases of the salmonid life cycle: 1) spawning, egg incubation,
and fry emergence (combined), 2) juvenile summer rearing, and 3) juvenile winter
rearing. HabRate generates its quality ratings based upon compositing published fishhabitat relationships from other river systems. It predicts that juvenile Chinook salmon
rearing is limited in the summer by the relative lack ofjuvenile rearing habitat, primarily
lack of pool habitat and low pool complexity (Riehle 2001). 88% of the stream reaches
in the Basin were designated as "poor" for summer rearing (Riehle 1999). However, this
model has not yet been validated by field observations.
Like the Habitat Suitability Index (Raleigh et al. 1986) and the Instream Flow
Incremental Methodology Models (Bovee 1982), HabRate is a model that is based on the
evaluation of physical habitat variables. The relation of these variables to biological
3
interactions and processes are implied, not explicit, and the patterns are stereotyped and
contingent shifts in behaviors (e.g., switching prey preferences, changing habitat
preferences due to the presence of predators, competitors, or ontogenic needs) are not
considered. Unfortunately, this ignores a large body of habitat studies in the literature
that indicate that habitat selection is influenced by more than just the physical nature of
the habitat itself. Many biological factors influence the selection of habitat by juvenile
salmonids, including life stage requirements (Lister and Genoe 1970; Stein, Reimers, and
Hall 1972), inter- and intra-specific competitive interactions (Fausch 1984; Bayley and Li
1996), foraging opportunities (Everest and Chapman 1972; Fausch 1988), and the risk of
predation (Werner et al 1983).
This study had two primary goals. The first goal was to quantitatively assess the
distribution, habitat utilization, and size ofjuvenile Chinook salmon (Oncorhynchus
tshawytscha) in six selected stream reaches in the Metolius Basin. Habitat utilization
was investigated at three spatial scales: study reaches, habitat units, and habitat subunits
(edges, mid-channel, or microhabitat patches). The sizes of juvenile Chinook salmon
were investigated in relation to water temperature and invertebrate drift among study
reaches, with the objective to describe how differences in water temperature, combined
with the availability of drifting invertebrates, may function to set the scope for growth of
juvenile Chinook salmon. Additionally, data was collected on the composition of fish
communities in each study reach.
The second goal was to use the collected data to develop an approach to
understanding the relative quality of habitat available to Chinook salmon, and to develop
a model to estimate smolt production. The main emphasis of my approach was to
4
quantify responses (growth and densities) of juvenile Chinook salmon rearing in
ecologically different stream reaches, and use those responses as guides to rating the
relative quality of the study reaches.
During the freshwater phase of their life history, juvenile salmon face two major
challenges: grow large, and survive. The selection of habitat is a reflection of the
strategies that are be adopted to face these two challenges. Growing to a larger size
confers several advantages for stream dwelling juvenile salmon, as both short-term
survival and long-term fitness are often size dependent (Holtby et al. 1990). Fishes that
grow larger in their first year of life have lower rates of overwinter mortality (Schindler
1999; Quirm and Peterson 1996), and are less vulnerable to predation (Werner et al.
1993). Larger fishes also have a competitive advantage over smaller conspecifics in
selecting prime feeding positions in rearing areas (Fausch 1983). Ultimately, adult size
and fecundity are positively related (Healey 1991), meaning that larger size confers
higher fitness.
Salmonids maximize energy gain (and therefore, growth) by selecting habitats
that offer maximum energy input (i.e. foraging opportunities) while minimizing energy
expenditures (Fausch 1983). Juvenile salmon feed primarily in the water column or at
the surface on drifting larval and adult insects (Chapman and Bjomn 1969). Yet
maximum foraging opportunities often increase risk of predation, as those areas in a
stream that provide the highest potential for foraging (e.g. mid-channel habitats) also are
more likely to present the greatest exposure to predators. The risk of predation has been
shown to affect a foraging fish's choice of where and when to feed (Werner et al. 1983),
as there is a trade-off between energy intake and security (Lima and Dill 1990). Recent
5
studies of die! activity patterns suggest that in the presence of predators, juveni!e salmon
adopt a nocturnal feeding pattern, trading !ess efficient foraging potential for a reduced
risk of predation at night (Metcalf et al. 1999; Bradford and Higgins 2001).
Juvenile Chinook salmon show a strong preference for pool habitat, and have
been observed to aggregate in small schools in pool habitat during all seasons (Everest
and Chapman 1972; Hillman et al. 1992; Roper et al. 1994). From an energetic
standpoint, pool habitat is less costly to juvenile Chinook salmon, which have deep, slabsided bodies that are better suited to quick movements in slower velocities, as opposed to
cylindrically shaped steelhead or rainbow trout, which are better suited to holding
position in faster velocities (Bisson et al. 1988). Hiliman et al. (1987) reported that less
than 5% of observed juvenile Chinook were located in riffles, however, these fish were
typically found behind large boulders, where water velocities were comparable to pools.
The presence of both instream structure and overhead cover are important
elements of nursery habitat for juvenile salmonids in rivers (Giannico and Healey 1999).
The margins of stream habitat also provide important rearing areas for juvenile
salmonids, particularly in their first few weeks or months after emergence from the gravel
(Moore and Gregory 1988). Habitat at smaller spatial scales may provide cover from
predators (Shirvell 1990), refuge from main channel velocity (Fausch 1993) and may
potentially decrease aggressive interactions between competitors by increasing visual
isolation (Fausch 1993). Note then that change in physical structure of stream habitat
affects utilization through changes in interactions among species or in fish behavior.
That is why the addition of large wood, in addition to pool formation (Montgomery et al.
6
1995), has been so successful in increasing carrying capacity for salmonid fishes. (Bisson
et al. 1987; Bilby and Bisson 1998; Mossop and Bradford 2004; Roni and Quinn 2001).
Activity patterns, foraging strategies, and habitat selection are affected by
differences in water temperature. Although water temperature is a physical measure, it is
independent of habitat and its effects on fish are directly linked to metabolic processes.
Growth of juvenile salmon has a parabolic relationship to water temperature, with
maximum growth obtained between 15-19° C, depending on ration size (Diana 1994).
The potential or "scope" for growth is reduced on either end of the temperature spectrum:
at high temperatures, a greater portion of energy ingested is required for metabolic
maintenance; at low temperatures, the amount of rations that can be ingested and
metabolized is limited (Brett 1952; Brett et al. 1969; 1982).
Behavior and distribution of juvenile salmonids is also affected by temperature
(Hillman et al. 1987, 1992; Riehle and Griffith 1993; Roper et al. 1994; Shirvell 1994).
hi the Umpqua River Basin in southern Oregon, Roper et al. (1994) found that juvenile
Chinook salmon were most abundant in reaches with stream temperatures ranging from
100 C to 140 C, even though adjacent reaches with similar habitat but warmer
temperatures were available. A study of mid-Columbia river tributaries showed that at
temperatures above 140 C, juvenile Chinook salmon were present in the water column at
all hours of the day, but between 90 C and 14° C, juvenile Chinook hid during the day and
emerged to actively feed at dusk (Hillman et al 1992). Below 9° C, salmonids have been
observed to remain concealed at all hours of the day, and often hid in interstitial spaces of
the substrate (Hillman et al 1992; Riehle and Griffith 1993). Conversely, as temperatures
increase, activity of juvenile salmon also increases. Smith and Li (1983) demonstrated
7
that fish will seek faster, food bearing velocities at higher temperatures, seeking the
greatest net profit with respect to feeding locations.
For all the above reasons, habitat models can be more biologically realistic by
incorporating biological elements of varying stream habitats. The Ideal Free Distribution
(IFD) Theory (Fretwell and Lucas 1970; Fretwell 1972) provides a good starting point.
The IFD describes a conceptual relationship between the spatial distribution of animals
and resource availability and competitive interactions. The IFD describes habitat choice
being affected by per capita availability of resources in habitat patches or habitat units of
different quality. The IFD in its original form assumes that animals have complete "ideal"
knowledge of the available resources, they are "free" to move between patches (and
travel time and energy expenditure for movement is negligible), and they are all of equal
competitive ability. Based on these assumptions, the IFD predicts that animals should
distribute themselves among patches of resources in proportion to the resources available
within those patches - this numerical response has been termed "resource-matching". A
patch with a greater amount of resources should support a larger number of individuals
than a patch with fewer resources, and will be occupied first.
Given three habitat patches with varying amounts ofresources, indicated by the
solid arrows (Figure 1), we can evaluate their respective carrying capacities, K1, K2, and
K3, by tracking the per capita availability of resources as populations increase. As the
number of residents increase in a habitat patch, the per capita availability of resources
declines, thereby causing density-dependent limits on occupation. Colonizers should fill
the best patch first until they hit point A, where resources per capita of the best and next
best patch are equal. At this point, colonists begin filling the next best and the best at the
8
same rate. The pattern of movement at point B reflects the same logic. Note that
resources per capita are always larger than zero and theoretically reflect the same per
capita minimum resource requirements.
Best Patch
A
Next Best
Worst
Minimum requirement
>
K'
K2
K3
Population Size
Figure 1. Conceptual model of the Ideal Free Distribution
The IFD presumes that resources per capita eventually become equalized among
patches, such that when the habitat is fully seeded, each forager will have the same
amount of resources per capita, regardless of whether its patch is rich or poor. Hughes
and Grand (2000) found the IFD model incomplete and argued correctly that
incorporating the physiological costs of occupation as well as the availability of resources
would make the model more realistic. By incorporating the energetic constraints of living
at different temperatures, Hughes and Grand displayed that the predictions of the IIFD
model would change at different temperatures.
My approach was to conduct a field experiment. The concept was to introduce
Chinook fry into the waters of the Metoijus Basin and examine their behavior, growth
and distribution in relation to ambient levels of invertebrate drift, stream temperatures,
and associated fish communities. At the same time I quantified patterns of habitat use in
9
relation to ontogeny while measuring and noting key habitat features. I also planned to
examine density-dependent effects by increasing stocking density in the second year of
the study year. At a minimum, I wanted to examine which features of individual study
reaches helped to explain observed patterns of habitat utilization and growth, and
determine whether or not the concept of using the scope for growth as index of habitat
quality would be supported.
10
STUDY AREA
The Metolius River is a tributary of the Deschutes River, and fonns on the eastern
slope of the Cascade Mountains in Central Oregon (Figure 2). The river originates from
large springs at the base of Black Butte, and flows north and east approximately 45 km
before entering Lake Billy Chinook. Summertime base flows are primarily spring-fed, as
several large springs are located in the river and tributaries. Water temperatures in the
basin are cold, as the springs range from 4
90
C.
There is one major lake in the
system, Suttle Lake, which is drained by Lake Creek.
The habitat in the mainstem Metolius River is dominated by riffles, with pools
representing only about 10% of available habitat. Habitat availability in the tributaries is
highly variable, with as little as 0% pools in Heising Spring to as much as 50% pools in
one reach in Candle Creek (USFS habitat survey data).
The Metolius River basin supports native spawning populations of redband
(rainbow) trout (Oncorhynchus my/dss), bull trout (Salvelinus confluentus), mountain
whitefish (Prosopium williamsoni), long-nose and speckled dace (Rhinicthys sp), and
several species of sculpin (Cottus sp.). Non-native species include brown trout (Salmo
trutta) and brook trout (S. fontinalis). The Metolius Basin was also the historic home of
one of Oregon's two indigenous populations of sockeye salmon (0. nerka), which once
used Suttle Lake as a rearing area. A large population of kokanee salmon (0. nerka)
currently resides in both Suttle Lake and Lake Billy Chinook.
11
Reregulating Dam
,.
j
Rainy Creek
Racing Creek
Jefferson Creek
Candle Creek
Martel
Creek
Round Butte Dam
Lake Billy Chinook
Abbot Creek
Canyon Gre
Opal Springs Dam
tudy Area (map on page 15)
First Cre
Suttle Lake
I
ead of the Metolius
2.4 0 2.4 4.8 7.2 Kilomss
'2
""SteeI head
Falls
Figure 2. Location Map of the Pelton Round Butte Project, Lake Billy Chinook, and the
Metolius Basin Study Area.
12
METHODS
Approach
The study was designed as a field experiment. The main object was to investigate
differences in habitat use and growth of planted juvenile Chinook salmon in ecologically
different reaches of the Metolius Basin, with the aim of using the observations of the fish
as a means to describing the relative quality of the habitat. The fry were of Deschutes
River hatchery origin and reared in hatch boxes in the Metolius Basin in 2002 and at the
Round Butte Hatchery in 2003. Since the fish were all of the same size at release, any
reach - specific differences in length, weight, or condition can be attributed to ecological
conditions of the reaches in which they were rearing. Additionally, no Chinook are
currently present in the system, so it could be assumed that if a Chinook was observed it
was one that was released in conjunction with this study. A secondary goal was to
determine whether or not different density-dependent patterns would emerge after
releasing different numbers of juvenile Chinook salmon fry into different tributaries of
the Metolius Basin. To approach this secondary goal, different densities of Chinook fry
were released at five locations in the Upper Metolius during successive years, with
approximately 2
/2
times the number of fry released in the second year of the study.
The study was designed hierarchically, in order to investigate distribution of fish
at multiple spatial scales. The Metolius Basin comprises tributaries with different
characteristics and within each of them are reaches that differ from one another in terms
of their geology, topography, hydrology and microclimates and therefore in the
availability of habitat and microhabitat features. Field sampling encompassed the
following activities with study reaches and their study sites: measurement of available
13
and selected habitat features, repeated day and night snorkel observations through the
summer growing season, measuring growth at the end of the summer, and determining
the availability of drifting invertebrates. This enabled me to track changes in habitat use
through ontogeny and distribution of fry throughout the system. Habitat quality would be
measured in terms of standing crops and growth. As discussed in the Introduction,
measurements of temperature and drifting invertebrates were used to interpret the
patterns for standing crops and growth.
Study Reaches and Sites
Six study reaches in the Metolius Basin were examined in this study. Two of
these study reaches were located in the Metolius River (referred to as Metolius
Headwaters and Metolius Mainstem) and four were located in tributaries: Lake Creek,
Canyon Creek, Spring Creek, and Heising Spring. These six reaches were chosen for
study because they are each unique in terms of habitat availability, flow regime, and
water temperature regimes (Table 1). Three study reaches, Lake Creek, Canyon Creek,
and the Metolius Mainstem, exhibit a mixture of pool and riffle habitat, while the other
three study reaches, Spring Creek, Heising Spring, and the Metolius Headwaters are
dominated by riffle habitat.
A total of 30 sites in the 6 study reaches were selected for snorkel surveys; three
each in Spring Creek and Heising Spring, five each in the Metolius Mainstem and the
Metolius Headwaters, and seven each in Lake Creek and Canyon Creek (figure 3). Study
sites were evenly distributed along the length of each reach, depending on accessibility.
14
Sites ranged from 50 120m in length, and included a variety of pool habitat (if
available), and riffle habitat.
Table 1. Physical attributes of study reaches in the upper Metolius Basin.
Temperature MayOctober 2003
Mm-Max (Average) °C
Stream
Code
Metolius Headwaters
MH
Dominant
Habitat
riffle
Spring Creek
SP
riffle
8 1°-107°(90°)
66°-110°(91°)
Heising Spring
HS
riffle
53°-68°(58°)
Lake Creek
LK
POOl / riffle
7 0° - 24 9° (16 0°)
Metolius Mainstem
MM
pool / riffle
6 6° - 13 5° (9 3°)
Canyon Creek
CY
pool / riffle
2.7° - 9.20 (5.7°)
Figure 3. Map of the Metolius River Basin Study Area. Yellow dots indicate study sites, red dots indicate Chinook fry release
sites, and purple dots indicate invertebrate drift sites. Created using ArcView 3.2.
16
Fry Releases
The Chinook salmon used in this study were spawned from hatchery origin
Deschutes River fish at the ODFW Round Butte hatchery near Madras, Oregon.
Approximately 54,300 fry were released in 2002 and approximately 140,000 were
released in 2003. These fry were spawned from 177 adult female Chinook salmon in
2002, and from 211 females 2003. In 2002, the Chinook fry were reared in hatch boxes
on Spring Creek in the Metolius Basin until release (see Schulz 2002 for description and
methods). In 2003, the fry were reared at the Round Butte Hatchery, and transported by
truck to the release sites. In each year, the fry were all approximately the same size and
weight at release, although they were slightly larger in 2003 (approximately 1600 per
pound in 2002 and 1250 per pound in 2003).
Table 2. Chinook salmon fry released into the Metolius Basin in 2002 and 2003.
Release
Metolius
Canyon
Lake
Spring
Heising
Estimated
Sites
Headwaters
Creek
Creek
Creek
Spring
Totals
2002
releases
12,800
10,400
10,400
11,000
10,400
54,300
2003
releases
36,504
36,574
37,213
14,678
14,748
139,217
Percent
Increase
185%
251%
257%
33%
42%
158%
(+1- 400)
In both years, the Chinook fry were released at the same five locations in the
Metolius Basin (Table 2, Figure 3). Greater numbers of juvenile Chinook salmon were
introduced in all release sites in 2003. Although we did not directly introduce fry into
17
the Metolius Mainstem study reach, the numbers released upstream of this reach were
increased from approximately 34,200 in 2002 to approximately 88,400 in 2003.
Habitat Inventory
Habitat surveys were conducted on each of the selected study sites prior to
sampling efforts, in the spring of each year. To keep consistent with U.S. Forest Service
Level II survey protocols, we identified main channel habitat units as either riffles or
pools. Measurements of lengths, widths, maximum depths, average depths (for riffles)
and pooi tail crests (for pools) were taken for each habitat unit. Habitat subunits were
defined as the edges or mid-channels of pool, riffle or side channel habitats, and
microhabitat patches. Microhabitat patches were defined as areas that provided either
refuge from main channel velocity or significant cover, and were identified by one of five
major formative features: bank alcove, boulder, emergent vegetation, naturally occurring
wood, or placed wood. Any associated habitat types (i.e. those that were not the
dominant formative feature) were also recorded. The length, width, maximum and
average depths, substrate type, and location (bank, mid-channel, or island) of each
subunit was recorded. Sketches were drawn of each site (see Figure 4 for example),
noting the location of each of the habitat units and subunits.
18
Section/Siie#
,'i4-
fotal Site Length:
i
Date:
31'S Top:
:;s lttM:
;ubttnit types:
3
i3ouder
Emergent Veg.
Alcove
Edge
Mid-channel
hland
.4
L
L-
Figure 4. Representative sketch diagram of a study site in the Metolius Basin. The large
arrows indicate direction of flow and the approximate location of the thalweg. Two main
channel habitat units are in this site; a 45m long pooi downstream of a 55m long riffle.
Circled numbers indicate microhabitat patches and their formative and associated
features; W = natural wood, WP = placed wood, EV = emergent vegetation, A = bank
alcove.
19
Stream Discharge
Seasonal measurements were taken at the lower end of each of the reaches in each
season. Lake Creek has an influx of large spring near its mouth, and therefore two
discharge measurements were taken in Lake Creek, one at the mouth of the creek below
the springs, and the other in the upper Lake Creek, above the springs. Discharge
measurements were taken using a Marsh-McBumey Flo-Mate electronic flow meter,
using methods described by Gore (1996).
Water Temperature
Stream temperatures were recorded by placing temperature data loggers (Optic
StowAwaysTM by Onset) into sites in each of the study reaches. Temperatures were
recorded every hour from May23 to October 1, 2002, and February 15 to October 10,
2003. The loggers were placed at the time of fish release (March 15) in 2002, but
technical difficulties were experienced and no data were recorded for the period of March
15 - May 22, 2002. In both years of the study, all temperature data loggers were pulled
at the beginning of October.
20
Seasonal Snorkel Surveys
Seasonal daytime snorkeling surveys were conducted on each of the study sites in
both years of the study: spring (May), summer (July) and fall (September). Night snorkel
surveys were also conducted on a sub-sample of study sites (4 in spring 2002, 8 in
summer and fall 2002, 10 in all seasons 2003) to investigate die! differences in densities
and I or habitat associations. Night dives were conducted in four of the study reaches:
Lake Creek, Canyon Creek, Metolius Headwaters, and Metolius Mainstem. No night
surveys were conducted on Spring Creek or Heising Spring, because those reaches were
located on private property. Night diving was always conducted at least 48 hours before
or after day snorkeling to allow for the fish to resettle.
Divers made a single pass at each site, moving upstream from the bottom of each
unit to the top. All fish observed were identified by species and size class and their
locations were recorded. Fish greater than 8 inches were considered adults and those less
than 8 inches were considered juveniles. Locations for the fish were recorded as one of
the following habitat subunits: main channel or main channel edge (within 0.25m of the
bank) within a riffle, pool, or side channel, or within a microhabitat patch. Each of these
habitat subunits were identified and measured during habitat surveys conducted prior to
snorkeling efforts. Each diver wrote his observations on a cuff made from 4-inch PVC
pipe, which were transferred to a data sheet after the dive was over. The majority of sites
were surveyed using two divers, one moving up each bank, but the sites in the Mainstem
Metolius study reach were surveyed using three or four divers.
Data from all divers was combined on the data sheet at the conclusion of each
dive. Therefore, inter-diver variability cannot be determined. Also, due to the presence
21
of bull trout in the system, snorkeling was the only approved method of observing and
collecting fish, and no other method can be used for calibrating snorkel counts.
Juvenile Chinook Size and Condition
Juvenile Chinook salmon were captured from each of the study reaches for
measurement during August 26-29, 2002, May 19-22, 2003 and September 22-25, 2003.
Fish were captured by either diver hand netting or diver-directed seine netting. After
capture, the fish were anesthetized in a solution of 2.5 ml MS-222 to IL of fresh water.
The fish were weighed to the nearest 0.1 gram with an OhausTM model C305 digital scale,
measured to the nearest mm, and placed in a recovery bucket of clean water. After
recovery, fish were returned to the site of capture.
Condition factors are often used to indicate the nutritional condition or "well
being" of an individual fish (Busacker Ct al. 1990). The formula used for calculating
condition factors (K) was:
K = (weight / (fork length)3) x 100,000)
Invertebrate Drift
The invertebrate productivity of a stream influences the patterns and behaviors of
foraging fish. The abundance and composition of invertebrate populations in streams
has been used as an indicator of the relative quality of stream ecosystems, both in terms
of fish production and the ecological "health" of the system (Resh and Grodhaus 1983).
22
Invertebrate drift samples were taken from each of the six study reaches on
September 24-25, 2002, and May 30-31 and September 26-27, 2003. Drift samples
were taken from the same areas from which juvenile Chinook salmon were collected for
measurement. Four samples were taken at each site using 0.3m by 0.3m drift nets placed
randomly in the main channel current. Sampling began at dusk (-1900h in fall, and
-.21O0h in spring) and each net was set for 20 minutes. Samples were preserved in 95%
ETOH in WhirlPakTM bags, and taken to a lab for processing. Processing involved
sorting and counting individual invertebrates from the drift samples using a dissecting
microscope. For large samples, a sub-sample (1/2 - 1/8, depending on the size of the
sample) was taken and processed. Samples were split using a plankton splitter, and the
half that was processed (or split further into quarters or eighths) was chosen at random by
throwing dice. The resulting counts and biomass estimates for split samples were
multiplied by the split, giving an estimate for the total sample.
After sorting and enumeration of the samples, biomass was measured by placing
the invertebrates into pre-weighed coffee filters in a drying oven for 48 hours at 60°C. In
addition to the insect samples, eight test coffee filters were also placed in the oven with
no contents, to determine if the filters themselves lost weight during the drying process.
All samples were weighed to the nearest thousandth of a gram immediately after removal
from the drying oven, and were adjusted for filter weight loss.
23
A drift density calculation was used to account for differences in drift velocity
and depth and to allow for comparison among samples. The formula (modified from
Smock 1996) is:
Drift Density =
(N)
(t)(W)(H)(V)(3 600 seconds/hour)
Where N represents the number or biomass (grams) of invertebrates in the
sample, t is the time the net was in the water (in hours), W is net width (m), H is height of
water in net (m), V is the velocity of water at the net mouth (mis). Results are expressed
as either the number of invertebrates or the biomass (grams) of invertebrates drifting per
cubic meter of flowing water per second.
Data Analyses
Habitat Utilization
In this study, data were collected on three spatial scales: study reaches, habitat
units (pools and riffles), and habitat subunits (edges, mid-channels, and microhabitat
patches). Statistical analyses were performed at the stream reach and habitat unit scales.
Density calculations (fish / m2 of habitat) were used for analysis of differences among
study reaches and habitat units. Densities were also calculated for habitat subunits, but
for purposes of comparison, Ivlev's Electivity Index (ff1) was used.
24
Study reaches - Parametric ANOVA and non-parametric Kruskal-Wallis ANOVA
tests were used to investigate the relative differences in means and medians of densities
in pools and riffles among the six study reaches for each sample period. Densities of
juvenile Chinook salmon in poois (fish/rn2) were compared among the Lake Creek,
Canyon Creek, and Metolius Mainstem study reaches, as these were the only reaches that
contained pool habitat, and riffle densities were compared among all six study reaches for
daytime observations, and among four study reaches (Lake Creek, Canyon Creek,
Metolius Mainstem, and Metolius Headwaters) for nighttime observations. No nighttime
surveys were conducted on Spring Creek or Heising Spring.
If significant differences at the p <0.05 level were found using both ANOVA
analyses, Bonferroni's multiple comparison procedure was used to determine which of
the study reaches had significantly higher counts or densities. Bonferroni 's procedure
was selected because the number of pools and riffles was not equally represented in each
study section. Spring night 2002 observations were not included in this analysis, as
sample sizes (3 pools and 2 riffles over four study sections) were insufficient.
Habitat Units - Two-sample t-tests were used to investigate the differences in
means between densities in pools and densities in riffles. This analysis was performed on
the three reaches that had both habitat unit types: Lake Creek, Canyon Creek, and the
Metolius Mainstem.
Several attempts were made to further analyze data at the habitat
unit scale to try and tease out which specific habitat parameters (i.e. depth, area, substrate
type, etc.) could help to explain differences in density, particularly in the study reaches
that had only riffle habitat. However, several interpretational issues were encountered,
25
including spatial autocorrelation, lack of independence among study sites and pseudo
replication that complicate and may potentially invalidate standard statistical tests at this
spatial scale. Analysis at this spatial scale is important, but more investigation is needed.
Habitat Subunits - Habitat subunit utilization by juvenile Chinook salmon was
evaluated using Ivlev's Electivity Index (1961; as described by Peckarsky 1996). This
non-parametric index is used to relate the amount of a resource utilized compared to the
amount of a resource available in the environment. Selection or avoidance was
determined for seven habitat subunits: 1) pool mid-channel, 2) pool edge, 3) riffle midchannel, 4) riffle edge, 5) side channel mid - channel, 6) side channel edges and 7)
microhabitat patches. Ivlev's Electivity Index (E1) was adapted as follows:
E1 = (r1p,) / (r1 +p).
where r is the percentage of juvenile Chinook salmon counted in a particular habitat
subunit type, and p is the percentage of that habitat subunit type available. This index
returns a value between -1 and 1, with numbers close to -1 indicating a low rate of
occurrence in that habitat type (-1 indicates absence), and numbers close to + 1 indicating
a high rate of occurrence. Values near zero indicate that a habitat was used in proportion
similar to its availability. Index values were generated for each seasonal survey on each
stream (e.g. spring 2002 day dives, fall 2003 night dives), and is the result of the pooling
of all dives on that stream during each season.
26
Densities were also calculated for each of the study reaches for each sample
period. Total edge habitat area was calculated as O.5m of the total bank length (O.25m for
both banks) for each habitat type. Mid-channel habitat area was calculated as the total
amount of area in each habitat unit (pool, riffle, or side channel) minus the area of edge
habitat and subunit habitat. Densities were calculated by dividing the total number of
juvenile Chinook salmon observed in each habitat type by the total area of each habitat
type surveyed in all dives in each stream in each season.
This combined approach (summing totals from all dives in a stream) was used
instead of using individual study sites or habitat units because this provided a more
reliable estimate for the entire stream, as results would be less likely to be influenced by a
large number of fish in one particular habitat unit. The majority of habitat units and
subunits had zero fish, and it was important to incorporate these zero counts into density
estimates.
Fish Size and Condition
A non-parametric Kruskal - Wallis ANOVA test was used to investigate
differences among study reaches for fork length, weight, and condition factor for each
sample season. Due to the fact that different numbers of fish were collected from each
study reach, Bonferroni's multiple comparison procedure was used to examine statistical
similarities or differences among the study reaches. Cumulative size and condition data
for all seasons was summarized using a non-parametric cumulative percent rank method:
fish measurements were ranked from 0 to 1 in relation to the smallest (rank = 0) and
largest (rank = 1) fish collected in each specific season.
27
Invertebrate Drift
Non-parametric Kruskal-Wallis analysis of variance tests were used to compare
drift density of invertebrate counts and biomass among study reaches in each collection
season. Although a standard one-way ANOVA typically gave the same significance
results, a nonparametric ANOVA test was chosen because of the non-equality of
variances between study reaches.
Heterogeneity among study reaches was examined
using Tukey's studentized range HSD (Honest Significant Difference) procedure for
means comparisons.
Fish Size and Condition vs. Water Temperature and Invertebrate Drift
Multiple regression analyses were perfonned on juvenile Chinook salmon
measurement data versus invertebrate data and temperature for each season to examine
the relationship between these variables (Table 3). Fork lengths were highly related to
weights (p <0.001; R2
0.98) and therefore only fork lengths were used in the models.
Averages were calculated for each of the invertebrate drift metrics for each of the study
reaches in each of the seasons. Since fish growth has been demonstrated to have a
curvilinear relationship with temperature (Brett et al 1969; Brett and Groves 1979, Brett
et al. 1982), a squared temperature term was added to the models (Ramsey and Schafer
1997).
28
Table 3. Response and explanatory variables used in multiple regression analysis of
juvenile Chinook salmon measurements vs. invertebrate drift and temperature.
Explanatory Variables
Study Period
Response Variables
in Model
Average Drift Density (Counts)
Fall 2002
Fork Length (mm)
Average Drift Density (Biomass)
Condition Factor (K)
Max Temperature Units
(Max Temperature Units)2
Average Drift Density (Biomass)
Spring 2003
and
Fall 2003
Fork Length (mm)
Condition Factor (K)
Max Temperature Units
(Max Temperature Units)2
A backward stepwise selection process was used to select the final model for each
of these analyses. Simple linear regression analyses indicated that count drift densities
and biomass drift densities were significantly correlated in spring 2003 (p = 0.007;
Adjusted R2 = 0.47) and fall 2003 (p <0.001; Adj. R2 = 0.70), but were only marginally
correlated in fall 2002 (p = 0.052; Adj. R2 =0.17). Because of these correlations, count
drift densities were not included in the full models in spring or fall 2003, but were left in
the faIl 2002 model.
Note: All statistical analyses were conducted using Statgraphics Plus 5.1 TM
software.
29
RESULTS
Habitat Inventory
The composition and dimensions of the available habitats to juvenile Chinook
salmon differed among study reaches (Table 4). The number of sites in each study reach
varied from 3 to 7. This variation in the numbers of sites in each study reach was due to
the differing lengths of the study reaches, some reaches were as short as 0.5 1cm, and
others were more than 5 km. In sites in the three pool / riffle sections, the percentage of
pooi habitat ranged from 42% in the Metolius Mainstem to 71% in Canyon Creek.
Maximum and residual pooi depths were significantly different among the three study
sites (ANOVA; d. f. =2, 36, p <0.001 for max depths, p = 0.0 15 for residual depths,
Tukey' s HSD), with the Metolius Headwaters the deepest, Lake Creek the shallowest,
and Canyon Creek intermediate in depth. Riffle habitat was similar among the study
sections in terms of depth in five of the six study reaches, with only the Metolius
Mainstem having significantly deeper riffle depths (ANOVA; d. f. =5, 28, p <0.001,
Tukey's HSD).
Table 4. Summary of selected physical variables gathered from available main channel and side channel habitats surveyed in six study
reaches of the Metolius River Basin.
Study
Reach
# Study
Sites
#
Pool Area
Pools
m2 (%)
Metolius
5
5
Mainstem
Canyon
7
14
Creek
Lake
7
20
Creek
Spring
3
Creek
Metolius
5
0
Headwaters
Heising
3
0
Spring
* All depths are in meters
Pool Max.
Depths (mean)
Pool Residual
Depths (mean)
#
Riffles
5210
(42.2%)
4975
(70.9%)
2491
(60.4%)
1.5-2.0(1.8)
0.75 1.45 (1.1)
4
1.05-1.5(1.3)
0.6- 1.3 (0.9)
7
0.5 1.2 (0.9)
0.2 1.35 (0.5)
12
60 (1.9%)
0.7
0.4
3
5
3
Riffle Area
m2 (%)
5786
(46.8%)
2025
(28.9%)
1506 (36.6)
2955
(94.8%)
7325
(100%)
3750
(98.4%)
Average Riffle
Depths (mean)
# Side
Channels
Side Channel
Area m2 (%)
0.5-0.7(0.6)
5
1349(11%)
0.25 - 0.5 (0.3)
1
18 (0.2%)
4
123 (3%)
1
102 (3.3%)
0.15-0.4
(0.3)
0.3-0.4
(0.35)
0.25 -0.45
(0.3)
0.25 - 0.35
(0.3)
0
1
60 (0.6%)
31
Stream Discharge
Flows were significantly lower in the second year of the study. Spring 2003
measurements were an average 84% of spring 2002 measurements and summer 2003
measurements were an average of 78% of 2002 (Table 5). Fall measurements were
similar between years (Table 5). The differences between spring and summer patterns
can be explained by greater snowpack and runoff in spring and summer 2002. Snowpack
in the High Oregon Cascades was 115% of normal in 2002, but was only 85% of normal
in 2003 (Source: National Weather and Climate Center www.ocs.orst.edu). It is
interesting to note that even the flows from the Metolius Headwaters, which are spring
fed and ostensibly unaffected by snowpack dropped by approximately 10% to 20% in
2003.
32
Table 5. Comparison of seasonal stream discharge measurements (m3/sec) for study
reaches in the Metolius River Basin.
Spring 2002 and 2003
Study Reach
Spring 2002
Spring 2003
2003 as Percent of 2002
Headwaters
3.20
2.56
80%
Lake Creek
2.80
2.48
89%
S. Fork Lake Cr.
1.30
0.82
63%
Spring Creek
Mainstem
3.30
2.85
86%
10.52
9.47
90%
4.09
3.56
87%
2.13
1.99
93%
Heising Spring
Canyon Creek
Summer 2002 and 2003
Study Reach
Summer 2002
Summer 2003
2003 as Percent of 2002
Headwaters
3.01
2.32
77%
Lake Creek
2.28
1.70
75%
S. Fork Lake Cr.
0.70
0.32
46%
Spring Creek
2.67
2.70
101%
Mainstem
9.21
8.51
92%
Heising Spring
3.77
3.51
93%
Canyon Creek
2.71
1.60
59%
Fall 2002 and 2003
Study Reach
Fall 02
Fall 03
2003 as Percent of 2002
Headwaters
2.66
2.39
90%
Lake Creek
1.80
1.88
104%
S. Fork Lake Cr.
0.32
0.35
110%
Spring Creek
2.43
2.33
96%
Mainstem
Heising Spring
Canyon Creek
8.21
7.86
96%
3.88
4.26
110%
1.45
1.45
100%
33
Water Temperature
Summer (May to October water temperature patterns were similar in study
reaches in 2002 (Figure 5) and 2003 (Figure 6). In both years of the study, Lake Creek
was the warmest stream, with maximum temperatures of 22.1°C in 2002 and 24.9 °C in
2003. Heising Spring was the coldest stream in both years, with maximum temperatures
of 7.5 °C in both years. Cumulative daily maximum temperatures (termed maximum
temperature units, or MTU5) were used to compare water temperatures among study
reaches for each study season: fall 2002 (May 23 - September 30), spring 2003 (April 30
- May 30) and fall 2003 (May 23 - September 30) (Table 9).
Table 6. Cumulative daily maximum temperature units (MTUs) for each season for study
reaches in the Metolius Basin.
Fall 2003
Fall 2002
Spring 2003
Study Reach
(May 23 - Oct 1)
(Apr 30 - May 30)
(May23 - Oct 1)
Lake Creek
2443
400
2538
Metolius Mainstem
1510
347
1585
Metolius Headwaters
1441
322
1353
Spring Creek
1243
313
1331
Canyon Creek
1072
221
1028
Heising Spring
880
209
868
34
2002 Maximum Water Temperatures
0
a,
E
a)
I-
Metolius Mainstem
- Canyon Creek
Spring Creek
0
May-02
June-02
- - Metolius Headwaters
- Lake Creek
Heising Spring
August-02
July-02
September-02
Figure 5. Daily maximum water temperatures in study reaches in the Upper Metolius
Basin, May to October, 2002.
Ii
2003 Maximum Water Temperatures
25
20-
4
if
C.)
/'sIJj
f\f,'V
I
a
E
10 -
V
:
_.'_4ø
-.
/_.\#
S
-
*
Canyon Creek
- - Met Headwaters
0
May-03
Spring Creek
June-03
July-03
Lake Creek
Met Mainstem
Heising Spring
August-03
I
September-03
Figure 6. Daily maximum water temperatures in six study reaches in the Upper Metolius
Basin, May to October, 2003.
35
Densities and Habitat Utilization
Study Reaches - Juvenile Chinook salmon densities (fish per square meter) in
pools and riffles are compared among study reaches in separate analyses. Densities of
juvenile Chinook salmon in poois were significantly higher in Lake Creek than Metolius
Mainstem or Canyon Creek in five of six sample periods in 2003, with the one exception
being spring 2003 (Table 10; ANOVA, p < 0.02 for all analyses). In two of the three
night sampling seasons, densities of juvenile Chinook salmon were significantly higher in
the Metolius Mainstem poois than in Canyon Creek pools. There were no significant
differences in the densities of juvenile Chinook salmon in riffles among study reaches for
any sample season in either year (Table 10; ANOVA, p > 0.05 for all analyses).
36
Table 7. Comparisons of densities of juvenile Chinook salmon in pools and riffles
among study reaches in the Metolius basin in 2002 and 2003 sample periods. Bold type
indicates significant differences
Sample Period
Spring Day 2002
Summer Day
2002
Summer Night
2002
Fall Day
2002
Fall Night
2002
Spring Day
2003
Spring Night
2003
Summer Day
2003
Summer Night
2003
Fall Day
2003
Fall Night
2003
Habitat Type (n)
ANOVA
p-value
K-W ANOVA
p-value
Group
Companson*
Pools (23)
0.09
0.16
No Differences
Riffles (29)
0.11
0.33
No Differences
Pools (26)
0.12
0.19
No Differences
Riffles (33)
0.18
0.16
No Differences
Pools (11)
0.46
0.82
No Differences
Riffles (10)
0.94
0.63
No Differences
Pools (26)
0.28
0.13
No Differences
Riffles (33)
0.57
0.39
No Differences
Pools (11)
0.55
0.43
No Differences
Riffles (10)
0.85
0.52
No Differences
Pools (39)
0.23
0.65
No Differences
Riffles (34)
0.86
0.55
No Differences
Pools (17)
0.008
0.019
LK>MM>CY
Riffles (11)
0.48
0.21
No Differences
Pools (39)
<0.001
<0.001
LK>CY, MM
Riffles (34)
0.24
0.26
No Differences
Pools (17)
0.009
0.002
LK>CY, MM
Riffles (11)
0.90
0.41
No Differences
Pools (39)
0.002
<0.001
LK>CY, MM
Riffles (34)
0.18
0.39
No Differences
Pools (17)
0.021
0.002
LK>MM>CY
Riffles (11)
0.77
0.80
No Differences
* Bonferroni's multiple comparison procedure for differences among study reaches. LK = Lake Creek, CY
= Canyon Creek, MM = Metolius Mainstem.
37
Habitat Units - Densities were significantly higher in pools than in riffles in Lake
Creek (Table 11; t-test, p <0.001). In Canyon Creek, pools had significantly higher
mean densities than riffles, and the significance was marginal (Table 11; t-test, p =
0.06 1). In the Metolius Mainstem, densities were not significantly different between
pools and riffles (Table 11; t-test, p = 0.153).
Table 8. Minimum, maximum, and mean densities (fish / m2) of juvenile Chinook
salmon in pool and riffle habitat in six study reaches in the Metolius Basin. Bold type
indicates significant differences.
Significance
Pool Densities
Riffle Densities
Study Reach
(t-test)
mm - max (mean) mm - max (mean)
Pools > Riffles
Lake Creek
0 0.33 (0.03)
0 -1.4 (0.16)
p < 0.001
Pools > Riffles?
Canyon Creek
0-0.025 (0.004)
0-0.056 (0.007)
p = 0.061
Metolius
Riffles = Pools
0- 0.02 (0.002)
0-0.008 (0.00 1)
Mainstem
p=O.l53
0-0.11 (0.01)
SpringCreek
0-0.11 (0.09)
Metolius
Headwaters
0 - 0.1(0.02)
NA
Heising Spring
0 0.14 (0.04)
NA
(n = one pool)
38
Habitat Subunits The selection and avoidance habitat subunits by juvenile
Chinook salmon varied among study reaches for day and night observations (Tables 12
and 13). For purposes of comparison, habitat subunit utilization was evaluated using
Jvlev 's Electivity Index (JET), which relates the amount of habitat utilized compared to
the amount of that habitat available. Raw numbers and densities of juvenile Chinook
salmon in habitat subunits in each study reach in each season are presented in Appendix
Tables C1-C6.
Among the three riffle dominated study reaches (Table 12), riffle edge habitat
was highly selected for in both day and night in the Metolius Headwaters (lET 0.70 and
0.90) and during the day in Heising Spring (IEI 0.96), but was neither selected nor
avoided in Spring Creek (-0.09). Mid channel riffle habitat was strongly avoided in both
Spring Creek (lET -0.88) and Heising Spring (lET 0.96), but was only weakly avoided in
the Metolius Mainstem (lET -0.31 and -0.29). Microhabitat patches were positively
selected in all riffle dominated reaches (lET 0.32 to 0.61).
Among study reaches with a mixture of pool and riffle habitat (Table 13), the only
subunit habitat type that was strongly avoided in both day and night surveys in all study
reaches was mid-channel riffle habitat (lET -0.44 to -1.0). In the Metolius Mainstem,
electivity values were similar in day and night observations, with positive selection of
pool edge (lET 0.70 and 0.90), riffle edge (TEl 0.89 and 0.70), and microhabitat patch
habitat (IEI 0.74 for both night and day). Mid-channel pooi habitat was avoided in the
Metolius Mainstem in both day and night observations, but the avoidance was greater at
night (lET -0.70) and than during the day (JET -0.22).
39
In Canyon Creek, pooi edge habitat, riffle edge habitat, and microhabitat patch
habitats were all positively selected in both day and night observations (Table 10; lET
0.42 to 0.94). However, mid-channel pool habitat in Canyon Creek was selected
differently between night and day observations, with strong avoidance during the day
(lET -0.82) and strong preference at night (TEl 0.67).
In Lake Creek, pooi edge habitat was the only habitat subunit type that was
strongly selected in both day and night observations (Table 10; TEl 0.57 and 0.89,
respectively). Mid channel riffle and mid channel pooi habitats were used similar to
their availability in both day and night observations (TEl 0.12 and -0.13, respectively).
Microhabitat patches were avoided in Lake Creek during the day (lET 0.49), but were not
strong preferred or avoided at night (lET -0.11).
Microhabitat patches - Microhabitat patches were considered a type of habitat
subunit for this study. Patches formed by natural wood were the most frequently
occupied patch type for juvenile Chinook salmon, as they were occupied in 24.9% of all
observations. Patches with the associated cover types of natural wood and overhanging
vegetation were the most frequently occupied by juvenile Chinook salmon (25.2% and
26.5%, respectively). For a discussion of the utilization of microhabitat patches, please
see Appendix B: Microhabitat Patch Utilization.
40
Table 9. Indices show relative preference (positive values), avoidance (negative values),
or neither (values near 0) of habitat subunits in day and night surveys in 2002 and 2003.
Metolius Headwaters
Spring Creek
Heising Spring
Habitat Subunit Type
Day
Night
Day*
Day*
Riffle Mid-Channel
-0.31
-0.29
-0.88
-0.96
Riffle Edge
0.70
0.90
-0.09
0.96
Microhabitat Patch
0.50
0.32
0.61
0.59
Side Channel Mid
N/A
N/A
0.00
-1.0
Side Channel Edge
N/A
N/A
-1.0
-1.0
* No nighttime surveys were conducted on Spring Creek or Heising Spring.
Table 10. Habitat subunit electivity indices for juvenile Chinook salmon in pool/riffle
stream reaches in the Metolius Basin. Indices show relative preference (positive values)
and avoidance (negative values) of habitat subunits in day and night surveys. Values
reflect average electivity values from seasonal surveys in 2002 and 2003.
Metolius Mainstem
Canyon Creek
Lake Creek
Habitat Subunit Type
Day
Night
Day
Night
Day
Night
Pool Mid-Channel
-0.22
-0.70
-0.82
0.67
0.12
-0.13
Pool Edge
0.70
0.96
0.94
0.94
0.57
0.89
Riffle Mid-Channel
-1.0
-1.0
-0.97
-1.0
-0.44
-0.72
Riffle Edge
0.89
0.70
0.71
0.42
-0.21
0.60
Microhabitat Patch
0.74
0.74
0.71
0.68
-0.49
-0.11
Side Channel Mid
-0.5
N/A
-1.0
N/A
0.39
-1.0
Side Channel Edge
0.70
N/A
0.91
N/A
0.05
-1.0
41
Night vs. Day Snorkeling
Greater numbers of juvenile Chinook salmon were seen at night than during the
day in 15 of 20 surveys of 2002 and 27 of 30 surveys in 2003 (Table 11). In several sites,
zero fish were seen during the day, yet fish were observed at night. In no cases were
juvenile Chinook salmon observed during the day when none were observed at night.
Table 11. Night vs. day snorkeling survey counts ofjuvenile Chinook salmon in sites in
the Metolius basin in 2002 and 2003. The statistic is expressed as a percentage of day
snorkeling counts from the same sites. CY = Canyon Creek, LK Lake Creek, MH =
Metolius Headwaters, MM = Metolius Mainstem, and number indicates study site.
2002 Observations
Site
Spring Night 2002
Summer Night 2002
Fall Night 2002
CY-3
200%
92%
113%
CY-1
N/A
0 fish to 1 fish
1000%
LK-5
160%
99%
116%
LK-2
N/A
200%
0 fish to 1 fish
MH-4
50%
200%
88%
MR-i
N/A
33%
0 fish to 1 fish
MM-4
N/A
250%
300%
MM-3
167%
550%
0 fish to 5 fish
Site
Spring Night 2003
Summer Night 2003
Fall Night 2003
CY-4
100%
500%
0 fish to 6 fish
CY-3
550%
160%
CY-1
0 fish to 7 fish
1100%
0 fish to 9 fish
0 fish to 7 fish
LK-7
622%
87%
100%
LK-5
Ofishto 78 fish
93%
115%
LK-2
113%
171%
141%
MH-4
MH-1
MM-4
197%
125%
98%
171%
100%
MM-3
0 fish to 14 fish
0 fish to 5 fish
0 fish to 10 fish
0 fish to 19 fish
2003 Observations
138%
0 fish to 2 fish
0 fish to 12 fish
42
Fish Communities
The composition of fish communities observed varied among study reaches
(Table 12). Bull trout and juvenile Chinook salmon were the only species that were
observed in all study reaches, although bull trout counts were low in most reaches. For
more details concerning the composition of fish species in the study reaches, please see
Appendix D: Fish Communities.
Table 12. Summary of fish species observed in six study reaches in the Metolius Basin,
2002 and 2003 combined. Species are listed left to right from most abundant to least
abundant. Trout species include bull trout, redband trout, brown trout, and brook trout.
%
%
Juvenile
trout
Adult
trout
Study Reach
Species Observed
Metolius Headwaters
RBT, CHK, COT, BRT*, KOK*, BUT*,
WHF*, LND*
98
2
Metolius Mainstem
WHF, RBT, BRT, BUT, COT, CHK,
BKT*
73
27
92
8
80
20
Lake Creek
Canyon Creek
BRT, CHK, RBT, BUT, WHF,
SPD, LND, COT*
BUT, CRK, KOK, RBT, BRT, COT,
BKT*
Heising Spring
CHK, BUT, RBT*
100
0
Spnng Creek
WHF, CHK, RBT, BRT, COT,
BUT, KOK, BKT*
94
6
* Indicates species represented less than 1% of observed fish.
Species Codes: CHK = Chinook, BUT = Bull trout, BRT Brown trout, BKT Brook trout, RBT =
Redband trout, WHF = Mountain whitefish, LND = long nosed dace, SPD = speckled dace, COT = Cottid
spp (Sculpin), KOK = Kokanee salmon (present only in fall surveys)
A fish was counted as an adult if it was 8 inches or greater in length. The
percentages of adult trout were higher in the Metolius Mainstem and Canyon Creek study
sections, with adults representing 27 and 20 percent of all trout observed, respectively.
The other four study sections had smaller percentages of adult trout, ranging from 0% in
Heising Spring to 8% in Lake Creek.
43
Fish Size and Condition
Fork Lengths - Results from K-W ANOVA tests indicate significant differences
in the fork lengths of juvenile Chinook salmon among study reaches in all three seasons,
as well as for cumulative percent rank data combining all seasons (Figure 7). Mean fork
lengths of juvenile Chinook salmon were largest in the Metolius Headwaters and
Metolius Mainstem study reaches in all seasons, and were the smallest in Heising Spring
in fall 2002 and fall 2003, and Canyon Creek in spring 2003 (Figure 7; Table 13).
Weight (g) was positively correlated with fork length in all seasons (p <0.001; R2 = 98.2)
and therefore only fork lengths are presented.
Condition Factors - Results from K-W ANOVA tests indicate that condition
factors were significantly different in all collection seasons (Figure 8a, b, and c). An
analysis on combined data from all collection seasons also indicated significant
differences among study sections (Figure 8d). Lake Creek had the highest mean condition
factor in all collection seasons, and the lowest mean condition factors were found in
Heising Spring in fall 2002 and fall 2003 and in Canyon Creek in spring 2003 (Table 14).
Fork Length Fall 2002
Fork Length Spring 2003
-1 13
_ 81
E
E 103
-c
a) K - W ANOVA;
)93
C
83
73
U-
p<o.001
I
I
E
I
d.f. = 5, 83
I
I
I
-r
CY
HS
LK
MH
MM
E
E
-c
0)
C
ci)
51
I
T
CY
HS
0
I
0)
0
C
MH
MM
SP
d.f.= 5,371
0.8
C
LK
I
I
d) K-W ANOVA;
CD
p<o.00i
I
Fork Length - All Seasons
d.f. = 4, 145
101
I
I
I
41
C
H
c)K-WANOVA;
I
p<o.00l
-
121
T
d.f.= 5,132
SP
Fork Length Fall 2003
b)K-WANOVA;
71
LL
0
63
=
p<0.001
0.6
0.4
0
_J 0.2
71
U-
61
-
cy
HS
LK
MH
sP
LL
0
cy
HS
LK
MH
MM
sP
Figure 7. Box-and-whisker plots ofjuvenile Chinook salmon fork lengths for a) fall 2002, b) spring 2003, c) fall 2003, and d)
cumulative percent rank in six study reaches in the Metolius Basin. Note: no fish were observed or collected in the Metolius
Mainstem reach (MM) in fall 2003. Study reach codes: CY = Canyon Creek, HS = Heising Spring, LK Lake Creek, MH
Metolius Mainstem, MM = Metolius Mainstem, and SP = Spring Creek.
45
Table 13. Juvenile Chinook salmon collection sample sizes, fork lengths (mm), and
Bonferroni's multiple range tests results in 2002 and 2003 collection periods.
Fall 2002
Fork lengths
Bonferroni MRT *
Section
n
Metolius Headwaters
20
mm - max (mean)
86 - 105 (95.9)
Spring Creek
22
71 - 96 (83.2)
Metolius Mainstem
3
76 92 (85.3)
Canyon Creek
17
70-89 (80.3)
Lake Creek
21
63-82 (75.6)
XX
Heising Spring
6
64-73 (68.5)
X
.
.
X
X
XX
XX
Spring 2003
Fork lengths
Section
n
Metolius Headwaters
17
mm - max (mean)
58 - 75 (68.8)
Metolius Mainstem
12
64 - 77 (69.0)
Spring Creek
24
49-69 (58.6)
Canyon Creek
20
Lake Creek
41
Heising Spring
24
44-54 (48.4)
53-71(60.0)
41 56 (49.4)
Bonferroni MRT
X
X
X
X
X
X
Fall 2003
Fork lengths
Section
n
Metolius Headwaters
30
mm - max (mean)
94 - 120 (102.7)
SpringCreek
15
83-103 (94.6)
Canyon Creek
22
73 - 102 (90.0)
LakeCreek
73
61-111 (83.2)
Heising Spring
10
68 78 (73.7)
Metolius Mainstem
N/A
No Fish Collected
Bonferroni MRT
X
XX
X
X
X
N/A
*yertical X's signify statistically similar groups, and side-by-side X's indicate statistical similarity.
Condition Factors Fall 2002
Condition Factors Spring 2003
1.6
1.6
a) K-W ANOVA;
0
d.f.=5, 83
p=0.003
1.4
C
T
C1
0
I
0.8
CY
T
I
.4-.
1
-r
-D
C
0.8
I
I
CY
MH MM SP
LK
Condition Factors FaIl 2003
I-
I
I
C
00
HS
<9.001
CD
U-
I
0
b) K-W ANOVA;
d.f. = 5, 132
0
0
-4-.
HS
LK
1
-r
MH
MM
T
SP
Condition Factors - All Seasons
1.6
1.6
0
0
4-.
U-
U-
Co.
0
0Co.
d) K-W ANOVA;
C
T
4-.
Cl
0
-o
l.2
d.f.=5,371
p<O.01
C
00
0 08
HS
LK
MH
SP
-r
LK
MH
I
I
0.8
CY
I
I
CY
HS
MM
SP
Figure 8. Box-and-whisker plots of condition factors (weight / length3 * 100,000) ofjuvenile Chinook salmon collected in a) fall
2002, b) spring 2003, c) fall 2003 and d) all seasons in six study reaches in the Metolius Basin. Study reach codes: CY = Canyon
Creek, HS = Heising Spring, LK Lake Creek, MH = Metolius Mainstem, MM = Metolius Mainstem, and SP = Spring Creek.
47
Table 14. Juvenile Chinook salmon sample sizes, condition factors, and Bonferroni's
multiple range tests results in 2002 and 2003 collection periods.
Fall 2002
Study Reach
n
Condition Factors
mm - max (mean)
Lake Creek
21
0.97-1.42 (1.20)
Metolius Headwaters
20
1.06 1.50 (1.18)
Canyon Creek
17
1.10 - 1.23 (1.16)
Spring Creek
22
1.03 - 1.25 (1.13)
Metolius Mainstem
3
1.09 1.12 (1.10)
Heising Spring
6
0.84 1.34 (1.02)
Study Reach
n
Condition Factors
.
mm - max (mean)
LakeCreek
41
0.89-1.31 (1.11)
Metolius Mainstem
12
1.02 1.18 (1.10)
Metolius Headwaters
17
0.92 1.18 (1.10)
Spring Creek
24
0.73 - 1.41 (1.05)
Heising Spring
24
0.87 1.35 (1.02)
CanyonCreek
20
0.81-1.27 (1.01)
Study Reach
n
Condition Factors
mm - max (mean)
Lake Creek
73
0.97-1.51 (1.25)
Spring Creek
15
1.06 - 1.35 (1.17)
Metolius Headwaters
30
1.05 - 1.27 (1.16)
Canyon Creek
22
1.00-1.27 (1.12)
Heising Spring
10
1.00 1.15 (1.08)
Metolius Mainstem
N/A
No Fish Collected
.
Bonferroni MRT
X
X
X
X
X
X
X
X
X
Spring 2003
Bonferroni MRT
X
X
X
X
X
X
X
X
Fall 2003
Bonferroni MRT
X
X
X
X
X
X
N/A
X's signify statistically similar groups, and side-by-side X's indicate statistical similarity.
48
Invertebrate Drift
Drft Density of Invertebrate Counts - Drift densities were significantly
different among study reaches in all three sample seasons: fall 2002 (Figure 9a),
spring 2003 (Figure 9b) and fall 2003 (Figure 9c). Comparison among all study
reaches (all seasons combined) indicate that drift density counts were statistically
higher in the Metolius Headwaters study section, and drift densities in the other five
study sections were statistically similar (Figure 9d).
Results from Tukey's HSD procedure indicate that the study reaches split into
two homogenous groups in each study season (Table 15). In fall 2002, the Lake
Creek study reach had significantly higher drift densities than Canyon Creek, whereas
the other four study reaches were not statistically different from each other. In both
spring and fall 2003, the Metolius Headwaters had the highest drift densities, and was
in a class by itself.
Drift Densities ofInvertebrate Biomass - Biomass drift densities between
study reaches were not significantly different in fall 2002 (Figure 1 Oa), but were
significantly different in spring 2003 (Figure lOb) and fall 2003 (Figure lOc). The
highest mean biomass drift densities in all sample seasons were collected in the
Metolius Headwaters study reach (Figure lOd). Results from Tukey's studentized
range HSD procedure indicate that the study reaches fall into one of two homogenous
groups in spring 2003 and fall 2003 (Table 16). In spring 2003, only the Heising
Spring and Metolius Headwaters study reaches differed from each other (the other
four study reaches were similar to both), while in fall 2003 the Metolius Headwaters
study reach was identified as a significantly different group by itself.
Invertebrate Count Drift Density
Fall 2002
300
250
a) K-W ANOVA;
d.f.=5,17
p=0.004
0
o 200
>,
150
a)
a 100
aI-
50
0
cy
HS
LK
MH
MM
SF
CY
:
C
MM
SP
250
250
U)
MH
300
300
>,
LK
All Seasons Combined
FaIl 2003
200
HS
d) K-W ANOVA;
c) K-W ANOVA;
d.f. = 5, 18
200
>
p=0.002
150
150
d.f.=5,64
p<0.001
=
C
a)
a)
o 100
0
o 50
_
0
50
-F
8
0
0
0
CY
HS
LK
MH
MM
SF
CY
HS
LK
I
I
MH
I
MM
SP
Figure 9. Box-and-whisker plots of invertebrate drift density (counts) of in six study reaches in the Metolius Basin, a) fall
2002, b) spring 2003, c) fall 2003, and d) all seasons combined. Y-axis values indicate the number of invertebrates drifting per
cubic meter of water per second. Study reach codes: CY = Canyon Creek, HS = Heising Spring, LK = Lake Creek, MH =
Metolius Mainstem, MM = Metolius Mainstem, and SP = Spring Creek.
50
Table 15. Number of invertebrate drift samples, count drift density (number of
invertebrates drifting / m3 of stream / second), and Tukey's HSD results from six
study reaches in the Metolius Basin in 2002 and 2003.
Fall 2002
Study Reach
n
Drift Density Counts
mm - max (mean)
Lake Creek
4
20.5 - 93.4 (42.7)
Metolius Headwaters
4
14.5 - 53.9 (38.3)
Metolius Mainstem
4
5.1-15.8(9.9)
Spring Creek
3
6.9-12.4 (9.4)
Heising Spring
4
Canyon Creek
4
1.5-9.2(6.7)
3.0-4.2 (3.7)
Tukey's HSD**
x
X
X
X
X
X
X
X
X
X
Spring 2003
Study Reach
n
Drift Density Counts
mm - max (mean)
Metolius Headwaters
4
40.8-92.1 (73.5)
Lake Creek
4
31.6-44.7 (38.8)
Metolius Mainstem
4
24.8 - 36.0 (28.4)
Spring Creek
4
11.5-57.5 (26.1)
Heising Spring
4
3.1 -23.5 (8.0)
Canyon Creek
3
7.5-8.6(8.0)
Study Reach
n
Drift Density Counts
mm - max (mean)
Metolius Headwaters
4
103.8 -255.0 (160.1)
Spring Creek
4
46-131.5(75.4)
Lake Creek
4
25.7 - 66.0 (49.5)
Metolius Mainstem
4
28.9-35.3 (31.5)
Canyon Creek
4
9.3 - 50.1 (24.3)
Heising Spring
4
1.9- 14.7 (7.8)
Tukey's HSD**
x
x
x
x
x
x
FaIl 2003
Tukey's HSD**
x
x
x
x
x
x
* Indicates one drift sample compromised during sampling (net blown out by current).
**Veica1 X's signify statistically similar groups, and side-by-side X's indicate statistical similarity.
Invertebrate Biomass Drift Density
Spring 2003
FaIl 2002
(0
E
2.5
2.5
a) K-W ANOVA;
d.f. = 5,17;
E
C',
E
.Q 1 5
p=o.217
0
b) K-W ANOVA;
d.f.= 5,17;
p = 0.008
clD.
>-.
>-.
C
a,
C
0
a,
0 0.5
cy
HS
LK
MH
MM
cy
sP
FaIl 2003
MH
MM
sP
3
0)
0
LK
Al! Seasons Combined
3
E
HS
C,,
2.5
2.5
E
c) K-W ANOVA;
U)
(0
0
d.f= 5,18;
p=0.032
9-
a 0.5
0.5
0
0
0
CY
HS
LK
MH
MM
SP
cy
HS
LK
MH
MM
sP
Figure 10. Box-and-whisker plots of drift density (biomass) of invertebrates in six study reaches in the Metolius Basin, a) fall
2002, b) spring 2003, c) fall 2003, and d) all seasons combined. Y-axis values indicate the biomass of invertebrates (in grams)
drifting per cubic meter of stream per second. Study reach codes: CY = Canyon Creek, HS = Heising Spring, LK = Lake Creek,
MH = Metolius Mainstem, MM = Metolius Mainstem, and SP = Spring Creek.
52
Table 16. Number of invertebrate drift samples, biomass drift density (grams of
invertebrates drifting / m3 of stream / second), and Tukey's HSD comparisons from
six study reaches in the Metolius Basin in 2002 and 2003.
Fall 2002
Section
n
Biomass drift density (g)
mm - max (mean)
Metolius Headwaters
4
0.08 - 0.41 (0.29)
Heising Spring
4
0.01 - 0.60 (0.22)
No
Spring Creek
3*
0.02 - 0.48 (0.21)
Significant
Lake Creek
4
0.01 - 0.33 (0.13)
Differences
Metolius Mainstem
4
0.07 - 0.09 (0.08)
Canyon Creek
4
0.02 - 0.05 (0.03)
Section
n
Biomass drift density (g)
mm - max (mean)
Metolius Headwaters
4
1.13-2.85 (1.86)
Lake Creek
4
1.04-2.08 (1.38)
Spring Creek
4
0.32-2.77 (1.25)
Metolius Mainstem
4
0.58 - 0.93 (0.72)
Canyon Creek
3*
0.36 - 0.46 (0.41)
Heising Spring
4
0.20 - 0.41 (0.28)
Section
n
Biomass drift density (g)
mm - max (mean)
Metolius Headwaters
4
0.86-1.90 (1.34)
Spring Creek
4
0.27 1.07 (0.67)
Metolius Mainstem
4
0.36 - 0.54 (0.46)
Lake Creek
4
0.27 - 0.61 (0.45)
Canyon Creek
4
0.22 - 0.79 (0.41)
Heising Spring
4
0.14 0.70 (0.33)
Tukey's HSD**
Spring 2003
Tukey's HSD**
Fall 2003
Tukey's HSD**
X
* Indicates one drift sample compromised during sampling (net blown out by current).
**Veltical X's signify statistically similar groups, and side-by-side X's indicate statistical similarity.
53
Size and Condition vs. Invertebrate Drift and Water Temperature
The results of multiple regression analyses of juvenile Chinook salmon fork
length and conditions versus cumulative daily maximum temperature units (MTU's;
see Table 9) and invertebrate biomass drift densities indicate that model containing
invertebrate drift biomass + MTUs
- MTUs2 explained 68 and 59% of the variation in
fork lengths ofjuvenile Chinook salmon in Fall 2002 and Spring 2003 (Table 17). In
fall 2003, the selected model contained only MTUs - MTUs2, and invertebrate drift
biomass was not included (Table 17). Addition of the squared temperature term to
the multiple regression models increased the R2 value by 0.21, 0.09, and 0.33 in each
season (fall 2002, spring 2003, and fall 2003, respectively) indicating a curvilinear
relationship with temperature, particularly in fall samples. A polynomial regression of
MTU + MTU2 alone explained between 41 and 63 percent of the variation in fork
lengths (Figure 11; p <0.001 in all seasons,
= 0.63, 0.55, and 0.41). Interestingly,
invertebrate drift density biomass was positively related to fork lengths in all seasons
(Figure 12, p <0.001 in all seasons,
= 0.29, 0.42, and 0.38), yet this variable was
not selected in the fall 2003 multiple regression model. For explanation of model
variable selection, please see Methods (page 27).
Table 17. Significance results of multiple regression analyses ofjuvenile Chinook
fork lengths and conditions versus invertebrate drift density and water temperatures.
Fall 2002
Fall 2003
Spring 2003
Fork
Length
Condition
Factor
= mv DD + MW
= mv DD + MW
- MTU2
- MTU2
(p <0.001, R2 = 0.68)
(p <0.001, R2 = 0.59)
= MW
= mv DD
(p
0.026, R2
0.08)
(p <0,001, R2 = 0.11)
= MW - MTU2
(P <0.001, R2 0.41)
MW
(p <0.001, R2 = 0.39)
54
Results of multiple regression analysis of condition factors versus MTUs and
invertebrate drift density indicate that only one of the two variables was significantly
correlated with condition factor in each season. Condition factors were positively
correlated with count drift density in fall 2002 (p = 0.026, R2 = 0.08), and with
MTU's in spring 2003 (p <0.001, R2 = 0.11) and fall 2003 (p < 0.001, R2 = 0.39).
55
113
103
-
c,)
C
93
I.-
83
-Ia)
0
LL
.73
63
800
1100
1400
2000
1700
2300
2600
Maximum Temperature Units
81
b) Spring 2003:
-c
C
a)
-j
p<0.001,R2=0.55
71
61
0
IL
51
Fork Length = -48.445 + 0.664 (MTU) - 0.000 10 (MTU"2)
41
200
240
280
360
320
400
Maximum Temperature Units
121
111
101
91
81
71
61
800
1100
1400
1700
2000
2300
2600
Maximum Temperature Units
Figure 11. Polynomial regression display of juvenile Chinook salmon fork lengths
versus cumulative daily maximum temperature units (MTUs) in a) fall 2002, b)
spring 2003, and c) fall 2003. Lines indicate fitted regression and 95% confidence
intervals.
56
115
Fork Length = 73.35 + 56.05 * Avg. DD Biomass
a
105
0
Fall 2002
C)
p<0.001,R2=0.29
-J
0
LL
85
a
a
75
a
a
a
65
a
0
0.05
0.15
0.1
0.2
0.3
0.25
Average Drift Density Biomass (g)
80
-c
Th70
C
a)
-J
b) Spring 2003
:p<o.001,R2 0.42
-
B
8
8
B
B
a
a
a
B
60
0
B
U-
B
B
Fork Length = 47.43 + 10.25 * Avg. DD Biomass
40
0
0.4
0.8
1.2
1.6
2
Average Drift Density Biomass (g)
120 :
110
Fork Length= 75.11 + 10.23 * Avg. DD Biomass
100
90
80
70
60
0
0.3
0.6
0.9
1.2
1.5
Average Drift Density Biomass (g)
Figure 12. Regression displays ofjuvenile Chinook salmon fork lengths versus
average invertebrate drift density biomass in a) fall 2002, b) spring 2003, and c) fall
2003. Lines indicate fitted regression and 95% confidence intervals.
57
Comparisons to HabRate
The qualitative HabRate ratings for each of the six reaches sampled during
this study differed from the estimated potentials for juvenile Chinook salmon
production and growth for each reach generated by this study (Table 18). Lake
Creek and the Metolius Headwaters study reaches are potentially the best for
production of Chinook salmon smolts, and the Metolius Headwaters and Mainstem
are potentially the best for growth.
Table 18. Comparison of HABRATE summer rearing ratings, estimated smolt
production, and corresponding ranking and ratings of sampled streams reaches in the
Metolius River Basin.
Study Rating
HABRATE Rating
Study Rating
Stream
Growth
Density
For Summer Rearing
Metolius
Good
Poor
Good
Headwaters
Lake Creek
Poor
Poor
Good
Spring Creek
Poor
Poor
Fair
Heising Spring
Poor
Poor
Poor
Canyon Creek
Fair
Poor
Poor
Metolius Mainstem
Poor
Poor
Good
This study and HabRate seem to agree on the limited productive potential of
the Mainstem Metolius River, which represents the largest amount of available
habitat in the basin, and presents the best temperatures for growth. I estimated
production of less than 200 smolts per kilometer of stream from the Mainstem
Metolius, and HabRate's ranking for summer rearing was a similar "poor". Please
see Appendix A: Smolt Production Estimates for a more detailed discussion.
58
DISCUSSION
The field observations made in this study were not consistent with the
qualitative predictions of HabRate (Table 17). Canyon Creek was predicted to be the
best quality for juvenile Chinook, yet my observations indicated that is was one of the
poorest in terms of both density and growth ofjuvenile Chinook salmon (Table
8,
figure 7). Lake Creek and the Metolius Headwaters, which were rated as poor by
HabRate, were observed to be the best in terms of density and growth, respectively
(Table 8, Figure 7).
HabRate's approach is based solely upon physical habitat availability, with
the assumption that habitat will be used consistently regardless of stream reach (i.e. a
pool in one reach is of the same importance as a pool in another reach). The lack of
pool habitat was identified as a major limiting factor by HabRate, which is based on
the assumption that pools are the most important habitat type for juvenile Chinook
salmon. This assumption is well supported by published literature, as several studies
have reported that Juvenile Chinook salmon show a strong preference for pool habitat
(Everest and Chapman 1972; Hillman et at. 1992; Roper et al. 1994). And while I
found that densities of juvenile Chinook salmon were higher in pools than in riffles in
Lake Creek and Canyon Creek, utilization of pools and riffles was similar in the
Metolius Mainstem study reach (Table 8). Additionally, some of the highest densities
were observed in the Metolius Headwaters study section, which consists entirely of
riffle habitat (Table 5). These observations indicate that pooi habitat is not the only
type of habitat that can be utilized, and there are several factors other than physical
habitat that influence habitat choice.
59
HabRate does not account for ecological interactions, such as food
availability, competition, or potential risk of predation. My observations indicated
that utilization of habitat was not consistent among all study reaches, and the data
suggest that the unique ecological conditions among reaches help to explain these
inconsistent patterns. Several other habitat quality models (e.g. IFIM (Bovee 1992)
and HSI (Raleigh et al. 1986), see Fausch et al. 1988 for a review of models) also
depend heavily upon quantitative habitat parameters, but few of them are formal
arguments relating ecological or physiological interactions related to a species
production. Almost all of them are correlations of physical habitat attributes to
standing crops. My observations lead me to believe that the ecological settings of
individual streams provide the context of understanding of patterns. My approach to
this study was to quantify two major responses of juvenile Chinook salmon: growth
and habitat utilization. First, I present a new conceptual model based on growth
capacity for evaluating the quality of habitat in the Metolius Basin for juvenile
Chinook salmon. Second, I discuss some of the effects of community composition
and water temperature on habitat selection, utilization, and diurnal activity patterns.
Growth is one of the best indicators of the quality of the habitat in which fish
are living, since it is often the last process in the energy equation (Diana 1994). My
growth capacity model is based upon the foundations of bioenergetics: all creatures
must ingest energy to meet metabolic demands, and have some left over to grow. The
basic energy budget, as described by Webb (1978) is:
PQR= EQM+QG
60
where Q represents energy in different forms, p denotes the coefficient of assimilation
of the ingested ration (QR) which is available for, metabolism (QM) and growth (QG).
Metabolic demands (EQM) include costs for standard metabolism, SDA or AHI, and
other physiological (e.g., costs of osmoregulation), behavioral (e.g., seasonal
migration), and ecological (e.g., ecological) activities, all of which are temperature
influenced (F.E.J. Fry 1947, Brett 1952; Warren and Davis 1967; Brett et al 1969).
I adapted the concept of the Scope for Growth (Warren and Davis 1967) as an
index by which to rate habitat quality for juvenile Chinook salmon. The Scope for
Growth was first conceived to describe the fundamental physiological capacity of an
organism to grow along a factor gradient (sensu Fry 1947). For the sake of argument,
I have redrawn the scope for growth as presented by Brett (1969) (Figure 13).
Although Brett's model was created for sockeye salmon, I found it useful as a
conceptual tool for describing patterns in the sizes of juvenile Chinook salmon
collected in the Metolius Basin in relation to water temperatures and invertebrate
drift.
As water temperatures increase (the X-axis), the capacity to ingest and
metabolize food (the Y-axis) increases and then drops off as appetite wanes, as
indicated by the heavy dashed line A in Figure 13. Concomitantly, metabolic costs
increase following the Q° principal, as indicated by the heavy solid line B in Figure
13. The difference between the two lines (assimilated ration less metabolic costs), is
defined as the Scope for Growth at any specified temperature.
61
A) Maximum Energetic Intake
High Invertebrate Drift
Medium Invertebrate Drift
/
/
/
/
/SP
MW
MM
Low mv D
/
LK
-
V
HS
B) Minimun Intake for
(Metabolic Maintenance)
0
0
5
10
15
20
25
Water Temperature -
Figure 13. The Scope for Growth for juvenile salmon (Redrawn from Brett et al.
1969). Vertical arrows indicate maximum summer time temperatures observed in
each Metolius Basin study reach. Horizontal dashed lines indicate potential levels of
invertebrate drift availability. The vertical axis describes energy rate to express both
prey availability and metabolic costs.
If I plot vertical lines on Figure 13, each corresponding to the maximum
temperatures observed in each study reach (Figures 5 and 6), and the length of each of
the vertical lines is indicative of the scope for growth at that particular temperature,
the relative differences in growth among study reaches correspond well with the
scopes for growth indicated by the model (Figure 7, Table 13). Fish rearing in
temperatures that are not optimal for metabolic performance (i.e. too warm or too
cold) will have less energy available for growth, since all metabolic demands must be
met before any growth can take place. Fork lengths of juvenile Chinook salmon
62
among study reaches in the Metolius Basin could be explained by the predicted
curvilinear relationship with temperature, with 68%, 61%, and 41% (fall 2002, spring
2003, and fall 2003, respectively) of the variation in fish size explained by an
exponential function of temperature plus temperature squared (Figure 10).
The Y-axis in Brett's model indicates the ration of food intake, expressed as
percent body weight. My version uses invertebrate drift density as an index of
energetic intake, and takes into account the ecological consequences of prey
availability. In other words, prey may be available at levels below ad libitum ration
levels, which would reduce the energy available for growth. If the amount of
invertebrate drift was less than the maximum percent body weight that could be
ingested (e.g. 4%, as represented by the "low" line in Figure 13), the scope for growth
would be limited by available invertebrate drift. This model suggests that habitats
can be rated by understanding the effects of temperature on metabolic costs and the
constraints of prey availability. This model provides a better explanation for my
observations of growth.
The Metolius Headwaters reach,. which had the largest fish in all sample
periods, has the largest predicted relative scope for growth. Heising Spring, which
had the smallest fish in all sample periods, has the smallest relative predicted scope
for growth (Figure 13) (see Figure 7, Table 13 for comparison of fish sizes). The
similarity of lengths and weights between Canyon Creek and Lake Creek in fall 2002
and fall 2003 can also be explained by the model. These two streams differ greatly in
terms of temperature (Figures 5 and 6), and yet the size of the juvenile Chinook
salmon rearing in them was not statistically different (Figure 7, Table 13). Assuming
63
that temperature is the only factor influencing metabolic performance (and therefore,
growth) conditions in Lake Creek (above the optimum range), and the conditions in
Canyon Creek (consistently below the optimum range) resulted in similar sized fish.
In warmer temperatures (e.g. Lake Creek) the model predicts that the amount
of energy (rations) available has to be greater in order for fish to maximize their
growth. The highest densities of juvenile Chinook salmon were observed in Lake
Creek (Table 8), which was the study reach with the highest temperatures (Figures
5
and 6). However, the juvenile Chinook in Lake Creek tended to be smaller (Figure 7,
Table 13). The density of invertebrate drift counts was among the highest in Lake
Creek in all sample seasons, and invertebrate biomass was particularly high in spring
(Figures 9 and 10, Tables
15
and 16). The growth capacity model indicates that the
scope for growth is limited at high temperatures, i.e. the habitat would produce
smaller fish, which is the pattern that was observed. However, greater levels of
invertebrate drift (i.e. energy availability) may explain why the fish were able to live
at high densities in Lake Creek; the habitat was able to support high densities of small
fish.
At low temperatures, the growth capacity model predicts that the amount a
fish can eat is minimized due to metabolic limitations therefore maximum growth
under those conditions will be attained at smaller rations. Densities of juvenile
Chinook were relatively low in Canyon Creek (Table 8), yet the fish were statistically
the same size as those in Lake Creek (Figure 7, Table 13). Temperatures in Canyon
Creek were cold (Figures 5 and 6), and invertebrate drift densities were among the
lowest observed (Figures 9 and 10, Tables
15
and 16). Again, this meets the
64
expectations of the growth capacity model, especially as predicted under conditions
of low invertebrate prey availability.
These interpretations of my observations in Lake Creek and Canyon Creek are
by no means definitive. However, the point is that there is not a unique way to obtain
the same growth; therefore, there is no unique way to rate habitat. The growth
capacity model is more inclusive of other factors. This approach is a hypothesis that
appears to fit the facts, but must be tested. It is unknown whether the fish would
have grown larger at lower densities, or been smaller at higher densities (i.e.
resources were limiting), or if sizes would have remained the same regardless of
density (i.e. resources were not limiting). Controlled experiments, either in a closed
natural setting or laboratory environment, could aid in the understanding of the
relations between invertebrate drift, water temperature, and density-dependent effects.
This bioenergetic growth capacity model has links to work of other
researchers, and may aid in the understanding of density - dependent population
limitations and the concept of carrying capacity of stream habitats. The Ideal Free
Distribution Theory (IFD) (Fretwell and Lucas 1970; Fretwell 1972; Fraser and Sise
1980; Gilliam and Fraser 1987; Tyler and Gilliam 1995; Giannico and Healey 1999)
predicts that animals should distribute themselves among patches of resources in
proportion to the resources available within those patches. IFD models have focused
exclusively on foraging resources (i.e. the income side of the equation). Hughes and
Grand (2000) modified this concept by incorporating a physiological growth
component. Through simulations they demonstrated that the choice of habitat
depends not only according to the available resources, but is also affected by the
65
energetic limitations placed on individuals by water temperature. My growth
capacity model is an advancement of Hughes and Grand's (2000) in that there are
both physiological and ecological constraints on ration size. Fish living in warmer
water have a greater capacity for metabolic turnover and their maximum potential
ration increases. At cooler temperatures, metabolic turnover is limited, and it will
take a lesser amount of food rations for a fish to reach "fullness". Yet the potential
for growth in both warm and cold water is reduced, which helps to explain my
observations of growth.
In addition to the physiological constraints on growth, other ecological factors
may influence the suitability of habitat for juvenile Chinook salmon. For instance, an
important hypothesis generated from my work is that the risk of predation by adult
trout may play a major role in both the habitat selection and diurnal actively patterns
of juvenile Chinook salmon. The study reaches with the greatest presence of adult
trout were Canyon Creek and the Metolius Mainstem (Table 12). In Canyon Creek,
juvenile Chinook salmon avoided mid-channel pool habitats during the day, but
preferred them at night (Table 10). In the Metolius Mainstem, juvenile Chinook
salmon showed a strong avoidance of mid-channel habitat in both day and night
surveys (Table 10). Additionally, the increases in the numbers of juvenile Chinook
salmon seen at night were the most dramatic in Canyon Creek and the Metolius
Mainstem (Table 11). In summer and fall of 2003, zero juvenile Chinook salmon
were observed during daytime dives in 8 of 12 study sites in these two reaches.
However, in all cases, Chinook were observed in subsequent night dives. These
observations suggest that juvenile Chinook salmon in the Metolius Mainstem may
66
have selected edge habitats closer to cover at all times, and in Canyon Creek adopted
a nocturnal feeding regimen as a strategy to minimize the risks of predation. In the
case of the Metolius Mainstem, mid-channel habitat was potentially lethal during both
day and night, and therefore the most suitable habitat for juvenile Chinook salmon
was along the edges, regardless of the habitat unit type. Note then that the potential
Scope for Growth (Figure 13) was the highest in the Metolius Mainstem, yet the
observed densities of juvenile Chinook salmon were the lowest (Table 8). In Canyon
Creek, the nighttime utilization of pooi habitats suggest that nocturnal feeding,
although less efficient, minimized the energy expenditure of avoiding predation,
which concurs with the results of recent studies (Metcalf et al. 1999; Bradford and
Higgins 2001). The point here is that a lethal community interaction (predation)
outweighs the potential suitability of the habitat.
Cold temperatures may also serve as a plausible explanation for the did
activity patterns observed in Canyon Creek. Salmonids have been observed to hide
themselves in interstitial spaces during the day, as water temperatures approach 8 °C
in the onset on winter (Riehle and Griffith 1993). This behavior has also been
observed in the summer and fall (Hillman et al. 1991, Fraser et al 1995). However,
none of these researchers noted the presence or absence of predators in their study
sustems, and it is debatable whether this hiding behavior at low temperatures is due
purely to energetic constraints (i.e. minimization of energy expenditures) or are an
artifact of predation avoidance.
In summary, I found that the growth and densities of juvenile Chinook salmon
in the Metolius Basin varied widely, and I believe potential explanations for these
67
variations must go beyond the physical nature of the habitat itself. Habitat was
utilized differently in each of the study reaches, and my observations suggest that the
biological uniqueness of each of the reaches helps to explain these variations. A
bioenergetic approach including invertebrate drift as an index of energetic income
and water temperatures as an index of energetic expense helps to explain patterns of
growth among study reaches. Fish community composition, particularly the presence
or absence of predators, helps to explain some of the patterns of habitat selection and
diel activity ofjuvenile Chinook salmon in the Metolius Basin.
Future Research Directions
The growth capacity model presented in this discussion provides insight into
the roles of invertebrate drift and water temperature. Although this conceptual model
does potentially increase the understanding of observed patterns of fish abundance
and size, the data collected in this study is insufficient in terms of determining how
invertebrate drift can be translated to rations or percent body weight on the Y-axis of
Figure 13 (i.e. the low, medium, and high horizontal lines). Further investigation on
the energetic equivalents of invertebrate drift (e.g. Cummins and Wuycheck 1971)
will be necessary to further refine the model.
Additionally, I was unable to examine density-dependence clearly in my study
because sufficient numbers of disease free fry could not be obtained. Although the
numbers of fry released in the second year of the study were increased (Table 2), I
feel that the numbers were insufficient to saturate the habitat. It is possible that there
68
may have been localized density-dependent effects near release locations, but the
spatial extent and potential severity of these effects are unknown.
The data collected for this study will be available to fisheries managers in the
Metolius and Deschutes River Basins. The data can be incorporated into HabRate
models of relative habitat quality in the Metolius Basin, and can increase the accuracy
of GIS models. The data that I collected will provide future research opportunities
for several directions of study that were not specifically addressed in this thesis. I
observed annual differences in invertebrate abundance and the condition and growth
of juvenile Chinook salmon within study reaches, particularly Lake Creek.
Additionally, the ecological conditions within study reaches, particularly stream
discharge, were different between years (Table 5). These intra-annual differences
pose the question about long-term variation that could not sufficiently be addressed in
a two-year study, but suggest the need for long-term monitoring. Data were also
collected on the community composition of invertebrate drift samples, and juvenile
Chinook salmon were collected and stored for potential stomach content analysis.
Hopefully the data collected for this thesis project will provide the basis for future
research efforts, both personally and for other fisheries scientists interested in either
the ecology of juvenile Chinook salmon or the management of fisheries in the
Metolius River Basin.
69
BIBLIOGRAPHY
Bilby, R.E. and Bisson, P.A. 1998. Function and distribution of large woody debris.
Pages 324-346 In R.J. Naiman and R.E. Bilby, editors. River ecology and
management: lessons from the Pacific coastal region. Springer-Verlag, New
York.
Bisson, P. A., Bilby, R.E., Bryant, M.D., Dollof, C.A., Grette, G.B., House, R.A.,
Murphy, M.L. Koski, K.V. and Sedell, J.R. 1987. Large woody debris in
forested streams in the Pacific Northwest: past, present, future. Pages 143-190
in: E.O. Salo and T.D. Cundy, Editors. Streamside management: forestry and
fisheries interactions. University of Washington College of Forest Resources,
Seattle WA.
Bisson, P.A., K. Sullivan, and J. Nielsen. 1998. Channel hydraulics, habitat use, and
body form ofjuvenile coho salmon, steelhead, and cutthroat trout in streams.
Transactions of the American Fisheries Society 117: 262-273.
Bradford, M. J., and P. S. Higgins. 2001. Habitat-, season-, and size-specific
variation in die! activity patterns of juvenile Chinook salmon (Oncorhynchus
tshawytscha) and steelhead trout (Oncorhynchus mykiss). Canadian Journal
of Fisheries and Aquatic Sciences 58: 365-3 74.
Brett, J. R. 1952. Temperature tolerances in young salmon. Journal of the Fisheries
Resource Board of Canada 9: 265-321.
Brett, J.R. 1971. Energetic responses of salmon to temperature. A study of some
thermal relations in the physiology and freshwater ecology of sockeye salmon
(Oncorhynchus nerka). American Zoologist 11: 99-113.
Brett, J.R., J.E. Shelbourn, and C.T. Shoop. 1969. Growth rate and body
composition of fingerling sockeye salmon, Oncorhynchus nerka, in relation to
temperature and ration size. Journal of the Fisheries Research Board of
Canada 26: 2363-2394.
Brett, J.R. W.C. Clarke, and J.E. Shelboum. 1982. Experiments on thermal
requirements for growth and food conversion efficiency of juvenile Chinook
salmon. Nanaimo, B.C. Department of Fisheries and Oceans, Fisheries
Research Branch.
Burke, J.L, K.K. Jones, and J. M. Dambaucher. In Press. Summary of a channel
habitat evaluation methodology of salmon and steelhead in the Middle
Deschutes Basin. Oregon Department of Fish and Wildlife.
70
Busacker, G. P., I. R. Adelman, and E. M. Goolish. 1990. Growth. Pages 363-388 in
C. B. Schreck and P.B. Moyle, editors. Methods for Fish Biology. American
Fisheries Society, Bethesda, Maryland.
Chapman, D. W. and T. C. Bjornn. 1969. Distribution of salmonids in streams, with
special reference to food and feeding. Pages 153-176 in T. G. Northcote,
editor. Symposium of salmon and trout in streams. H. R. MacMillan
Lectures in Fisheries, University of British Columbia, Vancouver.
Cummins, K. W., and Wuycheck, J.C. 1971. Caloric equivalents for investigations in
ecological energetics. Mitt. Internat. Verein Linmol 18: 1-158.
Diana, J.S. 1995. Biology and Ecology of Fishes. Cooper Publishing Group LLC,
Cannel, Indiana, USA.
Dill, L. M., R. C. Ydenberg, and A. H. G. Fraser. 1981. Food abundance and
territory size in juvenile coho salmon (Oncorhynchus kisutch). Canadian
Journal of Zoology 59: 1801 - 1809.
Everest, F.E., and D.W. Chapman. 1972. Habitat selection and spatial interactions
by juvenile chinook salmon and steelhead trout in two Idaho streams. Journal
of the Fisheries Resource Board of Canada 29: 91-100.
Fausch, K.D. 1983. Profitable stream positions for salmonids: relating specific
growth rate to net energy gain. Canadian Journal of Zoology 62: 441-451.
Fausch, K.D. 1993. Experimental analysis of microhabitat selection by juvenile
steelhead (Oncorhynchus mykiss) and coho salmon (0. kisutch) in a British
Columbia stream. Canadian Journal of Fisheries and Aquatic Sciences. 50:
1198-1207.
Fraser, D. F. and T. B. Sise. 1980. Observations of stream minnows in a patchy
environment. Ecology 61: 790-797.
Fraser, N. H. C., J. Heggenes, N. B. Metcalfe, and J. E. Thorpe. 1995. Low summer
temperatures cause juvenile fish to become nocturnal. Canodian Journal of
Zoology 73: 446-45 1
Fretwell, S. D. 1972. Populations in a seasonal environment. Princeton University
Press, Princeton, New Jersey.
Fretwell, S. D. and H. L. Lucas Jr. 1970. On territorial behavior and other factors
influencing habitat distribution in birds. I. Theoretical development. Acta
Biotheoretica XIX: 16-36.
71
Frissell, C. A., Liss, W. J., Warren, C. E., and Hurley, M. D. 1986. A hierarchical
framework for stream habitat classification: viewing stream in a watershed
context. Environmental Management 10: 199-2 14.
Fry, F.E.J. 1947. Effects of the environment on animal activity. The Ontario
Fisheries Research Laboratory 68.
Giannico, G. R. and M. C. Healey. 1999. Ideal Free Distribution theory as a tool to
examine juvenile coho salmon (Oncoryhncus kisuch) habitat choice under
different conditions of food abundance and cover. Canadian Journal of
Fisheries and Aquatic Sciences 56: 2362-2373.
Gilliam , J. F. and D. F. Fraser. 1987. Habitat selection under predation hazard: test
of a model with foraging minnows. Ecology 68(6): 1856-1862.
Gore, J. A. 1996. Discharge measurements and streamfiow analysis. Pages 53 - 74 in
F. R. Hauer and G.A. Lamberti, editors. Methods in Stream Ecology.
Academic Press, San Diego, California.
Healey, M. C. 1991. Life history of Chinook salmon. Pages 3 12-393 in C. Groot
and L. Margolis, editors. Pacific Salmon Life Histories. University of British
Columbia Press, Vancouver.
Hiliman, T. W., J. S. Griffith, and W. S. Platts. 1987. Summer and winter habitat
selection by juvenile chinook salmon in a highly sedimented Idaho stream.
Transactions of the American Fisheries Society 116: 185-195.
Hillman, T.W, J.W. Mullan, and J.S. Griffith. 1992. Accuracy of underwater
accounts ofjuvenile chinook salmon, coho salmon, and steelhead. North
American Journal of Fisheries Management 12: 598-603.
Hoitby, L.B., B.C. Anderson, and R.K. Kadowski. 1990. Importance of smolt size
and early ocean growth to interannual variability in marine survival of coho
salmon (Oncorhynchus kisutch). Canadian Journal of Fisheries and Aquatic
Sciences 47: 2181-2194.
Hughes, N. F. and T. C. Grand. 2000. Physiological ecology meets the ideal-free
distribution: prediction the distribution of size-structured populations across
temperature gradients. Experimental Biology of Fishes 59: 285-298.
Ivlev, V.S. 1961. Experimental ecology of the feeding of fishes. Yale University
Press, New Haven, Connecticut.
Lima, S. L., and L. M. Diii. 1990. Behavioral decisions made under the risk of
predation: a review and prospectus. Canadian Journal of Zoology 68: 619640.
72
Lister, D. B. and L. S. Genoe. 1970. Stream habitat utilization by cohabiting
underyearlings of chinook and coho salmon in the Big Qualicum River,
British Columbia. Journal of the Fisheries Research Board of Canada. 27:
1215-1224.
Metcalfe, N. B., N. H. C. Fraser, and M. D. Burns. 1999. Food availability and the
nocturnal vs. diurnal foraging trade-off in juvenile salmon. Journal of Animal
Ecology 68: 371-38 1.
Montgomery, D. R., Buffington, J. M., Smith, R.D., Schmidt, K.M., and Pess, G.
1995. Pool spacing in forest channels. Water Resources Res. 31: 1097-1105.
Mossup, B, and M.J. Bradford. 2004. Importance of large woody debris for juvenile
Chinook salmon habitat in small boreal forest stream in the upper Yukon
River basin, Canada. Canadian Journal of Forest Resources 34: 1955-1966.
Myers, J.M., R.G. Kope, G.J. Bryant, D. Teel, L.J. Lierheimer, T.C. Wainwright,
W.S. Grand, F.W. Waknitz, K. Neely, S.T. Lindley, and R.S. Waples. 1998.
Status review of chinook salmon from Washington, Idaho, Oregon, and
California. U.S. Dept. Conimer., NOAA Tech. Memo. NMFS-NWFSC-35,
443 p.
Nehlson, W. 1995. Historical salmon and steelhead runs of the Upper Deschutes
River and their environments. Portland General Electric Company. Portland,
Oregon.
Quinn, 1. P., and N.P. Peterson. 1996. The influence of habitat complexity and fish
size of over-winter survival and growth of individually marked juvenile coho
salmon (Oncorhynchus kisutch) in Big Beef Creek Washington. Canadian
Journal of Fisheries and Aquatic Sciences 53: 1555-1564.
Peckarsky, B. L. 1996. Predator-Prey Interactions. Pages 43 1-541 in F. R. Hauer
and G. A. Lamberti, editors. Methods in Stream Ecology. Academic Press,
San Diego, California.
Portland General Electric Company (PGE) and The Confederated Tribes of
the Warm Springs Reservation of Oregon (Tribes). 2004. Pelton Round Butte
Project Fish Passage Plan. Exhibit D in the Pelton Round Butte Project
Settlement Agreement, July 2004. Portland General Electric Company.
Portland, Oregon.
Rader, R. B. 1997. A functional classification of the drift: traits that influence
invertebrate availability to salmonids. Canadian Journal of Fisheries and
Aquatic Sciences 54: 1211-1234.
73
Ratliff, D. E., and E. Schulz. 1999. Fisheries Program and the Pelton Round Butte
Hydroelectric Project (Oregon) 1956-1995. Portland General Electric
Company. Portland, Oregon.
Riehie, M. D. and J. S. Griffith. 1993. Changes in habitat use and feeding
chronology of juvenile rainbow trout (Oncorhynchus mykiss) in fall and the
onset of winter in Silver Creek, Idaho. Canadian Journal of Fisheries and
Aquatic Sciences 50: 2119-2128
Riehle, M.D., W. Weber, A. Stuart, S. Theisfeld, and D. Ratliff. 1997. Progress
report of the multi-agency study of bull trout in the Metolius River System,
Oregon. Proceedings of the Friends of the Bull Trout Conference, May 1994.
Calgary, Alberta.
Riehle, M. 2000. Habitat availability and limiting factors for anadromous fish
habitat upstream of Pelton Round butte Project dams - Progress Report. In
Portland General Electric Pelton Round Butte Project, Annual Fisheries
Workshop, 2001. Portland General Electric, Portland, Oregon.
Reinhardt, U. G. and M. C. Healey. 1997. Size-dependent foraging behavior and
use of cover in juvenile coho salmon under predation risk. Canadian Journal
of Zoology 75: 1642-1651.
Reisenbichler, R. R., J.D. McIntyre, and R. J. Hallock. 1982. Relation between size
of Chinook salmon (Oncorhynchus tshawytscha), released at hatcheries and
returns to hatcheries and ocean fisheries. California Fish and Game 68: 57-59.
Resh, V. H., and E. P. McElravy. 1993. Contemporary quantitative approaches to
biomonitoring using benthic macroinvertebrates. Pages 159-194 in D, M,
Rosenberg and V. H. Resh, editors. Freshwater Biomonitoring and Benthic
Macroinvertebrates. Chapman and Hall, New York, New York.
Roni P, and T.P. Quinn. 2001. Density and size ofjuvenile salmonids in response to
placement of large woody debris in western Oregon and Washington streams.
Canadian Journal of Fisheries and Aquatic Sciences 58: 282-292.
Roper, B. B., D. L. Scarnecchia, and T. J. La Man. 1994. Summer distribution and
habitat use by chinook salmon and steelhead in a major basin of the south
Umpqua river, Oregon. Transactions of the American Fisheries Society
123:298-30.8
Smock, L. A. 1996. Macroinvertebrate movements: drift, colonization, and
emergence. Pages 371 - 390 in F. R. Hauer and G. A. Lamberti, editors.
Methods in Stream Ecology. Academic Press, San Diego, California.
74
Schindler, D. E. 1999. Migration strategies of young fishes under temporal
constraints: the effect of size-dependent overwinter mortality. Canadian
Journal of Fisheries and Aquatic Sciences 56(suppl. 1): 61-70.
Schulz, E. 2002. Spring Creek Hatchboxes Progress Report 2001. In Portland
General Electric Pelton Round Butte Project, Annual Fisheries Workshop,
2002. Portland General Electric, Portland, Oregon.
Shirvell, C.S. 1990. Role of instream rootwads as juvenile coho salmon
(Oncorhynchus kisutch) and steelhead trout (0. mykiss) cover habitat under
varying streamfiows. Canadian Journal of Fisheries and Aquatic Sciences 47:
852-861.
Shirvell, C. S. 1994. Effect of changes in streamfiow on the microhabitat use and
movements of sympatric juvenile coho salmon (Oncorhynchus kisutch) and
Chinook salmon (Oncorhynchus tshaiiytscha) in a natural stream. Canadian
Journal of Fisheries and Aquatic Sciences 51: 1644-1652.
Smith, J. J. and H. W. Li. 1983. Energetic factors influencing foraging tactics of
juvenile steelhead trout (Salmo gairdneri). Pages 173 - 180 in D.L. G Noakes
et al. editors. Predators and Prey in Fishes. Dr. W. Junk, Publishers, The
Hague, Netherlands.
Tyler, J. A. and J. F. Gilliam. 1995. Ideal free distribution of stream fish: a model
and test with minnows, Rhinichthys atratulus. Ecology 76: 580-592.
Warren, C. E. and G.E. Davis. 1967. Laboratory studies on the feeding,
bioenegetics, and growth of fish. Pages 175-214 in S.D. Gerking, editor. The
biological basis for freshwater fish production. Blackwell Scientific
Publications, Oxford.
Webb, P.W. 1978. Partitioning of energy into metabolism and growth. Pages 184214 in S.D. Gerking, editor. Ecology of freshwater fish production. John
Wiley and Sons, New York.
Werner, E. E., G. G. Mittelbach, D. J. Hall, and J. F. Gilliam. 1983. Experimental
tests of optimal habitat use in fish: the role of relative habitat profitability.
Ecology 64(6): 1525-1539.
Werner, E. E., J. F. Gilliam, D. J. Hall, and G. G. Mittelbach. 1983. An
experimental test of the effects of predation risk on habitat use in fish.
Ecology 64(6): 1540-1548.
75
APPENDIX A: Smolt Production Estimates
Over the past two decades, quantitative habitat surveys have been performed
on all streams in the Metolius Basin potentially available to anadromous fish. These
data were obtained from the Deschutes National Forest and the Confederated Tribes
of the Warm Springs of Oregon and combined with density estimates from the six
study reaches to create population estimates for the entire basin. Maximum densities
observed in 2002 or 2003 fall snorkel surveys were used to generate estimates, as I
felt that fall was the best indicator of the numbers of juvenile Chinook salmon that
have survived through the growing season.
Similarity Codes
The six study reaches examined in this study represent five of the sixteen
streams in the Metolius Basin (two study reaches were located in the Metolius River).
Each of the remaining eleven streams in the basin was assigned a similarity code,
based on water temperature, habitat availability, and the author's knowledge of the
streams in the Metolius Basin (Table Al).
Density estimates from the most similar study reach were used to generate
population estimates. Canyon Creek and the Metolius Mainstem were typical of the
majority of habitat in the Metolius Basin, and therefore were the most commonly
used similarity code. Lake Creek was used for the smaller streams in the Basin,
including Brush Creek, Abbott Creek, and First Creek. Spring Creek and Heising
Spring are unique spring riffle streams, and were not similar to any other streams in
the basin.
76
Appendix Table Al. Similarity code assignments of streams in the Metolius River
Basin.
Similarity
Code
Assigned Streams
Canyon Creek
CY
Bear Valley Cr., Cabot Cr., Candle Cr., Canyon
Cr., Jack Cr., Jefferson Cr., Link Cr., Roaring Cr.,
Whitewater River
Metolius Mainstem
MM
Metolius River, reaches 1-7
Metolius Headwaters
MH
Metolius River, reach 8
Lake Creek.
LK
Abbott Cr., Brush Cr., First Cr., Lake Cr.
Spring Creek
SP
Spring Creek
Heising Spring
HS
Heising Spring
Study Stream
Habitat Data
Habitat data for the sixteen streams potentially available to anadromous fish
was compiled from stream surveys collected by the Deschutes National Forest and the
Confederated Tribes of Warm Springs between 1989 and 2002 (Appendix Table A2).
If more than one survey existed for a stream, the most recent data were used. For
each reach, data were compiled on the lengths and areas of pool, riffle, and side
channel habitats. The amount of available edge habitat was calculated by multiplying
the length of available habitat by two, to represent both banks of the streams. Area
estimates were generated by multiplying the length of habitat units by their average
widths. For purposes of comparison, all habitat data were converted into metric units
(meters and square meters). Surveys before 1996 included three categories of main
channel habitat: pools, riffles, and glides. For this study, glides were lumped into the
riffle category. Data on microhabitat patches (pocket pools) was available only for
surveys conducted on the mainstem of the Metolius River.
77
Appendix Table A2. Habitat in all streams in the Metolius Basin potentially available
to anadromous fish. Data compiled from habitat surveys by the Confederated Tribes
of the Warm Springs Reservation of Oregon (Whitewater River) and Deschutes
National Forest (all other streams).
78
Appendix Table A2. Habitat in all streams the Metolius Basin.
Pool
Length*
362
Pool
Area**
Riffle
Length
4424
2144
Riffle
Area
23656
6402
6187
585
28596
7194
7057
28433
21501
22681
4145
5174
Stream
Year reach Length
1989
1936
Abbott Creek
1
4960
1989
2
2157
0
Abbott Creek
0
1801
1
1595
Bear Valley Creek
1990
2332
464
156
Bear Valley Creek
1990
2
527
173
648
4596
713
Brush Creek
1989
1
4773
115
1845
Brush Creek
1989
2
0
1986
0
2905
Brush Creek
1989
53
129
3
2959
6491
4932
Cabot Creek
1996
1
7472
980
2091
Candle Creek
1995
1
2537
147
1513
2427
Candle Creek
1995
2
3096
5352
573
1044
993
Candle Creek
1995
3
1290
250
4
478
1383
Candle Creek
1996
1861
1667
1883
815
Candle Creek
1996
138
373
5
953
24033
6112
Canyon Creek
1989
1
14912
4767
3423
3875
10110
1989
2
4623
Canyon Creek
2688
1500
11859
4022
1989
45
139
Canyon Creek
3
2033
8472
1989
2871
7619
Canyon Creek
4
2673
2475
10943
4530
1022
Canyon Creek
1989
5
2464
399
First Creek
1989
1
5853
Reach I of First Creek dries up each summer
First Creek
15554
1989
2
8297
11165
4705
3377
4460
First Creek
1989
3
2431
2101
333
707
10897
Heising Spring
1
1047
1997
525.78
0
0
Jack Creek
29102
1995
1
6194
4193
1183
8210
Jack Creek
2001
1428
21514
2
2524
16012
1096
2001
1029
Jack Creek
3
179
91
87
964
1996
Jefferson Creek
1
2130
438
3000
2562
18816
Jefferson Creek
1996
2
174
2615
18899
2792
1293
Jefferson Creek
1996
3
5477
36291
5941
460
3066
11468
Jefferson Creek
1996
4
1677
1677
125
836
Jefferson Creek
1996
5
1850
14385
1957
48
267
Lake Creek
2002
1
1931
1275
5636
2491
11009
Lake Creek
2002
4205
2
1287
1365
997
3071
Lake Creek
2002
3
4345
5892
17432
2451
7243
Lake Creek
2002
4
6079
11632
3862
1375
2636
2002
Lake Creek
5
5964
12631
3862
1692
3571
Lake Creek
2002
6
2092
845
14474
3928
3109
Link Creek
1997
1
5844
888
280
587
3100
Metolius River
1991
1
960884
25339
2793
56043
47885
1991
Metolius River
1.1
16283
215897
8430
576
7638
1989
Metolius River
8472
8142
215897
2
288
7638
Metolius River
2000
2496
1592
23799
3381
50544
2
Metolius River
2000
5699
120416
3
4320
2497
52765
Metolius River
2000
4
80540
3968
25645
5840
1859
Metolius River
2000
43539
5
1899
507
8463
2606
Metolius River
7710
2000
565
981
6
149
1175
Metolius River
2000
1185
13755
72139
7
4051
6218
Metolius River
2000
2377.14
4457
54630
8
110
1356
1995
Roaring Creek
1
1746
1495
18750
59
745
1995
Roaring Creek
2
1301
10
1147
57
6251
Spring Creek
1997
1100
1
596
82
892
12020
* All lengths are in meters. **A11 areas are in square meters
Side Chan
Length
Side Chan
Area
174
928
45
232
0
386
0
0
1532
3079
926
194
305
0
2576
1840
150
351
553
15
68
0
62
0
0
864
299
99
46
256
0
1384
1013
20
440
604
224
0
2
811
983
90
363
181
443
149
425
97
214
348
270
70
230
139
102
102
51
18
444
236
686
0
699
187
194
143
6
741
0
NA
5631
2756
197
1060
402
1705
405
1175
430
653
1031
517
142
1070
642
2038
1348
1348
268
9382
3251
11455
0
8113
2292
2431
780
NA
79
Density Estimates for Habitat in Sampled Stream Reaches.
Maximum fall density estimates for each of the seven habitat classifications in
the six sampled stream reaches are presented in Appendix Table A3. For raw
numbers and density calculations for all seasons, see Appendix Tables Cl - C6.
Appendix Table A3. Maximum fall juvenile Chinook salmon density estimates
(fishlm2) for subunits in sampled stream sections in the Metolius River Basin.
Pools
Study Reach
Side Channels
Riffles
MicroHab
patches
Middle
Edge
Middle
Edge
Middle
Edge
Canyon Creek
0.0034
0.3871
0.0005
0.0200
0
0
0.1592
Lake Creek
0.1873
2.0789
0.0388
0.7317
0.7407
0.2264
0.2222
Metolius Headwaters
N/A
N/A
0.0363
0.0400
N/A
N/A
0.0386
Metolius Mainstem
0.0015
0.1481
0
0.0615
0.0051
0
0.0099
0.0250
0
0
0.0050
0.186
0
0
0.0372
Spring Creek
0.1217
0.0017
0
Heising Spring
N/A
N/A
0.0
* N/A indicates habitat type was not sampled in study reach
Study Reach Smolt Production Estimates
Data on the available habitat in each study reach (Appendix Table A2) were
combined with maximum fall density calculations (Appendix Table A3) to generate
smolt population estimates for each study reach (Appendix Table A4). The Metolius
Headwaters and Lake Creek are potentially the best reaches in terms of smolt
production, each supporting in excess of 2,000 smolts per kilometer of stream. Lake
Creek, because it is longer, was estimated to support about 50,000 fish. The Metolius
Headwaters is less than a kilometer in length, and could produce an estimated 2240
smolts. Canyon Creek and the Metolius Mainstem, which are indicative of the
majority of the habitat in the Metolius Basin, could potentially support and estimated
193 and 139 fish per kilometer, respectively. Spring Creek and Heising Spring,
80
which are each less than a kilometer in length, and were estimated to produce 157 and
195 smolts, respectively.
The average weights ofjuvenile Chinook salmon collected in fall 2003 were
combined with the estimated numbers to generate an estimated biomass of juvenile
Chinook salmon (kg/km) that could be supported in each of the study reaches. The
Metolius Headwaters was estimated to support the greatest biomass of juvenile
Chinook salmon, at 36.2 kg/km of stream. Lake Creek was second at 18.0 kg/kin,
and the other four reaches were estimated to support between 1.6 to 2.8 kg/km.
Appendix Table A4. Chinook smolt production estimates for the streams that
contained the six study reaches in the Metolius River Basin.
Estimated
Length of
Estimated
Study Reach
Fall Biomass (mean
stream* (km)
Fall Numbers
(g)**)
Metolius
Headwaters
0.79
Lake Creek
2 1.1*
Heising Spring
0.52
195 (372 fish /km)
1.6 kg/km (4.4)
Spring Creek
0.55
157 (282 fish / 1cm)
2.8 kg/km (10.2)
Canyon Creek
18.6*
3,593 (193 fish / 1cm)
1.6 kg/lun (8.4)
Metolius Mainstem
557*
7,738 (139 fish / kin)
1.8 kg/km (12.75)
2,240 (2841 fish / km)
49,950 (2369 fish /
36.2 kg/km (12.75)
18.0 kg/kin (7.6)
* Stream length is greater than study reach length for Canyon Creek, Lake Creek, and Metolius
Mainstem
** Mean weights are from fall 2003 fish collection.
Basin-Wide Smolt Production Calculations
Estimates of the number of smolts that could be potentially produced in each
of the streams in the Metolius basin were generated by multiplying the available
amount of each habitat type in each stream (Appendix Table A2) by the densities
81
from the corresponding similar study reach (Appendix Table Al). Pool, riffle, and
side channel edge densities were multiplied by the length (m) of those habitats in each
reach, and multiplied by two to account for habitat on both banks. Pool, riffle, and
side channel mid-channel densities were multiplied by the estimated area (m2) of each
of those habitats.
Numerical population estimates and a percentage breakdown of the total
potential contribution of each stream in the entire basin are presented in Appendix
Table A5. I estimate that a total ofjust over 128,000 Chinook smolts could be
produced by the habitat in the Metolius Basin.
Appendix Table A5. Juvenile Chinook salmon smolt population estimates for pooi, riffle, and side channel habitats in all streams
available to anadromous fish in the Metolius River Basin, based on maximum fall density estimates.
# of
Similarity
Pool
Pool
Riffle
Riffle
Side
Side
Total
Percent
Stream
Subunit
Reaches
Code
Mid
Edge
Mid
Edge
Mid
Edge
Estimate of total
Abbott Creek
2
LK
362.6
1505.5 1166.8 9611.5
721.0
85.4
NA
13452.8
10.5%
Bear Valley
2
CY
7.6
493.0
3.4
78.3
0.0
0.0
NA
582.3
0.5 %
Creek
Brush Creek
3
LK
157.7
697.7
1663.3
13677.4
Candle Creek
5
CY
33.7
1228.3
28.0
Cabot Creek
I
CY
16.7
758.4
14.4
Canyon Cr
First Creek
5
CY
95.9
3035.6
33.1
308.4
259.6
428.2
3
LK
2223.7
15426.4
776.9
Jack Creek
Jefferson Creek
3
85.3
1832.4
26.2
28.6
963.7
50.6
8
CY
CY
HS
LK
CY
MHJMM
2
CY
2.7
1
SP
108.6
3
CY
41.5
Heising Spring
Lake Creek
Link Creek
Metolius River
Roaring Creek
Spring Creek
Whitewater R.
Total
5
1
6
1
0.0
4885.9
10.5
289.8
0.0
0.0
17949.2 2771.1
216.6
3.0
1669.5 1981.0
54.0
12.7
0.0
20.6
508.4
77.0
286.0
0.0
28.1
0.0
0.0
0.0
0.0
9959.1
548.6
101.4
228.5
567.2
195.4
18219.6
23.5
0.0
0.0
0.0
0.0
0.0
0.0
2846.0
0.0
278.0
0.0
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
194.6
0.0
0.0
0.0
0.0
NA
5648.6
105.7
27.5
327.4
16510.1
12.9%
1598.4
1.2 %
1049.2
0.8 %
3592.8
29036.3
2.8 %
22.6 %
2172.3
1.7 %
1610.2
1.3 %
195.4
0.2 %
46949.7
36.6 %
253.5
0.2%
195.5
9978.9
7.8 %
175.1
0.0
NA
NA
156.7
0.1 %
0.1 %
NA
NA
954.3
0.7 %
0.0
128268.1
83
Smolt Population Estimates - Discussion
The population estimates generated in this study (Appendix Table A5) provide a
rough outline for distribution of Chinook fry for future release efforts. However, there
are several reasons that the estimated numbers and biomass of juvenile Chinook salmon
in this study may potentially underestimate or overestimate the number of Chinook
salmon that could be supported by the Metolius Basin. The primary concern was that of
saturation: due to limitations in the number of adults that were spawned, I don't think I
had enough fish to saturate the habitat. Also, the methods of release most likely did not
allow for the maximum use of the habitat. I released fish into only five locations around
the basin, and those releases were done in relatively short stretches (-200m) of stream.
In future fry release efforts I would recommend the wide dispersal of fry throughout the
basin, both in terms of number of streams and the habitats in those streams. I would
suggest releasing the fry in small numbers (- 20 to 50 at a time) in slow water over
several miles of stream. Because these will be fry produced in a hatchery or hatch box
environment, they should be helped as much as possible to locate adequate habitat for
rearing, specifically edge habitat habitats with access to cover that provide refuge from
velocity.
My maximum population estimates (-128,000 juveniles) are based on the
observations of fish that were not naturally produced in the Basin. The fish that were
used in this study were of hatchery origin, and were released in the basin into unfamiliar
habitat, often in fairly quick water. These fry had been reared in a stable hatchery or
hatch box environment, and until release, had not been exposed to the harshness of a
natural stream environment. Naturally produced Chinook fry may distribute themselves
84
in different patterns or may have dissimilar survival rates. An important direction of
future research will be the comparison of my observations of distribution and growth
with those of naturally produced juvenile Chinook in the Metolius Basin.
It is also important to consider that the estimates generated in this study relate to
the number of successful smolts and returning spawners for the Metolius Basin only.
Some of the adult fish passed over the Pelton Round Butte Project could potentially
migrate up one of the other tributary streams (Crooked River, Deschutes River, or Squaw
Creek), or experience mortality before successfully spawning. Incorporating currently
available spawning and rearing habitat in the Deschutes River and Squaw Creek would
results in more accurate predictions of production capacity, and would undoubtedly
increase estimates of run size. Additionally, if passage facilities are successfully
implemented at the Opal Springs area in the Crooked River, more spawning and rearing
habitat would be made available to migrating salmon, and the numbers that could be
supported would increase.
85
APPENDIX B: Microhabitat Patch Utilization
Microhabitat Patches - Microhabitat patches, which in this study are considered a
type of habitat subunit, were identified by their formative feature and associated cover
types. The formative feature is the dominant structure that creates the patch, and
typically created a refuge from velocity. Five formative features were identified: natural
wood (wood that had fallen naturally into the stream), placed wood (wood that had been
physically placed in the stream at part of habitat restoration efforts), bank alcoves (areas
of slow velocity along the banks), emergent vegetation, and boulders. Associated cover
types were features that provided an element of cover for the microhabitat patch, but
were not the primary cause of formation. These cover types included natural wood,
placed wood, boulders, emergent vegetation, overhanging vegetation, undercut banks,
and bank alcoves.
Patches with formative features of natural wood, emergent vegetation, and bank
alcove were present in all of the study reaches. Patches formed by placed wood are
present in all reaches except Lake Creek, and overhanging vegetation and boulder
patches were present only in the Metolius Mainstem study reach. All associated cover
types were present in every study reach.
The presence or absence of fish was used the basis for analysis of use of
microhabitat patches. Natural wood was the most numerous type of formative subunit
and had the highest juvenile Chinook salmon occupancy rate of 24.9 % (Appendix Table
Bi). Placed wood, which is the formative type that can be directly attributed to habitat
restoration efforts, was occupied by juvenile Chinook salmon in only 12.9% of
observations. However, 80% of observations of placed wood patches did have at least
86
one fish (which was not necessarily a juvenile Chinook). Among the other patch types,
emergent vegetation had juvenile Chinook salmon in 15.5% of observation, and bank
alcoves had a juvenile Chinook salmon occupancy rate of 14.1%.
Among associated cover types, overhanging vegetation and natural wood were the
two most important and were occupied in 26.5% and 25.2% of observations by juvenile
Chinook salmon, respectively (Appendix Table B2). Placed wood was very important in
terms of all fish, and was occupied in 81.1% of all observations by at least one fish of any
species. However, they were only occupied by juvenile Chinook salmon in 13.5% of
observations, about half that of natural wood patches. Microhabitat patches formed by
boulders or associated with undercut banks appeared to be the least important for juvenile
Chinook salmon, as zero fish were observed in these patch types.
87
Appendix Table B 1. Habitat occupation based on the presence or absence ofjuvenile
Chinook salmon (JCS) and other community fishes by formative microhabitat patch types
from all observations within the Metolius Basin.
#with
%
%
Formative
# of
# with
# Obser- # with
with
with
fish, no
Patch Type
subunits vations
no fish
JCS
fish
JCS
Natural
55
510
124
75.7
24.9
127
259
Wood
Emergent
Vegetation
44
348
54
181
113
67.5
15.5
Bank
Alcove
29
240
34
67
139
42.0
14.1
Placed
Wood
26
210
27
141
42
80.0
12.9
Boulder
2
12
0
1
11
8.3
0.0
Appendix Table B2. Habitat occupation based on the presence or absence of juvenile
Chinook salmon (JCS) and other community fishes by associated microhabitat patch
types from all observations in the Metolius Basin.
%
%
Associated
# Obser# with
# with fish,
# with
with
with
Patch Type
vations
JCS
no fish
no JCS
fish
JCS
Overhanging
204
54
101
49
76.0
26.5
Vegetation
Natural Wood
600
151
295
154
74.3
25.2
744
124
351
269
63.8
16.7
480
75
239
166
65.4
15.6
Boulder
42
6
19
17
59.5
14.3
Placed Wood
222
30
150
42
81.1
13.5
Undercut Bank
36
0
10
26
27.8
0.0
Bank
Alcove
Emergent
Vegetation
88
APPENDIX C: Snorkel Observations
Figures Cl through ClO display seasonal day and night snorkel data from 2002
and 2003. For each stream, juvenile Chinook counts (total number of juvenile Chinook
salmon) and densities (juvenile Chinook salmon I m2) are shown. For all graphs, the
direction of stream flow is from left to right. X - axis (study sites) is not to scale.
89
LAKE CREEK
LK Day Counts 2002
LK Day Counts 2003
250
250
Spring
200
o FaIl
150
'
200
Surmr
C,
150
C,
No
Data
E
50
2002
rI I
0
LK7
LK6
LK5
100
No
Data
2002
50
-
LK4
0
LK3
LK2
LK1
LK7
LK6
o
o Spring
200
Surmr
o Fall
150
100
LK2
LK1
Suniier
100
Data
50
Spring
o FaIl
150
No
E
z
LK3
250
200
'
LK4
LK Night Counts 2003
LK Night Counts 2002
250
0
LK5
50
2002
0
0
LK7
LK5
LK2
LK7
LK5
LK2
Appendix Figure Cl. Day and night counts ofjuvenile Chinook salmon in the Lake
Creek study reach, 2002 and 2003.
LK Day Densities 2002
LK Day Densities 2003
0.5
0.5
E 0.4
o Fall Density
0
' 0.2
No
No
Data
2002
Data
2002
a)
0.4
Surr1Tr Density
x 0.3
U)
Spring Densfty
o Spring Density
(s
0
LK6
LK7
LK5
LK4
0.3
0.2
-LK3
0.1
0
LK2
LK1
LK Night Densities 2003
LK Night Densities 2002
0.5
0
0.5
o Spring Density
0.4
- U Surrrrr Density
0.4
0.3
-.
0.3
0.2
.
U)
Surrrrer Density
o Fall Density
0 FaIl Densty
No
0.2
Data
C
0.1
0.1
2002
0
0
LK7
LK5
LK2
Appendix Figure C2. Day and night densities ofjuvenile Chinook salmon in the Lake
Creek study reach, 2002 and 2003.
90
METOLIUS HEAD WATERS
MH Day Counts 2003
MH Day Counts 2002
200
200
O Spring
z 150
Sunimr
0
o Spring
Surmr
o Fall
150
o Fail
100
100
50
50
0
0
MH5
M-14
M-I1
MH2
Fv}13
LI
MH4
MH5
MH Night Counts 2002
MH1
200
o
i 150
Spring
Surrrrr
0
o Spring
150
Sunir
o FaIl
100
E
MH2
MH Night Counts 2003
200
z
MH3
100
1
No
Data
50
50
Spring
2002
0
0
MH4
o Fail
MH4
MH1
MH1
Appendix Figure C3. Day and night counts ofjuvenile Chinook salmon in the Metolius
Headwaters study reach, 2002 and 2003.
MH Day Densities 2002
MH Day Densities 2003
0.12
0.12
o Spring Density Surmr Density
o Fall Density
0.1
E
=
0.08
0.06
0.1
0.08
0.06
>,
0.04
0.04
C
0.02
rl
0
MH5
MH4
0.02
0
M-13
I-I2
M-l1
M-15
Sumner Density
o Fall Density
riFLfl,
MH3
MH1
v1-t2
0.12
o Spring Density
0.1
Sunrr Density
0.08
>
M-14
Spring Density
MH Night Densities 2003
MH Night Densities 2002
0.12
ii
o
o Fall Density
- 0.06
No
Data
Spring
2002
0.04
0.02
0
o
0.1
Spring Density
Surriner Density
0.08
o
0.06
FaIl Density
0.04
0.02
0
ryI
MH4
MH1
Appendix Figure C4. Day and night densities ofjuvenile Chinook salmon in the Metolius
Headwaters study reach, 2002 and 2003.
91
CANYON CREEK
CYDayCounts 2002
CYDay Counts 2003
50
0
50
40
o Spring
30
SurrtTer
o FaIl
30
C'
.0
E
No
Data
2002
i
z
No
Data
2002
0
0 Spring
U Surrtrer
0 Fall
40
20
IL
10
0
CY7 CY6 CY5 CY4 CY3 CY2 Cvi
CY7
CY6
CY Night Counts 2002
o Spring
O Surrner
o Fall
0
.0
20
E
z
CY2
Cvi
50
40
30
CY3
CY4
CY Night Counts 2003
50
C'
CY5
-
40
30
20
Not
Surveyed
2002
10
0
0
CY4
CY3
CY4
CY1
CY3
CY1
Appendix Figure C5. Day and night counts ofjuvenile Chinook salmon in the Canyon
Creek study reach, 2002 and 2003.
CY Day Densities 2002
0.03
-
0.025
E
?
CYDay Densities 2003
0.03
0 Spring Density
0.02
o Fall Density
!. 0.015
-
No
Data
2002
0.01
0.005
No
Data
2002
0
flr,rl
0.005
0
CY7 CY6
CY Night Densities 2002
0.03
0.025 - a Spring Density
:
0.01
C
0.005
CY5 CY4 CY3 CY2 Cvi
CY Night Densities 2003
0.03
. 0.015
>'
o Fall Density
0.01
CY7 CY6 CY5 CY4 CY3 CY2 CY1
I
Sun-rrer Density
0.02
0.015
>..
0.02
o Spring Density
0.025
Surmr Density
U Sunirer Density
Surrrrer Density
0.02
a Fall Density
--
o Spring Density
0.025
o Fall Density
0.015
Not
0.01
Surveyed
2002
0.005
0
0
CY4
CY3
Cvi
CY4
CY3
CY 1
Appendix Figure C6. Day and night densities ofjuvenile Chinook salmon in the Canyon
Creek study reach, 2002 and 2003.
92
METOLIUS MAINSTEM
MM Day Counts 2002
MM Day Counts 2003
30
x
0
0
a,
.0
30
O Spring
25
Surmer
o FaIl
20
15
E
10
z
5
o Spring
25
Surrner
20
o Fall
15
10
ri-ra fl-
0
MM5
MM4
MM3
M2
5
0
MM5
MM1
MM Night Counts 2002
MM1
30
o Spring
o Spring
25
Sunr
x0 20
Mtv2
MM3
MM Night Counts 2003
30
25
MM4
o FaIl
Surrner
20
:a, 15
o FaIl
15
.0
No
E 10
I-i
0
10
I
Data
Z5
5
0
MM4
MM3
Appendix Figure C7. Day and night counts ofjuvenile Chinook salmon in the Metolius
Mainstem study reach, 2002 and 2003.
MM Day Densities 2002
MM Day Densities 2003
0.01
0.01
O Spring Density
0.008
I 0.006
o FaIl Density
C.)
o Spring Density
0.008
SumtEr Density
SumTer Density
0.006
0.004 -
0.004
0.002 -
0.002
-
o Fall Density
U)
0
flflr
0
MM5
MM4
MM3
MM2
MM1
MM5
MM Night Densities 2002
MM4
MM3
MtVQ
MM1
MM Night Densities 2003
0.01
o
0.008
0.006
Spring Density
Surmer Density
o
FaIl Density
0.004
0.002
0
MM4
Mv
M3
Appendix Figure C8. Day and night densities ofjuvenile Chinook salmon in the Metolius
Mainstem study reach, 2002 and 2003.
93
SPRING CREEK
SP Day Counts 2003
SP DayCounts 2002
120
I
120
o Spring
100
Surrner
C-) 80
o Fall
o Fall
60
40
z 20
20
0
0
IT
SPI
SP2
SP3
SP Day Densities 2002
0.14
o Spring Density
0.12
E
Surrrner Density
0.08
[3 Fall Density
0.06
0.04
a
0.02
0
Spi
SP2
SP Day Densities 2003
0.14
- C.,'
o Spring Density
0.12
-
Surrnr Density -
0.1
o Fall Density
0.08
0.06
I
SP3
-
Suriir
80
U:
SP3
0 Spring
100
0.04
0.02
0
SF2
SP3
SP1
SF2
Spi
Appendix Figure C9. Daytime counts and densities ofjuvenile Chinook salmon in the
Spring Creek study reach, 2002 and 2003.
HEISING SPRING
HS Day Counts 2002
I
C-)
'4-
0
E
z
HS Day Counts 2003
140
140
120
100
80
60
o Spring
Surrnr
120
100
80
o FaIl
60
40
20
40
20
0
0
HS3
0.14
C.)
(I,
HS1
HS3
HS Day Densities 2002
HS2
HS1
HS Day Densities 2003
0.14
0.12
I
HS2
D Spring Density
Surmer Density
0.1
o
0.08
FaU Density
0.12
0.1
0.08
' 0.06
0.06
0.04
0.04
0.02
0.02
0
0
HS3
HS2
HS1
HS3
HS2
HS1
Appendix Figure ClO. Daytime counts and densities ofjuvenile Chinook salmon in the
Heising Spring, 2002 and 2003.
94
Appendix Table Cl. Raw numbers of juvenile Chinook salmon observed in habitat
subunits during spring snorkel surveys in the Metolius River Basin, 2002 and 2003.
Spring Day 2002
MH
Pools
Stream
cy
HS
LK
MH
MM
SP
Totals
Middle
0
NA
0
NA
0
0
0
Edge
43
NA
Riffles
Middle Edge
o
0
8
0
NA
0
0
0
0
0
0
51
5
12
5
3
4
0
29
Side Pools
Middle Edge
Side Riffles
Middle Edge
0
0
0
NA
NA
NA
0
0
0
0
NA
NA
NA
NA
1
NA
0
0
0
NA
NA
NA
0
NA
0
0
0
1
Patches
Pool Riffle
31
7
Total
87
NA
0
NA
80
92
1
99
16
15
NA
47
120
322
14
102
35
120
450
Spring Day 2003
MH
Stream
cy
Pools
Middle Edge
Riffles
Middle Edge
Side Pools
Middle Edge
0
NA
0
7
0
0
0
0
NA
0
101
NA
NA
81
1
0
1
MH
MM
SP
NA
NA
0
17
4
NA
NA
12
1
0
1
0
0
0
0
0
12
89
17
0
107
0
Totals
0
HS
LK
Side Riffles
Middle Edge
0
0
NA
NA
2
0
NA
NA
Patches
Pool Riffle
15
8
NA
56
23
203
9
14
313
0
NA
1
2
0
0
NA
NA
NA
1
0
3
17
Total
30
157
108
224
26
14
559
Spring Night 2002
MH
Stream
cy
LK
MH
MM
Totals
Pools
Middle Edge
Riffles
Middle Edge
0
0
3
10
0
0
0
NA
NA
0
6
0
0
0
0
13
0
0
7
1
Side Pools
Middle Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Side Riffles
Middle Edge
Side Pools
Middle Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Side Riffles
Middle Edge
Patches
Pool Riffle
0
0
0
NA
NA
NA
NA
NA
NA
0
0
Total
0
3
0
7
10
NA
31
37
5
0
34
59
5
5
Spring Nicjht 2003
Stream
cy
LK
MH
MM
Totals
Pools
Middle Edge
2
6
0
0
8
Riffles
Middle Edge
17
0
1
128
0
13
0
12
16
0
16
66
157
1
81
MH
Patches
Pool Riffle
0
0
0
0
0
NA
NA
NA
NA
0
0
0
NA
16
16
1
5
101
3
110
Total
21
152
183
32
388
95
Table C2. Densities ofjuvenile Chinook salmon in habitat subunits during spring snorkel
surveys in the Metolius River Basin, 2002 and 2003.
2002 SprinQ Day Density
Pools
Riffles
Stream Middle Edge Middle Edge
CY
0
0.58
0
0.1
HS
NA
NA
0
0.32
LK
0
0.1
0
0.12
MH
NA
NA
0
0.048
MM
0
0
0
0.059
SP
0
0
0
0
Totals
0
0.23
0
0.097
2003 SDrinQ Day Density
Pools
Riffles
Stream Middle Edge Middle Edge
cy
0
0.06
0
0
HS
NA
NA
0
2.693
LK
0
0.78
0
0.018
MI-I
NA
NA
0.002 0.064
MM
0.002
0.01
0
0.015
SP
0
0
0
0
Totals
1E-03
0.3
7E-04 0.342
Side Pools
Middle
Edge
NA
NA
NA
NA
0
0
NA
NA
0
0
0
0
0
0
Side Pools
Middle
Edge
NA
NA
NA
NA
0
0.4444
NA
NA
0
0
0
0
0
0.0976
Side Riffles
Middle
Edge
0
0.6667
0
0
0
0
NA
0
NA
0
NA
0
NA
0.019
Side Riffles
Middle
Edge
0
0
0
NA
0
NA
0
0
0
0.1509
NA
0.0294
NA
0.0571
MH Patches
Pool
Riffle
0.15 0.0335
NA
0.1415
0
0.0066
NA
0.0619
0.037 0.0173
NA
0.2017
0.066 0.0808
MH Patches
Pool
Riffle
0.073 0.0383
NA
0.0991
0
0.1508
NA
0.127
0.005 0.01 04
NA
0.0235
0.024 0.0785
2002 Srinq Niqht Density
Pools
Middle Edge
0
0.25
Riffles
Middle Edge
0
0.1
0
1
NA
NA
NA
0
0
0
0
NA
0
NA
0.48
NA
0.311
Side Pools
Middle
Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
2003 SDrincl Niciht Density
Pools
Riffles
Stream Middle Edge Middle Edge
CY
0.001
0.32
0
0.057
LK
0.007
3.37
0
0.571
MH
NA
NA
0.006
2.64
MM
0
0.36
0
0.062
Totals
0.002
1.26
0.003 0.994
Side Pools
Middle
Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Stream
CY
LK
MH
MM
Totals
0.28
Side Riffles
Middle
Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Pool
NA
NA
NA
0.032
0.032
Side Riffles
Middle
Edge
NA
NA
0
0
NA
NA
NA
NA
0
0
MH Patches
Pool
Riffle
NA
0.0089
NA
0.2273
NA
0.1258
0.079 0.0233
0.079 0.1031
MH Patches
Riffle
0.0597
NA
0.0761
NA
0.0743
96
Table C3. Raw numbers of juvenile Chinook salmon observed in all habitat subunits
during summer snorkel surveys in the Metolius River Basin, 2002 and 2003.
Summer Day 2002
Stream
cy
HS
LK
MH
MM
SP
Totals
Pools
Middle Edge
4
36
NA
NA
89
NA
NA
4
24
0
0
121
38
2
Riffles
Middle Edge
Side Pools
Middle Edge
0
0
NA
NA
0
0
NA
NA
0
3
52
3
13
2
9
0
26
0
0
4
68
I
NA
45
0
0
NA
0
Side Riffles
Middle Edge
0
0
0
NA
0
NA
0
MH
Patches
Pool Riffle
0
0
0
NA
0
13
2
15
NA
NA
43
0
0
0
NA
NA
5
0
0
78
0
Total
56
18
160
78
4
34
350
Summer Day 2003
Stream
cy
HS
LK
MH
MM
SP
Totals
Pools
Middle Edge
Riffles
Middle Edge
0
0
11
15
NA
588
NA
2
32
0
0
0
77
125
0
47
206
0
0
25
624
15
3
2
0
2
0
20
Side Pools
Middle Edge
NA
NA
NA
NA
23
0
NA
NA
Side Riffles
Middle Edge
0
0
0
2
2
0
0
NA
19
5
13
NA
NA
NA
0
NA
0
0
0
0
0
7
0
0
NA
19
30
MH
Patches
Pool Riffle
0
NA
2
72
0
6
98
Total
30
22
755
199
0
40
1046
Summer Nicjht 2002
Pools
Riffles
Side Pools
Stream
Middle
Edge
Middle
Edge
cy
0
40
4
26
0
0
0
0
0
41
37
22
0
22
3
1
0
7
LK
MH
MM
Totals
0
3
Middle
NA
NA
NA
NA
NA
Edge
NA
NA
NA
NA
NA
Side Riffles
Middle
NA
Edge
NA
MH
Patches
Pool Riffle
NA
8
0
0
0
NA
NA
NA
NA
0
NA
0
3
32
Total
12
69
57
3
5
16
3
48
154
Summer Nicht 2003
Pools
Stream
Middle
cy
8
LK
MH
MM
155
0
5
Totals
168
Riffles
Edge
23
87
Side Pools
Middle
Edge
0
12
0
0
20
82
13
NA
123
102
Side Riffles
MH
Patches
Pool Riffle
NA
6
Edge
NA
NA
NA
NA
Middle
NA
0
0
0
NA
Middle
NA
NA
NA
NA
NA
NA
NA
NA
13
0
0
0
0
NA
4
4
1
Edge
NA
1
41
7
55
Total
37
275
124
29
465
97
Table C4. Density ofjuvenile Chinook salmon (fish/rn2) observed in all habitat subunits
during sunmier snorkel surveys in the Metolius River Basin, 2002 and 2003.
2002 Summer Day Density
Stream
CY
HS
LK
MH
MM
SP
Totals
Pools
Middle
Edge
0.00107 0.482
NA
NA
0.04749 0.026
NA
NA
0.00078
0
0.41 739
0
0.0112
0.172
Riffles
Middle
Edge
0
0.06
0.0008 0.3467
0.0421 0.0482
0.0012 0.416
0
0
0.0014 0.025
0.003 0.1503
Side Pools
Middle Edge
NA
NA
NA
NA
Riffles
Middle
Edge
0
0
0.0005
0.4
0.0531
0.055
0.01 72
0.032
0
0
0.0007
0
0.0089 0.064
Side Pools
Middle Edge
NA
NA
NA
NA
Side Riffles
Middle Edge
0
NA
0
0
0
0
0
NA
NA
NA
0
0
0
0
0
0
0
0
NA
NA
0
0
0
0
MH Patches
Pool
Riffle
0.0623
0
NA
0.0035
0.0984
0
NA
0.0269
0
0
NA
0.0084
0
0.0196
2003 Summer Day Density
Stream
CY
HS
LK
MH
MM
SP
Totals
Pools
Middle
Edge
0.00227 0.125
NA
NA
0.24639 0.308
NA
NA
0
0
0.43478
0.05015
0
0.16
0.681
0
NA
NA
0
0
0
0.06
0.087
0
Side Riffles
Middle Edge
0
0
0
0
0.258
0
NA
NA
0
0
NA
NA
0.015
0
2002 Summer Niqht Density
Pools
Riffles
Stream
Middle
Edge Middle
Edge
CY
0
0.086
0
0
LK
0.07346 1.083
0
0
MH
NA
NA
0.0082
0.12
MM
0.00038 0.207
0
0
Totals
0.0082 0.355 0.0035 0.0314
Side Pools
Middle Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Side Riffles
Middle Edge
NA
NA
2003 Summer NiQht Density
Pools
Riffles
Stream
Middle
Edge Middle
Edge
CY
0.00451 0.436
0
0
LK
0.19291 2.289 0.0354 0.5275
MH
NA
NA
0.0307
0.04
MM
0.0019 0.385
0
0
Totals 0.03226 0.988 0.0181 0.1595
Side Pools
Middle Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Side Riffles
Middle Edge
NA
NA
0
NA
NA
0
0
NA
NA
0
0
0
NA
NA
NA
NA
0
0
MH Patches
Pool
Riffle
0.01
0.0096
NA
0.0088
0
0.0852
NA
0.045
0
0
NA
0.003
0.0101
0.0246
MH Patches
Pool
Riffle
NA
0.1592
NA
0.1667
NA
0.0399
0.015 0.0388
0.015 0.048
MH Patches
Pool
Riffle
NA
0.0532
NA
0.0455
NA
0.0511
0.02 0.0543
0.02 0.0516
98
Table C5. Raw numbers ofjuvenile Chinook salmon observed in all habitat subunits
during fall snorkel surveys in the Metolius River Basin, 2002 and 2003.
Fall Day 2002
Stream
Pools
Middle Edge
cv
0
HS
LK
MH
MM
SP
NA
47
NA
0
15
NA
2
NA
0
0
Totals
48
17
1
Riffles
Middle Edge
1
1
0
0
6
0
0
0
0
101
0
7
48
52
Side Pools
Middle Edge
NA
NA
NA
NA
1
0
NA
NA
1
0
NA
NA
2
0
Side Riffles
Middle Edge
0
0
MH
Patches
Pool Riffle
0
3
Total
20
0
6
0
0
0
0
NA
0
7
105
NA
0
NA
0
NA
0
NA
NA
35
87
0
1
3
NA
3
3
0
0
49
224
Fall Day 2003
Stream
Cv
HS
LK
MH
MM
SP
Totals
Pools
Middle Edge
0
8
NA
NA
447
22
NA
NA
Riffles
Middle Edge
0
0
0
7
44
3
0
0
1
167
0
7
0
5
454
31
216
1
1
12
MH
Patches
Pool Riffle
Side Pools
Middle Edge
NA
NA
NA
NA
25
0
NA
NA
0
0
NA
NA
25
0
Side Riffles
Middle Edge
0
0
Side Pools
Middle Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Side Riffles
Middle Edge
NA
NA
0
0
NA
NA
NA
NA
0
0
Patches
Pool Riffle
NA
8
0
4
NA
13
Side Pools
Middle Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Side Riffles
Middle Edge
NA
NA
Patches
Pool Riffle
NA
2
0
0
NA
21
0
0
3
NA
NA
0
0
NA
NA
0
NA
0
NA
0
3
0
0
Total
4
8
28
548
14
181
1
3
14
41
782
1
Fall Niqht 2002
MH
Stream
CY
LK
Pools
Middle Edge
0
18
19
21
MH
MM
NA
Totals
19
NA
4
43
0
Riffles
Middle Edge
0
15
18
0
33
0
15
0
1
16
Total
26
74
31
2
2
9
2
27
140
Fall Niqht 2003
MH
Stream
cy
LK
MH
MM
Totals
Pools
Middle Edge
6
121
NA
14
79
NA
4
5
131
98
Riffles
Middle Edge
0
0
15
10
97
1
0
112
0
11
0
NA
NA
NA
0
0
2
Total
22
227
NA
NA
NA
NA
31
129
0
0
2
37
389
11
99
Table C6. Densities of juvenile Chinook salmon (fish/rn2) observed in all habitat
subunits during fall snorkel surveys in the Metolius River Basin, 2002 and 2003.
2002 Fall Day Density
Pools
Stream
Middle
Edge
CY
0
0.2007
HS
NA
NA
LK
0.02508 0.026
MH
NA
NA
MM
0.00019
0
SP
0
0
Totals 0.00444 0.0768
Riffles
Middle
Edge
5E-04
0.02
0
0.16
0.039
0
0.007
0
0
0
0
0
0.004
0.0234
Side Pools
Middle Edge
NA
NA
NA
NA
0.02963
0
NA
NA
0.0051
0
0
0
0.00578
0
Side Riffles
Middle
Edge
Side Pools
Middle
Edge
NA
NA
NA
NA
0.74074
0
NA
NA
0
0
0
0
0.07231
0
Side Riffles
Middle
Edge
0
0
0
0
0.22642
0
NA
NA
0
0
0
0
0
NA
NA
0
0
0
NA
NA
0
0
MH Patches
Riffle
Pool
0.01437
0
NA
0
0
0.0459
NA
0.02189
0.00115
0
0.00504
NA
0.01229
0
2003 Fall Day Density
Stream
CY
HS
LK
MH
MM
SP
Totals
Pools
Middle
Edge
0
0.0668
NA
NA
0.1873 0.2115
NA
NA
0
0.0149
0.12174
0
0.03649 0.1057
2002 Fall Niqht Density
Pools
Stream
Middle
Edge
CY
0
0.3871
LK
0.03489 0.875
MH
NA
NA
MM
0
0.1185
Totals
0.0038 0.4125
2003 Fall Niqht Density
Pools
Stream
Middle
Edge
CY
0.00339 0.2654
LK
0.15059 2.0789
MH
NA
NA
MM
0.00152 0.1481
Totals 0.02516 0.7871
Riffles
Middle
Edge
0
0
0
0.1867
0.055
0.03
0.023
0
0.002
0.009
0
0.0147
0.025
0.0384
Riffles
Middle
Edge
0
0
0.029
0.007
0.7317
0
0.0615
0.1675
0.005
0
Riffles
Middle
Edge
0
0
0.027
0.036
0.4396
0.04
0
0
0.02
0.135
0
0
NA
NA
0.05714
0
Side Pools
Middle
Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Side Riffles
Middle
Edge
NA
NA
0
0
NA
NA
NA
NA
Side Pools
Middle
Edge
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Side Riffles
Middle
Edge
NA
NA
0
0
0
0
NA
NA
NA
NA
0
0
MH Patches
Pool
Riffle
0
0
NA
0
NA
0
NA
0.03715
0.02623
0.00876
0.00115
0
0.01029
0.001 68
MH Patches
Pool
Riffle
NA
0.1592
0.22222
0.01619
0.01
0.01
0.01 55
0.02699
MH Patches
Pool
Riffle
NA
0.01774
NA
0.09091
NA
0.03861
0
0.0155
0
0.03468
100
APPENDIX D: Fish Communities
Appendix Figures Dl - D6 display the species of fish observed in day and night
snorkel surveys in each of the study reaches in 2002 and 2003. Red hues indicate adult
fish, and blue hues indicate juvenile fish. Species Codes are as follows: CHK = Chinook,
BUT Bull trout, BRT = Brown trout, BKT = Brook trout, RBT = Redband trout, WHF
= Mountain whitefish, LND = long nosed dace, SPD = speckled dace, COT = Cottidae
species (sculpins), KOK = Kokanee salmon. Kokanee salmon were present only in fall
surveys.
Metolius Headwaters Day 2002
Adult BRT
3, <1%
Adult BUT
1<1%
Adult RBT Adult KOK
\103,2% 1 5<1%
Adult BRT
3, <1%
Adult UNK
1, <1%
Adult KOK
5<1%
Adult RBT
1,
27, 2%
Juvenile BRT
4, <1%
Juvenile BUT
4, <1%
Juvenile BRT
8, <1%
Juvenile
RBT, 1248, 86%
Juvenile RBT
5676, 94%
Adult BRT
6, <1%
COT
3, <1%
WHF
Juvenile CHK
125, 9%
COT
Juvenile BUT
2, <1%
Adult
1, <1%
LND
Juvenile CHK
267, 4%
COT
6, <1%
Metolius Headwaters Night 2002
Adult BUT
6, <1%
Adult RBT
78, 1% Juvenile CHK
604, 10%
Adult BRT
3, <1%
COT
16, 1%
Juvenile BRT
8, <1%
Adult BUT
4, <1%
Adult RBT
41,2%
Adult
KOK, 96, 5%
Adult WHF
2, <1%
Juvenile BUT
12, <1%
Juvenile CHK
436, 21%
Juvenile BRT
<1%
Juvenile RBT,
Juvenile RBT,
5273, 89%
Metolius Headwaters Day 2003
1481,71% -
Juvenile BUT
<1%
Metolius Headwaters Night 2003
Appendix Figure Dl. Fish species observed in the Metolius Headwaters study reach in day and night snorkel surveys, 2002 and 2003.
Metolius Mainstem Day 2002
COT Adult BRT
67, 4%
64, 4%
/
Juvenile UNK
19, 1%
Metolius Mainstem Night 2002
Adult BUT
17, 1%
Adult BRT
50, 7%
COT
19, 3%
Adult BUT
2, >1%
Adult RBT
187, 10%
Adult RBT
- 83, 11%
Juvenile RBT
530, 30%
Adult WHE
77, 10%
Juvenile RBT
316, 42%
Adult UNK
5, 1%
Juvenile BUT
36,2%
22, 1%
Juvenile CHK
30, 4%
Adult WHF
796, 45%
Juvenile BRT,
Juvenile CHK
43, 2%
Note 2875 juvenile whitefish were also observed in day 2002 surveys.
Juvenile BRT
Juvenile BUT
120, 16%
46, 6%
Note. 948 juvenile whitefish were also observed in night 2002 surveys.
Adult BRT
Juvenile COTAdult BRT
23, 1%
38, 2% Adult BUT
8, >1%
Juvenile UNK
Adult RBT
2>1%
101, 5%
764, 41% Odult
Juvenile RBT
KOK
430, 23%
Juvenile BUT
Juvenile BRT
100, 5°i'
\
Juvenile CHK
28, 1%
Adult WHF
415, 22%
Adult UNK
2, >1%
Metolius Mainstem Day 2003
2896 iuvenile whilefish were also observed in day 2003 Surveys
I
COT
40, 5%
Juvenile RBT
338, 43%
30,4% -
Juvenile BUT23, 3%
Adult BUT
11,1%
Adult RBT
55, 7%
Adult KOK
--
Adult WI-IF
354%
Juvenile CHK
75,9%
Juvenile BKT
1, >1%
Juvenile BRT
126, 16%
Metolius Mainstem Night 2003
1563 iuvenile whilefish were also observed in niaht 2003 surveys
Appendix Figure D2. Fish species observed in the Metolius Mainstem study reach in day and night snorkel surveys, 2002 and 2003.
Lake Creek Day 2002
Lake Creek Night 2002
Adult BRT Adult BUT
Adult RBT
23, 2%
1, <1%
[ND 48, 3%
24, 2Ault UNK
8, 1%
6, <1%
COT
2, <1%
Adult WHF
SPD
LND
17,2%
SPD
9%
73,
Adult BUT
1, <1%
Adult BRT
45, 5%
Adult RBT
COT
1, <1%
12, 1%
1, <1%
Juvenile WHF
269, 18%
Juvenile CHK
248, 16%
Juvenile BUT
2, <1%
Juvenile UNK
9, 1%
Juvenile BRT
542, 35%
Juvenile RBT
331, 22%
LND
COT
7, <1%
SPD
361,13%
9, <1%
Adult BRT
37, 1%
Adult RBT
20, 1%
Juvenile UNK
1, >1%
Juvenile RBT
103, 12%
/Juvenile CHK
271, 32%
Juvenile BUT
<1%
Juvenile UNK
<1%
Juvenile BRT
283, 34%
Adult KOK
1, <1%
Adult UNK
4, <1%
--Adult UNK
WHF-
Juvenile
44, 5%
SPD
[ND
44, 3%
Adult BRT
Adult BUT
21,2%
1, <1%
179, 13%
Adult RBT
8, 1%
COT
3, <1%
9, <1%
Juvenile WHF
243, 9%
Juvenile UNK
1, <1%
/
Juvenile RBT-
Juvenile CHK
1441, 55%
239, 9%
Juvenile BUT
1, <1%
Juvenile BRT
311, 12%
1 plus CHK
1, <1%
Lake Creek Day 2003
Juvenile CHK
556, 42%
Juvenile WHF
135, 10%
Juvenile RBT
143, 11%
Juvenile BUT
1, <1%
1 plus CHK
Juvenile BRT
243, 18%
1, <1%
Lake Creek Night 2003
Appendix Figure D3. Fish species observed in the Lake Creek study reach in day and night snorkel surveys, 2002 and 2003.
Canyon Creek Day 2002
COT
3, 1%
Juvenile RBT
3, 1%
Canyon Creek Night 2002
Adult BRT
3, 1%
Adult BUT
39, 9%
COT
3, 1%
Adult BRT
2, 1%
Adult BUT
12, 5%
Juvenile RBT
7, 3%
Adult RBT
11,5%
Adult RBT
27, 6%
Juvenile CHK
45, 18%
Juvenile BUT
194, 44%
Juvenile BKT
1, <1%
Juvenile CHK
163, 37%
Juvenile BUT163, 67%
Juvenile BRT,-7
5, 1%
Juvenile UNK
1, <1%
COT
24, 6%
Adult BKT
1, <1%
Juvenile RBT
CT
Adult BUT
41, 11%
5,1%
Juv. BKT/ BUT
Hybrid, 1, <1%
Juvenile BUT
143, 39%
Al
1
Adult RBT
1, <1%
Juvenile BKT
2, <1%
Adult UNK
1, <1%
Adult KOK
42, 9%
Adult BUT
15, 3%
Juvenile RBT3, 1%
Adult KOK
93, 25%
Juvenile CHK
79, 18%
Adult UNK
1, <1%
Juvenile CHK
68, 18%
Canyon Creek Day 2003
Juvenile UNK
1, <1%
Adult
BUT, 15, 3%
Juvenile BUT
263, 60%
1PLUS CHK
1, <1%
Canyon Creek Night 2003
Appendix Figure D4. Fish species observed in the Canyon Creek study reach in day and night snorkel surveys, 2002 and 2003.
Spring Creek Day 2002
COT
Adult
BKT,1,<1%
Spring Creek Day 2003
Adult
Adult
BRT, 7, 3%
BUT, 1, <1%
14, 6%Juvenile UNK
3, 1%
Juvenile RBT
40, 16%
Adult
RBT, 8, 3%
Adult
Juvenile UNK
KOK,2,1%
1<1%
Adult UNK
7, 3%
Juvenile BUT
4, 2%
Juvenile WHF
12,7%
COT
4, 2%
Adult BKT
1, <1%
Adult BRT
2, 1%
Adult BUT
4, 2%
Adult RBT
9, 5%
Juvenile RBT,
54,32%
-
Juvenile BRT
8, 3%
Juvenile CHK
68, 40%
Juvenile CHK
1PLUS CHK
156, 62%
1, <1%
Note: 196 juvenile Whitefish were also observed in Spring Creek in Day 2002.
Juvenile UNK
6, 4%
Juvenile BUT
14, 10%
Juvenile BUT
5, 3%
Juvenile BRT
9. 5%
Juvenile
UNK, 2, 1%
Juvenile BKT
1, <1%
Juvenile
BUT, 19,8%
Juvenile
RBT, 1, <1%
Juvenile CHK
116, 86%
Heising Spring Day 2002
Juvenile CHK
207, 91%
Heising Spring Day 2003
Appendix Figure D5. Fish species observed in the Spring Creek and Heising Spring study reaches in day surveys, 2002 and 2003.