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Environmental Toxicology and Chemistry, Vol. 21, No. 9, pp. 1922–1926, 2002
q 2002 SETAC
Printed in the USA
0730-7268/02 $9.00 1 .00
ACUTE AND CHRONIC TOXICITY OF ZINC TO THE MOTTLED SCULPIN
COTTUS BAIRDI
JOHN WOODLING,* STEPHEN BRINKMAN, and SHANNON ALBEKE
Colorado Division of Wildlife, 6060 Broadway, Denver, Colorado 80216, USA
( Received 11 April 2001; Accepted 4 March 2002)
Abstract—The acute and chronic toxicity of zinc to wild mottled sculpin (Cottus bairdi) was measured with 13-d and 30-d flowthrough toxicity tests, respectively. Exposure water hardness was 48.6 mg/L as CaCO3 and 46.3 mg/L as CaCO3 in the acute and
chronic tests, respectively; pH was slightly above neutral; and temperature near 128C. The median lethal concentration (LC50) after
96 h was 156 mg Zn/L, but decreased with exposure duration to a median incipient lethal level (ILL50) of 38 mg Zn/L after 9 d,
the lowest zinc LC50 reported for any fish species. The 30-d chronic no-effect and lowest-effect concentrations were 16 mg Zn/L
(no mortality) and 27 mg Zn/L (32% mortality), respectively. The ILL50 was 32 mg Zn/L. No sublethal growth differences were
observed during the chronic test. Analysis of the results from these tests suggested that mottled sculpin may experience acute and
chronic toxicity at zinc concentrations lower than any other fish species tested to date. Protection of aquatic communities in stream
reaches contaminated by metals seem to require determination of zinc toxicity to lotic species other than trout and other species
amenable to aquaculture.
Keywords—Zinc
Mottled sculpin
Toxicity test
Acute toxicity
Chronic toxicity
The current study had three objectives. The first objective
was to develop a 96-h zinc median lethal concentration (LC50)
value for recently hatched wild C. bairdi to assess acute toxicity. The second objective was to conduct a 30-d chronic
toxicity test to determine both mortality rates and decreased
growth rates of mottled sculpin that survived zinc exposure.
The third objective was to compare results to data for salmonids to determine relative zinc sensitivity.
INTRODUCTION
Although the toxicity of zinc to several fish species has
been well documented and reviewed [1], the toxicity of this
metal is not well known for other cold water, littoral fishes
such as sculpin (Cottus spp). Sculpin species inhabit many
streams in the western United States [2], including two species
in Colorado [3], the mottled sculpin (Cottus bairdi) and the
Paiute sculpin (Cottus beldingi). Sculpin were absent and trout
numbers were depressed in a 19.3-km-long segment of the
Eagle River downstream of an inactive mining operation dating
to the 1800s near Minturn, Colorado, USA (Colorado Division
of Wildlife, Denver, CO, USA, unpublished data). At the same
time, sculpin were present in the mainstem Eagle River immediately upstream of the mine operation, downstream of the
stream reach impacted by mine operation, and in the mouths
of three tributaries that enter the mainstem in the 19.3-kmlong metal-contaminated reach. Sculpin failed to appear,
whereas brown trout (Salmo trutta) numbers increased, in the
19.3-km-long reach during the course of a 10-year federally
mandated restoration program that began in 1988. Zinc was
the principal metal of concern through the last one half of a
12-year period. Sculpin seemed to be more sensitive to zinc
contamination of the Eagle River than were trout species.
The toxicity of zinc to various trout species has been determined through multiple toxicity tests and is used in deriving
the U.S. Environmental Protection Agency ambient water quality criteria for zinc [4]. If sculpin are more sensitive to zinc
than are trout species, existing criteria and restoration objectives may not be adequate to protect a diverse aquatic community. Determining the relative metal toxicity of a variety of
native lotic species is required to assure that appropriate water
quality criteria and restoration objectives are chosen for stream
reaches contaminated by metals.
METHODS AND MATERIALS
Organisms
A total of 134 recently emerged C. bairdi was collected
from the White River approximately 5 km east of Meeker,
Colorado, USA, on August 8, 2000, for the acute toxicity test
by using pulsed direct current from a backpack electrofisher
unit (Smith Root, Vancouver, WA, USA). Hardness and conductivity at the site of collection were 240 mg/L as CaCO3
and 454 mS/cm, respectively. The fish were transported in an
aerated, iced cooler to the Colorado Division of Wildlife
Aquatic Toxicology Laboratory in Fort Collins, Colorado,
USA. Upon arrival, fish were immersed in a 3% sodium chloride solution for 3 min to remove potential ectoparasites, then
placed in a glass aquarium supplied with a mixture of dechlorinated Fort Collins municipal tap water and on-site well
water. The mixture approximated that of the White River (hardness 225 mg/L as CaCO3, conductivity 450 mS/cm, temperature 188C). Over the next 36 h, the amount of well water used
was slowly decreased until only dechlorinated municipal tap
water was used (hardness 50 mg/L as CaCO3). The fish were
acclimated to dechlorinated municipal tap water for 10 d before
initiation of the acute toxicity test. Five of this group died
during transport to the laboratory. No additional mortality occurred during the acclimation period. Fish were fed a concentrated suspension of brine shrimp nauplii (San Francisco Bay
Brand, Newark, CA, USA) supplemented with starter trout
* To whom correspondence may be addressed
(john.woodling@state.co.us).
1922
�Zinc toxicity to C. bairdi
chow (Silver Cup, Hanford, CA, USA). Fish were observed
feeding on both types of food.
A second group of 170 mottled sculpin was collected on
August 30, 2000, at the same White River location for the 30d chronic exposure. These organisms were collected, transported, and handled in the same manner as the first group. No
mortality occurred during the transportation to the laboratory
or during the 21-d acclimation period before initiation of the
chronic test.
Toxicant
Chemical stock solutions were prepared by dissolving a
calculated amount of reagent-grade zinc sulfate heptahydrate
(ZnSO4·7H2O) (Mallincrodt, Paris, KY, USA) in deionized water. New stock solutions were prepared as needed during the
two toxicity tests.
Acute test methods
A continuous-flow diluter [5] was used to deliver the exposure solutions. The source water consisted of dechlorinated
municipal tap water. The diluter was constructed of polyethylene and polypropylene components and Nalgene food-grade
vinyl tubing. A zinc stock solution was delivered to the diluter
via a peristaltic pump (model C/L, Cole-Palmer, Barrington,
IL, USA) at a rate of 2.2 ml/min. The diluter delivered five
concentrations of zinc and control. Nominal zinc concentrations for the acute test were 1,000, 500, 250, 125, 62.5, 31.2,
and 0 mg Zn/L. A flow splitter allocated each concentration
equally among four replicate exposure chambers at a rate of
40 ml/min. Exposure chambers consisted of polyethylene containers with a capacity of 2.8 L. Test solutions overflowed
from the exposure chambers into a water bath that was maintained at 128C with a temperature-controlled recirculator (Polyscience, Nile, IL, USA). An outdoor photocell regulated the
fluorescent lighting to provide a natural August photoperiod
of 13 h of daylight and 11 h of darkness each day.
Five mottled sculpin were randomly placed in each of the
exposure chambers for the acute toxicity test. Mortality was
monitored and recorded several times daily. Dead sculpin were
measured for total length (mm), blotted dry with a paper towel,
and weighed (g). Sculpin did not receive food during the first
96 h but thereafter were fed a concentrated suspension of brine
shrimp nauplii supplemented with starter trout chow twice
daily on weekdays and once daily on weekends. After 8 d, an
additional treatment was initiated to provide mortality data at
a nominal zinc concentration of 31 mg Zn/L. Five sculpin were
randomly added to each of the four replicates at 31 mg Zn/L
and treated as described in the preceding paragraph. Zinc exposure continued for 13 d for all nominal concentrations. Control fish were monitored for 21 d. Aquaria were siphoned to
remove uneaten food and feces as needed.
Randomly chosen surviving fish and dead fish from the
acute toxicity test were preserved in Bouin’s solution and taken
to the Colorado Division of Wildlife Aquatic Animal Health
Laboratory for necropsy and examination. Preserved specimens were examined with a dissecting microscope for parasitic
infestations and then dissected. Various tissues were embedded
in paraffin, sectioned, stained, and examined with a compound
microscope for both disease and internal parasites.
Chronic test methods
Seven mottled sculpin were randomly placed in each exposure chamber for the 30-d chronic toxicity test exposure.
Environ. Toxicol. Chem. 21, 2002
1923
Mortality was monitored daily. Nominal zinc concentrations
for the chronic test were 200, 100, 50, 25, 12.5, and 0 mg Zn/
L. Flow rate of the zinc stock solution was reduced to 1.6 ml/
min. A natural September–October photoperiod of 11.5 h of
daylight and 12.5 h of darkness was created as defined above.
All other aspects of fish care and handling and test methods
were identical to those of the acute test. Lengths and weights
of all fish that survived the 30-d exposure were determined
after the fish were killed with metomidate hydrochloride (Wildlife Laboratories, Fort Collins, CO, USA).
Water quality analysis
Exposure water characteristics were measured daily during
the acute test on weekdays in two randomly selected aquaria.
Exposure water characteristics during the chronic test were
measured weekly in one randomly selected replicate chamber
for each nominal concentration. Hardness and alkalinity were
determined according to standard methods [6]. Measurements
for pH were conducted with a pH meter (model 811, Orion,
Cambridge, MA, USA) calibrated before each use with pH
7.00 and pH 4.00 buffers. Conductivity was determined with
a conductance meter (model 35, Yellow Springs Instruments,
Yellow Springs, OH, USA). Dissolved oxygen was measured
with a dissolved oxygen meter (model 58, Yellow Springs
Instruments).
Water samples for zinc analysis were collected daily during
the acute test from all exposure concentrations. A different
replicate tank was sampled daily from each exposure concentration. Water samples for zinc were collected daily during the
chronic test for the first 7 d and weekly thereafter from one
randomly selected replicate chamber for each exposure concentration. Total (acid soluble) samples were collected in disposable Falcon polystyrene tubes (Becton Dickinson, Franklin
Lakes, NJ, USA) and immediately preserved with triple distilled nitric acid (Ultrext, Phillipsburg, NJ, USA) to pH , 2.
Dissolved samples were passed through a 0.45-mm filter (Acrodisc, Ann Arbor, MI, USA) before acidification. Water samples were analyzed for zinc with an Instrumentation Laboratory Video 22 (Allied Analytical Systems, Franklin, MA, USA)
atomic absorption spectrometer with air–acetylene flame and
Smith–Hieftje background correction. The spectrometer was
calibrated before each use and the calibration was verified with
a National Institute of Standards and Technology (Gaithersburg, MD, USA) traceable standard from an outside source.
Statistics
All LC50 values were based on dissolved zinc concentrations and estimated by the trimmed Spearman–Karber technique [7,8] with Toxstatt software (Ver. 3.5, Western EcoSystems Technology, Cheyenne, WY, USA). The median incipient lethal level (ILL50) concentrations were the LC50 values derived at the time mortality ceased. The lengths, weights,
and survival of sculpin used in the chronic test were analyzed
by analysis of variance (ANOVA). Survival proportions were
arcsine transformed before ANOVA [9]. Treatment means
were compared to the control by William’s one-tailed test (p
, 0.05). Sculpin length and weight data were normal with
homogeneity of variance according to Shapiro–Wilk’s test and
Bartlett’s test, respectively.
RESULTS
Acute test
Exposure water hardness averaged 48.6 mg/L as CaCO3,
temperature 12.28C, and pH was slightly basic at 7.4 (Table
�1924
Environ. Toxicol. Chem. 21, 2002
J. Woodling et al.
Table 1. Mean, standard deviation, and range of water quality characteristics of exposure water used for zinc toxicity tests (acute and chronic)
conducted with mottled sculpina
pH
(SU)
Temperature
(8C)
Hardness
(mg/L as
CaCO3)
Alkalinity
(mg/L CaCO3)
Conductivity
(mS/cm)
Oxygen
(mg/L O2)
Acute test
Mean
SD
Range
7.38
0.13
7.2–7.6
12.2
0.3
11.6–12.8
48.6
1.1
46.2–50.4
36.0
1.4
34.0–39.0
85.2
2.1
81.4–90.5
9.1
0.19
8.8–9.5
Chronic test
Mean
SD
Range
7.56
0.08
7.4–7.7
11.8
0.3
11.2–12.5
46.3
2.7
42.8–49.8
35.9
1.0
34.6–37.8
81.3
2.5
78.3–87.8
8.8
0.2
8.4–9.3
a
SU 5 standard units; SD 5 standard deviation.
1). Measured zinc concentrations were consistent for the duration of the test in each of the treatments and close to the
desired nominal concentrations (Table 2). Dissolved and total
zinc concentrations were virtually identical. The 96-h LC50
was 156 mg Zn/L. All sculpin exposed to dissolved zinc concentrations greater than or equal to 487 mg/L died within 96
h. Mortality in lower zinc concentrations increased with duration of exposure. Complete mortality occurred at all exposure
concentrations greater than or equal to 69 mg/L by the ninth
day of the test, and 40% mortality was observed at a concentration of 34 mg/L (Table 2). No additional mortality occurred
after 9 d through the end of test, at 13 d. All fish in the control
treatments survived. The LC50 values declined with time, with
an ILL50 of 38 mg/L at 9 d (Table 3). The average length of
mottled sculpin used in the acute test was 31.4 mm, with a
range of 24 to 40 mm. These fish were considered to be youngof-the-year because 21-mm-long mottled sculpin collected 8
d before collection of test organisms at the same location still
had a yolk sac.
Gross and microscopic examination of organisms used in
the tests failed to find external or internal parasites or disease.
Chronic test
Exposure water characteristics also were constant during
the chronic test (Table 1) and were similar to those of the acute
test. As with the acute test, measured zinc concentrations were
consistent for the duration of the test in each of the treatments
and close to the desired nominal concentrations (Table 2).
Dissolved and total zinc concentrations were virtually identical. All sculpin exposed to dissolved zinc concentrations
greater than or equal to 53 mg/L died by the 19th day of the
30-d test. At the culmination of the 30-d chronic test, a 32%
mortality had occurred at a concentration of 27 mg Zn/L, with
no mortality at a concentration of 16 mg Zn/L. No fish died
after the 19th day of the chronic test. The ILL50 was 32 mg
Zn/L.
Even though the nominal exposure concentrations were different during the two toxicity tests, the 30-d test provided a
replicate study for portions of the 13-d acute test. The LC50s
determined for day 5 through day 13 during the chronic test
were similar to LC50s calculated at the same times during the
acute test (Table 3).
The average length and weight of all sculpin that died within the first 96 h of the 30-d chronic test were 36.8 mm and
0.545 g, respectively. Mean length and weight of fish surviving
the chronic exposure were 41.3 mm and 0.707 g, respectively.
The increase in length of 4.5 mm was significant (p , 0.0001,
t test with a pooled variance with an F test to check variance
equality), as was the increase in weight (p , 0.0016) of 0.162
g. Mean length and weight of control fish at the end of the
chronic test were 40.6 mm and 0.67 g, respectively. Mean
lengths of fish in the chronic exposure at 16 mg Zn/L or fish
surviving the exposure at 27 mg Zn/L were 39.6 mm and 40.2
mm, respectively, whereas mean weights were 0.62 g and 0.63
g. No differences in length and weight were determined among
control fish, sculpin in the exposure at 16 mg Zn/L, or sculpin
that survived exposure at 27 mg Zn/L during the 30-d chronic
test.
DISCUSSION
Mottled sculpin inhabit trout streams throughout much of
western Colorado. The water quality of many of these streams
continues to be degraded by metal loadings attributable to past
and present mining activities, some of which date back to the
1860s. A wealth of data have been developed regarding the
effects of metals on trout because of the sensitivities of the
various species to metals, ease of aquaculture, and economic
importance. However, effects of zinc on sculpin were un-
Table 2. Mean zinc concentrations (mg/L) (13-d acute tests and 30-d chronic tests). Standard deviations are given in parentheses
Concentration
Acute test
Nominal Zn (mg/L)
Total Zn (mg/L)
Dissolved Zn (mg/L)
0
,10 (3)
,10 (2)
31.2
35 (3)
34 (3)
62.5
70 (4)
69 (4)
125
138 (10)
128 (4)
250
251 (7)
249 (7)
500
489 (12)
487 (12)
Chronic test
Nominal Zn (mg/L)
Total Zn (mg/L)
Dissolved Zn (mg/L)
0
,5 (4)
,5 (2)
12.5
15 (2)
16 (3)
25
28 (2)
27 (2)
50
53 (2)
53 (2)
100
104 (3)
102 (2)
200
216 (10)
210 (5)
1,000
1,005 (25)
1,001 (28)
�Zinc toxicity to C. bairdi
Environ. Toxicol. Chem. 21, 2002
Table 3. Median lethal concentrations (LC50s) of zinc (95%
confidence intervals) to mottled sculpin at different durations of
exposure
Estimated LC50 (mg/L)
Duration of
exposure
96 h
5d
6d
7d
8d
9d
13 d
21 d
30 d
Acute test
Chronic test
156 (125–193)
92 (71–120)
62 (47–80)
45 (37–55)
41 (34–51)
38 (31–48)
38 (31–48)
—
—
94 (72–122)
57 (40–80)
48 (40–55)
42 (37–46)
38 (34–43)
33 (29–38)
32 (28–37)
32 (28–37)
known. The results of these toxicity tests indicated that mottled
sculpin were more sensitive to acute and chronic zinc exposure
than were other freshwater trout and char.
The 96-h LC50 for the mottled sculpin was 156 mg Zn/L
at a hardness of 48.6 mg/L CaCO3. In comparison, the lowest
recorded 96-h LC50 for juvenile rainbow trout (Oncorhynchus
mykiss) in water at a hardness of 46.8 mg/L as CaCO3 was
370 mg Zn/L [10]. Juvenile brook trout (Salvelinus fontinalis)
were less sensitive than sculpin, with a lowest recorded 96-h
LC50 in soft water (46.8 mg/L as CaCO3) of 1,550 mg Zn/L
[10]. The 96-h zinc LC50s for brown trout for fish of different
ages were 392, 871, and 1,033 mg Zn/L in toxicity tests that
used the same water source as the present study [11]. Only
one fish species, the striped bass (Morone saxatillis), seemed
to be more sensitive to acute zinc exposure than the mottled
sculpin. The striped bass mean zinc 96-h LC50 (normalized
to a hardness of 50 mg/L as CaCO3) was 119 mg/L [3]. The
mottled sculpin seemed to be the second most sensitive fish
species to acute 96-h zinc exposure for which data were available.
In addition, the mottled sculpin was more sensitive to
chronic zinc exposure than freshwater trout and char. The 30d LC50 for mottled sculpin was 32 mg Zn/L. In comparison,
the lowest zinc chronic value for O. mykiss was 276 mg/L [4].
The chronic value was 36 mg Zn/L [12,13] for the flagfish
(Jordaneila floridae), the only fish species with chronic zinc
sensitivity similar to that of the mottled sculpin. The mottled
sculpin seemed to be the most sensitive fish species to chronic
zinc exposure, although relatively few chronic toxicity tests
have been performed on other fish species.
An exposure of 96 h is the defined basis for assessing acute
toxicity for fish [4]. However, 96 h seemed to be an insufficient
exposure to accurately assess acute zinc toxicity in the mottled
sculpin. The zinc concentration that resulted in mottled sculpin
death decreased fourfold during the acute test as exposure time
period increased from 4 d to 7 and 8 d. In addition, the onset
of mottled sculpin acute mortality was delayed in comparison
to mortality observations made during 96-h acute toxicity tests
to various trout and char species. In our past toxicity work,
most trout mortalities occurred during the second 24-h period
of 96-h toxicity tests conducted at similar hardness levels and
temperatures. Few if any trout died during the last 24-h period
of a given 96-h toxicity test. In contrast, sculpin mortality did
not begin until the third 24-h period of either the acute or
chronic exposure test of the current study. In instances where
high levels of mortality are measured for a few days past the
1925
initial 96-h exposure, the use of ILL50 data may be preferable
to describe acute toxicity.
The ILL50 determinations for both the acute and chronic
test were similar. Mottled sculpin exposed to ILL50 zinc concentrations from 38 mg Zn/L to 32 mg Zn/L experienced significant mortality in a time period of 9 to 19 d, respectively,
in the acute and chronic toxicity tests. However, current U.S.
Environmental Protection Agency zinc criteria [14] suggest
that a 30-d exposure at an average zinc level of 64 mg Zn/L
or 61.5 mg Zn/L would be protective at the hardness levels of
the test water in this study. The ILL50 levels for C. bairdi
determined in our study are approximately 50% less than the
zinc concentrations assumed to be safe based on current U.S.
Environmental Protection Agency zinc criteria. We expect
short-term mortality for wild mottled sculpin populations exposed to zinc concentrations currently expected to be safe,
based on current U.S. Environmental Protection Agency chronic zinc criteria.
Use of wild fish could influence the outcome of toxicity
tests. Disease or parasitic infections and the stress of capture,
transportation, or captivity could induce mortality at lower
concentrations than in cultured fish. Disease and external or
internal parasitic infections were not evident and did not seem
to influence the results of either the acute or chronic test.
Capture, transportation, or captivity did not seem to have any
influence on test results because no mortality occurred during
either the 10- or 21-d acclimation periods before the acute or
chronic tests. In addition, no control fish died during either of
the toxicity tests. Lack of control fish mortality coupled with
a significant increase in length and weight of all fish surviving
the chronic test compared to fish that died in the initial 96 h
also were indications that use of wild fish did not greatly
influence results.
Examination of results of the current study indicated that
the mottled sculpin will not survive exposure to zinc concentrations that support brown trout and brook trout. This observation was consistent with field observations on a metal-contaminated segment of the Eagle River in Colorado. Brook trout
and brown trout, but not sculpin, inhabited three Eagle River
sampling sites where dissolved zinc concentrations ranged
from 315 mg Zn/L to 711 mg Zn/L after a metal contamination
reduction program (Colorado Division of Wildlife, unpublished data). Low numbers of sculpin were collected at a fourth
downstream Eagle River site in the years after dissolved zinc
concentrations dropped from 330 mg Zn/L to less than 166 mg
Zn/L. Sculpin were always collected through the multiyear
sampling program at an upstream reference site where dissolved zinc exceeded a 10 mg Zn/L detection limit in only 3
of 12 annual low-flow, high-metal-concentration sampling
events (range 15–71 mg Zn/L). No obvious habitat differences
existed to preclude sculpin colonization at the middle three
Eagle River sampling sites. However, Eagle River hardness
concentrations were approximately twice those in the present
study. Still lower instream zinc concentrations are required for
mottled sculpin to colonize the three middle Eagle River sampling sites.
Much of the available zinc toxicity test data were developed
with fish species that are routinely spawned and reared in
aquaculture facilities, such as trout. Few data exist for most
lotic fish species that are not amenable to fish culture techniques. A need exists to study more riverine fish species, such
as longnose dace (Rhinichthys cataractae) and flannel mouth
sucker (Catostomus latipinnis), that would be expected to in-
�1926
Environ. Toxicol. Chem. 21, 2002
habit stream reaches where zinc toxicity usually has been defined based on trout.
Death was the measurable end point during the chronic test.
No growth differences were observed at any zinc concentration
where test organisms survived. Sublethal responses to zinc
with mottled sculpin need to be determined. Additional toxicity
tests would be required to determine possible growth effects
and changes in production of stress hormones such as cortisol
[15] at zinc levels less than the ILLs determined in this study.
Acknowledgement—We wish to acknowledge fish collections by Jenny Ketterlin, Jenn Logan, Amie Stauffer, and Ann Widmer; fish care
assistance by Daria Hanson; and the editing efforts of Brighid Kelly
and two anonymous reviewers.
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4. U.S. Environmental Protection Agency. 1987. Ambient water
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5. Benoit DA, Mattson VR, Olsen DC. 1982. A Continuous flow
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Methods for the Examination of Water and Wastewater, 16th ed.
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7. Hamilton MA, Russo RC, Thurston RV. 1977. Trimmed Spearman–Karber method for estimating median lethal concentrations
in toxicity bioassays. Environ Sci Technol 11:714–719.
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10. U.S. Environmental Protection Agency. 1978. The acute toxicity
of zinc to rainbow and brook trout. Comparison in hard and soft
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T, Woodling JD. 1999. Impaired adrenocortical response to stress
by brown trout, Salmo trutta, living in metal-contaminated water
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Text
Arch Environ Contam Toxicol (2008) 54:466–472
DOI 10.1007/s00244-007-9043-z
Acute Toxicity of Aqueous Copper, Cadmium, and Zinc to the
Mayfly Rhithrogena hageni
Stephen F. Brinkman Æ Walter D. Johnston
Received: 28 August 2007 / Accepted: 31 August 2007 / Published online: 5 October 2007
� Springer Science+Business Media, LLC 2007
Abstract Heptageniid mayfly nymphs have been suggested as sensitive indicators of metal contamination in
streams based on biomonitoring studies, experimentation in
situ, and experimentation in microcosm. Laboratory tests
were conducted to evaluate the sensitivity of Rhithrogena
hageni, a heptageniid mayfly, to waterborne copper, cadmium, and zinc. Tests were conducted with soft water
(hardness = 40–50 mg/L) at about 12�C. Toxicity endpoints were survival and moulting (%/day). Median 96 hr
lethal concentrations were 0.137, 10.5, and 50.5 mg/L for
copper, cadmium and zinc, respectively. The average daily
moulting rate of survivors significantly decreased after
exposure to these metals in solution.
Introduction
Aquatic insects are often used to assess biological impacts
of trace metal pollution. Case studies of contaminated
rivers in the Rocky Mountain region have found reduced
mayfly abundances immediately downstream of pointsource inputs of metals (Winner et al. 1980; Cain et al.
1992; Clements et al. 2000). Heptageniid mayflies have
been recognized as especially sensitive to metals in streams
(Leland et al. 1989; Peckarsky and Cook 1981; Clements
1994; Clements and Kiffney 1995; Clements et al. 2002)
and in microcosm experiments (Clements 2004). Rhithrogena hageni has been identified as a strong indicator of
metal contamination (Nelson and Roline 1993; Kiffney
and Clements 1994; Clements et al. 2000). Kiffney and
Clements (1994) found that the concentration of zinc correlated with reduced heptageniid abundances in stream
microcosms was well below the hardness-based ambient
aquatic life criterion for zinc (United States Environmental
Protection Agency 1996).
Ambient aquatic life water quality criteria and standards
are generally derived from results of laboratory toxicity
tests conducted with only one species and one toxicant
(United States Environmental Protection Agency 1985a).
However, acceptable data from such tests are lacking for
mayflies. Results of a single study were used for the
development of US aquatic life water quality criteria for
cadmium (United States Environmental Protection Agency
2001). No mayfly toxicity data were used for the development of water quality criteria for copper or zinc (United
States Environmental Protection Agency 1985b; 1996).
The objective of this study was to provide toxicity data for
use in developing copper, cadmium and zinc criteria and
state standards. We conducted a series of experiments to
determine the lethality of each metal to R. hageni in a
controlled laboratory setting.
Materials and Methods
S. F. Brinkman � W. D. Johnston
Aquatic Toxicology Laboratory, Colorado Division of Wildlife,
Fort Collins, Colorado, USA
S. F. Brinkman (&)
Colorado Division of Wildlife, 317 West Prospect Rd.,
Fort Collins, CO, USA
e-mail: steve.brinkman@state.co.us
123
Collection and Handling
Rhithrogena hageni nymphs were collected by hand from
shallow riffles on the Cache la Poudre River (Larimer
County, CO, USA), which has no history of metal contamination. Nymphs were collected from the same site in
�Arch Environ Contam Toxicol (2008) 54:466–472
467
October, November, and December of 2005 for the zinc,
copper, and cadmium tests, respectively. Nymphs were
gathered at least seven days prior to each test. Individuals
were identified to genus in the field using a taxonomic key
from Ward and Kondratieff (1992). Species identity was
verified by two independent experts at Colorado State
University.
Nymphs were transported in a 30-liter cooler along with
cobble substrate from the collection site. The transport unit
was aerated with airstones connected by nylon tubing to a
battery-operated pump. Temperature was maintained near
ambient conditions (4–6�C) during transport to the Colorado Division of Wildlife aquatic toxicology laboratory in
Fort Collins, Colorado, USA. Nymphs were carefully
transferred with a paint brush to glass holding tanks containing Cache la Poudre River water. Holding tanks were
aerated and incubated at 4�C. Water was gradually
replaced (50% per day) with test dilution water and the
incubator temperature was gradually increased (2�C per
day) to test temperature (11–12�C).
Test Methods
Source water for the zinc toxicity test consisted of a mixture of onsite well water and reverse osmosis water. A
conductivity controller maintained the diluent source water
hardness near 45 mg/L. Dechlorinated municipal tap water
(Fort Collins, CO, USA) was used for the cadmium and
copper tests, due to logistical constraints. Both diluent
sources had similar water quality characteristics (Table 1).
Source water supplied a continuous-flow serial diluter
(Benoit et al. 1982) constructed of Teflon, polyethylene,
and polypropylene components. The diluter delivered five
concentrations of metal toxicant with a 50% dilution ratio
and a control. A flow splitter allocated each concentration
equally among four replicate exposure chambers at a rate
of 40 mL/min. Food-grade vinyl tubing delivered test
solutions to exposure chambers. Metal stock solutions were
prepared by dissolving a calculated amount of metal sulfate
salts in deionized water. A concentrated stock solution was
Table 1 Mean (SD) water quality parameters of exposure water in
cadmium, copper, and zinc toxicity tests. ND = not determined
Hardness (mg/L)
Cache la Copper
Poudre
test
Cadmium
test
Zinc
test
40.2
44.0 (3.5)
48.0 (2.0)
44.4 (1.1)
Alkalinity (mg/L) 36.4
34.5 (1.0)
34.5 (0.6)
39.9 (1.3)
Temperature (�C)
pH (SU)
5.0
7.95
11.1 (0.4) 12.0 (0.3) 11.9 (0.1)
7.72 (0.03) 7.66 (0.10) 7.77 (0.07)
Dissolved
oxygen (mg/L)
ND
ND
9.07 (0.15) ND
delivered to the diluter by peristaltic pump at a rate of 2.0
mL/min.
Exposure chambers consisted of 1.25 L, cylindrical,
polypropylene containers equipped with an air-lift system
constructed from half-inch polyvinyl chloride (PVC) pipe.
Water collected from the center of the container flowed
down through the PVC pipe immersed in a temperaturecontrolled water bath, then up to the top of the container
where an elbow diverted the flow in a circular pattern. The
air-lift maintained dissolved oxygen levels at saturation
levels and provided continuous, circular flow in the exposure chamber. Two 5 · 5 cm, unglazed, ceramic tiles were
placed in each unit to serve as a substrate.
Ten R. hageni nymphs were randomly assigned to each
of the 24 exposure chambers. Each chamber was assigned
to one of six treatment levels with four replicates for each
treatment level. Mortality, defined as failure to respond to
repeated prodding, and occurrence of exuvia were recorded
daily. Nymphs were not fed during the experiments.
Physical and chemical characteristics of exposure water
were measured daily for the first 96 hours of the test.
Hardness and alkalinity were determined titrimetrically
according to standard methods (APHA 1998). A Thermo
Orion 635 meter was used to measure pH and temperature.
Dissolved oxygen was measured using an Orion 1230
dissolved oxygen meter. Electronic meters were calibrated
prior to each use.
Water samples were collected daily for dissolved metal
analysis during the first 96 hours of the test. Exposure
water was passed through a 0.45 lm filter and immediately
preserved with high-purity nitric acid to pH \2. Chambers
with no remaining survivors were not sampled. Metal
concentrations were measured using an Instrumentation
Laboratory Video 22 (Allied Analytical Systems, Franklin,
MA) atomic absorption spectrometer with air/acetylene
flame and Smith–Hieftje background correction. The
spectrometer was calibrated prior to each use and the calibration verified using a National Institute of Standards and
Technology (NIST) traceable quality assurance/quality
control (QA/QC) standard from an outside source. Sample
splits and spikes were collected and prepared during each
sampling event to verify reproducibility and to quantify
analytical recovery. Mean recovery for the QA/QC standard was 101% (range 97–104%) and for spiked samples
was 100% (range 97–102%). The mean percentage difference between sample splits was \3.3%. Detection limits
for all three metals were \0.01 mg/L.
Median lethal concentrations (LC50) of cadmium and
zinc were estimated using the trimmed Spearman–Karber
technique with automatic trim (Hamilton et al. 1977;
1978). Spearman–Karber could not be used to estimate
copper LC50 due to the nature of the observed concentration–response relationship; therefore probit analysis was
123
�468
Arch Environ Contam Toxicol (2008) 54:466–472
used. Both survival at termination and moulting rate
(%/day) were analyzed with one-way analysis of variance
(ANOVA). Survival data were arcsine-transformed prior to
ANOVA. No transformation was used for moulting data.
Assumptions of normal error distribution and homogeneous group variances were tested using the Shipiro–Wilk
and Levene tests, respectively.
Treatment means were compared to the control using
Williams’ one-tailed test (Williams 1971; 1972) with the
type I error rate fixed at 0.05 to determine no-observedeffect concentrations (NOEC) and lowest-observed-effect
concentrations (LOEC). Survival data of the cadmium and
copper tests did not meet assumptions of normality or
homogeneity of variance and were analyzed using Steel’s
nonparametric many–one rank test.
Results
Water quality parameters were reasonably consistent
among the different metal tests (Table 1). Standard deviations of each parameter indicated constant water quality
within each experiment. Dissolved oxygen was at saturation in the cadmium test (Fort Collins elevation 1520 m)
but was not measured in the copper or zinc tests. Nymph
survival in the control treatments was 100% in the cadmium and copper tests and 97.5% in the zinc test. Survival
Discussion
Test conditions and apparatus appeared suitable for maintaining and exposing Rhithrogena hageni. The air-lift
system provided constant circular flow and maintained
Copper
Me a n Sur v iv a l (% )
Fig. 1 Mean survival (%) of R.
hageni versus duration of
exposure to copper, cadmium,
and zinc (mg/L). Asterisks
indicate significantly less than
control (p \ 0.05)
decreased with increasing metal concentrations (Fig. 1).
Copper, cadmium, and zinc LC50s after 96 hours were
0.137, 10.5, and 50.5 mg/L, respectively. Survival continued to decline after 96 hours in most metal treatments. No
survivors remained after seven days of exposure to copper
concentrations ‡0.138 mg/L, the lowest concentration tested. Nymph survival declined at cadmium concentrations
‡3.52 mg/L (LOEC) but remained high at concentrations
£1.88 mg/L (NOEC) (Fig. 1). In the zinc test, the LOEC
and NOEC after 10 days were 10.8 and 5.3 mg/L,
respectively.
The daily moulting rate (%/day) was significantly
reduced by exposure to high concentrations of copper,
cadmium and zinc (Fig. 2). Control moulting rate was
similar in each test and ranged from 9.3 to 11.7% per day.
Moulting was significantly reduced at copper concentrations ‡0.483 (LOEC), but not £0.256 (NOEC). The
cadmium LOEC and NOEC were 3.52 and 1.88 mg/L,
respectively. The LOEC and NOEC for zinc were 10.8 and
5.33 mg/L, respectively.
100
<0.01
80
0.14
60
0.26
40
0.48
20
0.85
*
0
0
48
96
144
192
1.57
240
Cadmium
Me a n Sur v iv a l (% )
100
<0.01
80
*
60
40
0.96
1.88
3.52
20
*
*
0
0
48
96
144
192
7.03
14.3
240
Me a n Sur v iv a l (% )
Zinc
100
<0.01
80
5.3
10.8
60
21.1
20
*
*
*
0
*
79.4
40
0
48
96
144
Hours
123
192
240
39.5
�Arch Environ Contam Toxicol (2008) 54:466–472
Copper
Mo ulting s (% /da y )
Fig. 2 Daily moulting rate
(%/day) versus concentrations
of copper, cadmium, and zinc.
Asterisks indicate significantly
less than control (p \ 0.05)
469
16
14
12
10
8
6
4
2
0
*
*
0
0.2
0.4
*
0.6
0.8
1
1.2
1.4
1.6
1.8
Mo ulting s (% /da y )
Cadmium
14
12
10
8
6
4
2
0
*
0
Mo ulting s (% /da y )
*
*
2
4
6
8
10
12
14
16
Zinc
12
10
8
6
4
2
0
*
*
*
*
0
10
20
30
40
50
60
70
80
90
Concentration (mg/L)
saturated levels of dissolved oxygen. The use of a continuous flow-through diluter to deliver exposure solutions
minimized variation in exposure concentrations. Survival
in control treatments was at least 97% for up to 10 days.
Test organisms moulted regularly in the control treatments.
Thus we conclude that our test apparatus provided the
conditions necessary for survival of R. hageni nymphs. The
same exposure apparatus also proved suitable for toxicity
tests with nymphs of other mayfly and stonefly species
(Colorado Division of Wildlife, unpublished data).
R. hageni nymphs were acutely sensitive to metals in the
order: Cu [ Cd [ Zn. Median lethal cadmium and zinc
concentrations were 77 and 379 times greater, respectively,
than the copper LC50. The relative sensitivity was consistent with limited metal toxicity data available for mayflies.
Ephemerella subvaria was at least six times more sensitive
to copper than cadmium (Warnick and Bell 1969). Epeorus
latifolium was more sensitive to waterborne copper than
zinc (Hatakeyama 1989). Clements (2004) found heptageniid abundance in colonized trays was unaffected by
zinc concentrations up to 30 times the United States
Environmental Protection Agency criterion. Abundance
was only slightly reduced when cadmium was added to
zinc. However, the addition of copper to the mixture
caused sharp decreases of heptageniid abundance.
A sublethal endpoint, daily average moultings (%/day),
was significantly reduced by high concentrations of copper,
cadmium, and zinc. The moulting rate declined as cadmium and zinc exposure concentrations increased and was
reduced at cadmium and zinc concentrations that also
reduced survival. In contrast, copper reduced the moulting
rate at much higher than lethal concentrations. Reduction
of the moulting rate (relative to control) varied among the
metals. Moulting was affected most by zinc and was
reduced to about 13% of control at 79 mg/L. Cadmium and
copper reduced moulting by about one-half to one-third of
control. Reduced moulting was probably the result of
impaired growth and/or development. Increased moulting
interval and reduced growth has been previously reported
for the mayfly, Epeorus latifolium, when exposed to copper
and zinc (Hatakeyama 1989). The long-term consequences
of increased moulting interval are unknown but it might
reduce the chance of survival to the adult reproductive
stage.
Mayflies are poorly represented in databases used to
derive ambient aquatic life water quality criteria for metals.
Our results indicate that current acute Cd, Cu, and Zn
criteria adequately protect R. hageni nymphs. LC50 values
for Cd, Cu, and Zn were 10,500, 16.8, and 830 times higher
than United States Environmental Protection Agency’s
123
�470
acute criteria, respectively, when adjusted for test water
hardness. Nymphs exposed to the higher concentrations of
Cd and Zn continued to experience mortality after the 96
hour acute exposure period. All nymphs exposed to copper
‡0.138 mg/L died within eight days of exposure. These
results suggest that chronic toxicity values may be much
lower than acute thresholds. Reported acute/chronic ratios
are £434 for Cd and £41 for Zn (United States Environmental Protection Agency 1996; 2001). If we apply the
highest reported acute-chronic ratios, it appears that
R. hageni should be protected by chronic criteria. Acutechronic ratios for copper are as high as 152, though most
are less than 40 (United States Environmental Protection
Agency 1985b). Additional tests are necessary to determine
whether R. hageni is protected by chronic criteria.
Comparison of Laboratory Results to Field
Observations
Based on our laboratory exposures, R. hageni appears to be
tolerant of short-term exposure to waterborne cadmium and
zinc. No significant decrease in survival was detected at
concentrations as high as 1.88 mg/L Cd or 5.33 mg/L Zn.
Tolerance of R. hageni to acute Cd and Zn exposures may
be due to slow biological uptake of these metals. Uptake of
aqueous cadmium and zinc was extremely slow in a congeneric species, R. morrisonii. (Buchwalter and Luoma
2005). Our observed tolerance of R. hageni to zinc contrasts with numerous biomonitoring studies that have
attributed reduced heptageniid abundance to much lower
concentrations of zinc. For example, abundances of R.
hageni and other heptageniid mayfly species in the east
fork of the Arkansas River were reduced downstream of
the Leadville Mine Drainage Tunnel where zinc concentrations ranged from 0.1 to 1.0 mg/L (Clements 1994;
Nelson and Roline 1996; Clements 2004). Following the
installation of a treatment plant, zinc concentrations dropped below criteria levels and abundances of R. hageni and
other heptageniids at downstream sites increased (Nelson
and Roline 1996; Clements 2004).
The apparent discrepancy between the laboratoryderived lethal concentrations and concentrations found to
decrease abundance in biomonitoring studies could arise
from several causes. Synergism may occur in metal mixtures typically found in streams thus increasing toxicity in
situ (Clements 2004). Also, sensitive taxa may be eliminated or reduced by pulses of metals undetected by grab
samples collected during biomonitoring studies. However,
it is unlikely that a pulse of metal as high as the concentrations used in our laboratory tests would ever occur in
places such as the Arkansas River. Field observations may
also be confounded by other environmental variables
123
Arch Environ Contam Toxicol (2008) 54:466–472
unrelated to metals such as stream size, temperature, flow,
and nonmetal inputs.
Differences between effect concentrations observed in
the laboratory and in situ may have been due to experimental factors. Insufficient test duration or the use of a
tolerant life stage could have resulted in toxicity thresholds
much greater than those that have been observed in
streams. Mortality in our test did not cease at 96 hours but
continued to increase until test termination. Thus, longer
exposures might have resulted in significantly lower lethal
thresholds. In addition, late-instar nymphs may be more
tolerant of metals than earlier instars. Use of late-instar
nymphs was necessary due to the difficulty of identifying
and handling early instars. Smaller individuals were more
sensitive to a metal mixture for several mayfly species
including R. hageni (Kiffney and Clements 1996; Clark
and Clements 2006). In metal-impacted streams, the
reduction or elimination of metal-sensitive early instars
may be offset by recolonization of tolerant late instars from
clean tributaries or from upstream of the metal source.
However, heptageniid mayflies drift only rarely (Rader
1997), therefore recolonization by metal-tolerant instars
would be slow.
Indirect effects of metals could also have contributed to
differences between metal concentrations that caused
lethality in the laboratory and decreased abundance in
streams. Increased drift of mayflies (Leland et al. 1989;
Clements 1999) and increased risk of predation (Clements
1999) in response to metal exposure could reduce mayfly
abundance in metal-impacted streams. Metal-caused shifts
in periphyton communities (Hatakeyama 1989; Medley
and Clements 1998; Hill et al. 2000), which are a primary
food source for scrapers such as heptageniid mayflies
(Merritt and Cummins 1996), could influence their abundance as well.
Perhaps most important is the possible influence of dietary rather than waterborne metal exposure affecting mayfly
abundance in metal impacted streams. Hexagenia rigida
accumulated Cd and Zn primarily from the diet and not
from the water (Hare et al. 1991). Copper, Cd, and Zn
concentrations in invertebrates have been found to be more
strongly correlated with metal content of aufwuchs
(periphyton and associated embedded abiotic material that
serves as food for grazing benthic invertebrates) than with
water or sediment concentrations (Kiffney and Clements
1993; Beltman et al. 1999). Several experiments have
documented toxicity of dietary metals to mayflies. Growth
and emergence were reduced in Epeorus mayflies fed diatoms with elevated levels of copper or zinc (Hatakeyama
1989). Baetis tricaudatus mayflies experienced reduced
growth when fed metal-contaminated biofilm (Courtney
and Clements 2002; Carlisle and Clements 2003) and cadmium-dosed diatom mats (Irving et al. 2003). Reduced
�Arch Environ Contam Toxicol (2008) 54:466–472
growth from dietary exposure to metals may be due to food
avoidance (Hatakeyama 1989; Irving et al. 2003; Wilding
and Maltby 2006) or reduced food quality (Courtney and
Clements 2002; Carlisle and Clements 2003).
Metal toxicity is generally assumed to occur through
waterborne exposure and environmental regulations do no
take into account the potential impact of dietary sources of
metals to aquatic organisms. In instances where dietary
exposures exert their own toxicity or interact with waterborne exposures, water quality criteria and standards may
underprotect organisms in aquatic environments. Future
studies on the effects of dietary versus aqueous exposure,
for both early and late instars of aquatic invertebrates, may
help explain differences between laboratory toxicity tests
and field studies.
Acknowledgments This study was supported by EPA region 8 and
by US Fish and Wildlife Service Federal Aid Grant F-243. The
authors wish to thank Daria Hansen for her assistance with the tests,
and Dr. William Clements whose comments greatly improved this
manuscript.
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�
https://cpw.cvlcollections.org/files/original/667fb5d763d65c171dc27d8de14d45e1.pdf
6adf3c97b412a4fe1fb1b83dc307dd7c
PDF Text
Text
Curriculum vitae
Adam G. Hansen, Ph.D.
11 December 2024
CURRENT APPOINTMENT
2024-present. Senior Aquatic Research Scientist (class V), Lake and Reservoir Ecology
Colorado Parks and Wildlife, 317 W. Prospect Rd., Fort Collins, CO 80526
Phone: (970) 472-4432; Email: adam.hansen@state.co.us
EDUCATION
Ph.D. 2014. Aquatic and Fishery Sciences, University of Washington, Seattle, WA.
B.S. 2008. Fishery Biology, Colorado State University, Fort Collins, CO.
RESEARCH INTERESTS
Aquatic ecology; Bioenergetics modeling; Food webs; Lake and reservoir management;
Limnology; Population dynamics; Predator-prey interactions; Salmonid ecology and
conservation; Sport fish harvest management;
OTHER APPOINTMENTS
2015-2024.
2017-2023.
2013-2015.
2009-2013.
2009.
2007-2008.
Aquatic Research Scientist IV, Lake and Reservoir Ecology: Colorado Parks and
Wildlife, Fort Collins, CO.
Affiliate Faculty Member: Department of Fish, Wildlife, and Conservation
Biology, Colorado State University, Fort Collins, CO.
Research Scientist Engineer III: Washington Cooperative Fish and Wildlife
Research Unit (WACFWRU), University of Washington, Seattle, WA.
Graduate Fellow and Research Assistant: WACFWRU, School of Aquatic and
Fishery Sciences, University of Washington, Seattle, WA.
Research Associate I: Fish Physiological Ecology and Stream Fish Ecology
Laboratories, Department of Fish, Wildlife, and Conservation Biology, Colorado
State University, Fort Collins, CO.
Aquatic Research Technician: Colorado Division of Wildlife, Steamboat Springs,
CO.
REFEREED PUBLICATIONS
In Press
38. Chao Guo, Wei Li, Shiqi Li, Chuansong Liao, Jie Ke, Xingwei Chi, A.G. Hansen, Chuanbo Guo,
and Jiashou Liu. In press. Density-dependent effects of zooplanktivorous thin sharpbelly
(Toxabramis swinhonis) on plankton assemblages and water quality: implications for lake
rehabilitation. Water Biology and Security.
37. Lepak, J.M., A.G. Hansen, B.M. Johnson, K. Battige, E.T. Cristan, C.J. Farrell, W.M. Pate, K.B.
Rogers, A.J. Treble, and T.W. Walsworth. In press. Cyclical multi-trophic-level responses to a
volatile, introduced forage fish: learning from four decades of food web observation to
inform management. Fisheries.
2024
36. Shiqi Li, Chao Guo, Chuansong Liao, Jie Ke, A.G. Hansen, Xuefeng Shi, Jiashou Liu, Tanglin
Zhang, E. Jeppesen, and Wei Li. 2024. Improvement of water quality through coordinated
�multi-trophic level biomanipulations: application to a subtropical emergency water supply
lake. Science of the Total Environment 955:176888.
35. Lepak, J.M., W.M. Pate, P. Cadmus, A.G. Hansen, K.D. Gallaher, and D. Silver. 2024.
Response of an invasive aquatic crustacean to the fish toxicant rotenone. Lake and
Reservoir Management 40:330-337.
34. Hansen, A.G., J.M. Lepak, E.I. Gardunio, and T. Eyre. 2024. Evaluating harvest incentives for
suppressing a socially-valued, but ecologically-detrimental, invasive fish predator. Fisheries
Management and Ecology 31:e12699.
33. Farrell, C.J., A.G. Hansen, M.M. Brandt, C.M. Myrick, and B.M. Johnson. 2024. An evaluation
of the relative size, body condition, and survival of triploid walleye in the wild. North
American Journal of Fisheries Management 44:172-188.
2023
32. Lepak, J.M., A.G. Hansen, E.T. Cristan, and D. Williams. 2023. Rainbow smelt (Osmerus
mordax) influence on walleye (Sander vitreus) recruitment decline: mtDNA evidence
supporting the predation hypothesis. Journal of Fish Biology 103:1543-1548.
31. Hansen, A.G., M.W. Miller, E.T. Cristan, C.J. Farrell, P. Winkle, M.M. Brandt, K.D. Battige,
and J.M. Lepak. 2023. Gill net catchability of walleye (Sander vitreus): are provincial
standards suitable for estimating adult density outside the region? Fisheries Research
266:106800.
30. Hansen, A.G., C.J. Farrell, and B.M. Johnson. 2023. Simulated effects of imperfect sterile
sport fish stocking on persistence of fertile fish in new exploited populations. North
American Journal of Fisheries Management 43:908-934 (Feature Article).
29. Lepak, J.M., B.A. Wolff, B.M. Johnson, M.B. Hooten, and A.G. Hansen. 2023. Predicting
sport fish mercury contamination in heavily managed reservoirs: implications for human
and ecological health. PLOS ONE 18(8):e0285890.
28. Hansen, A.G., A.K. McCoy, G.P. Thiede, and D.A. Beauchamp. 2023. Pelagic food web
interactions in a large invaded ecosystem: implications for reintroducing a native top
predator. Ecology of Freshwater Fish 32:552-570.
27. Chao Guo, Shiqi Li, Jie Ke, Chuansong Liao, A.G. Hansen, E. Jeppesen, Tanglin Zhang,
Wei Li, and Jiashou Liu. 2023. The feeding habits of small-bodied fishes mediate the
strength of top-down effects on plankton and water quality in shallow subtropical lakes.
Water Research 233:119705.
2022
26. Hansen, A.G., E.T. Cristan, M.M. Moll, M.W. Miller, E.I. Gardunio, and J.M. Lepak. 2022.
Factors influencing early growth of juvenile tiger trout stocked into subalpine lakes as
biocontrol and to enhance recreational angling. Fishes 7:342.
25. Chao Guo, Shiqi Li, Wei Li, Chuansong Liao, Tanglin Zhang, Jiashou Liu, Lin Li, Jiaxin Sun,
Xingwei Cai, and A.G. Hansen. 2022. Spatial variation in the composition and diversity of
fishes inhabiting an artificial water supply lake, Eastern China. Frontiers in Ecology and
Evolution 10:921082.
24. Cristan, E.T., A.G. Hansen, and J.M. Lepak. 2022. Effects of ethanol preservation on larval
and fingerling walleye and gizzard shad body size. North American Journal of Fisheries
Management 42:874-881.
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�23. Farrell, C.J., B.M. Johnson, A.G. Hansen, C.A. Myrick, E.C. Anderson, T.A. Delomas, A.D.
Schreier, and J.P. Van Enennaam. 2022. Cytological and molecular approaches for ploidy
determination: results from a wild walleye population. North American Journal of Fisheries
Management 42:849-856.
22. Hansen, A.G., J.A. Gardner, K.A. Connelly, M. Polacek, and D.A. Beauchamp. 2022. Resource
use among top-level piscivores in a temperate reservoir: implications for a threatened
coldwater specialist. Ecology of Freshwater Fish 31:469-491.
21. Chao Guo, Wei Li, Shiqi Li, Zhan Mai, Tanglin Zhang, Jiashou Liu, A.G. Hansen, Lin Li, Xingwei
Cai, and B.J. Hicks. 2022. Manipulation of fish community structure effectively restores
submerged aquatic vegetation in a shallow subtropical lake. Environmental Pollution
292:118459.
20. Farrell, C.J., B.M. Johnson, A.G. Hansen, and C.A. Myrick. 2022. Induced triploidy reduces
mercury bioaccumulation in a piscivorous fish. Canadian Journal of Fisheries and Aquatic
Sciences 79:202-212 (Editor’s Choice Award).
19. Lepak, J.M., A.G. Hansen, M.B. Hooten, D. Brauch, and E.M. Vigil. 2022. Rapid proliferation
of the parasitic copepod Salmincola californiensis (Dana) on kokanee salmon, Oncorhynchus
nerka (Walbaum), in a large Colorado reservoir. Journal of Fish Diseases 45:89-98 (Cover
story for journal issue).
2021
18. Rohan, S.K., D.A. Beauchamp, T.E. Essington, and A.G. Hansen. 2021. Merging empirical and
mechanistic approaches to modeling aquatic visual foraging using a generalizable visual
reaction distance model. Ecological Modeling 457:109688.
2019
17. Hansen, A.G. 2019. Size-dependent retention of pelagic-oriented kokanee in multimesh gill
nets. North American Journal of Fisheries Management 39:921-932.
16. Litz, M.N.C., J.A. Miller, R.D. Brodeur, E.A. Daly, L.A. Weitkamp, A.G. Hansen, and A.M.
Claiborne. 2019. Energy dynamics of subyearling Chinook salmon reveal the importance of
piscivory to short term growth during early marine residence. Fisheries Oceanography
28:273-290.
15. Hansen, A.G., J.S. Thompson, L.N. Hargis, D. Brauch, and B.M. Johnson. 2019. Predatory
threat of introduced yellow perch in a salmonid-dominated reservoir food web. North
American Journal of Fisheries Management 39:172-190.
2018
14. Hansen, A.G., J.A. Gardner, K.A. Connelly, M. Polacek, and D.A. Beauchamp. 2018. Trophic
compression of lake food webs under hydrologic disturbance. Ecosphere 9(6):e02034.
13. Spanjer, A.R., P.W. Moran, K.A. Larsen, L.A. Wetzel, A.G. Hansen, and D.A. Beauchamp.
2018. Juvenile coho salmon growth and health in streams across an urbanization gradient.
Science of the Total Environment 625:1003-1012.
2017
12. Johnson, B.M., W.M. Pate, and A.G. Hansen. 2017. Energy density and dry matter content in
Page | 3
�fish: new observations and an evaluation of some empirical models. Transactions of the
American Fisheries Society 146:1262-1278.
11. Borin, J.M., M.L. Moser, A.G. Hansen, C. Donoghue, D.A. Beauchamp, C. Pruitt, S.C. Corbett,
J.L. Ruesink, and B. Dumbauld. 2017. Energetic requirements of the North American green
sturgeon (Acipenser medirostris) feeding on burrowing shrimp (Neotrypaea californiensis) in
estuaries: importance of temperature, reproductive investment, and residence time.
Environmental Biology of Fishes 100:1561-1573.
2016
10. Hansen, A.G., J.G. Gardner, D.A. Beauchamp, R. Paradis, T.P. Quinn. 2016. Recovery of
sockeye salmon in the Elwha River, Washington after dam removal: dependence of smolt
production on the resumption of anadromy by landlocked kokanee. Transactions of the
American Fisheries Society 145:1303-1317.
9. Sorel, M.H., A.G. Hansen, and D.A. Beauchamp. 2016. Trophic feasibility of reintroducing
anadromous salmonids in three reservoirs on the North Fork Lewis River, Washington: prey
supply and consumption demand of resident fishes. Transactions of the American Fisheries
Society 145:1331-1347.
8. Sorel, M.H., A.G. Hansen, K.A. Connelly, A.C. Wilson, E.D. Lowery, and D.A. Beauchamp.
2016. Predation by northern pikeminnow and tiger muskellunge on juvenile salmonids in a
high-head reservoir: implications for anadromous fish reintroductions. Transactions of the
American Fisheries Society 145:521-536.
2015
7. Hovel, R.A., D.A. Beauchamp, A.G. Hansen, and M.H. Sorel. 2015. Development of a
bioenergetics model for the threespine stickleback Gasterosteus aculeatus. Transactions of
the American Fisheries Society 144:1311-1321.
6. Hansen, A.G., and D.A. Beauchamp. 2015. Latitudinal and photic effects on diel foraging and
predation risk in freshwater pelagic ecosystems. Journal of Animal Ecology 84:532-544.
2014
5. Hansen, A.G., and D.A. Beauchamp. 2014. Effects of prey abundance, distribution, visual
contrast and morphology on selection by a pelagic piscivore. Freshwater Biology 59:23282341.
4. Garcia, R.L., A.G. Hansen, M. Chan, and G.E. Sanders. 2014. Gyrodactylid Ectoparasites in a
population of rainbow trout (Oncorhynchus mykiss). The Journal of the American
Association for Laboratory Animal Science 53:92-97.
2013
3. Hansen, A.G., D.A. Beauchamp, and E.R. Schoen. 2013. Visual prey detection responses of
piscivorous trout and salmon: effects of light, turbidity, and prey size. Transactions of the
American Fisheries Society 142:854-867.
2. Hansen, A.G., D.A. Beauchamp, and C.M. Baldwin. 2013. Environmental constraints on
piscivory: insights from linking ultrasonic telemetry to a visual foraging model for cutthroat
trout. Transactions of the American Fisheries Society 142:300-316.
Page | 4
�2012
1. Lepak, J.M., K.D. Kinzli, E.R. Fetherman, W.M. Pate, A.G. Hansen, E.I. Gardunio, C.N.
Cathcart, W.L. Stacy, Z.E. Underwood, M.M. Brandt, C.M. Myrick, and B.M. Johnson. 2012.
Manipulation of growth to reduce mercury concentrations in sport fish on a whole-system
scale. Canadian Journal of Fisheries and Aquatic Sciences 69:122-135.
BOOK CHAPTERS
3. Beauchamp, D.A., A.G. Hansen, and D. Parrish. 2024. Chapter 7: Coldwater fish in large
standing waters. In Standard methods for sampling North American freshwater fishes (2nd
edition). Edited by S.A. Bonar, W.A. Hubert, and D.W. Willis. American Fisheries Society,
Bethesda, Maryland.
2. Hansen, A.G. In press. Rainbow Smelt (Osmerus mordax, Mitchell). Fishes of Colorado,
Colorado Parks and Wildlife, Denver.
1. Hansen, A.G. In press. Tiger Trout (Salvelinus fontinalis × Salmo trutta). Fishes of Colorado,
Colorado Parks and Wildlife, Denver.
PUBLICATIONS IN REVIEW OR REVISION
4. Walsworth, T.E., A.G. Hansen, and J.M. Lepak. Submission pending. Alternate ecosystem
states in a predator-prey system supported by an invasive forage fish. Canadian Journal of
Fisheries and Aquatic Sciences.
3. Chao Guo, Wei Li, A.G. Hansen, Shiqi Li, Jie Ke, Chuansong Liao, Jing Yuan, Chuanbo Guo,
Jiashou Liu. Submission pending. Diverse foraging in small-bodied fishes: effects on water
quality and submerged macrophytes in shallow subtropical lake ecosystems. NPJ Clean
Water.
2. Hansen, A.G., J.M. Lepak, W.M. Pate, D. Brauch, and B.W. Avila. Submitted. Not just water
over the dam: upstream ecosystem disruption following reoperation for environmental
flows. Ecological Applications.
1. Farrell, C.J., B.M. Johnson, A.G. Hansen, C.M. Myrick, and B.W. Avila. In revision. Induced
sterility illuminates the effects of reproduction on growth. Canadian Journal of Fisheries and
Aquatic Sciences.
TECHNICAL REPORTS
19. J.M. Lepak, A.G. Hansen, T.E. Walsworth, W.M. Pate, and C.J. Farrell. Lake and reservoir
research. 2024. Annual report. Colorado Parks and Wildlife, Aquatic Research Section, Fort
Collins, CO. 196 pages.
18. Hansen, A.G., J.M. Lepak, W.M. Pate, and C.J. Farrell. Lake and reservoir research. 2023.
Annual summary report. Colorado Parks and Wildlife, Aquatic Research Section, Fort Collins,
CO. 85 pages.
17. Farrell, C.J., B.M. Johnson, C.A. Myrick, and A.G. Hansen. 2023. Triploid walleye: a new
frontier for nonnative predator management in the west. Colorado State University,
Department of Fish, Wildlife, and Conservation Biology. Final Report to Colorado Parks and
Wildlife. January 5th, 2023. 169 pages.
16. Hansen, A.G., J.M. Lepak, E.T. Cristan, W.M. Pate, and C.J. Farrell. Coldwater lake and
reservoir research projects. 2022. Annual summary report. Colorado Parks and Wildlife,
Page | 5
�Aquatic Research Section, Fort Collins, CO. 42 pages.
15. Hansen, A.G., J.M. Lepak, E.T. Cristan, W.M. Pate, and C.J. Farrell. Coldwater lake and
reservoir research projects. 2021. Annual summary report. Colorado Parks and Wildlife,
Aquatic Research Section, Fort Collins, CO. 151 pages.
14. Silver, D.B., B.M. Johnson, W.M. Pate, A.G. Hansen, and K. Christianson. 2021. History and
outcomes of opossum shrimp (Mysis diluviana) introductions in Colorado. Colorado Parks
and Wildlife, Technical Publication Number 58. 39 pages plus appendices and data.
13. Hansen, A.G. Coldwater lake and reservoir research projects. 2020. Annual summary report.
Colorado Parks and Wildlife, Aquatic Research Section, Fort Collins, CO. 75 pages.
12. Hansen, A.G. Coldwater lake and reservoir research projects. 2018. Annual summary report.
Colorado Parks and Wildlife, Aquatic Research Section, Fort Collins, CO. 85 pages.
11. Hansen, A.G., M. Polacek, K.A. Connelly, J.R. Gardner, and D.A. Beauchamp. 2017. Food web
interactions in Kachess and Keechelus Reservoirs, Washington: implications for threatened
adfluvial bull trout and management of water storage. Washington Cooperative Fish and
Wildlife Research Unit. Final report to Washington Department of Ecology. 67 pages.
10. Clark, C.P., S. Ball, S. Burgess, A.G. Hansen, and D.A. Beauchamp. 2017. Growth,
distribution, and abundance of pelagic fishes in Lake Washington: March and October 2016.
Washington Cooperative Fish and Wildlife Research Unit report #WACFWRU-17-01. 39
pages.
9. Hansen, A.G., J.R. Gardner, and D.A. Beauchamp. 2015. Growth, distribution, and
abundance of pelagic fishes in Lake Washington: March and October 2015. Washington
Cooperative Fish and Wildlife Research Unit report #WACFWRU-16-01. 30 pages.
8. Hansen, A.G., K.A. Connelly, and D.A. Beauchamp. 2015. Growth, distribution, and
abundance of pelagic fishes in Lake Washington: March and October 2014. Washington
Cooperative Fish and Wildlife Research Unit report #WACFWRU-15-01. 29 pages.
7. Hansen, A.G., and D.A. Beauchamp. 2015. Evaluation of factors affecting bull trout and
kokanee production in Kachess and Keechelus Reservoirs, Yakima River Basin, Washington.
Washington Cooperative Fish and Wildlife Research Unit. Final Report to Washington
Department of Ecology. 43 pages.
6. Beauchamp, D.A., A. McCoy, and A.G. Hansen. 2014. Quantifying pelagic food web
interactions in Lake Tahoe: a road map for re-introduction of Lahontan cutthroat trout.
Washington Cooperative Fish and Wildlife Research Unit. Final report (2012-2013) to the
U.S. Fish and Wildlife Service.
5. Beauchamp, D.A., A. McCoy, and A.G. Hansen. 2014. Baseline data collection in preparation
for a localized mysid reduction experiment in Lake Tahoe. Washington Cooperative Fish and
Wildlife Research Unit. Final report (2012-2013) to the U.S. Fish and Wildlife Service.
4. Hansen, A.G., D.A. Beauchamp, and E. Lowery. 2014. Growth, distribution, and abundance
of pelagic fishes in Lake Washington: March and October 2013. Washington Cooperative
Fish and Wildlife Research Unit report #WACFWRU-14-01.
3. Hansen, A.G., D.A. Beauchamp, and E. Lowery. 2013. Growth, distribution, and abundance
of pelagic fishes in Lake Washington: March-April and October 2012. Washington
Cooperative Fish and Wildlife Research Unit report #WACFWRU-13-01.
2. Johnson, B.M., J. Butteris, C.M. Clapp, S.D. Cossey, C.C. Deguelle, M.J. Dodrill, R.E. Dritz,
D.A. Falconi, R.T. Fortier, T.L. Goodin, A.G. Hansen, and 15 others. 2009. Effects of an
Page | 6
�anticipated illegal introduction of walleye into Blue Mesa Reservoir, Colorado. Final report
to Colorado Parks and Wildlife. Colorado State University, Fort Collins, CO.
1. Hansen, A.G., and K.T. Bentley. 2008. Inventory of fishes inhabiting Spottlewood, Graves,
and Sand Creeks on Meadow Springs Ranch and Soapstone Prairie Natural Area, Larimer
County, CO. Final report to the City of Fort Collins (Natural Resources Department), and
Colorado Parks and Wildlife. Colorado State University, Fort Collins, CO.
PROFESSIONAL PRESENTATIONS
2024
67. Beauchamp, D.A., A.G. Hansen (primary presenter), and D.L. Parrish. Chapter 7: Coldwater
fish in large standing waters. American Fisheries Society Annual Meeting. Honolulu, Hawaii.
Symposium: What’s new? Standard Methods for Sampling North American Freshwater
Fishes. September 17th, 2024.
66. Beauchamp, D.A., A.G. Hansen (primary presenter), and D.L. Parrish. Chapter 7: Coldwater
fish in large standing waters. Poster submission for American Fisheries Society Annual
Meeting. Honolulu, Hawaii. September 16th, 2024.
65. Walsworth, T.E., A.G. Hansen, and J.M. Lepak. Untangling drivers of cyclic walleye
dynamics. Utah Chapter of the American Fisheries Society Annual Meeting. St. George,
Utah. February 5th, 2024.
2023
64. Lepak, J.M., D. Winkelman, A.G. Hansen, J. Ewert, and T. Eyre. Sterile tiger muskellunge
(Esox lucius x E. masquinongy) as undesirable fish species control agents. Colorado State
University Cooperative Fish and Wildlife Research Unit annual review. May 3rd, 2023. Fort
Collins, CO.
2022
63. Farrell, C.J., B.M. Johnson, A.G. Hansen, B.W. Avila, and C.A. Myrick. Does reproduction
limit lifetime growth? Evidence from a population of mixed-ploidy walleye. PERCIS
V. September 22nd, 2022. České Budějovice, Czechia.
62. Farrell, C.J., B.M. Johnson, A.G. Hansen, B.W. Avila, and C.A. Myrick. Does reproduction
limit lifetime growth? 152nd Meeting of the American Fisheries Society. August 25th, 2022.
Spokane, WA.
61. Hansen, A.G., and D. Brauch. Achieving coexistence: a case history of Colorado’s premier
kokanee-lake trout fishery. 152nd Meeting of the American Fisheries Society. August 25th,
2022. Spokane, WA.
60. Beauchamp, D.A., R. Johnson, B. Jensen, and A.G. Hansen. Environmental and ecological
constraints on smolt production for salmonids introduced above dams. 152nd Meeting of
the American Fisheries Society. August 23rd, 2022. Spokane, WA.
59. Hansen, A.G., and C.J. Farrell. Are walleye a boost or bane to Colorado fisheries? A
continental division. 152nd Meeting of the American Fisheries Society. August 22nd, 2022.
Spokane, WA.
58. Hansen, A.G., and C. Tucker. Integrating angler dynamics and walleye biology to explore
alternative harvest strategies for broodstock in Pueblo Reservoir. Colorado Parks and
Wildlife Southeast Region Conservation Days. May 11th, 2022.
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�57. Farrell, C.J., B.M. Johnson, A.G. Hansen, C.A. Myrick, M.M. Brandt, and J. White. Results
from the CPW-CSU triploid walleye project. Colorado Parks and Wildlife Northeast Region
Biology Days. April 28th, 2022.
56. Hansen, A.G. Assessment of walleye broodstocks in Chatfield, Cherry Creek and Pueblo
reservoirs. Colorado Parks and Wildlife Northeast Region Biology Days. April 28 th, 2022.
55. Hansen, A.G., and J.M. Lepak. The dynamic history of walleye and their forage base—
rainbow smelt—in Horsetooth Reservoir. Colorado Parks and Wildlife Northeast Region
Biology Days. April 28th, 2022.
54. Jackson, K.N., C.J. Farrell, B.M. Johnson, C.A. Myrick, A.G. Hansen, and Y. Kanno. Prey
selection of diploid and triploid walleye in a prey-limited system. Colorado State University
Celebrate Undergraduate Research and Creativity Showcase. April 21st, 2022. Fort Collins,
Colorado.
53. Jackson, K., C.J. Farrell, B.M. Johnson, C.M. Myrick, and A.G. Hansen. Prey selection of
diploid and triploid walleye in a prey-limited system. Colorado/Wyoming Chapter of the
American Fisheries Society Annual Meeting, March 3rd, 2022.
52. Farrell, C.J., B.M. Johnson, A.G. Hansen, and C.M. Myrick. Triploid walleye: some
considerations for mangers. Colorado/Wyoming Chapter of the American Fisheries Society
Annual Meeting, March 3rd, 2022.
2021
51. Hansen, A.G., and D. Brauch. Population dynamics of lake trout in Blue Mesa Reservoir,
Colorado: new insights from linking a simple population model to long-term survey data.
American Fisheries Society, Western Division Virtual Meeting hosted by Utah Chapter.
Symposium: Advancements in the Ecology and Management of Nonnative Lake Trout. May
14th, 2021.
2020
50. Hansen, A.G., C.J. Farrell, and B.M. Johnson. Simulated effects of triploid walleye induction
rate on diploid persistence in a newly stocked population. Biology Committee Webinar,
Upper Colorado River Endangered Fish Recovery Program. September 3rd, 2020.
49. Farrell, C.J., A.G. Hansen, B.M. Johnson, and C.M. Myrick. Does ploidy affect mercury
bioaccumulation in walleye? American Fisheries Society, Virtual Annual Meeting. September
2020.
48. Hansen, A.G. How low can we go? Simulated effects of triploid walleye induction rate on
the probability of diploid persistence in a newly stocked population. Virtual meeting among
representatives of CO, UT, and the USFWS. March 23rd, 2020.
47. Farrell, C., B.M. Johnson, C.M. Myrick, A.G. Hansen, M. Brandt, and J. White. A preliminary
assessment of adult diploid and triploid walleye in Narraguinnep Reservoir, Colorado.
Annual meeting of Colorado/Wyoming Chapter of the American Fisheries Society. Laramie,
WY. February 25th, 2020 (Voted best student paper).
46. Farrell, C.J., B.M. Johnson, C.A. Myrick, A.G. Hansen, M.M. Brandt, and J. White. Induced
triploidy for managing invasive walleye: study overview and preliminary findings. Colorado
Parks and Wildlife Aquatic Biologist Meeting, Evergreen, Colorado. January 22nd, 2020.
45. Hansen, A.G., and D. Brauch. Population dynamics of lake trout in Blue Mesa Reservoir: new
Page | 8
�insights from confronting simple models with long-term survey data. Colorado Parks and
Wildlife Aquatic Biologist Meeting, Evergreen, Colorado. January 22nd, 2020.
44. Brauch, D., and A.G. Hansen. Blue Mesa Reservoir lake trout management update. Colorado
Parks and Wildlife Aquatic Biologist Meeting, Evergreen, Colorado. January 22 nd, 2020.
43. Hansen, A.G., E.I. Gardunio, and T. Eyre. Population dynamics of smallmouth bass in two
upper Colorado River basin reservoirs: short-term responses to an angler harvest incentive
program. Upper Colorado River Basin Endangered Fish Recovery Program Annual
Researcher’s Meeting. Durango, Colorado. January 14th, 2020.
2019
42. Farrell, C.J., B.M. Johnson, C.A. Myrick, A.G. Hansen, M.M. Brandt, and J. White. Induced
triploidy for managing invasive walleye: study overview and preliminary findings.
Presentation to Colorado Parks and Wildlife senior advisory staff, Brush, Colorado.
December 10th, 2019.
41. Hansen, A.G., B.M. Johnson, and C.J. Farrell. How low can we go? Simulated effects of
triploid walleye induction rate on the probability of establishing a new diploid population.
Presentation to Colorado Parks and Wildlife senior advisory staff, Brush, Colorado.
December 10th, 2019.
40. Hansen, A.G., and D.A. Beauchamp. Pelagic food web interactions in Lake Tahoe:
considerations for the reintroduction of Lahontan cutthroat trout. Joint AFS-TWS Annual
Meeting, Reno, NV. October 3rd, 2019.
39. Hansen, A.G., and D. Brauch. Assessing emerging threats to kokanee in Blue Mesa
Reservoir: illegally introduced yellow perch and gill lice. Colorado Parks and Wildlife
Coldwater Reservoir Management Meeting, Buena Vista, Colorado. March 3 rd, 2019.
38. Farrell, C., B.M. Johnson, C.M. Myrick, A.G. Hansen, M. Brandt, and J. White. Induced
triploidy for managing invasive walleye: study overview and preliminary findings. Annual
meeting of Colorado/Wyoming Chapter of the American Fisheries Society. Fort Collins, CO.
February 28th, 2019.
37. Hansen, A.G., and C. Tucker. Integrating angler dynamics and walleye biology to explore
alternative harvest strategies for broodstock in Pueblo Reservoir. Colorado Parks and
Wildlife Aquatic Biologist Meeting, Salida, Colorado. January 24th, 2019.
2018
36. M. Miller, E. Cristan, K. Paik, A. Smith, J. Wyer, K. Hall, C.A. Myrick, and A.G. Hansen. What
is limiting the growth of northern pike Esox lucius in College Lake? A bioenergetics
approach. Poster submission for Colorado-Wyoming Chapter of the America Fisheries
Society Annual Meeting, Laramie, Wyoming. February 2018.
35. Brauch, D, and A.G. Hansen. Riding a salmon “high”: factors contributing to a rebound of
Colorado’s premier kokanee salmon fishery. Colorado-Wyoming Chapter of the American
Fisheries Society Annual Meeting, Laramie, Wyoming. February 2018.
34. Hansen, A.G., E. I. Gardunio, and T. Eyre. Biological effectiveness of incentive-based harvest
tournaments for controlling nonnative piscivores in fluctuating coldwater reservoirs. Upper
Colorado River Basin Endangered Fish Recovery Program Annual Researcher’s Meeting.
Vernal, Utah. January 2018.
Page | 9
�33. Hansen, A.G., and E. I. Gardunio. Biological effectiveness of incentive-based harvest
tournaments for smallmouth bass in Ridgway Reservoir. Colorado Parks and Wildlife Aquatic
Biologist Meeting, Gunnison, Colorado. January 2018.
2017
32. Hansen, A.G. How will altered or more demanding water use regimes affect reservoir food
webs and fisheries? North American Lake Management Society Conference, Westminster,
Colorado. November 2017.
31. Hansen, A.G. Harvest tournaments: collaborating with anglers to reconcile native fish
conservation and warm water sport fishing in western Colorado. Invited speaker at the
Colorado State University student subunit of the American Fisheries Society. Fort Collins,
Colorado. October 2017.
30. Hansen, A.G., J.A. Gardner, K.A. Connelly, and M. Polacek, and D.A. Beauchamp. A
bioenergetics-based food web evaluation of factors affecting bull trout and kokanee
production in Kachess and Keechelus Reservoirs. Yakima Basin Science and Management
Conference. June 2017.
29. Litz, M.N.C, J.A. Miller, R.D. Brodeur, E.A. Daly, L.A. Weitkamp, and A.G. Hansen.
Energy dynamics and growth of juvenile Chinook salmon reveal the importance of piscivory
during early marine residence. 3rd PICES/ICES Early Career Scientist Conference. Busan,
Korea. May 2017.
28. Hansen, A.G. Model evaluation of an incentive-based fishing tournament for smallmouth
bass in Ridgway Reservoir, Colorado. Presentation to Area 18 Colorado Parks and Wildlife
managers, Montrose, Colorado. February 2017.
2016
27. Hansen, A.G. Environmental and behavioral controls on predator-prey interactions in large
lakes. Invited speaker at the Colorado State University student subunit of the American
Fisheries Society. Fort Collins, Colorado. October 2016.
26. Hansen, A.G., J.A. Gardner, K.A. Connelly, M. Polacek, and Beauchamp, D.A. Baseline food
web interactions in Lake Kachess: seasonal predation by northern pikeminnow and burbot
on prey important for bull trout. Yakima Basin Science and Management Conference. June
2016.
2015
25. Hansen, A.G., and D.A. Beauchamp. Reservoirs, irrigation demand, drought, and threatened
adfluvial bull trout in the Yakima River Basin, Washington. Salvelinus confluentus Curiosity
Society annual meeting. September 2015.
24. Hansen, A.G., and D.A. Beauchamp. Reservoirs, irrigation demand, drought, and threatened
adfluvial bull trout in the Yakima River Basin, Washington. American Fisheries Society
Annual Meeting. August 2015.
23. Hansen, A.G., D.A. Beauchamp, and M. Polacek. Food web structure of Kachess and
Keechelus Reservoirs: identifying and quantifying important interactions for bull trout.
Yakima Basin Science and Management Conference. June 2015.
22. Hansen, A.G., and D.A. Beauchamp. Reservoirs, irrigation demand, drought, and threatened
Page | 10
�adfluvial bull trout in the Yakima River Basin, Washington. Annual Washington Cooperative
Fisheries and Wildlife Research Unit meeting. April 2015.
21. Sorel, M.H., D.A. Beauchamp, and A.G. Hansen. Evaluating predation risk for reintroduced
anadromous salmonids in Merwin Reservoir on the Lewis River, Washington. Annual
Washington Cooperative Fisheries and Wildlife Research Unit meeting. April 2015.
20. Hansen, A.G., and D.A. Beauchamp. Evaluation of factors limiting bull trout and kokanee
production in Kachess and Keechelus Reservoirs, Yakima River Basin, Washington.
Presentation to Yakima River Basin Integrated Water Management Plan working group.
March 2015.
19. Hansen, A.G., and D.A. Beauchamp. Reservoirs, irrigation demand, drought, and threatened
adfluvial bull trout in the Yakima River Basin, Washington. Post-Doc Symposium, School of
Aquatic and Fishery Sciences, University of Washington. February 2015.
2014
18. Hansen, A.G., and D.A. Beauchamp. Environmental and behavioral controls on pelagic
predator-prey interactions: implications for the growth and survival of sockeye salmon in
Lake Washington. WDFW Brown Bag Lunch Seminar Series, Olympia, Washington.
December 2014.
17. Hansen, A.G., and D.A. Beauchamp. Effects of prey abundance, distribution, visual contrast,
and morphology on selection by a pelagic piscivore. Eco-Lunch Seminar, School of Aquatic
and Fishery Sciences, University of Washington. November 2014.
16. Beauchamp, D.A., A.G. Hansen, and E.R. Schoen. How the visual foraging environment
affects pelagic food webs. Invited seminar at the University of Vermont. October 2014.
15. Hansen, A.G., and D.A. Beauchamp. Effects of prey abundance, distribution, visual contrast,
and morphology on apparent selection by cutthroat trout in Lake Washington. Annual
Washington Cooperative Fisheries and Wildlife Research Unit meeting. April 2014 (Award
for best talk).
2013
14. Hansen, A.G. Persisting in the pelagic: environmental and behavioral controls on predatorprey interactions. Ph.D. defense seminar. School of Aquatic and Fishery Sciences, University
of Washington. December 2013.
2012
13. Schoen, E.R., D.A. Beauchamp, and A.G. Hansen. How do turbidity and fine-scale prey
density affect the foraging and capture success of Chinook salmon? Alaska Chapter of the
American Fisheries Society Annual Meeting. October 2012.
12. Rogers, K.B., A.G. Hansen, C. Kennedy, and B. Rosenlund. Using horizontal acoustic beaming
to evaluate cutthroat trout population size in backcountry lakes. Western Division of the
American Fisheries Society Annual Meeting. March 2012.
2011
11. Hansen, A.G., and D.A. Beauchamp. Effects of a temperature-oxygen squeeze on piscivory:
insights from linking a visual foraging model with ultrasonic telemetry of cutthroat trout.
Graduate Student Symposium, School of Aquatic and Fishery Sciences, University of
Page | 11
�Washington, Seattle, Washington. November 2011.
10. Hansen, A.G., D.A. Beauchamp, and C.M. Baldwin. Foraging of piscivorous cutthroat trout
tracked with ultrasonic telemetry in relation to seasonal shifts in reservoir stratification.
American Fisheries Society Annual Meeting. Invited symposium: Cognitive, Sensory, and
Behavioral Frontiers Exploring Fish Movement and Habitat Use. Seattle, Washington.
September 2011.
9. Beauchamp, D.A., A.G. Hansen, and E.R. Schoen. Developing visual foraging models as a
framework for predicting pelagic predation risk, foraging success and distribution. American
Fisheries Society National Meeting. Invited symposium: Cognitive, Sensory, and Behavioral
Frontiers Exploring Fish Movement and Habitat Use. Seattle, Washington. September 2011.
8. Hansen, A.G., D.A. Beauchamp, and C.M. Baldwin. Foraging of piscivorous cutthroat trout
tracked with ultrasonic telemetry in relation to seasonal shifts in reservoir stratification.
Society for Northwestern Vertebrate Biology and the Washington Chapter of the Wildlife
Society joint Annual Meeting. Special session for the Washington Cooperative Fish and
Wildlife Research Unit (School of Aquatic and Fishery Sciences, University of Washington).
Gig Harbor, Washington. March 2011.
2010
7. Stacy, W.L., J.M. Lepak, K.D. Kinzli, E.R. Fetherman, W.M. Pate, A.G. Hansen, E.I. Gardunio,
C.N. Cathcart, and Z.E. Underwood. Manipulation of sport fish growth to reduce mercury
bioaccumulation on a whole-lake scale. Western Division American Fisheries Society
Student Colloquium. Moscow, Idaho. December 2010.
6. Hansen, A.G., and D.A. Beauchamp. Light mediated reaction distance of Chinook salmon to
fish prey. Graduate Student Symposium, School of Aquatic and Fishery Sciences, University
of Washington, Seattle, Washington. November 2010.
5. Rogers, K.B, A.G. Hansen, C. Kennedy, and B. Rosenlund. Using hydroacoustics to evaluate
cutthroat trout population size in remote backcountry lakes. High Mountain Lakes
Symposium, Shepherdstown, West Virginia [via webcast]. October 28th, 2010.
4. Lepak, J.M., W.M. Pate, C.N. Cathcart, E.R. Fetherman, K.D. Kinzli, M.M. Brandt, W.L.
Stacy, Z.E. Underwood, E.I. Gardunio, and A.G. Hansen. Manipulation of sport fish growth to
reduce mercury bioaccumulation on a whole-lake scale. Colorado/Wyoming American
Fisheries Society Annual Meeting. Laramie, Wyoming. April 2010.
2009
3. Hansen, A.G., and D.A. Beauchamp. Visual foraging models: measuring the effects of light,
turbidity, and prey density on piscivory by coastal cutthroat trout. Graduate Student
Symposium, School of Aquatic and Fishery Sciences, University of Washington, Seattle,
Washington. November 2009.
2. Rogers, K.B, A.G. Hansen, C. Kennedy, and B. Rosenlund. Using hydroacoustics to evaluate
cutthroat trout population size in remote backcountry lakes. HTI Hydroacoustic Idea
Exchange. Bear Lake, Utah. June 2009.
2007
1. Hansen, A.G. Past and present population characteristics of a diverse sport fish community
in a small Colorado impoundment. Western Division American Fisheries Society Student
Page | 12
�Colloquium. Bozeman, Montana. October 2007.
OTHER CONTRIBUTIONS, NEWS & INTERVIEWS
Research on long-term population dynamics of lake trout and kokanee in Blue Mesa
Reservoir, Colorado highlighted in a story written by Erik Cristan. Title: Angler incentives:
Lucrative lake trout in Blue Mesa Reservoir. Colorado Outdoors Magazine,
September/October 2021, Vol. 70, No. 5.
Research on harvest management of walleye in Colorado highlighted in a story written by
Dan England. Title: Managing Walleye: One Minor Change Can Have a Big Impact. Colorado
Outdoors Magazine, July 2020 Fishing Guide, No. 29.
Colorado walleye research featured on FOX 31 News, Denver: Colorado Parks and Wildlife
conducts aquatic research despite single-digit temperatures, by Ashley Michels. Aired
October 30th, 2019. Link: https://kdvr.com/2019/10/30/cpw-conducts-aquatic-researchdespite-single-digit-temperatures/
Colorado walleye research featured on CBS 4 News, Denver: Wildlife scientists research
Colorado walleye in sunshine or winter weather, by Conor McCue. Aired October 30th, 2019.
Link: https://denver.cbslocal.com/2019/10/30/colorado-parks-wildife-walleye-scientists/
Interviewed by Wilbur Flachman for short story on fall turnover in high mountain lakes. Title:
True tales from the lying log. Thirst Colorado, September/October 2019, Vol. 4, No. 6.1.
News release highlighting Hansen et al. (2018), Ecosphere. Title: Intensive use of lake water
affects freshwater food webs. Released through the School of Aquatic and Fishery Sciences,
University of Washington. July 2nd, 2018.
Interviewed by Geoff Mueller, Senior Editor, The Drake Magazine, for primer on tiger trout
and tiger muskie research, management, and angling opportunities. Title: Going on safari: a
tail of two tigers. Summer 2018, Vol. 20, Issue 2.
Research pertaining to biological effectiveness of harvest incentives for controlling invasive
smallmouth bass highlighted in a story written by Dan England. Title: Bucket Biology.
Colorado Outdoors Magazine, May/June 2018, Vol. 67, No. 3.
Sorel, M.H., D.A. Beauchamp, and A.G. Hansen. 2015. Reintroducing native salmon above
formally impassable dams on the Lewis River. Washington State Lake Protection Agency.
WATERLINE, June 2015 issue.
TEACHING & STUDENT ADVISING
Graduate student committee member (2024-present): Lucca Sterrer. Advised by Dr. Derek
Houston, Department of Biology, Western Colorado University. Masters project title:
Exploring the effects of harmful algal blooms on the foraging patterns of kokanee salmon in a
freshwater ecosystem.
Graduate student committee member (2018-2023): Collin Farrell. Advised by Dr. Brett
Johnson and Dr. Chris Myrick, Department of Fish, Wildlife, and Conservation Biology,
Colorado State University. PhD project title: Triploid walleye: a new frontier for managing
coolwater predators in the west.
Co-instructor: FW496, Independent Study in Fishery Biology, Colorado State University (CSU;
spring 2017, fall 2017, spring 2018). Undergraduate course focused on field application and
interpretation of fisheries science principles through research on a long-term study lake.
Page | 13
�Undergraduate research conducted during this course resulted in numerous oral (4 total)
and poster (4 total) presentations at CSU’s student subunit of the American Fisheries Society,
Celebrate Undergraduate Research and Creativity Symposium, Multicultural Undergraduate
Research, Art and Leadership Symposium, and at the Colorado-Wyoming Chapter of the
American Fisheries Society Annual Meeting.
Guest-instructor: sampling field trip to College Lake for FW204 students, Introduction to
Fishery Biology, Colorado State University (fall 2017).
Advised and assisted with project development for Amy Duarte (Humboldt State University;
2014) and Haila Schultz (University of Puget Sound; 2015), two summer undergraduate
interns supported through the Joint Institute for the Study of the Atmosphere and Ocean
(JISAO) program at the University of Washington, Seattle.
Guest lecture: Implementing Bioenergetics Models in R. University of Washington, FISH
530, spring 2013 and 2015: Application of Bioenergetics Models to Aquatic Food Webs.
Graduate course taught by David A. Beauchamp.
Undergraduate teaching assistant: FW 301, Ichthyology Laboratory, Colorado State
University (fall 2006, spring 2007, spring 2008).
PROFESSIONAL SERVICE
Symposium organizer: Advancements in the Ecology and Management of Nonnative Lake
Trout. Western Division American Fisheries Society Annual Meeting. May 14th, 2020.
Associate Editor (April 2019-August 2021): North American Journal of Fisheries Management.
Editor (2016-2020): The Angler, newsletter for the Colorado/Wyoming Chapter of the
American Fisheries Society.
Anonymous reviewer (Journals = 23; Manuscripts = 53): Ecological Applications (1 ms);
Ecology and Evolution (2 ms); Ecology of Freshwater Fish (4 ms); Environmental Biology of
Fishes (3 ms); Environmental Pollution (1 ms); Fish and Fisheries (5 ms); Fisheries (3 ms);
Fisheries Oceanography (1 ms); FACETS (2 ms); Fisheries Research (2 ms); Hydrobiologia (1
ms); Journal of Fish Biology (3 ms); Lake and Reservoir Management (2 ms); Limnology and
Oceanography (2 ms); Movement Ecology (2 ms); NeoBiota (1 ms); North American Journal of
Fisheries Management (7 ms); Northwest Science (2 ms); PLOS ONE (1 ms); Scientific Reports,
Nature Research Group (1 ms); The Journal of the American Association for Laboratory
Animal Science (2 ms); The Open Fish Science Journal (1 ms); Transactions of the American
Fisheries Society (4 ms);
Past Treasurer, Vice President, and President (2007-2008) for Colorado State University
student subunit of the American Fisheries Society.
PROJECT COLLABORATIONS AND FUNDING
Upper Gunnison River Water Conservancy District: 63,148. Exploring the effects of harmful
algal blooms on the foraging patterns of kokanee in a freshwater ecosystem. Collaboration
Dr. Derek Houston, Dept. of Biology, Western Colorado University.
Colorado Species Conservation Trust Fund: $361,000. Evaluating tiger muskellunge as a
multi-purpose management tool: protecting native fish species from multiple conservation
threats. Collaboration with Dr. Jesse Lepak, Department of Fish, Wildlife, and Conservation
Biology, Colorado State University.
Page | 14
� Colorado Species Conservation Trust Fund: $182,000. Project extension: Triploid walleye: a
new frontier for managing cool water predators in the west. Collaboration with Dr. Brett
Johnson, Department of Fish, Wildlife, and Conservation Biology, Colorado State University.
Colorado Species Conservation Trust Fund: $182,000. Triploid walleye: a new frontier for
managing cool water predators in the west. Collaboration with Dr. Brett Johnson,
Department of Fish, Wildlife, and Conservation Biology, Colorado State University.
Washington State Department of Ecology: $78,334. Effects of pumping dead storage on food
web interactions and adfluvial bull trout in Kachess and Keechelus Reservoirs, Yakima River
Basin, Washington.
Page | 15
�
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Bibliography of literature on mountain whitefish, Prosopium williamsoni
September, 2001
Colden V. Baxter
Ph.d candidate, Fisheries
Dept. Fisheries and Wildlife
Oregon State University
Corvallis, OR 97331
References:
Baxter, C. V. 2002. Fish movement and assemblage dynamics in a Pacific Northwest
riverscape. Ph.D. Oregon State University, Corvallis, OR.
Baxter, G. T., and J. R. Simon. 1970. Wyoming fishes.
Begout Anras, M. L., P. M. Cooley, R. A. Bodaly, L. Anras, and R. J. P. Fudge. 1999.
Movement and habitat use by lake whitefish during spawning in a boreal lake:
integrating acoustic telemtry and geographic information systems. Transactions of
the American Fisheries Society 128: 939-952.
Bergersen, E. P. 1973. Fish production and movements in the lower Logan River, Utah.
Pages 183 pp. Department of Wildlife Resources. Utah State University, Logan,
Utah.
Bergstedt, L. C., and E. P. Bergersen. 1997. Health and movements of fish in response to
sediment sluicing in the Wind River, Wyoming. Canadian Journal of Fisheries
and Aquatic Sciences 54: 312-319.
Brown, C. J. D. 1952. Spawning habits and early development of the mountain whitefish,
Prosopium williamsoni, in Montana. Copeia : 109-113.
Brown, L. G. 1972. Early life history of the mountain whitefish Prosopium williamsoni
(Girard) in the Logan River, Utah. Pages 47 pp. Department of Wildlife
Resources. Utah State University, Logan Utah.
Davies, R. W., and G. W. Thompson. 1976. Movements of mountain whitefish
(Prosopium williamsoni) in the Sheep River watershed, Alberta. Journal of the
Fisheries Research Board of Canada 33: 2395-2401.
Dill, W. A., and L. Shapalov. 1939. An unappreciated California game fish, the Rocky
Mountain whitefish, Prosopium williamsoniI. California Fish and Game 25: 226227.
Donald, D. B. 1987. Assessment of the outcome of eight decades of trout stocking in the
mountain national parks, Canada. North American Journal of Fisheries
Management 7: 545-553.
DosSantos, J. M. 1985. Comparative food habits and habitat selection of mountain
whitefish and rainbow trout in the Kootenai River, Montana. Department of Fish
and Wildlife Management. Montana State University, Bozeman, MT.
Ellison, J. P. 1980. Diets of mountain whitefish, Prosopium williamsoni (Girard) and
brook trout, Salvelinus fontinalis (Mitchill), in the Little Walker River, Mono
County, California. California Fish and Game 66: 96-104.
�Erickson, J. 1966. Summarization of life history and management studies on the Rocky
Mountain Whitefish in the Snake River drainage, 1952-1964. Administrative
Report Project : 0166-23-5501, Wyoming Game and Fish Commission.
Gaffney, J. J. 1960. Utilization of mountain whitefish, Coregonus williamsoni, in
Montana. Proceedings of the Montana Academy of Sciences 19: 92-106.
Godfrey, H. 1955. On the ecology of Skeena River whitefishes, Coregonus and
Prosopium. Journal of the Fisheries Research Board of Canada 12: 499-528.
Goodnight, W. H., and T. C. Bjornn. 1971. Fish production in two Idaho streams.
Transactions of the American Fisheries Society : 769-780.
Haas, G. 1998. Bibliography of mountain whitefish literature.
Hagen, H. K. 1970. Age, growth and reproduction of the mountain whitefish in Phelps
Lake, Wyoming. Pages 399-415 in C. C. Lindsey and C. S. Woods, eds. Biology
of Coregonid fishes. University of Manitoba Press, Winnepeg, MB, Canada.
Holt, R. D. 1960. Comparative morphometry of the mountain whitefish, Prosopium
williamsoni. Copeia : 192-200.
Ihnat, J. M., and R. V. Bulkley. 1984. Influence of acclimation temperature and season on
acute temperature preference of adult mountain whitefish, Prosopium williamsoni.
Environmental Biology of Fishes 11: 29-40.
Laasko, M. 1951. Food habits of the Yellowstone whitefish Prosopium williamsoni
cismontanus (Jordan). Transactions of the American Fisheries Society 80: 99-109.
Liebelt, J. E. 1970. Studies on the behavior and life history of the mountain whitefish
(Prosopium williamsoni Girard). Pages 45 pp. Department of Zoology. Montana
State University, Bozeman, MT.
McHugh, J. L. 1940. Food of the Rocky Mountain whitefish. Journal of the Fisheries
Research Board of Canada 5: 131-137.
McHugh, J. L. 1941. Growth of the Rocky Mountain whitefish. Journal of the Fisheries
Research Board of Canada 5: 337-343.
McPhail, J. D. 1999. The mountain whitefish (Prosopium williamsoni): a review of the
distribution, biology, and life history of a neglected recreational species. Bull
trout conference attended by Stephanie Gunckel, McPhail gave this talk, Calgary?
Naesje, T. F., B. Jonsson, and O. T. Sandlund. 1986. Drift of cisco and whitefish larvae in
a Norwegian River. Transactions of the American Fisheries Society 115: 89-93.
Nelson, J. S. 1962. Effects on fishes of changes within the Kananaskis River system.
Pages 107 pp. Department of Zoology. University of Alberta, Edmonton, Alberta.
Northcote, T. G., and G. L. Ennis. 1994. Mountain whitefish biology and habitat use in
relation to compensation and improvement possibilities. Reviews in Fisheries
Science 2: 347-371.
Northcote, T. G., and D. W. Wilke. 1963. Underwater census of stream fish populations.
Transactions of the American Fisheries Society 92: 145-151.
Overton, C. K., D. A. Grove, and D. W. Johnson. 1978. Food habits of Rocky Mountain
whitefish (Prosopium williamsoni) from the Teton River in relation to their age
and growth. Northwest Science 52: 226-232.
Pettit, S. W., and R. L. Wallace. 1975. Age, growth, and movement of mountain
whitefish, Prosopium williamsoni, in the North Fork Clearwater River, Idaho.
Transactions of the American Fisheries Society : 68-76.
�Pontius, R. W., and M. Parker. 1973. Food habits of the mountain whitefish, Prosopium
williamsoni (Girard). Transactions of the American Fisheries Society : 764-773.
Rajagopal, P. K. 1979. The embryonic development and the thermal effects on the
development of the mountain whitefish, Prosopium williamsoni (Girard). Journal
of Fish Biology 15: 153-158.
Ricker, W. E. 1941. The consumption of young sockeye salmon by predaceous fish.
Journal of the Fisheries Research Board of Canada 5: 293-313.
Rockhold, A., and J. D. Berg. 1995. Mountain whitefish monitoring project in the Lochsa
River drainage of northern Idaho. Pages 44 pp. U.S. Fish and Wildlife Service,
Idaho Fishery Resource Office, Ahsahka, Idaho.
Scott, W. B., and E. J. Crossman. 1973. Freshwater fishes of Canada. Fish. Res. Board
Can. Bull. 184: 966.
Shepard, B. B., J. J. Fraley, W. T.M., and P. J. Graham. 1982. Flathead River Fisheries
Study-1982. Environmental Protection Agency Region VIII, Water Division
through the Flathead River Basin Environmental Impact Study, Denver, CO,
USA.
Shepard, B. B., and P. J. Graham. 1983. Flathead River Fisheries Study-1983.
Environmental Protection Agency Region VIII, Water Division through the
Flathead River Basin Environmental Impact Study, Denver, CO, USA.
Stalnaker, C. B., R. E. Gresswell, and R. E. Siefert. 1974. Early life history and feeding
of young mountain whitefish. Pages 46pp. Prepared for U.S. Environmental
Protection Agency, Washington, D.C.
Swanson, S. M., R. Schryer, R. Shelast, P. J. Kloepper-Sams, and J. W. Owens. 1994.
Exposure of fish to biologically treated bleached-kraft mill effluent. 3. Fish
habitat and population assessment. Environmental Toxicology and Chemistry 13:
1497-1507.
Thompson, G. E., and R. W. Davies. 1976. Observations on the age, growth,
reproduction, and feeding of mountain whitefish (Prosopium williamsoni) in the
Sheep River, Alberta. Transactions of the American Fisheries Society : 208-219.
Wydoski, R. S. 2001. Life history and fecundity of mountain whitefish from Utah
streams. Transactions of the American Fisheries Society 130: 692-698.
Wydoski, R. S., and R. R. Whitney. 1979. Inland fishes of Washington. University of
Washington Press, Seattle, WA, USA.
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U.S. Fish & Wildlife Service
News Release
Idaho Fish and Wildlife Office • Boise - Chubbuck - Spokane
1387 S. Vinnell Way, Boise, Idaho 83709 • http://www.fws.gov/idaho
208-378-5243 (Boise Headquarters) • 208-378-5262 (fax)
for immediate release
April 6, 2010
CONTACT: Steve Duke, 208-378-5345
Mountain Whitefish Occurring in the Big Lost River, Idaho
Will Not Receive ESA Protection
Cooperative conservation efforts encouraged to continue
The U.S. Fish and Wildlife Service announced today that its review of the status of mountain whitefish
(Prosopium williamsoni) in Idaho’s Big Lost River concludes that protection under the federal Endangered
Species Act (ESA) is not warranted.
The status review finds that the mountain whitefish in the Big Lost River is not a listable entity as defined by
the ESA. The ESA defines a vertebrate animal as a “species” if the Service determines it is a separate species, subspecies or Distinct Population Segment (DPS). According to the statute, a population cannot be considered for the
protections of the ESA unless it qualifies as a listable entity. Based on the best available scientific information and
genetic data, as well as information presented for Service review, the mountain whitefish in the Big Lost River is
not a separate species, subspecies or DPS compared to other mountain whitefish found in the West and therefore
cannot be considered for the protections of the ESA.
Genetic data provided to the Service demonstrated that many populations of mountain whitefish show a high
degree of genetic structuring, which indicates they are geographically isolated. Although the Service considered
this information to be indicative of relative reproductive isolation of various populations, it was not sufficient to
identify the mountain whitefish in the Big Lost River as a new species or subspecies, and they do not have other
characteristics that suggest they may be a different species. Although the mountain whitefish in the Big Lost
River do not qualify for listing under the ESA, the Service notes the mountain whitefish in the Big Lost River are
an important component of the native diversity of that natural system, and emphasizes that its finding should not
be construed to mean the fish are not worthy of preservation on a local level.
“The Service strongly supports continued cooperative conservation of mountain whitefish and its habitat in the
Big Lost River basin,” Gary Burton, acting Idaho State Supervisor for the Service, said.
Working with others to conserve, protect and enhance fish, wildlife, plants and their habitats
for the continuing benefit of the American people.
�Western Watersheds Project first petitioned the Service to list the Big Lost River mountain whitefish in 2006.
After reviewing the petition in 2007, the Service determined that the petitioned action was not warranted, based
on a lack of substantial information indicating the mountain whitefish in the Big Lost River may be a separate
species, subspecies, or DPS. The Western Watersheds Project then filed a complaint in 2008 challenging the
Service’s finding. In response to that lawsuit, the United States District Court in Boise, Idaho, directed the Service
to conduct a status review of mountain whitefish in the Big Lost River and, within one year, issue a finding on
whether the population should be protected as a threatened or endangered species. The court ordered the Service
to make a final listing determination by March 31, 2010.
Mountain whitefish, sometimes known as mountain herring, are members of the Salmonidae family. The
species is found throughout mountainous areas of northwestern North America in both the United States and
Canada. It is known to occur in the States of Washington, Oregon, Idaho, Wyoming, Montana, Colorado, Utah,
Nevada and California. The preferred habitat for mountain whitefish is cold water streams and lakes, and some
populations are restricted to lakes or isolated sink basins.
Mountain whitefish in the Big Lost River reside in a closed basin (sink) in southeast Idaho. The Big Lost River
valley is the only one of five sink drainages in Idaho that contains mountain whitefish. Additional populations of
mountain whitefish occur in other sink drainages, such as the Lahontan Basin in California and Nevada, and the
Bonneville Basin in Utah.
For further information, please contact Steve Duke, U.S. Fish and Wildlife Service, Idaho Fish and Wildlife
Office, by mail at 1387 S. Vinnell Way, Room 368, Boise, ID 83709; by telephone at 208-378-5345; by facsimile
at 208-378-5262; or by electronic mail at: fw1srbocomment@fws.gov. Persons who use a telecommunications
device for the deaf (TDD) may call the Federal Information Relay Service (FIRS) at 800-877-8339.
- FWS The mission of the U.S. Fish and Wildlife Service is working with others to conserve, protect and enhance fish,
wildlife and plants and their habitats for the continuing benefit of the American people. We are both a leader and
trusted partner in fish and wildlife conservation, known for our scientific excellence, stewardship of lands and
natural resources, dedicated professionals and commitment to public service. For more information on our work
and the people who make it happen, visit www.fws.gov.
�
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COLORADO
Parks and Wildlife
Department of Natural Resources
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Tawni Brooks Firestone, Ph.D.
Phone: 303.435.6214 | Email: Tawni.Firestone@state.co.us
Current Position: Aquatic Research Scientist, Toxicology and Epidemiology
Colorado Parks and Wildlife
Faculty Affiliate
Colorado State University
EDUCATION
Doctor of Philosophy in Fish, Wildlife,
and Conservation Biology: 2018−2022
Colorado State University
Dissertation Title: Detection and Transmission of
Renibacterium salmoninarum in Colorado Inland
Trout
Bachelor of Science in Biology: 2009-2013
Minor: Neuroscience
University of Wisconsin – Oshkosh
High Honors 2012-2013.
Gamma Sigma Alpha National Honor Society.
PUBLICATIONS (Published in Peer-Reviewed Scientific Journals; * Corresponding Author)
1. Dils R, TBR Firestone*, PA Schaffer, ER Fetherman, and DL Winkelman. 2025. Renibacterium
salmoninarum in Chinook Salmon (Oncorhynchus tshawytscha) following intraperitoneal injection:
Description of histological progression and bacterial load dynamics. Diseases of Aquatic Organisms – In
Press
2. Riepe TB*, ZE Hooley-Underwood, and M Johnson. 2024. Temperature tolerance of larval Flannelmouth
Sucker acclimated to three temperatures. Fishes 9: 181.
3. Riepe TB*, Z Hooley-Underwood, RE McDevitt, A Sralik, and P Cadmus. 2023. Increased density of
Bluehead Sucker Catostomus discobolus larvae decreases critical thermal maximum. North American
Journal of Fisheries Management 43:1135−1142.
4. Riepe TB*, ER Fetherman, B Neuschwanger, T Davis, A Perkins, and DL Winkelman. 2023. Vertical
transmission of Renibacterium salmoninarum in Cutthroat Trout (Oncorhynchus clarkii). Journal of Fish
Diseases 46(4):303−319.
5. Riepe TB*, BW Avila, and DL Winkelman. 2022. Effects of 17α-ethinylestradiol and Density on Juvenile
Fathead Minnow Survival and Body Size Journal of Aquatic Pollution and Toxicology 6:60.
6. Kowalski DA*, R Cordes, TB Riepe, JD Drennan, and A Treble. 2022. Prevalence and distribution of
Renibacterium salmoninarum, the causative agent of bacterial kidney disease, in wild trout fisheries in
Colorado. Diseases of Aquatic Organisms 149:109−120.
7. Riepe TB*, V Vincent, V Milano, ER Fetherman, and DL Winkelman. 2021. Evidence for the use of mucus
swabs to detect Renibacterium salmoninarum in Brook Trout. Pathogens 10(4) doi: 1004.0460.
8. Johnson PTJ*, DM Calhoun, WE Moss, T McDevitt-Galles, TB Riepe, J Dallas, T Parchman, C Feldman, J
Cropanzo, J Bowerman, and J Koprivnikar. 2020. The cost of travel: how dispersal ability limits local
adaption in host-parasite interactions. Journal of Evolutionary Biology 34(3):512−524.
9. Johnson PTJ*, DM Calhoun, TB Riepe, T McDevitt-Galles, and J Koprivnikar. 2019. Community
disassembly and disease: realistic − but not randomized − biodiversity losses inhibit parasite transmission.
Proceedings of the Royal Society B 286(1902) doi: 2019.0260.
10. Riepe TB*, DM Calhoun, and PTJ Johnson. 2019. Comparison of direct and indirect techniques to detect
intestinal parasites in newts (Salamandridae Taricha). Diseases of Aquatic Organisms 134:137–146.
11. Johnson PTJ*, DM Calhoun, TB Riepe, and J Koprivnikar. 2019. Chance or choice? Understanding
selection by parasites in multi-host communities. International Journal for Parasitology 49:407–415.
12. Calhoun DM*, LK Leslie, TB Riepe, TJ Achatz, T McDevitt-Galles, VV Tkach, and PTJ Johnson. 2019.
Patterns of Clinostomum spp. infection in fishes and amphibians: integration of field, genetic, and
experimental approaches. Journal of Helminthology 94:1–12.
13. Koprivnikar J*, TB Riepe, DM Calhoun, and PTJ Johnson. 2018. Whether larval amphibians school does
not affect the parasite aggregation rule: testing the effects of host spatial heterogeneity in field and
experimental studies. Oikos 127:99–110.
Tawni B R Firestone
�PUBLICATIONS – In Review
1. Firestone TBR, ER Fetherman, K Huyvaert, J Drennan, RE McDevitt, B Yeatts, and DL Winkelman.
Leveraging detection uncertainty to estimate Renibacterium salmoninarum infection status among multiple
tissues and assays – Submitted to PLOS One
2. Firestone TBR, ER Fetherman, and DL Winkelman. Non-lethal detection of Renibacterium salmoninarum
in Cutthroat Trout Oncorhynchus clarkii comparing mucus, blood, and ovarian fluid samples to kidney
tissues – Submitted to Journal of Aquatic Animal Health
PUBLICATIONS – In Preparation
1. Firestone TBR, R Walters, T Swarr, B Felt, K Morben, M Baker, M May, and M McConville. Challenges in
eradication efforts for Zebra Mussels from Highline Lake, Colorado using EarthTec QZ.
2. Anderson J, DL Winkelman, TBR Firestone, JR Jasman, LB Barber, A Jastrow, R Fitzpatrick, and AM
Vajda. Estrogenic responses of fish exposed to wastewater impacted streams of the Colorado Front Range
3. Firestone TBR, M McConville, M Johnson, and P Cadmus. Measurement of cortisol from Cutthroat Trout
after magnesium chloride exposures and critical thermal maxima
4. Firestone TBR, R Dils, D Woller, A Held, and A Erenberger. The importance of a nuanced approach to
developing aquatic species-specific temperature standards: A review
5. Fetherman ER, R Brock, R Dils, BW Avila, and TBR Firestone. 2025. Susceptibility of XX, XY, and YY
Brook Trout Salvelinus foninalis to Renibacterium salmoninarum infection.
6. Firestone TBR, P Cadmus, A Townsend, J Anderson, and S Brinkman. Changes of thermal tolerance in
Brook Trout, Cutthroat Trout, and Mountain Whitefish after acute aqueous metal exposures
PROFESSIONAL REPORTS
1. Cadmus P, TBR Firestone, D Woller, and R Dils. 2024. Water Pollution Studies. Annual Report. Colorado
Parks and Wildlife, Aquatic Research Section.
2. Rust A, M McConville, M May, J Logan, T Swarr, J Ewert, T Riepe, P Cadmus and R Harris. 2024.
Examining changes to an alpine wetland and freshwater ecosystem of Straight Creek, Colorado. Colorado
Parks and Wildlife White Paper.
3. Cadmus P, TB Riepe, and D Woller. 2023. Water Pollution Studies. Annual Report. Colorado Parks and
Wildlife, Aquatic Research Section.
4. Cadmus P, TB Riepe, and M Bolerjack. 2022. Water Pollution Studies. Annual Report. Colorado Parks and
Wildlife, Aquatic Research Section.
5. Riepe TB. 2022. Transmission and detection of Renibacterium salmoninarum in Colorado inland trout.
Colorado State University, Ph.D. Dissertation.
6. Quynn K and TB Riepe. 2022. Research & Scholarly Writing Support: Institution Survey 2021-22. Colorado
State University Writes.
7. Fetherman ER, B Neuschwanger, and TB Riepe. 2022. Sport Fish Research Studies. Annual Report.
Colorado Parks and Wildlife, Aquatic Research Section.
8. Fetherman, ER, B Neuschwanger, TB Riepe, and BW Avila. 2021. Sport Fish Research Studies. Annual
Report. Colorado Parks and Wildlife, Aquatic Research Section.
9. Riepe TB and K Quynn. 2021. Institution Survey of Research Writing Support Programming for Graduate
Students, Postdocs, and Faculty – Report of Findings 2019-2020. Colorado State University Writes.
10. Riepe TB and SP Bombaci. 2020. University Survey of Diversity, Equity, and Inclusion Programs and
Contacts. Colorado State University.
11. Fetherman, ER, B Neuschwanger, BW Avila, and TB Riepe. 2020. Sport Fish Research Studies. Annual
Report. Colorado Parks and Wildlife, Aquatic Research Section.
12. Riepe TB and ER Fetherman. 2020. Transmission of Renibacterium salmoninarum (Bacterial kidney
disease) in hatchery-reared fish. Colorado Parks and Wildlife Fact Sheet.
Tawni B R Firestone
�PRESENTATIONS
1. Speaker: Firestone TBR and P Cadmus. 2025. Ecotoxicology: A Necessity for Biodiversity Conservation.
Aquatic Research Section. February 25, 2025. Virtual.
2. Invited Speaker: Firestone TBR. 2024. Integrating aquatic toxicology and disease research for ecosystem
health and species conservation. Western University, American Fisheries Society. Gunnison, CO. December
12, 2024.
3. Co-Author: Woller DU, TBR Firestone, and DL Winkelman. 2024. Comparing field-based temperature
standards to laboratory derived standards for Bluehead and Flannelmouth Suckers. Desert Fish Council
Meeting. Grand Junction, Colorado. November 21, 2024.
4. Speaker: Riepe TB, R Walters, M Baker, T Swarr, B Felt, K Morben, M McConville, M May, and A Rust.
2024. The use of EarthTec QZ® treatment in a Colorado Reservoir to control invasive Zebra Mussels.
American Fisheries Society National Meeting. Honolulu, HI. September 19, 2024.
5. Speaker: Riepe TB. 2024. Addressing complex toxicology challenges in aquatic ecosystems. American
Fisheries Society National Meeting. Honolulu, HI. September 17, 2024.
6. Co-Author: Hooley-Underwood ZE and TB Riepe. 2024. Effects of temperature eon early life stages of
Bluehead and Flannelmouth suckers; A summary of thermal studies conducted by Dr. Tawni Riepe. Dolores
River M&R team retreat. Durango, Colorado. April 8, 2024.
7. Speaker: Riepe TB, ZE Hooley-Underwood. 2024. Temperature tolerance of Flannelmouth Sucker larvae
acclimated to three temperatures. Colorado/Wyoming Chapter of the American Fisheries Society. Laramie,
Wyoming. February 29, 2024
8. Co-Author: Dils R, TB Riepe, P Schaffer, DL Winkelman, and ER Fetherman. 2024. Pathogenesis of
Renibacterium salmoninarum in Chinook Salmon following intraperitoneal injection: Description of disease
progression by qPCR and histopathology. Colorado/Wyoming Chapter of the American Fisheries Society.
Laramie Wyoming. February 29, 2024.
9. Co-Author: McDevitt R, TB Riepe, P Schaffer, C Wells, ER Fetherman, and DL Winkelman. 2024. The
susceptibility of Chinook Salmon to two strains of Renibacterium salmoninarum. Colorado/Wyoming
Chapter of the American Fisheries Society. Laramie, Wyoming. February 29, 2024.
10. Invited Speaker: Riepe TB. 2023. Bluehead Sucker and Flannelmouth Sucker Temperature Research
Update. Range wide 3-Species Conservation Team Meeting. Virtual. November 13, 2023.
11. Speaker: Riepe TB. 2023. What’s in your water samples? Colorado Parks and Wildlife Hatchery Manager’s
Meeting. Vail, Colorado. September 13, 2023.
12. Invited Speaker: McClaren J, TB Riepe, and A Harris. 2023 Student involvement in the Western Division
of AFS and how the WDAFS Early Career Professionals committee can help as students finish their degree
programs. Western Division of the American Fisheries Society. Boise, Idaho. May 10, 2023.
13. Speaker: Hatchery water quality testing and data analysis reports. Colorado Parks and Wildlife Hatchery
Staff Meeting. Pueblo, Colorado. May 2, 2023.
14. Invited Speaker: TB Riepe. The American Fisheries Society 2023 Chapter Annual Meeting Leadership
Update for the Western Division AFS. Colorado/Wyoming Chapter of the American Fisheries Society. Fort
Collins, Colorado. March 1, 2023.
15. Speaker: TB Riepe, RE McDevitt, A Sralik, and P Cadmus. Optimal temperature for egg development,
hatch success, larval survival, and thermal tolerance of Bluehead Suckers Catostomus discobolus.
Colorado/Wyoming Chapter of the American Fisheries Society. Fort Collins, Colorado. March 2, 2023.
16. Speaker: TB Riepe, RE McDevitt, ER Fetherman, and DL Winkelman. The effects of Renibacterium
salmoninarum infection on Brook Trout population characteristics. Colorado/Wyoming Chapter of the
American Fisheries Society. Fort Collins, Colorado. March 2, 2023.
17. Co-Author: McConville M, A Rust, M May, R Harris R, TB Riepe, and P Cadmus. What’s in your water?
32 years of River Watch water quality data. Colorado/Wyoming Chapter of the American Fisheries Society.
Fort Collins, Colorado. March 2, 2023.
18. Speaker: Riepe TB, McDevitt RE, Sralik A, and Cadmus P. Optimal temperatures for egg development,
hatch success, larval survival, and thermal tolerance of Bluehead Suckers Catostomus discobolus. Colorado
Parks and Wildlife Biologist Summit. Florissant, Colorado. January 19, 2023.
Tawni B R Firestone
�19. Invited Speaker: McConville M, and TB Riepe. Water quality testing and hatchery production water
sources. Colorado Parks and Wildlife Hatchery Manager’s Meeting. Loveland, Colorado. December 14,
2022.
20. Speaker: Riepe TB Transmission and detection of Renibacterium salmoninarum in Colorado inland trout.
Department of Fish, Wildlife, and Conservation Biology, Colorado State University Seminar. October 7,
2022.
21. Co-Author: Kowalski DA, RJ Cordes, TB Riepe, JD Drennan, and AJ Treble. 2022. Prevalence and
distribution of Renibacterium salmoninarum, causative agent of bacterial kidney disease, in wild trout
fisheries in Colorado. Wild Trout Symposium VIII. September 29, 2022. West Yellowstone, MT.
22. Symposium Organizer: Riepe TB, BW Avila, ER Fetherman, and DL Winkelman. Enhancing salmonid
disease management by understanding pathogen transmission and epidemiology. American Fisheries Society
National Meeting. Spokane, Washington. August 25, 2022.
23. Co-Author: Winkelman DL, TB Riepe, ER Fetherman, and BW Avila. 2022. Introduction to enhancing
salmonid disease management by understanding pathogen transmission. 152nd Annual Meeting of the
American Fisheries Society. Spokane, Washington. August 25, 2022.
24. Speaker: Riepe TB, ER Fetherman, and DL Winkelman. Horizontal and vertical transmission of
Renibacterium salmoninarum in Cutthroat Trout. 152nd Annual Meeting of the American Fisheries Society.
Spokane, Washington. August 25, 2022.
25. Co-Author: McDevitt R, TB Riepe, ER Fetherman, and DL Winkelman. The effects of Renibacterium
salmoninarum infection on Brook Trout population characteristics. 152nd Annual Meeting of the American
Fisheries Society. Spokane, Washington. August 25, 2022.
26. Speaker: Riepe TB, ER Fetherman, and DL Winkelman. Comparison of tissues for the detection of
Renibacterium salmoninarum in Cutthroat Trout. 151st Annual Meeting of the American Fisheries Society
National Meeting. Baltimore, Maryland. November 9, 2021.
27. Invited Speaker: Riepe TB. Bacterial kidney disease in Cutthroat Trout. Cutthroat Trout Chapter of Trout
Unlimited Quarterly Meeting. May 18, 2021.
28. Poster Presentation: Riepe TB, V Vincent, V Milano, ER Fetherman, and DL Winkelman. Evidence for the
use of mucus swabs to detect Renibacterium salmoninarum in Brook Trout. Western Division of the
American Fisheries Society. Virtual. May 14, 2021.
29. Poster Presentation: Riepe TB, V Vincent, V Milano, ER Fetherman, and DL Winkelman. Non-lethal
detections of Renibacterium salmoninarum (causing bacterial kidney disease) in Brook Trout (Salvelinus
fontinalis). Colorado/Wyoming Chapter of the American Fisheries Society. Virtual. February 24, 2021.
30. Speaker: Riepe TB, ER Fetherman, G Schisler, and DL Winkelman. Current results of CSU Renibacterium
salmoninarum experiments. Colorado Parks and Wildlife Hatchery Manager’s Meeting. Virtual. May 5,
2020.
31. Invited Speaker: Riepe TB, ER Fetherman, G Schisler, and DL Winkelman. Current results of CSU
Renibacterium salmoninarum experiments. Colorado Parks and Wildlife Aquatic Animal Health Staff
Meeting. Virtual. April 29, 2020.
32. Invited Speaker: Riepe TB, ER Fetherman, G Schisler, and DL Winkelman. Current results of CSU
Renibacterium salmoninarum experiments, and thoughts on future projects. Colorado Parks and Wildlife
Senior Staff Quarterly Meeting. Virtual. April 14, 2020.
33. Speaker: Riepe TB, ER Fetherman, DL Winkelman. Horizontal transmission of Renibacterium
salmoninarum in hatchery-reared inland trout. Colorado/Wyoming Chapter of the American Fisheries
Society. Laramie, Wyoming. February 26, 2020.
34. Speaker: Riepe TB, ER Fetherman, DL Winkelman. Comparison of tissues for the detection of
Renibacterium salmoninarum, the causative agent of bacterial kidney disease. Colorado/Wyoming Chapter
of the American Fisheries Society. Laramie, Wyoming. February 26, 2020.
35. Invited Speaker: Riepe TB. A SoFISHticated Disease. Vice President of Research Graduate Fellowship
Conference. Colorado State University. February 10, 2020.
36. Poster Presentation: Riepe TB, V Vincent, V Milano, ER Fetherman, and DL Winkelman. Non-lethal
methods used to detect Renibacterium salmoninarum in Brook Trout. Graduate Student Showcase. Colorado
State University. November 12, 2019.
Tawni B R Firestone
�37. Invited Speaker: Riepe TB. Greenback Cutthroat Trout and the future of bacterial kidney disease. Annual
Colorado Cooperative Fish and Wildlife Research Unit Coordinating Meeting. Fort Collins, Colorado. March
28, 2019.
38. Speaker: Riepe TB, E Fetherman, and D Winkelman. Past, present, and future of bacterial kidney disease.
Colorado/Wyoming Chapter of the American Fisheries Society. Fort Collins, Colorado. February 28, 2019.
39. Invited Speaker: Riepe TB, B Avila, and E Fetherman. Upcoming research projects. Colorado Aquaculture
Association. Nathrop, Colorado. February 1, 2019.
40. Poster Presentation: Garfield P, TB Riepe, and PTJ Johnson. Parasite abundance in different life stages of
newts (Taricha torosa and Taricha granulosa). University of Colorado-Boulder Science Discovery Program.
Boulder, Colorado. July 26, 2018.
41. Poster Presentation: Johnson PTJ, DM Calhoun, TB Riepe, T McDevitt-Galles, and J Koprivnikar. How
changes in host community diversity and composition affect parasite transmission. American Society of
Parasitologists. Boulder, Colorado. June 2018.
42. Poster Presentation: Gitlin S, TB Riepe, DM Calhoun, PTJ Johnson. In vitro cultivation for the parasite
Ribeiroia ondatrae. University of Colorado-Boulder Science Discovery Program. Boulder, Colorado. July
28, 2017.
43. Invited Speaker: Riepe TB. Yucatan Black Howler Monkeys: Endangered Species of Central America.
Atlas Preparatory Academy. Milwaukee, Wisconsin. October 15, 2015.
STUDENTS AND RESEARCH ASSOCIATES
• Master Student Committee Member (Jordan Anderson): Committee member for master student in the
Colorado Cooperative Fish and Wildlife Research Unit at Colorado State University studying the effects of
estradiol below wastewater treatment plants on Fathead Minnows. Fall 2024 - Present
• Research Associate (Riley Dils): Research support for research associate developing temperature tolerance
standards for adult Flannelmouth Sucker, Bluehead Sucker, and Roundtail Chub using an electrocardiogram
analysis. Summer 2024- Present.
• Master Student Committee Member (Darian Woller): Committee member for master student in the
Colorado Cooperative Fish and Wildlife Research Unit studying temperature criteria for field caught
Flannelmouth Sucker, Bluehead Sucker, and Roundtail Chub. Fall 2023 – Present.
• Honor Student Committee Member (Riley Dils): Committee member for an undergraduate honors student.
Aided in planning, designing, and executing a laboratory experiment focused on the pathogenesis of
Renibacterium salmoninarum in Chinook Salmon. Spring 2023 − Fall 2023.
• Master Student Liason (Rebecca McDevitt): Research and analytical support for a master’s student in the
Colorado Cooperative Fish and Wildlife Research Unit studying strain differentiation of Renibacterium
salmoninarum and effects of bacterial kidney disease on multiple strains of trout species in Colorado.
Colorado State University. Summer 2022 − Present.
• Honor Student Committee Member (Brooke Yeatts): Research support for an undergraduate honors
student. Aided in planning, designing, and executing a laboratory experiment focused on fish survival after
injections of Renibacterium salmoninarum. Colorado State University. Spring 2021 − Fall 2022.
PROFESSIONAL APPOINTMENTS
1. Faculty Affiliate – Colorado State University, Fish, Wildlife, and Conservation Biology. March 2023 –
Present.
2. American Fisheries Society Hutton Junior Fisheries Biology Program Judge. February 2023; February 2024;
February 2025
Tawni B R Firestone
�TEACHING
• Co-Instructor: Mastering your professional portfolio: CV/Resume and cover letter review workshop.
American Fisheries Society National Meeting. September 18, 2024.
• Guest Lecturer: Diseases and Toxicants in Aquaculture. FW402 – Fish Culture. Colorado State University:
Fish, Wildlife, and Conservation Biology. April 24, 2024.
• Guest Lecturer: Aquatic Disease Ecology and Toxicology. FW 467/567 – Wildlife Disease Ecology.
Colorado State University: Fish, Wildlife, and Conservation Biology. October 24, 2023.
• Using Program R in Fisheries Science: A Primer – Continuing Education Instructor: This half-day
course was intended for early career professionals and students who want to use R to estimate basic
population dynamic rates. Students used R to construct and apply an age-length key to estimate ages of
individual fish from their lengths, fit a von Bertalanffy growth function (VBGF) and fit a catch curve
analysis. Western Division of the American Fisheries Society. Boise, Idaho. May 10, 2023.
• Guest Lecturer: Diseases and Toxicants in Aquaculture. FW402 – Fish Culture. Colorado State University:
Fish, Wildlife, and Conservation Biology. April 21, 2023.
• Co-Instructor: FW467/567 Wildlife Disease Ecology: Evaluations of concepts in disease ecology including
parasite diversity, host responses to infection, host-parasite coevolution, disease transmission, host
population responses, community ecology of disease, drivers of disease emergence, and disease intervention
and management strategies. Colorado State University: Fish, Wildlife, and Conservation Biology. Fall 2021.
• Guest Lecturer: Diseases in Aquaculture: Fish Culture. Colorado State University: Fish, Wildlife, and
Conservation Biology. Spring 2021.
• Graduate Teaching Assistant FW402 Fish Culture Lecture and Laboratory: Foundations of fish culture
with an emphasis on system design and assembly, water quality measurement and management, and general
culture techniques. Colorado State University: Fish, Wildlife, and Conservation Biology. Online. Spring
2021.
• Beginner R Workshop Instructor: Uploading, Plotting, and Analyzing Data – Colorado Chapter of The
Wildlife Society Annual Conference. Virtual. February 17, 2021.
• Advanced R Workshop Instructor: Spatial and Occupancy Analysis. Colorado Chapter of The Wildlife
Society Annual Conference. Virtual. February 17, 2021.
• Beginner R Workshop Instructor: Uploading, Plotting, and Analyzing Data – Colorado State University:
Fish, Wildlife, and Conservation Biology. January 15, 2021
• Tips for Writing Manuscripts Workshop Instructor: Colorado State University: Fish, Wildlife and
Conservation Biology Graduate Student Organization. December 11, 2020.
• Advanced R Workshop Instructor: Spatial and Occupancy Analysis. Colorado State University – Pueblo:
Wildlife and Natural Resources. December 3, 2020.
• Youth Group Mentor: Academic support for middle school and high school students from ThornCreek
Church. 2017 – 2020.
• Science Discovery Mentor: High School Honor Students Emerging into the Sciences: University of
Colorado – Boulder. 2017, 2018.
INVITED PEER REVIEWS
• Biology, March 2025
• Biology. January 2025.
• Fishes. February 2024.
• Fishes. January 2024.
• Fishes. January 2024
• Biology. January 2024.
• Parasitology Research. August 2018.
Tawni B R Firestone
�CERTIFICATIONS
• Daniels Leadership – June 2023
• Colorado Department of Agriculture Pesticide Certification – July 2022
• American Fisheries Society Rotenone Application Certification – May 2022
• USGS Defensive Driving Certification − February 2022
• Florida Boating Safety License − July 2021
• Watercraft Inspection and Decontamination Certification − 2017
COURSEWORK AND CONTINUING EDUCATION
• Strategic Leadership Training – December 2024 (Daniels Leadership Training, 2 hours)
• Daniels Leadership Training – May – June 2023 (6 days of training through University of Denver, Daniels
College of Business)
• Colorado Department of Agriculture Pesticide Training – July 2022
• Planning and Executing Successful Rotenone and Antimycin Projects – May 2022 (American Fisheries
Society)
• Models for Ecological Data (ESS 575 − 4 credits)
• Fish and Wildlife Population Dynamics (FW 562 − 3 credits)
• Applied Generalized Regression (STAT 581A – 2 credits)
• Concepts in GIS (NR 505 − 4 credits)
• Wildlife Disease Ecology (FW 567 − 3 credits)
• Introduction to Statistical Methods (STAT 301 − 3 credits)
• Conservation Genetics of Wild Populations (FW 558 − 3 credits)
• Stream Biology and Ecology (BZ 471 − 3 credits)
• Writing Scientific Manuscripts (MIP 666 − 3 credits)
FUNDING AND AWARDS
• 2024 Species Conservation Trust Fund, Colorado Parks and Wildlife: “Flannelmouth Sucker and Bluehead
Sucker recruitment into the Gunnison River: A molecular-based approach” (Awarded $364,500)
• 2024 Best Mentor Award. Colorado/Wyoming Chapter of the American Fisheries Society Annual Meeting.
February 29, 2024.
• 2024 Philanthropy at Work, Colorado Parks and Wildlife: “Impacts of road salts on Cutthroat Trout and
Boreal Toad Populations” (Awarded: $9,00)
• 2023 Travel Grant. Colorado/Wyoming Chapter of the American Fisheries Society. March 2023 (Awarded
$2,000)
• 2021 Robert J Behnke − Rocky Mountain Flycaster’s Research Fellowship (Awarded $5,905).
• 2021 Colorado State University Writes Internship (Awarded $1,500).
• 2021 Best Poster Presentation. Colorado/Wyoming Chapter of the American Fisheries Society Annual
Meeting. February 24, 2021.
• 2020 Colorado State University Writes Internship (Awarded $1,500).
• 2020 Cutthroat Chapter of Trout Unlimited – Steven Bailey Memorial Research Fellowship
(Awarded $3,989).
• 2020 Vice President of Research Graduate Fellowship – Colorado State University (Awarded $4,000).
• 2019 West Denver Chapter – Trout Unlimited Graduate Fellowship (Awarded $3,800).
• 2019 Gregory L. Bonham Memorial Scholarship, Colorado State University (Awarded $1,200).
• 2019 – 2021 Species Conservation Trust Fund, Colorado Parks and Wildlife: “Transmission of
Renibacterium salmoninarum, the causative agent of bacterial kidney disease, in Colorado native greenback
cutthroat trout” (Grant Proposal: Awarded $325,046).
Tawni B R Firestone
�ANALYTICAL AND LABORATORY SKILLS
• Pathogen detection methods: Microscopic and morphologic techniques, bacterial and viral culture,
biochemical assays for pathogen identification, enzyme-linked immunosorbent assay, direct and indirect
fluorescent antibody test, quantitative and single-round polymerase chain reaction, and DNA extractions.
environmental DNA collection and analysis
• Water quality, metals, and analyte analysis: Collect and analyze metals and nutrients with flow injection
analysis, inductively coupled plasma analysis, and high-performance liquid chromatography. Analyze water
hardness and alkalinity with titration.
• Analytical methods: Bayesian statistics, information theoretic statistics, hierarchical analysis, SIR pathogen
transmission modelling, catch curve analysis, occupancy modeling, logistic and linear regression, species
distribution modeling, Arc GIS, R Markdown/R Studio, Program MARK, and Python.
• Fish sampling methods: Backpack, bank, and raft electrofishing, gill net sampling, dipnet, sein, and
plankton tow sampling.
PROFESSIONAL COMMITTEE CHAIRS
• 2024 – Present Secretary/Treasurer. Colorado/Wyoming Chapter of the American Fisheries Society.
• 2023 – 2024 Budget Committee Co-chair. Colorado/Wyoming Chapter of the American Fisheries Society.
• 2022 – 2023 Conference Arrangements Chair. Colorado/Wyoming Chapter of the American Fisheries
Society.
• 2021 − Present Early Career Professional Committee Chair. Western Division of the American Fisheries
Society.
• 2022 − 2024 Board Member. ThornCreek Church, Thornton, Colorado.
• 2021 − 2024 Student Liaison Committee Chair. Colorado/Wyoming Chapter of the American Fisheries
Society.
MEDIA INTERACTIONS
• December 2020 Trout Disease Study Progressing. Colorado Parks and Wildlife Press Release.
• September 2020 Electrofishing the Fraser River. Winter Park Times.
• February 2013 Sturgeon Spearing Season Wraps Up. The Northwestern.
OTHER RESEARCH CONTRIBUTIONS (Listed in Acknowledgements for Research Support)
• Adams, CM, DL Winkelman, PA Schaffer, DL Villeneuve, JE Cavallin, M Ellman, KS Rodriguez, and RM
Fitzpatrick. 2022. Elevated winter stream temperatures below wastewater treatment plants shift reproductive
development of female Johnny Darter Etheostoma nigrum: A field and histologic approach. Fishes 7(6): 261.
• Bombaci SP, and L Pejchar. 2022. Advancing equity in faculty hiring with diversity statements. BioScience
72(4): 365−371.
• Stewart TEM, DM Calhoun, and PTJ Johnson. 2022. Beyond single host, single parasite interactions:
Quantifying competence for complete multi-host, multi-parasite communities. Functional Ecology 36(8):
1845−1857.
• Avila BW, ER Fetherman, and DL Winkelman. 2022. Dual resistance to Flavobacterium psychrophilum and
Myxobolus cerebralis in Rainbow Trout (Onchorhynchus mykiss, Walbaum). Journal of Fish Diseases DOI:
10.1111/jfd.13605.
• Wood CL, M Summerside, and PTJ Johnson. 2020. How host diversity and abundance affect parasite
infections: Results from a whole-ecosystem manipulation of bird activity. Biological Conservation 248:
108683.
• McDevitt-Galles T, WE Moss, DM Calhoun, and PTJ Johnson. 2020. Phenological synchrony shapes
pathology in host-parasite systems. Proceedings of the Royal Society B 287: 20192597.
• Moss WE, T McDevitt-Galles, DM Calhoun, and PTJ Johnson. 2020. Tracking the assembly of nested
parasite communities: Using β-diversity to understand variation in parasite richness and composition over
time and scale. Journal of Animal Ecology 89(6):1532−1542.
Tawni B R Firestone
�•
•
•
•
•
•
•
Fetherman ER, B Neuschwanger, T Davis, CL Wells, and A Kraft. 2020. Use of Erymin 200 injections for
reducing Renibacterium salmoninarum and controlling vertical transmission in an inland Rainbow Trout
brood stock. Pathogens 9:547.
Kohl ZF, Calhoun DM, Elmer F, Peachey RBJ, Leslie KL, Tkach V, Kinsella JM, and Johnson PTJ. 2019.
Black-spot syndrome in Caribbean fishes linked to trematode parasite infections (Scaphanocephalus
expansus). Coral Reefs 38:917−930.
Happel, A. 2019. A volunteer-populated online database provides evidence for a geographic pattern in
symptoms of black spot infections. International Journal for Parasitology: Parasites and Wildlife 10: 156–
163
Johnson SK, MA Fitza, DA Lerner, DM Calhoun, MA Beldon, ET Chan, and PTJ Johnson. 2018. Risky
business: linking Toxoplasma gondii infection and entrepreneurship behaviors across individuals and
countries. Proceedings of the Royal Society B: Biological Sciences doi:10.1098/rspb.2018.0822
Johnson PTJ, DM Calhoun, AN Stokes, CB Susbilla, T McDevitt-Galles, CJ Briggs, JT Hoverman, VV
Tkach, and JC de Roode. 2018. Of poisons and parasites: the defensive role of tetrodotoxin against infections
in newts. Journal of Animal Ecology 87:1192−1204.
DM Calhoun, T McDevitt-Galles, and PTJ Johnson 2018. Parasites of invasive freshwater fishes and the
factors affecting their richness and abundance. Freshwater Science 37: 134−146.
ER Hannon, DM Calhoun, S Chadalawada, and PTJ Johnson. 2018. Circadian rhythms of trematode
parasites: applying mixed models to test underlying patterns. Parasitology 145(6):783−791.
Tawni B R Firestone
�
https://cpw.cvlcollections.org/files/original/ecfa807cf41169f34413d0281c009756.pdf
2b5ae5517131cc245bfcb93d220cc3e7
PDF Text
Text
DISEASES OF AQUATIC ORGANISMS
Dis Aquat Org
Vol. 57: 77–83, 2003
Published December 3
Efficacy of passive sand filtration in reducing
exposure of salmonids to the actinospore
of Myxobolus cerebralis
R. Barry Nehring1,*, Kevin G. Thompson1, Karen Taurman2, William Atkinson3
1
Colorado Division of Wildlife, 2300 South Townsend Avenue, Montrose, Colorado 81401, USA
2
Colorado Division of Wildlife, 317 West Prospect Street, Fort Collins, Colorado 80526, USA
3
Colorado Division of Wildlife, 925 Weiss Drive, Steamboat Springs, Colorado 80477, USA
ABSTRACT: The aquatic oligochaete Tubifex tubifex parasitized by Myxobolus cerebralis releases
triactinomyxon (TAM) actinospores that can infect some species of salmonids and cause salmonid
whirling disease. Silica sand was tested as a filtration medium for removal of TAMs from water containing the parasite. Laboratory tests indicated sand filtration removed > 99.99% of TAMs. In 2 different field tests, groups of 1 mo old rainbow trout Oncorhynchus mykiss were exposed for 2 wk to
filtered and unfiltered water from a spring-fed pond enzootic for M. cerebralis. In November 2000,
the exposure dose was estimated as between 3 and 5 TAMs fish–1. During a March 2001 exposure,
the estimated dose was between 286 and 404 TAMs fish–1. Fish were held for 6 mo post exposure
(p.e.) in laboratory aquaria for observation and evidence of clinical signs of whirling disease. We used
4 diagnostic techniques to assess the prevalence and severity of infection by M. cerebralis among fish
exposed to filtered and unfiltered water. These included polymerase chain reaction (PCR) for
genomic DNA of the parasite, histological evaluation for tissue damage, tissue digestion for quantification of cranial myxospores of the parasite, and total non-sampling mortality that occurred over 6 mo
p.e. All diagnostic tests verified that the prevalence and severity of infection was significantly
reduced among fish in treatment groups exposed to filtered water compared to those exposed to
unfiltered water in both the low-dose and high-dose exposures.
KEY WORDS: Salmonid whirling disease · Myxobolus cerebralis · Sand filtration
Resale or republication not permitted without written consent of the publisher
Salmonid whirling disease (WD) is caused by the
myxozoan parasite Myxobolus cerebralis. The parasite
requires 2 hosts to complete its life cycle, a salmonid fish
and the aquatic oligochaete Tubifex tubifex
(Markiw & Wolf 1983, Wolf & Markiw 1984). The parasite produces myxospores in salmonid fishes that are
either shed while the fish is alive (Nehring et. al. 2002)
or released into the aquatic environment from carcasses
of decaying fishes (El-Matbouli et al. 1992). Tubificid
worms feeding head-down in organically rich bottom
sediments can ingest these myxospores. Susceptible
strains of T. tubifex that ingest the myxospores become
infected, and subsequently release triactinomyxon
(TAM) actinospores of the parasite into the water. The
released TAM is infective to many species of salmonid
fishes, thus completing the parasite's life cycle.
The size and shape of the 2 spores are dramatically
different. The myxospores are quite small, measuring
approximately 8.7 µm in length and 8.2 µm in width.
They are circular in appearance when viewed dorsally
and somewhat ovoid in shape viewed laterally (ElMatbouli et al. 1992, El-Matbouli & Hoffmann 1998). In
contrast, the TAMs have the appearance of a grappling
hook and are much larger in size. Each caudal process
(arms of the grappling hook) measures 194 ± 20 µm in
length (Lom et al. 1997, El-Matbouli & Hoffmann
1998); therefore, the tip-to-tip distance across the
caudal processes is approximately 400 µm. We hypo-
*Email: barry.nehring@state.co.us
© Inter-Research 2003 · www.int-res.com
INTRODUCTION
�78
Dis Aquat Org 57: 77–83, 2003
thesized that the large size of the TAM might facilitate
its removal from small amounts of flowing water using
a silica-sand-based passive filtration system. Indeed,
passive sand filtration for removal of various waterborne pathogens has been in use in England, Germany
and the eastern United States since the 1800s (Hazen
1913, Bellamy et al. 1985). A passive flow-through
mechanical filtration system could be useful for
removal of TAMs from the small volumes of water
needed to augment water supplies for aquaculture or
from effluents of earth-bottom ponds contaminated
with the parasite.
In 1995, Myxobolus cerebralis infections were detected in Age 1 (16 mo old) wild rainbow trout Oncorhynchus mykiss in the Fryingpan River drainage in
central Colorado. By 1998, the abundance of Age 1
rainbow trout had declined 90% from the levels
observed in 1994 (Nehring & Thompson 2001). Water
filtration studies as described by Thompson & Nehring
(2000) were conducted throughout the drainage from
August 1998 through August 2002 to identify potential
sources of TAMs responsible for the M. cerebralis
infections in Age 1 wild rainbow trout in the river. The
water filtration studies provided strong empirical evidence that the effluent emanating from a series of
private fish ponds was the primary source of TAMs
flowing into the Fryingpan River. The pond discharge
flowed into the river 15 km upstream of the lower terminus of the 23 km study reach.
The objectives of our study were 2-fold. The first
objective was to develop and test a silica-sand passive
filtration system in the laboratory to determine the efficiency of trapping and removal of TAMs of the
Myxobolus cerebralis parasite. Our second objective
was to field test the efficiency of the system for attenuating or removing TAMs from a source of water
enzootic for the parasite in a continuous flow-through
situation. Flow-through testing was conducted on a
portion of the effluent from the spring-fed ponds in the
Fryingpan River drainage that were the source for
large numbers of TAMs of the M. cerebralis parasite.
We used 1 mo old rainbow trout not previously
exposed to the parasite as test organisms for the
flow-through testing experiments.
MATERIALS AND METHODS
Laboratory tests. The filter was constructed from a
379 l Rubbermaid™ stock water tank filled with a
10 cm-thick layer of 2.5 to 6 cm diameter granite river
rock. The layer of rock was overlaid with washed playground sand > 180 µm diameter. The sand layer was
40 cm deep and separated from the rock layer by a
1 mm mesh window screen. Water piped onto the top
of the filter passed through the sand and pooled in the
layer of river rock, where it passed through a 50.8 mm
diameter outlet valve. The approximate volume of the
sand used in the filter was 325 l. For the laboratory
tests, a reservoir containing 1900 l of tap water was
seeded with Myxobolus cerebralis TAMs and delivered to the top of the sand filter at an approximate flow
rate of 27 l min–1. The number of TAMs seeded in the
1900 l reservoir ranged from 687 000 to 1 442 000 for
the 6 laboratory tests. Densities of TAMs for the tests
averaged 443 l–1, ranging from 361 to 759 l–1. The
1900 l of sand-filtered water was collected at the outlet
of the Rubbermaid™ tank and filtered through a 20 µm
filter screen to collect any remaining TAMs. The concentrated filtrate was washed into a sample jar and
examined by stereozoom microscopy for detection of
TAMs using the protocol of Thompson & Nehring
(2000). The minimum detection limit by stereozoom
microscopy was < 0.035 TAMs l–1 based on detection of
1 TAM in 1.6 ml of filtered water scanned by stereozoom microscopy and drawn from 105 ml of filtrate
originally concentrated from 1900 l. As a quality control check, 1.6 ml of the filtrate was preserved in 70%
analytical grade ethanol and tested by polymerase
chain reaction (PCR) for the presence of DNA of the
M. cerebralis parasite (Schisler et al. 2001). The test
was a single-round modification of the test developed
by Andree et al. (1998); 6 individual tests were completed during the laboratory-testing phase.
Field tests. Upon completion of the laboratory tests, 2
continuous-flow experimental exposures were conducted on the effluent emanating from the spring-fed
ponds in the Fryingpan River drainage known to be
enzootic for Myxobolus cerebralis. Each flow-through
exposure lasted for 2 wk. The seasonal abundance of
TAMs in the pond effluent was well documented from
monthly filtrations conducted from July 1998 through
September 2000. This information facilitated testing
under 2 widely different levels of exposure. The first
test, carried out between November 5 and 19, 2000,
was a low-dose exposure. The second test was a highdose exposure conducted from March 5 to 19, 2001. At
the end of each 2 wk exposure, surviving rainbow trout
fry were transported to an aquatic toxicology laboratory to be held for 6 mo post-exposure (p.e.).
For each exposure, specific-pathogen-free (SPF)
1 mo old rainbow trout (mean weight 0.4 g) were
held in filtered and unfiltered effluent water. In each
experiment we exposed 1000 fish each to filtered and
unfiltered water to insure that enough test fish survived in each of the 2 treatments to seed each of 4
replicate aquaria with a minimum of 100 rainbow
trout fry for the 6 mo p.e. period. We used 2 exposure tanks similar to those in earlier studies (Thompson et al. 1999) for each experiment, one receiving
�Nehring et al.: Sand filtration of Myxobolus cerebralis actinospores
filtered water, the other unfiltered water. Each tank
was divided in half longitudinally and each half was
stocked with 500 rainbow trout fry. The volume of
each tank was approximately 190 1. A flow rate of
approximately 4.8 to 6.7 l–1 min was maintained for
each tank throughout the experiments. Total tank
volume was replaced 1.5 to 2.1 times h–1; 2 Rubbermaid™ stock tanks filled with silica sand were
needed to provide the required flow to the tank
receiving filtered effluent water in each experiment.
To monitor filtration efficiency and determine the
level of exposure to TAMs for the fish exposed to
unfiltered water, 24 h samples of filtered and unfiltered water were collected from each exposure tank
upstream of the test fish using a small siphon that
sub sampled the inflow to each tank. Siphons were
calibrated to collect 1900 l in 24 h. This volume was
passed through a 20 µm filter screen installed below
the siphon. The filtrate was collected and examined
by stereozoom microscope to estimate the relative
abundance of TAMs as previously described (Thompson & Nehring 2000). Ambient water temperature
during the field exposures ranged from 1.0 to 5.4°C
in November 2000 and 2.3 to 7.3°C in March 2001.
At the end of the 2 wk exposure, surviving test fish
were transported to the Colorado Division of Wildlife
Aquatic Toxicology wet laboratory at Fort Collins, Colorado. Groups exposed to filtered and unfiltered water
treatments were randomly divided into 4 replicate aquaria for each treatment and held in SPF well water or
dechlorinated tapwater until 1800 to 2400 degree-days
(°C × d) had elapsed to allow for adequate maturation of
Myxobolus cerebralis myxospores. Daily fluctuations in
water temperature were < 1°C during the p.e. period.
Over the 10 mo holding period for the 2 experiments,
water temperatures ranged from 7 to 15°C depending
upon season. For the low-dose exposure, there were 103
fingerling rainbow trout per replicate at the start of the
6 mo p.e. holding period. The protocol called for a minimum of 20 fish in each aquaria to be tested for
cranial myxospore concentrations at the end of the 6 mo
p.e. period. Results of previous long-term exposure studies (Thompson et al. 1999) indicated it was likely that
those fingerling rainbow trout exposed to unfiltered
water during the high-dose experiment would suffer
heavy mortality over the 6 mo p.e. holding period. To
insure that adequate numbers of fish per replicate would
survive to the end of the 6 mo holding period for pepsintrypsin digest (PTD) analysis in the high-dose experiment, each replicate aquarium was stocked with 218
trout. Each 90 l aquarium was supplied with fresh water
at a flow rate of 0.33 l min–1.
We used 3 techniques to determine the prevalence
and severity of infection by Myxobolus cerebralis
among treatment groups: PCR testing to detect
79
genomic DNA of the parasite (Andree et al. 1998,
Schisler et al. 2001), histological sectioning for
assessment of tissue damage (Baldwin et al. 2000),
and PTD analysis for detection and quantification of
cranial myxospores (Markiw & Wolf 1974). At 30, 60,
90, 120 and 150 d p.e., at least 5 fish per replicate
were sampled for PCR-testing. Fish were euthanized
in an aqueous solution of methane tricaine sulfonate
(MS222), frozen and shipped to a private laboratory
for PCR analysis.
At 94 d p.e. in the low-dose experiment, 2 fish from
each of 8 replicate aquaria were sacrificed for histological assessment of tissue damage. In the high-dose exposure, 10 fish exposed to filtered water and 20 fish exposed to unfiltered water and were sacrificed at 120 d
p.e. for histological assessment of tissue damage. Trout
euthanized for histological purposes were preserved in
Bouin’s solution for 24 to 72 h, then transferred to 70%
ethanol. Subsequently 3 or more tissue sections per
head were processed by standard histological techniques, stained with hematoxylin and eosin and examined for evidence of Myxobolus cerebralis infection by
light microscopy. Lesions were graded on a scale of 0
to 4, similar to that described by Baldwin et al. (2000),
with 0 indicating no evidence of infection and 4 being
most severe.
At the end of the 6 mo holding period, 20 or more fish
per replicate were euthanized and analyzed by the PTD
method for myxospores in cranial tissues (Markiw & Wolf
1974). Fish heads were separated from the remainder of
the body by cutting transversely on a vertical plane posterior to the operculum and the pectoral fin girdle; they
were then frozen and shipped to the Colorado Division of
Wildlife Aquatic Animal Health Laboratory for PTD
processing.
Initially, all test fish were fed a commercial trout
diet at a rate of 2.3% body weight d–1. The feeding
rate was adjusted once each month as the fish grew,
according to standard aquaculture guidelines (Piper
et al. 1982). Once each week all aquaria were
cleaned, and accumulated fecal material, detritus and
other waste products were siphoned off the bottom.
All aquaria were checked daily for moribund fish.
Dead fish were removed from the aquaria and
records of total mortality per replicate were kept
during the p.e. period.
A 2 sample mean Student’s t-test was used to test for
differences in mortality among and between treatments
(filtered versus unfiltered effluent) of rainbow trout
in the low-dose and high-dose field experiments. Chisquared tests were used to check for differences in
prevalence of infection in fish in the low-dose and
high-dose exposures as determined with the PCR and
PTD diagnostic tests. An alpha level of 0.05 was standard
for all tests of significance.
�80
Dis Aquat Org 57: 77–83, 2003
RESULTS
Laboratory tests
For the 6 laboratory tests, initial densities of TAMs in
the unfiltered water ranged from 361 to 759 l–1. Concentrated filtrate volumes collected from 1900 l of
water that passed through the sand filters ranged from
77 ml to 105 ml among the 6 tests. Sand filtration in all
6 tests reduced TAM levels below our minimum detection limits (< 0.035 spores l–1) with stereozoom
microscopy. Moreover, Myxobolus cerebralis DNA in
the filtered water was reduced below levels detectable
by single-round PCR-testing (Schisler et al. 2001).
Field tests
In none of the fish exposed to filtered water and
later analyzed by histopathology was there evidence
of Myxobolus cerebralis infection at either the lowdose or high-dose exposures. Among fish exposed to
unfiltered water in the low-dose test, histopathology
indicated 5 of 8 had tissue damage characteristic of
that caused by M. cerebralis (Baldwin et al. 2000).
The severity of infection was low for all 5 fish with
tissue damage, with each fish rated with a subjective
score of Grade 1 on a scale from 0 (no infection) to 4
(severe infection). Among the 20 fish exposed to
unfiltered water in the high-dose test, histopathology
indicated that 100% had severe tissue damage
(Grade 4) characteristic of that caused by M. cerebralis.
At the end of the 6 mo p.e. period, χ2 tests revealed
highly significant differences in the prevalence of infection between groups of fish exposed to filtered and
unfiltered water in both the low-dose and high-dose
experiments. Among fish exposed to filtered water in
the low-dose exposure, cranial myxospores were detected in only 1.3% of the fish tested, compared to
53.2% of the fish that tested positive after exposure to
unfiltered water (p = 0.0000; χ2 = 122.5). Among fish
exposed to filtered water in the high-dose exposure,
cranial myxospores were detected in only 25.5% of the
fish tested compared to 100% of the fish exposed to
unfiltered water (p = 0.0000; χ2 = 184.5).
No TAMs were detected in either experiment in
effluent-water filtrates that had passed through the
sand filters. In the November 2000 low-dose test,
TAMs were detected in 2 of 7 unfiltered effluent filtrates. Actinospores were found in all unfiltered effluent filtrates (n = 12) during the March 2001 high-dose
test. We estimated the range of exposure per fish in
each experiment based upon the aforementioned flow
rates through the holding tanks, tank volume, estimates of TAMs observed in the 24 h composite samples
and an average filtration net efficiency
of 50% (R. B. Nehring unpubl. data).
Table 1. Oncorhychus mykiss. Results of polymerase chain reaction (PCR),
Estimated cumulative exposure over
histopathology, and pepsin-trypsin digest (PTD) tests on rainbow trout exposed
the 2 wk exposure period, was 3 to 5
to filtered and unfiltered effluent water from spring-fed ponds enzootic for
Myxobolus cerebralis. Total sample size (n) and number of samples testing posiand 286 to 404 TAMs fish–1 for the
tive (n+) are presented for each exposure, test and treatment. MG: mean grade
November 2000 and March 2001
of lesions on scale of 0 to 4. Mean cranial myxospore levels for PTD test are for
experiments, respectively.
total sample (n)
Results for the PCR, histology, and
PTD tests are summarized in Table 1.
Nov 2000 (low-dose test)
Mar 2001 (high-dose test)
Assessment of subsequent infection in
PCR
fish using PCR indicated that sand filTreatment
n
n+
n
n+
tration was effective in dramatically
Filtered
129
1
100
14
reducing the number of fish that beUnfiltered
131
74
100
100
came infected by Myxobolus cerebralis during the 2 wk exposure in both
Histopathology
Treatment
n
n+
MG
n
n+
MG
the low-dose and high-dose exposures. In the low-dose exposure, signifFiltered
8
0
0
10
0
0
icantly fewer fish exposed to sandUnfiltered
8
5
1
20
20
4
filtered water tested PCR-positive
(0.8%) compared to the group exposed
PTD cranial myxospores
n
n+ Meana Rangeb
Treatment
n
n+ Meana Rangeb
to unfiltered water (56.5% tested posi2
tive) (p = 0.0000; χ = 98.3). Similarly, in
Filtered
159
2
3.84 6.97–604
145
37 4.183 0.611–97.2
the high-dose exposure, significantly
Unfiltered 293 156
49.4 0.76–1999 160 160 1873
1.58–5173
fewer fish exposed to filtered water
a
Mean myxospore concentration in total sample (n). Mean and range ×103
(14%) tested PCR-positive, compared
b
Range of cranial myxospore concentration among fish with detectable
to 100% of the fish exposed to the unmyxospores, Mean and range ×103
filtered water (p = 0.0000; χ2 = 150.9).
�Nehring et al.: Sand filtration of Myxobolus cerebralis actinospores
81
DISCUSSION
Similarly, at the end of the 6 mo p.e. period, PTD
testing revealed very large differences in the abunPassive sand filtration for the removal of pathogens
dance of cranial myxospores between groups of fish
from surface water has been practiced around the
exposed to filtered and unfiltered water in both the
world for almost 2 centuries. It has been in use in Englow-dose and high-dose experiments. Among fish
land, Germany and the eastern United States since the
exposed to filtered water in the low-dose experiment,
1800s (Hazen 1913, Bellamy et al. 1985). Sand and
mean concentrations of cranial myxospores were only
other substances such as diatomaceous earth are effec7.8% of the level observed in fish exposed to the
tive media for filtering water to remove bacteria and
unfiltered water. In the high-dose experiment, mean
other pathogens affecting human health, including
cranial myxospore levels among fish exposed to filspecies of Giardia and Cryptosporidium (Cleasby et al.
tered water were only 0.2% of the levels observed in
1984, Lange et al. 1986, Musial et al. 1987, Oram 1987,
fish exposed to unfiltered water (Table 1).
Schuler & Ghosh 1990, Schuler et al. 1991).
Although PCR testing indicated that infection prevaOur laboratory tests indicated that passive sand filtralence was much higher among test fish exposed to filtion was highly efficient in removing Myxobolus ceretered effluent in the high-dose test compared to the
bralis TAMs from water. However, sand filtration of pond
low-dose test, i.e. 14 versus 0.8%, mean cranial
effluent for removal of TAMs during the field exposures
myxospore concentrations were similar when anawas not 100% efficient. Schuler et al. (1991) and Arndt &
lyzed by PTD testing at the end of the p.e. period
Wagner (in press) also found that sand filtration was
(Table 1).
less than 100% efficient for the removal of various
There were large differences in the prevalence and
pathogens and particulates. This was particularly probseverity of infection between groups of fish exposed to
lematic among fish exposed to filtered water in the highunfiltered water in the low-dose and high-dose experdose experiment, where 14 and 25.5% of the fish tested
iments. In the low-dose test, 53.2% of fish exposed to
by PCR and PTD were shown to be infected, respecunfiltered water had detectable numbers of myxotively. Such levels of infection would be of great concern
spores compared to 100% among similarly exposed
to the salmonid aquaculture industry.
fish in the high-dose test. Among all fish exposed to
We believe that the integrity of the sand filters was
unfiltered water and subjected to PTD testing, the
compromised during the high-dose exposure test in
mean number of cranial myxospores was 37.9 times
March 2001. At this time the ice cover from winter
higher in the group of fish from the high-dose expowas beginning to melt in the spring-fed ponds. The
sure compared to those in the low-dose exposure
ponds were located on a flat terrace of land adjacent
(Table 1).
to a sloping pasture that drained into the ponds. SevTotal non-sampling mortality data for the 6 mo p.e.
eral hundred beef cattle were being held in the pasperiod for fish exposed to filtered and unfiltered water in
ture. Fecal material and detritus from the pasture
the low-dose and high-dose experiments are summawas washed into the ponds by melting snow, causing
rized in Table 2. Mortalities among treatment fish
the top 2 to 3 cm of sand in the filters to become
exposed to unfiltered water in both the low-dose and
plugged. This unanticipated problem necessitated
high-dose exposures began 60 d p.e. Although the difthe removal and replacement of the top 2 to 3 cm of
ferences in mortality were not great among treatment
sand once every other day during the 2 wk exposure
groups in the low-dose exposure, fish exposed to the unfiltered water suffered significantly
Table 2. Oncorhynchus mykiss. Total non-sampling mortality and percent
higher mortality (p = 0.034; t = 2.74) than
mortality among 4 replicates per treatment of rainbow trout fingerlings held for
those exposed to filtered water. In the
6 mo post-exposure after 2 wk of continuous exposure to sand-filtered and nonhigh-dose experiment mortality among
filtered effluent water from spring-fed ponds enzootic for Myxobolus cerebralis.
fish exposed to unfiltered water averEach of the 8 replicate aquaria contained 103 and 218 fish at the beginning of
aged 66.2% compared to 3.8% among
the 6 mo holding period in low-dose and high-dose exposures, respectively
the groups exposed to filtered water (p <
0.0001; t = 48.7). Differences in mean
Treatment
Mean
Range
Mean %
SD
mortality
mortality
percent mortality among fish exposed to
unfiltered water in the low-dose and
Low-dose (Nov 2000)
high-dose tests were highly significant
Filtered
4.25
2–7
4.13
2.16
(p < 0.0001; t = 26.59). In contrast, there
Unfiltered
10.75
8–17
10.44
4.07
were no significant differences in perHigh-dose (Mar 2001)
cent mortality among fish exposed to filFiltered
8.25
3–15
3.79
2.35
tered water in the low-dose versus the
Unfiltered
144.25
142–147
66.15
1.01
high-dose test (p = 0.838; t = –0.21).
�82
Dis Aquat Org 57: 77–83, 2003
period in order to maintain adequate flow of filtered
water to the test fish. We suspect this process may
have allowed a small amount of the unfiltered effluent to percolate vertically along the edges of the
stock tank and pass through to the test fish.
Periodic removal of the top layer of sand to keep
flow rates, hydraulic head loss and other filtration
parameters within acceptable levels in sand filtration
systems is common practice (Seelaus et al. 1986,
Schuler et al. 1991). The time period between successive removals of the surface layer of sand is
known as the ’filtration cycle’. While the 2 d filtration
cycle in our high-dose exposure was not an undue
hardship, it would be unacceptable in an operational
application. Trapping of particulates in the surface
sand can result in significant loss of head pressure
and dramatic declines in filtration efficiency. Even in
areas where the turbidity level and particulate loading in the water is quite low, filtration cycles are
generally 30 to 60 d (Seelaus et al. 1986, Schuler et
al. 1991). There are 2 common solutions to this problem: removal and replacement of the clogged sand
layer or designing a system that enables the sand
filter to be periodically back-flushed.
Other technologies have been developed and used
to remove infective stages of Myxobolus cerebralis
and other pathogens from water supplies in commercial aquaculture. These include ozone treatment
(Williams et al. 1982, Horsch 1987), ultraviolet irradiation (Hoffman 1974, 1975, Hedrick et al. 2000) and
chemical treatment of soils in ponds with calcium
oxide, calcium cyanamide, or chlorine or calcium
hypochlorite (Hoffman 1990). While these approaches may be effective in some cases, they can be
cost-prohibitive or prone to failure if electrical power
is interrupted. This certainly would be the case for
ultraviolet irradiation. Periodic shutdown of ozone
treatment systems can be problematic as well
(Horsch 1987). Chemical treatments of soils or water
may not be environmentally acceptable and can require periodic reapplication to maintain control of
the parasite. For these reasons, passive sand filtration
was our preferred method.
Based on the success of these tests, a slow sandfiltration system has been designed in collaboration
with civil engineers and constructed at the outlet of
the Myxobolus cerebralis -contaminated ponds on the
Fryingpan River. The system is designed for flow
rates up to 3 400 l min–1 on a sustained basis. The filter can be back-flushed to purge accumulated detritus in order to maintain head pressure and flow volume. Design criteria indicate that the filter should be
capable of reducing M. cerebralis TAM density by
≥ 95%. We hope that these efforts will lead to the
development of techniques for constructing wetland
‘biofilters’ capable of removing TAMs from the effluent of spring-fed ponds and small man-made lakes
enzootic for the M. cerebralis parasite
Acknowledgements. We wish to thank the many Colorado
chapters of Trout Unlimited, and the Whirling Disease Foundation for substantial amounts of funding that in large part
covered the costs of completing these studies. We are appreciative of the Colorado Division of Wildlife Aquatic Animal
Health Laboratory staff for completion of the PTD analyses as
well as L. Chittum, DVM, for the histological evaluations. In
addition, the authors and the Colorado Division of Wildlife are
deeply grateful to J. Gilchrist, L. Nichols, and the Nichols
family and staff at the Cap K Ranch for their cooperation in
allowing access to the ponds on the ranch so that these studies
could be conducted.
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Editorial responsibility: Carl Schreck,
Corvallis, Oregon, USA
Submitted: September 15, 2002; Accepted: July 1, 2003
Proofs received from author(s): September 29, 2003
�
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Text
American Fisheries SOGety Symposium 29,3341,2002
© 20Cl2 by the American Fisheries Society
Evaluation of Risk of High Elevation Colorado Waters
to the Establishment of Myxobolus cerebralis
GEORGE J. SCHISLER
Colorado Division of Wildlife, 317 West Prospect
*
Fort Collins, Colorado 80526, USA
ERIC P. BERGERSEN
Colorado Cooperative Fish and Wildlife Research Unit, 203 Wagar Building
Colorado State University, Fort Collins, Colorado 80523, USA
During 1992 and 1996, fish were inadvertently stocked into 226 waters in Colorado
from hatcheries that were later identified as MyxoboIus cerebralis-positive. Seventy-two high-ele
vation waters, previously classified as M. cerebralis-negative, were sampled to determine if stock
ing of fish from those hatcheries contributed ro the spread of M. cerebralis in these locations.
Pepsin-trypsin digest (PTD) and polymerase chain reaction (PCR) tests were used to test for M.
cerebralis in 1,743 fish. A total of 190 fish and 23 separate waters were identified as M. cerebralis
positive, with PTD. PCR identified 410 fish and 42 waters as positive for the parasite.
regression and Akaiki information criterion model selection was used to identify parameters con
tributing to the M. cerebralis e,tablishment in these high elevation waters. Within-drainage dis
tance
the nearest known M. cerebralis~positive water and relative abundanee of Tubifex tubifex
habitat were found to be more important contributors to the establishment of M. cerebralis than
the accidental srocking events.
ABSTHACT.
Myxobolus cere bralis, the
responsible for
salmonid whirling disease, was first identified in
the United States in the 1950s and has been
detected in at least 22 states (Bartholomew and
Reno, this volume). The parasite can be potential
ly
by several mechanisms. Infected fish may
swim upstream or downstream from a site of initial
exposure, carrying the parasite throughout a given
drainage. The waterborne triactinomyxon spore
(the stage infective to fish) can be carried down
stream from infected areas with water currents.
Mature myxospores can be passed through the
digestive systems of fish-eating birds, such as great
blue heron (Meyers et al. 1970), kingfishers
(Schaperclause 1954), black crested night
and mallard ducks (Taylor and Lott 1978), facili
tating transporr of the
into previously
unexposed habitats. Past evaluations suggest that
the most common route of transmission of M. cere
bra/is to new locations is transport of infected fish
(Meyers et al. 1970). In Colorado, accidental
stocking ofM. cerebralis-suspect fish raised the con
cern that many high-elevation waters, previously
'Corresponding author, (970) 472,4412; george.schisler@,tate.co,us.
free of the organism, may have become contami
nated with the parasite. A total of 226 high-eleva
tion waters were stocked by Roaring Judy State
Fish Fatchery in 1992 and the Pitkin and Durango
State Fish Hatcheries in 1996, when the facilities
were considered to be free of the parasite. Most of
these high-elevation stockings were aerial plants of
fingerling trout. Testing of the hatcheries by the
pepsin-trypsin digest method (PTD; Markiw and
Wolf 1975), during annual inspections later during
those years, resulted in identification of M. cere
bra/is. Additional fish were inadvertently stocked
from these hatcheries the following year into some
of the same or additional high-elevation habitats
because they were not removed from the stocking
schedules for those hatcheries. Actual M. cerebralis
status and infection severity of the fish stocked into
these high elevation waters is unknown, but it is
likely that the fish were exposed to the parasite
before stocking. The objective of this study was to
determine the extent of the spread of M, cerebralis
into high elevation waters presumed to be free of
the parasite, identify the contribution of spread due
to accidental stocking events, and determine the
threat of the parasite to high-elevation trout popu
lations in Colorado.
33
�34
SCHISLER AND BERGERSEN
METHODS
During 1998 and 1999, resident rainbow trout
Oncorhynchus mykiss, brown trout Sa/mo trutta,
brook trout Salvelinus fontinalis, and cutthroat trout
Oncorhynchus clarki were sampled from 72 waters
classified as M. cerebralis-negative before the acci
dental stocking events. Sampling sites included,
both, waters that had been stocked from the sus
pect hatcheries and those that had not been
stocked from suspect hatcheries. This was done to
distinguish between stocking- and nonstocking
related transfer of M. cerebralis to these high-eleva
tion habitats. Waters with a wide range of eleva
tions, 2,103-3,840 m (6,900-12,600 ft), and habi
tat types were sampled with gill nets, hook and
line, and electrofishing. An attempt was made to
collect a representative 60-fish sample from each
body of water to detect M. cerebralis at a higher
than 5% prevalence, with 95% confidence inter
vals (Ossiander and Wedemeyer 1973). In many
cases, very few fish or only native cutthroat trout
were found, so smaller samples were taken to pre
serve the existing populations. Sampling was
focused on fish that were obviously a result of nat
ural reproduction, to identify establishment of the
parasite rather than presence of the organism in
stocked fish. Wild brook, brown, and cutthroat
trout, as well as younger age classes of fish, were
preferentially sampled. Fish submitted for testing
were at least 1 year old, to increase the likelihood
that if mature myxospores were present, they would
be detected using the PTD method. Parallel single
tound polymerase chain reaction (PCR) and PTD
tests (Schisler et al. 2001) were conducted on
1,743 fish, during the study. Myxospore burden was
estimated for each fish (half-head) tested with
PTD. PCR band-strengths were rated as one of five
categories: negative (0), weak positive (1), positive
(2), strong positive (3), and very strong positive
(4). Prevalence and infection intensity were evalu
ated for fish in each of the waters tested. The
waters were then categorized as M. cerebralis-posi
tive or negative, based on the testing results.
Elevation, stocking history, presence of Tubifex
tubifex habitat, and proximity to known infected
waters were recorded for each of the waters tested.
Multiple fish species were often taken from the
same body of water, so waters were not classified by
species. One lake was sampled in both 1998 and
1999, so data were combined for that particular
lake. Samples from two other waters were incom
plete, or fish were too young for valid PTD testing
and were not included in the data set. The end
result was 69 waters used in the analysis. The
waters sampled in the study were classified into
three different categories, based on stocking histo
ry. Waters never stocked with fish from suspect or
positive facilities were classified as "Stock 0"
waters. Waters stocked with fish from hatcheries
the year before or the year of finding infected fish
at the facility (suspect fish) were classified as
"Stock 1" waters. Waters stocked with fish from
known-positive hatcheries (year after identifica
tion of infected fish at the facility) were classified
as "Stock 2" waters.
T. tubifex can be found in pristine environ
ments and are fairly ubiquitous throughout fresh
water salmonid habitat (Granath and Gilbert
2001). However, the likelihood of finding abun
dant T. tubifex is much greater in locations with
fine sediments and eutrophic conditions. Sauter
and Glide (1996) found that T. tubifex tend to pre
fer silt-clay substrate. Lazim and Leamer (1987)
found that most tubificids occurred in areas of high
organic content and Silt-clay sized particles. T.
tubifex may occur in very high densities in cases of
extreme organic enrichment or habitat degrada
tion, when many other invertebrate species are
eliminated (Aston 1973; Brinkhurst 1965; Lesto
chova 1994). Studies in Colorado have shown that
eutrophic, silty locations favorable to T. tubifex can
acr as point sources of M. cerebralis infection
(Allen 1999; Thompson and Nehring 2000).
Waters were categorized based on the presence of
obvious T. tubifex habitat. Very oligotrophic loca
tions with cobble-boulder or bedrock substrates
and minor amounts of available T. tubifex habitat
were classified as "Tubifex 0." Waters with an inter
mediate level of sedimentation, gravel-cobble sub
strate, and a moderate amount of organic material
deposition were classified as "Tubifex 1." Locations
with silt-sand-clay substrate and eutrophic condi
tions, such as beaver ponds, were classified as
"Tubifex 2." Classification into these types ofhabi
tats was not based on an absolute measure of total
sedimentation, eutrophication, or total T. tubifex
abundance. However, they are distinct enough for
any layperson to identify the differences in these
habitat types and rate them on a scale of 0-2.
Proximity to known M. cerebralis waters was
evaluated by relying on past pathogen testing, con
ducted by the Colorado Division of Wildlife
Aquatic Animal Health Laboratory in Brush, Col
�35
EVALUATION OF RISK OF HIGH ELEVATION COLOR.A,DO WATERS
orado. Both straight-line distances and within
drainage distances (km) to closest known M. cere
bralis-positive sites were estimated using measure
ments from Delorme 1:160,000 maps. Straight-line
distance was simply the most direct distance to the
nearest location that had previously tested positive
for M. cerebralis. Within-drainage distance was the
distance, following the streambed, to the nearest
upstream or downstream site that had previously
tested positive for M. cerebralis. Many sites in Col
orado have not been tested for M. cerebralis, so the
parasite is likely established in many more loca
tions than the current data reflects, and distances
recorded are based only on known positive sites.
Maximum distance recorded was limited to 40.2
km (25 mO, due to the presence of some waters in
dead-end drainages or in areas where limited test
ing had been done, which would have otherwise
resulted in recording of some waters as having infi
nite within-drainage distances to the next known
positive site.
A correlation matrix produced by PROC
CORR, a procedure in SAS system software, was
used to determine if significant collinearity existed
between factors. Elevation was correlated with our
0.2628, P <
measure of T. tubifex habitat (Rl
0.0001). Eutrophication and sedimentation lead
ing to abundant T tubifex habitat can occur at any
elevation given the correct circumstances. We felt
that relative amount of T. tubifex habitat was more
likely to have a direct effect on establishment of M.
cerebralis than elevation, and because these factors
wcre correlated, we removed elevation as a factor
in the modeling procedure. Straight-line distance
was correlated with within-drainage distance to
other M. cerebralis positive sites
= 0,4578, P <
0.0001). Because both of these parameters repre
sent essentially the same factor and were correlat
ed, we removed straight-line distance as a factor.
Apparent effects from individual factors may
be confounded due to interactions, and considering
each factor alone in highly complex natural sys
tems can be misleading.
Therefore, logistic regression analysis (PROC
GENMOD) in SAS system software was used, to
test all factors simultaneously and to determine
which (if any) of the parameters recorded con
tributed to M, cerebralis status of the waters tested.
The major factors recorded for each water and
included in the analysis as independent variables
T. tubifex habitat, within
were stocking
drainage distance to the nearest known positive
water, and all interaction terms. Stocking was used
as a categorical variable, with each of the three dif
ferent stocking classifications as a different catego
ry. T tubifex habitat was treated as a categorical
variable in one set of models and as a continuous
variable in another set of models. T. tubifex habitat
was used as a categorical variable in some models to
reflect the three distinct habitat types, as they were
classified during sampling as minimal, moderate, or
habitat was used in
abundant habitat. T.
other models as a continuous variable to describe a
range of habitats from low to high T. tubifex habitat
abundance. Treatment of the variable in this man
ner is useful because all waters may not
fit
perfectly inro one of the three categories described.
For all of the models, the sampling unit used
was individual waters, and the dependent variable
was the presence or absence of ?vL cerebralis. All of
the different combinations of variables resulted in
36 different models to be evaluated. Second order
Akaiki information criterion (AlCc) (Burnham
and Anderson 1998) was used as the model selec
tion procedure to idennfy the model that best
described the data without over-parameterization.
AICc is much like AIC (Lebreton et a1. 1992),
except a small-sample bias adjustment tenn is
added to the formula and is described as follows:
where
N number of samples, and
K number of parameters.
AICc values were calculated for each of the
alternative logistic regression models generated.
The models were then ranked based on these val
ues, with small AlCc values representing the best
models ~md large AlCc values representing poor
models of the information in the data. The AICc
values were then rescaled as follows to
the
model with the minimum AICc a value of and to
allow easily comparable, rankable models:
a
il, =
min AICc
Akaiki weights (Burnham and Anderson
2001) were then calculated for each of the models,
to provide "weight of evidence" for the strongest
models when compared with other models evaluat
ed. The Akaiki weight for each model is interpret
ed as approximately the probability that the model
�36
SCHISLER AND BERGERSE:-J
is the best in the set evaluated. The weights are cal
culated as follows:
ing elevation was fairly pronounced (Table 1).
There were some obvious exceptions, including
waters above 3,500 m that still produced high pro
portions of infected fish. Some low-elevation
waters also produced low proportions of infected
fish. This indicates that other factors influenced
infection prevalence besides simply elevation.
The raw data
that stocking history
had an effect on M. cerebralis status of the waters
tested (Table 2). A higher percentage of "Stock 2"
waters were identified as M. cerebratis-positive than
"Stock 1" or "Stock 0" waters. Only 25.0% of
"Stock 0" and only 25.7% of Stock 1 waters were
identified as M. cerebralis-positive, with PTO. PCR
testing identified 66.7% of "Stock 0" and 51.4% of
"Stock 1" waters as M. cerebralis-positive. Lower
elevation waters adjacent to known infected waters
made up the bulk of the M. cerebralis-positive
"Stock 0" waters. By contrast, 80.0% of the "Stock
2" waters were identified as M. cerebralis-positive,
by both PCR and PTo.
Tubifex tubifex habitat was generally reduced at
higher elevations, due to the lower sediment load
and organic content of most of the higher-elevation
waters. Presence of obvious T. tubifex habitat influ-
/2)
w = =--"---'-'---'---
This information was used to identify the best
models for describing the data from the 69 high
elevation waters sampled. The logistic re£(re,;SlCJn
and subsequent model selection allowed us to not
only identify the best models but also to quantify
relative importance and effects of the factors used
in the models.
RESULTS
Raw data suggested lower mean spore burdens, and
PCR band strengths occurred at higher elevation
waters. Mean myxospore burdens (half-heads)
increased from
per fish, at elevations greater
than 3,500 m, to 3,302 per fish, at elevations of
2,501-3,500 m. At elevations below 2,500 m,
per
mean myxospore burden increased to
fish. Corresponding mean peR band strengths had
a similar pattern of stronger strength with lower
elevation. Prevalence of infected fish with increas
Table 1. Mean PTD myxospore counts, mean PCR band strength ratings (half-head), and infection
prevalence for fish sampled at elevations ranging from 2,103-3,840 m (6,900-12,600 ftl.
Elevation
Test
Fish
Infected (%)
Mean
St. Dev
Range
< 2,500
PTD
PCR
221
221
25.8
62.0
5,727
1.71
17,528
1.57
0-175,000
0-4.00
2,501-3,500
PTD
PCR
965
965
11.4
23.8
3,302
0.56
19,538
1.14
0-291,644
0-4.00
> 3,500
PTD
PCR
557
557
4.1
7.7
1,386
0.17
14,072
0.67
0-278,133
0-4.00
Table 2. Infection prevalence of fish and percent of waters identified as M. cerebraJis positive by PTD and
PCR from waters classified by stocking history. "Stock 0" waters were never stocked with fish from suspect
or known-positive facilities. "Stock 1" waters were stocked with fish from hatcheries the year before or the
year of finding infected fish at the facility (suspect fish). "Stock 2" waters were stocked with fish after
confirmation of M. cerebra/is at the facility.
Fish
Waters
Stocking
N
%PTD+
%PCR
'J
%PTO+
%PCR+
Stock 0
Stock 1
Stock 2
751
676
316
8.3
17.6
5,6
28,5
14.8
24
35
10
25.0
25.7
80.0
66.7
51.4
80.0
56.3
�EVALUATION OF RISK OF HIGH ELEVATION COLORADO WATERS
enced M, cerebralis status of the waters tested (Table
3). PTD testing resulted in classifying 9.1 %, 23.8%,
and 61.5% of the populations in "Tubifex 0,"
"Tubifex I," and "Tubifex 2" waters as infected with
M. cerebralis. PCR testing identified a higher pro
portion of the populations as infected, but the pat
tern remained the same, with 45.5%, 52.4%, and
80.4% of the populations in "Tubifex 0," "Tubifex
I," and "Tubifex 2" waters identified as infected.
Average within-drainage distance to the near
est infected site was 11.2 km (N 23; SO 14.3)
for waters found to be M. cerebmlis-positive with
PTD testing, and 16.7 km (N = 42; SO = 14.7)
with peR testing. Average within-drainage dis
37
tances to the nearest infected sites were 24.9 km
(N 46; SO = 13.1) for waters found to be M. cere
bralis negative \vith PTD testing, and 26.1 km (N =
SO = 13.6) for peR testing.
Model Selection
The peR data were best described using a model
including T. tubifex habitat as a continuous vari
able and within-drainage dismnce (Tj> D). The sec
ond-choice model included T. tubifex habitat as a
categorical variable and Within-drainage distance
(T" D). Other models with interaction terms or
fewer parameters had larger AICc values and low
Akaiki weights (Table 4). The PTD data were best
Table 3. Infection prevalence of fish and percent of waters identified as M. cerebralis positive by PTO and
PCR for three categories of T. tubifex habitat.
Fish
Tubifex habitat
Minimal habitat
Moderate habitat
Abundant habitat
Waters
%PTD-,
4,0
4,4
22.3
N
553
543
647
N
22
21
26
%PCR+
7.5
15.7
43,7
%PTDI
9,1
23,8
61.5
%PCR+
45.5
52.4
80.4
Table 4. Best-fitting alternative models for predicting presence of M. cerebralis in high elevation Colorado
waters with PCR and PTO testing. N '" 69 for each model.
PCR testing
Model
T:, D
T"D
T" D, S, T,*5
T"D,T,*D
T" D,S
Parameters
- 2Iog(L(0))
AICc
Ll;
Akaiki weights'
3
4
7
4
5
80,5109
78.4234
72.3160
80.3440
78,5539
86,8801
87.0484
88,1521
88.9690
89,5063
0,0000
0,1683
1.2720
2,0889
2,6262
0.1904
0,1750
0,1077
0,0669
0.0512
Alec
Ll,
Akaiki weights'
66.6743
67.5965
67,8428
0,0000
0,9222
1.1685
0.2561
0,1615
0,1428
PTD testing
Model
l,D
T" D, S
T" D
T" 0, T,*O
T" D, S
T:, D, S,T, *D
Parameters
- 2Iog(L(0))
3
5
4
60.3051
56.6441
59,2178
..
__ _
..
... _----
4
59.9436
68.5686
1,8943
0,0993
6
6
56.3812
56.4847
69.7360
69,8395
3.0617
3,1652
0.0554
0,0526
'Akaiki weights for all other mode~s were < 0,05.
T, 1 tubifex habitat as a continuous variable.
T, = T. tubifex habitat as a categorical variable,
D = Within-drainage distance to nearest infected water.
S Stocking history as a categorical variable,
* Interaction term,
�SCHISLER AND BERGERSEN
38
fit with a model containing T. tubifex habitat as a
continuous variable and within-drainage distance
(T D). A model with both of these variables and
"
was the second-best
stocking
history (Til D,
model fit. As with the peR data, other models
with interaction terms or fewer parameters had
larger Alec values and low Akaiki weights.
These results indicate that a model containing
Within-drainage distance and T. rubifex habitat as a
continuous variable (T i , D) was the best overall fit
for both the PTD and peR data. Parameter esti
mates for models that included stocking history
indicate that a Within-drainage distance and T.
tubifex habitat were the most important factors
(Table 5), with stocking having a lesser influence
D, S) The best
model (T" D) pro,
(i.e.,
vides similar results for both the peR and PTD
data, except the likelihood of finding M. cerebralis
is greater with the peR data (Figures 1 and 2). This
is to be expected, considering the greater sensitivi,
ty of the peR test. Increasing distance to the near
est known-infected site in the models results in
lower probability of establishment of the parasite,
habitat results in
while an increase in T.
greater probability of establishment.
Although the model T\1 D, S was the second
choice model for PTD testing, as identified by the
Alec and Akaiki weight results, it provides some
on M. cerebra/is
insight into the effects of
establishment in the waters in this study. Waters in
the model not stocked with infected or suspect fish
have the lowest overall probability of establish-
Table 5. Parameter estimates and significance levels for the two best-fitting alternative models for
predicting presence of M. cerebra lis in high elevation Colorado waters as tested by PCR and PTD.
peR results
Model T" D
Parameter
df
Intercept
T tubifex
Distance
Model T" D
Parameter
Intercept
T tubifex
T tubifex
T tubifex
Distance
of
0
1
2
1
0
1
Estimate
Standard error
0.6689
0.7100
-0.0432
0.6061
0.3286
0.0195
Estimate
Standard error
2.5891
-1.4971
-1.6064
0.0000
-00505
0.7806
0.6897
0.7804
0.0000
0.0212
Estimate
Standard error
-1.2710
1.4944
-0.0685
0.7678
0.4739
0.0228
Estimate
Standard error
PTD results
Model = T" D
Parameter
df
Intercept
T tubifex
Distance
Mocel = T" D, S
Parameter
df
Intercept
5.5415
1.2434
T. tubifex
1.2610
0.4848
-0.0711
1.8409
0.0245
1.0676
Distance
Stocking
Stocking
Stocking
0
1
2
0
1.6867
1.0089
0.0000
0.0000
�EVALUATION OF RISK OF HIGH ELEVATION COLORADO WATERS
39
.....
c
C\J
E
0.8
..c
.!!l
:a
!\l
.....
III
L.U
~
~
0.6
.Q
::::
~
~
0.4
'<-
0
"0
0
2
0
.c
QJ
.:.t.
::;
o
o
T. tubifex Habitat
10
20
Distance (km)
o
30
40
Figure 1. PeR-model results (T" D) for effects of T. tubifex habitat and distance to nearest known-positive,
within-drainage site on M. cerebralis establishment.
ment of the parasite, followed by waters stocked
with suspect fish and waters stocked from hatch
eries after they were known to be contaminated
with M. cerebralis. However, the best-fitting mod
els indicated that the accidental stocking events
had less of an effect than the other two factors.
mSCUSSION
The raw data indicated that stocking history, ele
vation, presence of 1'. tubifex habitat, and distance
to known positive waters all contributed in some
way to the M. cerebralis status of the waters tested.
The best-fitting models identified presence of 1'.
tubifex habitat and within-drainage distance to
known infected waters as the most important vari
ables in the establishment of M. cerebraUs in high
elevation waters. The importance of stocking his
tory was low,
with the other factors in
this study. This was partially due to the small num
ber of "Stocked 2" waters in the data set, which
were the most heavily influenced by the stocking.
The contribution to M. cerebralis establishment
was not strongly influenced by the accidental
stocking that occurred in the "Stocked I" waters.
The high-elevation waters in this study were
stocked only one or two times with infected or sus
pect fish, and lower-elevation waters with long his
tories of stocking of infected fish are more likely to
be affected by stocking history.
Available T tubifex hahitat has long been
known to be a contributor to the intensity and
prevalence of M. cerel:rralis infection. This was the
case in this study as well, with low prevalence of
infection and low proportion of infected waters
where little T. tubifex habitat was available. Infec
tion levels may have been too low ro detect in
some locations with little or no obvious T. tubifex
habitat, which would
the false impression that
establishment had not occurred. However, the end
result is still a reduced risk from the parasite in
these locations.
The effect of distance ro known positive
waters on M. cerebralis status of the waters tested
in this study suggests that transport by anglers,
migrating fish, or other wildlife may he a con
tributing factor in the spread of the pathogen in
�40
SCHISLER AND BERGERSEN
+"'
s::
<J)
E
..c:
.~
0.8
J:l
....ro
Vl
UJ
~
~
0.6
..Q
~
<!)
u
~
0.4
'+
0
'D
0
0
..s::
2
0.2
Qj
-"
:.:::i
a
a
I tubifex Habitat
10
20
Distance (km)
o
30
40
Figure 2. PTD~model results (T" D) for effects of T. tubifex habitat and distance to nearest known-positive,
within-drainage site on M. cerebra lis establishment.
Colorado. It is intuitive that waters in close prox
imity to other known-positive waters have a
greater probability of becoming contaminated
with the
by these means.
The models selected provide some guidelines
for
waters at the highest risk for estab
lishment of M. cerebralis and could be used to set
priorities for testing or regulations. Other parame
ters not examined in this study may very well have
an effect on presence or absence of M. cerebra/is,
and the results of this study may be an over-simpli
fiGltion due to exclusion of rhese unknown vari
ables. The possibility exists that, with time, the
range of M. cerebralis will expand into even the
most remote locations in Colorado.
The results indicate that the accidental stock
ing events, occurring rhe year of identifying the
hatcheries as M. cerebralis-positive, did not con
tribute substantially to the
of parasite in the
waters. However, 1vi. cerebralis was
found in a high percentage of the few warers that
were stocked the year after the hatcheries were
identified as positive. Continued stocking would
surely contribute more to the likelihood ofM. cere
bralis establishment. Colorado Division of Wildlife
regulations will prohibit sLOcking of M. cerebralis
exposed fish into salmonid habitat by 2003. Many
trout populations in Colorado are somewhat pro
tected from M.
due to their high eleva
tions, long distances to other infected waters, lack
of T.
and preclusion of further
stocking of infected fish into high-elevation waters.
Populations with abundant T. tubifex habitat, and
close proximity to known M. cerebralis-comami
nated waters, are at high risk for establishment of
M. cerebralis and should be closely monitored.
REFERENCES
the distribution of
C/crnnm!s the causative agent
disease, in the Cache la Poudre Rlver, Colorado.
Master of Science Thesis. Department of Fishery
and Wildlife Biology, Colorado State University.
Fort Collins, Colorado.
IVFVYllnfllW
�EVALUATION OF RISK OF HIGH ELEVATION COLORAIX"l \Xi:J\TERS
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on the abundance of Tubificidae. Hydrobiologica
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sequential enzymatic digestions and purification by
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Fabrication of Stainless Steel Spherical Anodes for Use with
Boat-Mounted Boom Electroshockers
Article in North American Journal of Fisheries Management · November 1992
DOI: 10.1577/1548-8675(1992)012<0840:FOSSSA>2.3.CO;2
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�North American Journal of Fisheries Management 12:840-843. 1992
Fabrication of Stainless Steel Spherical Anodes
for Use with Boat-Mounted Boom Electroshockers
sidered to be the most practical means of approximating the electrical field of a sphere while
avoiding the mechanical disadvantages of spherical electrodes (Novotny and Priegel 1974; Novotny 1990). The purported disadvantages of
spheres include lack of availability, difficulty in
KENNETH F. TIFFAN
assembly,
and impeded boat maneuverability.
U.S. Fish and Wildlife Service
Lack of availability has probably limited the
National Fisheries Research Center-Seattle
familiarity of many fishery workers with spherical
Columbia River Field Station
Cook. Washington 98605. USA
electrodes. Advertisements for commercially
available spheres did not appear in Fisheries magazine (the American Fisheries Society bulletin) unAbstract.—A> frugal method of fabricating spherical til 1989. Labor and materials often result in high
anodes from stainless steel mixing bowls is presented. costs for custom-made or commercially sold stainWe believe that the purported mechanical disadvantages
less steel spherical anodes. Our method of fabriof using spherical electrodes are largely unfounded.
cating spherical electrodes boasts considerable
savings over currently available commercial prodSpherical electrodes are generally believed to ucts.
have superior electrical properties (Novotny and
Stainless steel is widely considered to be the
Priegel 1974; Novotny 1990). A 1982 question- most desirable material for electrodes (Reynolds
naire of U.S. fishery workers (Lazauski and Mal- 1983) because of its corrosion resistance and duvestuto 1990), however, revealed that the most rability (Novotny 1990). We found satisfactory
commonly used anode closely followed the "Wis- spherical anodes could be fabricated from readily
consin ring" design described by Novotny and available and inexpensive stainless steel mixing
Priegel (1974). The Wisconsin ring anode consists bowls and other stainless steel components. We
of large numbers of "dropper" electrodes sus- worked with mixing bowls from department stores
pended from a 1 -m-diameter ring, and it is con- and restaurant supply houses and found the difPATRICK J. MARTINEZ
Colorado Division of Wildlife
317 West Prospect
Fort Collins, Colorado 80526. USA
�841
MANAGEMENT BRIEFS
Tubing
4 x 1/4 in
Cable
4 ft x 1/4 in
Bolt
3/4 x 1/4 in
Plate
1/16 x 2 x 3 in
Pop-rivets
1/8 x 3/8 in
FIGURE 1.—Schematic diagram depicting fabrication of a spherical anode made from mixing bowls. All materials
are stainless steel.
A fitting for attaching the sphere to a '/4-in stainTerences in bowl quality to have inconsequential
less steel cable is made by flattening 2 in of one
effects on anode performance.
Sphere assembly begins by facing two bowls of end of a 4-in x i/i-in (inside diameter) segment of
identical diameter toward each other (Figure 1) stainless steel tubing. One end of the cable is then
and clamping their aligned rims together with two inserted into the tube until it contacts the restricVise-grips. A 3/i$-in drill bit is used to make one tion, and the tube is then crimped onto the cable.
or two holes for rivets in three quadrants of the Next, a 3/g-in hole is drilled through the flattened
bowls' rims (use two holes per quadrant in bowls portion of the tubing, !/2 in from the end. A Vi-in
11 in or more in diameter). The unriveted quad- x 3/4-in stainless steel bolt is used to attach the
rant becomes the top of the electrode. Stainless cable to the sphere's tab (Figure 1).
The tag end of the cable is attached to the boom
steel pop-rivets (Vfe in x % in) are passed through
of the electrofishing boat. Cable length adjustthese holes and set.
A 2-in x 3-in x V^-in tab is cut from stainless ments are made so the entire sphere rides just
steel plate to serve as an attachment point to a under the water's surface. Then the portion of the
cable dropper. This tab is drilled '/2 in from an end cable in contact with the water and the tab of the
with a 3/s-in drill bit. The undrilled end is then sphere are insulated to preserve the characteristics
slipped between the rims of the two bowls at the of the spherically produced electrical field.
Novotny (1990) listed six requirements for eftop of the electrode, leaving 2.5 in of the tab extending beyond the sphere's equator. Two 3/i6-in fective electrofishing electrode systems. A spherholes are then drilled through the rims and tab '/2 ical electrode produces the largest zone of effective
in from the edges of the tab. Rivets are set in these electric current distribution in the water without
holes to secure the tab to the sphere. It may be generating locally large current densities that waste
necessary, especially with smaller bowls whose rims available power and potentially harm fish (Noare less flexible, to attach the tab before the rivets votny and Priegel 1974; Novotny 1990). Novotny
are set in the other three quadrants.
(1990) also recommended that electrodes be adAt least one hole per hemisphere (placed at the justable to accommodate changes in water conbottom of each bowl) is drilled in each sphere to ductivity. Conductivities less than 100 p,S/cm are
facilitate rapid sinking and draining. Additional considered low (Reynolds 1983; Nelson and Little
holes can be drilled if desired (Figure 1).
1988; Zalewski and Cowx 1990). Measurements
�842
MANAGEMENT BRIEFS
TABLE 1.—Comparison of electrofishing catches per unit effort between 1987 (when cylindrical and cable anodes
were used) and 1988(spherical anodes) at reservoirs sampled in northwestern Colorado. Electrofishing was conducted
with two anodes, one from each boom, and two netters collecting fish, unless otherwise specified. In 1987, all fish
species electroshocked were collected. In 1988, primarily sportfish were targeted for collection.
Reservoir
Surface
area
(hectares)
Conductivity
(MS/cm)
Sampling
date
Anode style
Fish species
capturedb
8
Number
offish
per hour
Elkhcad
178
290
180
Jul 1987
Jul 1988
CD, 18,2
SP. 11.2
FH, RT, WS, FM, GS, SM, LM
NP. RT. RS. WS, CC, BG. SM
222
245
Hollenbeck
24
205
250
Aug 1987
Jul 1988
CD, 18,2
SP. 13, l c
GS, BG, LM
GS, BG, LM
338
425
Harvey Gap
79
510
500
Aug 1987
Jul 1988
CD, 18.2
SP, 13, l c
RB. WS, BG, SM, LM, BC
RB, WS, BG, SM, LM
288
240d
Rifle Gap
162
770
750
Aug 1987
Jul 1988
CB, 24, 2
SP, 9, 2
RB, GS, SM. WY
RB, GS. SM. WY
132
156
Mack Mesa
12
550
1.000
Jul 1987
Jul 1988
CD, 18,2
SP, 13. l c
RB. CP, SM, GS, BG, LM
CP, GS, BG. SM, LM
250
288
Kenney
249
800
610
Jul 1987
Oct 1988
CB. 12,2
SP, 9. 2
RB. BT, CP, RT, RN, FH, SD, FM, BB
RB. CP. RT. WF. BH. FM. BB. LM
28
400
2,390
2,790
Aug 1987
Jul 1988
CB, 6, 2
SP. 7. l e
CP, GS, BG. LM, BC
NP, CP. GS, BG, LM, BC, YP
98
141d
Rio Blanco
47
a
Entries are anode type, anode size, number of anodes. Anode type: CD = 3-in-diameter aluminum conduit; CB = '/i-in-diameter
stainless steel cable: SP = sphere. Anode size is given in inches submerged in water (length for conduit and cable, diameter for
spheres).
b
RB = rainbow trout Oncorhynchus mykiss\ MW = mountain whitefish Prosopium williamsoni; BT = brown trout Salmo trutta\
NP = northern pike Esox lucius; CP - common carp Cyprinus carpio; RT = round tail chub Gila robusta; RN = red shiner
Cyphnella lutrensis: FH =* fathead minnow Pimephales promelas; SD = speckled dace Rhinichihys osculus\ RS — redside shiner
Richardsonius balteatus\ WS = western white sucker Catotomus commersoni\ BS = bluehead sucker C. discobolus: FS = flannelmouth sucker C latipinnis; BB = black bullhead Ameiurus melas\ CC = channel catfish Ictalurus punctatus\ GS - green sun fish
Lepomis cyanellus; BG = bluegill L. macrochirus\ SM = smallmouth bass Micropterns dolomieu\ LM = largemouth bass M.
salmoides, BC = black crappie Pomoxis nigrotnaciilatus\ YP — yellow perch Perca flavescensi WY = walleye Stizostedion vitreum.
c
A single spherical anode was fastened centrally on a length of aluminum angle spanning the booms.
d
Electrofishing was conducted with a single netter collecting fish.
c
A spherical anode was mounted on one boom and another sphere of equal size, serving as the cathode, was mounted on the other
boom.
ranging from 100 to 500 /tS/cm are considered to
encompass normal (Reynolds 1983) to extremely
high water conductivities (Serns 1982). However,
we concur with Zalewski and Cowx (1990) that
conductivities over 1,000 ftS/cm fall in the high
range. We routinely encounter conductivities
ranging from 50 to 3,000 nS/cm in northwestern
Colorado, and many waters exceed 500 pS/cm.
Lennon (1959) suggested electrodes of various
sizes were needed to successfully electrofish over
the wide range of conductivities encountered in
fresh waters. Reynolds (1983) advised adjusting
electrodes to accommodate varying conductivities, emphasizing that this meant changing electrode diameter, not merely raising or lowering the
electrode in the water.
The wide size range of stainless steel mixing
bowls easily accommodates this requirement.
Smaller spheres for higher water conductivities and
larger spheres for less conductive waters are easily
fabricated and switched as needed. Because of the
incremental range of mixing bowl sizes available,
the advantages of always using the largest electrode
possible within physical constraints and limitations of the generator and electrical control system
can be maximized (Novotny and Priegel 1974;
Novotny 1990). We successfully electrofished with
spherical anodes over a wide range of water conductivities, increasing our catches per unit effort
over those obtained by the use of dropper anodes
in nearly all cases (Table 1).
The ability to fabricate spheres of various sizes
addresses both the assembly and adjustability requirements. Concerns about avoiding unnecessary
water disturbances, which could impair observation of fish and maneuverability of the boat (Novotny and Priegel 1974; Novotny 1990), were answered during our extensive use of spherical
anodes.
We operated boat-mounted boom shockers in
�MANAGEMENT BRIEFS
both lentic and lotic habitats and never experienced an impaired ability to see or net fish that
had succumbed to the electrical current. Our ability to operate in weedy habitats, a specific consideration of Novotny (1990), was not hampered by
our use of spherical anodes. Our electrofishing success in weedy areas was affected more by an inability to net stunned fish entangled in vegetation
or by choking of the boat motor's propulsion or
cooling system with weeds. Even in swiftly flowing
rivers, we successfully negotiated obstructions that
could have proven hazardous if ring electrodes had
been used.
Perhaps the most legitimate criticism of spherical anodes is their impairment of boat maneuverability. However, this can be largely overcome
with good boatmanship. In standing water, it was
difficult to suggest any notable disadvantages of
spherical anodes. We strongly advise that boat operation in flowing waters not be relegated to inexperienced crew members. Other than this caution, we believe the purported mechanical
disadvantages of spherical anodes are largely unfounded.
Acknowledgments
We thank John Sharber for his interest in our
study. We gratefully acknowledge Robert Schmitz
for the illustration. We also thank Tom Nesler,
Tom Powell, and Melissa Trammell for reviewing
preliminary drafts of this manuscript.
View publication stats
843
References
Lazauski, H. G., and S. P. Malvestuto. 1990. Electric
fishing: results of a survey on use, boat construction,
configuration and safety in the USA. Pages 327-339
i/i I. G. Cowx, editor. Developments in electric fishing. Cambridge University Press, Cambridge, UK.
Lennon, R. E. 1959. The electrical resistivity meter in
fishery investigations. U.S. Fish and Wildlife Service, Special Scientific Report Fisheries 287.
Nelson, K. L., and A. E. Little. 1988. Increasing the
effectiveness of electrofishing boats in low conductivity waters. Proceedings of the Annual Conference
Southeastern Association of Fish and Wildlife
Agencies 41(1987):230-236.
Novotny, D. W. 1990. Electric fishing apparatus and
electric fields. Pages 34-88 in I. G. Cowx and P.
Lamarque, editors. Fishing with electricity: applications in freshwater fisheries management. Alden
Press, Oxford, UK.
Novotny, D. W., and G. R. Priegel. 1974. Electrofishing boats: improved designs and operational guidelines to increase the effectiveness of boom shockers.
Wisconsin Department of Natural Resources, Technical Bulletin 73.
Reynolds, J. B. 1983. Electrofishing. Pages 147-163 in
L. A. Nielsen and D. L. Johnson, editors. Fisheries
techniques. American Fisheries Society, Bethesda,
Maryland.
Serns, S. L. 1982. Relationship of walleye fingerling
density and eleclrofishing catch per effort in northern Wisconsin lakes. North American Journal of
Fisheries Management 2:38-44.
Zalewski, M., and I. G. Cowx. 1990. Factors affecting
the efficiency of electric fishing. Pages 89-111 in I.
G. Cowx and P. Lamarque, editors. Fishing with
electricity: applications in freshwater fisheries management. Alden Press, Oxford, UK.
�
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Environmental
0 1994 Kluwer
Biology
of Fishes 401221-239,1994.
Academic
Publishers.
Printed in the Netherlands.
Fish species composition before and after construction of a main stem
reservoir on the White River, Colorado
Patrick J. Martinez’, Thomas E. Chart2”, Melissa A. Trammel12X4,John G. Wullschlegef~5 & Eric P. Bergersen2
’ Colorado Division of Wildlife, Wildlife Research Center, 317 West Prospect, Fort Collins, CO 80526, U.S.A.
’ Colorado Cooperative Fish and Wildlife Research Unit’, 201 Wagar Building, Colorado State University, Fort
Collins, CO 80523, USA.
3 Cooperators are the US. Fish and Wildlife Service, the Colorado Division of Wildlife, and Colorado State
University
4 Current address: Utah Division of Wildlife Resources, Moab Native Fishes Field Station, P 0. Box 388, Moab,
UT 84532, U.S.A.
5 Current address: Utah Division of Wildlife Resources, Northern Regional Office, 515 East 5300 South, Ogden
UT 84405, U.S.A.
Received
18.6.1993
Accepted
8.12.1993
Key words: Ichthyofauna, Colorado River Basin, Impoundment, Nonnative fish, Habitat changes, Distrubution, Ptychocheilus lucius, Gila, Catostomus, Rhinichthys, Cyprinidae, Centrarchidae, Ictaluridae, Salmonidae
Synopsis
The completion in the fall of 1984 of Taylor Draw Dam on the White River, Colorado, formed Kenney Reservoir - thus impounding the last significant free-flowing tributary in the Upper Colorado River Basin. Fishes
were sampled above and below the dam axis prior to closure of the dam and in the reservoir and river downstream following impoundment. While immediate effects of the dam to the ichthyofauna included blockage of
upstream migration to 80 km of documented range for endangered Colorado squawfish, the reservoir also
proved to have profound delayed effects on the river’s species composition. Pre-impoundment investigations
in 1983-1984 showed strong domination by native species above, within, and below the reservoir basin. By
1989-1990, non-native species comprised roughly 90% of the fishes collected in the reservoir and 80% of the
fishes collected in the river below the dam. Initially, fathead minnow, whose numbers quickly increased in the
new reservoir, dominated all post-impoundment
collections, but red shiner became the most abundant fish
collected in the river below the dam by 1989-1990. While agency stocking programs for the reservoir sought to
emphasize a sport fishery for salmonids, primarily rainbow trout, local enthusiasm for warmwater sport fishes
resulted in illicit transfers of these species from nearby impoundments. Several species, formerly rare or
unreported in the White River in Colorado, including white sucker, northern pike, green sunfish, bluegill,
largemouth bass and black crappie, were present in the river following impoundment. Our investigation indicates smaller-scale, main-stem impoundments that do not radically alter hydrologic or thermal regimes can
still have a profound influence on native ichthyofauna by facilitating establishment and proliferation of nonnative species.
�228
T
N
RK 184.6
Kenney Reservoir
lk 176.9
Draw Dam
Douglas
Utah
I (Colorado
Creek
Piceance
\
Creek
\
I
4
i
30 kilometers
g
Utah
blorado
Fig. I. White River/Kenney Reservoir study area. River kilometers (RK) are demarcated from the confluence of the White and Green
rivers in Utah (see inset).
Introduction
Dams and reservoirs have had profound effects on
the ecology of the Colorado River system (Mullan
et al. 1976, Stanford & Ward 1986a, b, c). Its endemic
fishes have been negatively affected by modifications resulting from impoundments
(Behnke &
Benson,’ Hickman 1983, Holden & Stalnaker 1975,
Miller 1946,1961, Minckley & Deacon 1968, lyus et
al. 1982, Vanicek et al. 1970). Further, competition
with non-native fish species, many of which thrived
in the modified environments within and downstream from reservoirs, may also have contributed
to the decline of native species (Stanford & Ward
1986~). Effects of damming a river have been classified as immediate and delayed (Holden 1979). Immediate effects include those that become apparent
when a dam becomes operational. Delayed effects
become evident several years after dam completion
’ Behnke, R.J. & D.E. Benson. 1980. Endangered and threatened fishes of the Upper Colorado River Basin. Cooperative Extension Service Bulletin 503A, Colorado State University, Fort
Collins. 34 pp.
(Holden 1979). The closure of Taylor Draw dam on
the main stem White River in October 1984, proved
to have both immediate and delayed impacts on the
river’s fish community.
Immediate effects included blockage of upstream migration to 80 km of river known to contain Colorado squawfish Ptychoceilus lucius (Martinez,* Chart 1986), a large piscivorous minnow listed as endangered by the U.S. Department of the Interior. Summertime aggregations of adult Colorado
squawfish below the dam following its closure were
believed to be composed of post-spawners returning to home ranges from spawning sites in the
Green and Yampa rivers. The death of several of
these adult fish in 1985 due to angling activity below
the dam prompted an emergency regulation prohibiting angling in this area (Martinez*).
In addition to these immediate effects on Colorado squawfish, the fish community of the White River also experienced both immediate and delayed
* Martinez, P.J.1986. White River Taylor Draw Project pre- and
postimpoundment fish community investigations. Colorado Division of Wildlife, Fort Collins. 121 pp.
�229
changes in species composition. Construction disturbance of the river channel, habitat conditions of
the reservoir, and changes in conditions below the
dam all appeared to favor proliferation of certain
non-native species. The final provision of the biological opinion issued for the Taylor Draw Reservoir Project (U.S. Department of the Interior, Fish
and Wildlife Service, 20 May 1982) required development of a fishery in Kenney Reservoir that would
not compete with endangered species in the White
River. While agency stocking programs emphasized a salmonid fishery to accommodate this provision, local enthusiasm for warmwater sport fishes
resulted in illicit introductions of warmwater sport
fishes from nearby impoundments in both Colorado and Utah. In this paper we document these
changes in the ichthyofauna in the White River,
Colorado, following the construction of Taylor
Draw Dam and formation of Kenney Reservoir.
Study area
The White River was one of the few remaining freeflowing tributaries in the entire Colorado River Basin (Stanford & Ward 1986a). A major tributary in
the Green River subbasin (Fig. l), the White River
drains more than 13 000 km2 in Colorado and Utah.
The White River flows about 400 km from its
source in Colorado’s Flattop Mountains to its confluence with the Green River at Ouray, Utah. Locations along the river were demarcated as river kilometers (RK) upstream from its confluence with
the Green River.
Taylor Draw Dam was completed on the White
River in October 1984, about 16 km east of Rangely,
Colorado, at RK 167.8. Kenney Reservoir, which
filled by January 1985, inundated about 10 km of the
river (to RK 176.9; Fig. 1). The reservoir was originally 275 ha, had a maximum depth of 15.2 m, and a
volume of 17 million cubic meters of water at a maximum elevation of 1620 meters above sea level;
however, these capacities have decreased an undetermined amount due to sediment deposition, particularly in the upper portion of the reservoir
(Trammel1 1991). Kenney Reservoir is about 8 km
long and 1.2 km at its widest point. Aside from im-
poundment, the dam’s influence on hydrologic and
thermal conditions in the White River were subtle
(Chart & Bergersen 1992).
Fish collections were made from RK 115.5, the
Colorado/Utah stateline, to RK 184.6, about 9 km
above the reservoir basin. The White River in this
area ranged in width from 20 to 50 m. Channel substrates were primarily cobble and rubble in flowing
areas and silt and sand in slower moving sections.
The hydrologic regime is characterized by extremes
in flow, with highest discharge during snowmelt in
spring and early summer, and lowest in late summer
and early fall. Turbidities of the river are typically
high in spring and during summer rainstorms. Summer water temperatures exceed 20” C, and the environment has been described as coolwater/warmwater (Martinez2, McConnell et al.‘). This segment of
the White River meanders through an agricultural
valley bordered by low rocky hills. Near the Colorado/Utah state line, surrounding lands become
more barren as the river flows through canyon areas. This topography supports vegetation characteristic of this semi-arid region (Wullschleger 1990).
Investigations of the river’s fish community in
Colorado in the years preceding construction of the
dam showed that native species dominated (Carlson et a1.4and Tyus et al. 1982). Fish collections reported in Carlson et a1.4during 1975-1977 revealed
that seven native species comprised 94.0% of fishes
collected while five non-native species accounted
for 6.0%. Miller et al.’ recorded five native species
accounting for 75.8% of the ichthyofauna and six
non-native species comprising 24.2% in two
reaches included in our study area. Lanigan & Berry (1981) showed non-native species dominated fish
collections in Utah in 1978-1979, but native fishes
3 McConnell, W.J., E.P. Bergersen & K.L. Williamson. 1984.
Habitat suitability index models: a low effort system for planned
coolwater and coldwater reservoirs (revised). U.S. Fish and
Wildlife Service FWSIOBS-82/10.3A, Fort Collins. 62 pp.
4 Carlson, C.A., C.G. Prewitt, D.E. Snyder, E.J. Wick, E.L.
Ames & W.D. Fronk. 1979. Fishes and macroinvertebrates of the
White and Yampa River, Colorado. Biological Sciences Series 1,
Bureau of Land Management, Denver. 276 pp.
5 Miller, W.H., D.L. Archer, H.M. Qus & K.C. Harper. 1982.
White River fishes study. Colorado River Fishery Project, U.S.
Fish and Wildlife Service, Salt Lake City. 23 pp.
�230
Table 1. Numbers of fishes collected in the White River, Colorado, above Kenney Reservoir basin (river kilometers 176.9-184.6) from
1983-1985, and below Taylor Draw Dam (river kilometers 115.5-167.8) from 1983-1985, and 1989 and 1990. Sampling methods included
combinations of drift nets (d), electrofishing (e), gill nets (g), and seining (s) as indicated. * = < 0.5%.
Above reservoir
Below dam
Year
Sampling methods
1983
e,s
1984
es
1985
e,s
1983
6s
1984
es
Roundtail chub
186
5.0
1
Native
463
2.7
1
128
1.3
1
*
1704
17.3
2467
25.1
3232
32.8
13
*
3
*
1562
20.0
1
*
2452
31.4
2346
30.0
1222
15.6
34
*
I
*
1609
8.2
5
7548
7618
13868
14
792
4.0
136
0.7
4828
24.5
7
Colorado squawfish
Speckled date
Bluehead sucker
Flannelmouth sucker
Mountain whitefish
Mottled sculpin
Total native
*
1226
33.1
1138
30.8
1032
27.9
15
*
4
*
*
3602
15167
Red shiner
Common carp
Fathead minnow
*
56
1.5
17
0.5
12
3469
20.1
8237
47.8
2985
17.3
12
*
Non-native
116
0.7
24
*
1920
11.1
18
3
*
2101
21.3
*
*
*
11
*
5
Rainbow trout
*
4235
21.4
4509
22.9
3508
17.8
2
*
7
78
l.0
25
2
*
76
0.9
*
*
67
1989
d,g,s
902
2.4
7
12629
33.7
6607
17.7
7792
20.8
18
*
*
*
*
*
*
Black bullhead
Channel catfish
*
1985
e,s
1
*
5249
13.0
33
3
9491
133
11591
49.5
1136
4.8
6140
26.2
48
*
20
*
6
*
9
*
13
*
1
*
300
1.3
18406
45.6
2684
6.6
7944
19.7
1604
4.0
2
*
1
*
*
*
*
205
0.5
8769
23.4
2
98
254
0.7
Green sunfish
Largemouth bass
Total fish
*
720
1.8
2
4169
Brown trout
Total non-native
2513
10.7
25
*
3377
8.4
110
27956
170
1.7
Black crappie
*
758
3.2
223
0.9
600
2.6
47
1990
d,g,s
*
1
*
*
80
143
96
2065
2299
195
5831
9461
19263
30864
3698
17232
9847
7813
19699
37417
23432
40355
�231
Table 2. Numbers of fishes collected in the White River, Colorado, encompassed by Kenney Reservoir basin (river kilometers 167.9176.8), 1983 and 1984, and in Kenney Reservoir, 1985 and 1987-1990. Sampling methods included combinations of electrofishing (e), gill
nets (g), and seining (s) as indicated. * = < 0.5%
River
Year
Sampling methods
1983
s
Roundtail chub
344
12.0
Reservoir
1984
s
1985
e,s
1987
e,gs
1988
em
63
11.5
333
4.4
66
0.9
1989
e,g,s
1990
em
Native
992
1.4
604
2.7
Colorado squawfish
Speckled date
Bluehead sucker
709
24.8
3696
275
405
1440
5614
50.4
41.8
5866
26.8
343
12.0
1601
11.9
Flannelmouth sucker
1.8
1621
7.4
4
0.7
75
13.8
407
5.4
198
2.6
70
12.8
1309
17.2
8
*
Mountain whitefish
Mottled sculpin
Total native
11903
*
1688
1.9
32.5
*
481
0.7
123
*
477
0.5
105
*
6942
10.0
2
*
5257
5.9
17
*
1
*
2836
595
0.7
246
212
8497
2321
8389
7869
Non-native
Red shiner
*
8
143
144
8
1.1
0.7
1.5
Common carp
24
31
6.8
73
1.0
1380
13208
191
3519
10.3
60.2
35.0
46.4
7
1.3
1309
17.2
*
Fathead minnow
13
*
28
*
White sucker
Black bullhead
Channel catfish
10
Rainbow trout
47
*
Brown trout
1.8
78
14.3
3
0.5
Green sunfish
Total fish
746
0.8
64302
72.6
14
*
29
*
28
*
1
3
286
3.8
*
396
0.6
2
82
*
*
2
4
*
158
I
*
Black crappie
Total non-native
211
*
57099
82.6
63
*
*
*
Largemouth bass
99
*
5
*
*
Bluegill
251
*
*
34
2660
3.8
15220
17.2
21
1523
13423
334
5261
60714
80650
2857
13426
21920
546
7582
69103
88519
�232
83
84
85
83
84
85
87
88
89
90
83
84
85
89
Below
dam
90
Year
Above
reservoir
Reservoir
basin
n Nativeq Non-native
Fig. 2. Percentage comparison of native and non-native fishes sampled above Kenney Reservoir basin, within the basin and reservoir
following completion, and downstream of Taylor Draw Dam, 1983-1990.
comprised the greater proportion in samples nearest to the Colorado/Utah stateline. These studies indicate prior to this investigation, the ichthyofauna
of the White River within the section described in
this paper was dominated by native species.
Methods
Fish samples were taken above the reservoir basin
from RK 176.9-184.6 (198~1985), within the river
and basin encompassed by the reservoir from RK
167.9-176.8 (1983-1985, 1987, 1989-1990) and below Taylor Dam from RK 115.5-167.8 (1983-1985
and 1989-1990). Sampling in the river was performed by various combinations of seining, electrofishing, gill netting, and drift nets, typically from June to
October. Details of these samplings are given in
Martinez, Chart (1987) and Trammel1 (1991). Seining was performed in backwater and low velocity
habitats using a 4.5 xl.2 m two-man seine with
15 mm mesh. Electrofishing (pulsed DC) from a
boat was performed during the day along shoreline
areas in all habitat types. Gill nets (multifilament
45.7x 3.6m x 19 mm square mesh or 30.5 mx
1.5 m x 19 mm square mesh) were used immediately below the dam and in the reservoir. Drift nets
(0.6 m x 2.4 m frames holding 1.2 m diameter trawls
fitted with 6.3 mm mesh) were set in the channels
directly below the spillway. In addition to gill nets,
sampling in the reservoir was conducted using bag
seines and electrofishing gear. The seine, 12.2 x
1.2 m, 9.5 mm wing mesh and 3.2 mm bag mesh, was
used to sample shoreline areas. Electrofishing was
�233
performed using boat-mounted equipment at night
near shore along the reservoir’s length. Gill nets
were set overnight in all major habitats (shallow
and deep coves, cliff and sloping areas, surface, bottom and midlake). Seining accounted for 85-99%
of fishes collected (Martinez2, Trammel1 1991). Typically, larger fish, and all Colorado squawfish, were
identified and released. Large samples of small fish
were preserved in 10% formalin and returned to the
laboratory for identification and enumeration.
Results
Pre-impoundment
species composition
Fish samples taken in 1983-1984 prior to closure of
Taylor Draw dam were dominated by four native
species; roundtail club Gilu robustu, speckled date
Rhinichthys osculus, bluehead sucker Catostomus
discobolus and flannelmouth
sucker Catostomus
luttipinnis (Tables 1,2). Three other native species
reported in pre-impoundment
collections, Colorado squawfish, mountain whitefish Prosopium wifliumsoni and mottled sculpin Cottus bairdi, comprised no more than 0.5% in 1983 or 1984. Overall,
native species accounted for over 97% of the fish
collected in 1983 (Fig. 2). In 1984, dominance by native species persisted, but not as overwhelmingly as
observed in 1983. Species composition above the
dam construction site in 1983 was about 88% native
and 12% non-native while below the dam axis
70.4% of the fish collected were native and 29.6%
were non-native.
Among introduced species, fathead minnows Pimephales promelas were rarely collected in 1983,
but after 1984, fathead minnow numbers increased
dramatically in samples both above and below the
dam axis (Tables 1, 2). The greater proportion of
this species below the dam axis may have been due
to ponding in the vicinity of the dam construction
area that probably enhanced fathead minnow reproduction. Additionally, other non-native species
were collected including red shiner Cyprinella lutrensis, common carp Cyprinus carpio, black bullhead Ameiurus melas and channel catfish Zctalurus
punctutus, none exceeding 1.5%. A single, 200 mm
black crappie Pomoxis nigromaculatus was sampled below the dam in 1984 (Table 1). These data
further substantiated preimpoundment dominance
by native fishes within the study area (Fig. 2).
Post-impoundment
fish community changes
The White River fish community began showing increased abundance of non-native species in 1984,
during construction of the dam; however, marked
changes occurred primarily in the reservoir in 1985,
the first year of impoundment. Fathead minnows
increased from 10.3% in the pre-impoundment
reservoir basin in 1984 to 60.2% of all fishes collected
in the reservoir in 1985 (Table 2). In this initial year
of impoundment, relative abundance of other nonnative species remained low. The most marked decrease among native species in the reservoir was observed for speckled date. Comprising about 20% to
30% of the fish collected throughout the study area
before impoundment, speckled date accounted for
only 1.8% of the fish collected in the reservoir in
1985.
Subsequent fish collections made in the reservoir
in 1987 consisted of 61.2% non-native species (Fig.
2). Although fathead minnow numbers dominated
samples, and undoubtedly the reservoir’s fish population, their relative abundance was offset by increased collection of stocked rainbow trout Oncorhynchus mykiss (Table 2). Originally stocked as the
reservoir began to fill in 1984, rainbow trout have
been stocked annually to provide a sport fishery in
Kenney Reservoir. The apparent increase in relative abundance of roundtail club, flannelmouth
sucker, and common carp in 1987 seemed due to
their susceptibility to gill nets set in shallower
depths. Bluehead sucker abundance, however, was
much lower in the reservoir in 1987 than in 1985.
Numbers of speckled date collected in 1987 continued to be conspicuously low.
Fathead minnows also dominated reservoir fish
collections (46.4%) in 1988 (Table 2). Black bullheads increased from 1.3% in 1985 to 17.2% (over
99% young-of-year) in 1988. The presence of adultsized green sunfish Lepomis cyanellus, bluegill Lepomis machrochirus, largemouth bass Micropterus
�234
salmoides and black crappie was attributed to illicit
introductions. Of the other native species collected,
most declined or increased little in relative abundance from previous observations, except Colorado squawfish. Their appearance was due to the
stocking of 17 000 juveniles in April 1988 as part of
an experiment to determine if they could be managed in a reservoir environment as a sport fish
(Trammel1 1991, Trammel1 et al. 1993).
Native fishes comprised only 12.1% of fish collected in the reservoir in 1989 (Fig. 2) while the remainder were non-native species, primarily fathead
minnows (Table 2). While percentages of other
non-native species were low, black crappie increased in relative abundance. Rare in 1988, black
crappie composed 3.8% of all fishes collected in the
reservoir in 1989. White suckers Catostomus commersoni were first recorded in the reservoir in 1989.
The only native species composing a notable percentage in the reservoir was the flannelmouth sucker (10%); all other native species accounted for less
than 1.0% in 1989. Of 246 Colorado squawfish collected in the reservoir in 1989,243 were from 32 000
fingerlings that had been stocked in April 1989. The
other three specimens had been stocked in 1988
(Trammel1 1991, Trammel1 et al. 1993).
Non-native species in reservoir fish collections
increased to 91.1% in 1990 (Fig. 1). Fathead minnow
numbers remained high (72.6%), their abundance
probably facilitating rapid expansion of black crappie whose numbers rose to 17.2% in 1990 (Table 2).
Relative abundance of other non-native species
was low, although common carp and bluegill were
collected in greater numbers than in 1989. Collection of white suckers in 1990 suggested that they had
become permanent residents within the drainage.
Six native species accounted for only 8.9% of the
fishes in 1990 reservoir samples with flannehnouth
sucker (5.9%) and roundtail chub (1.9%) being the
only species collected in appreciable numbers. Colorado squawfish collected in 1990 were from the final plants of juveniles in May (32 000), August
(1397), and September (14 200) (Trammel1 1991,
Trammel1 et al. 1993).
Fish collections above Kenney Reservoir following impoundment were made only in 1985. While
native fishes dominated (79.9%) fathead minnows,
particularly in the reservoir inflow, accounted for
over 90% (Table 1) of the 23.3% non-native fish
component (Fig. 2). Prior to impoundment, fish collections above the reservoir basin were dominated
by three native species, speckled date - 17.3%,
bluehead sucker - 25.1%, and flannelmouth sucker
- 32.8%.
After impoundment in 1985, native species, primarily speckled date, bluehead sucker and flannelmouth sucker, comprised 74.7% of fishes collected
in the river below Taylor Draw Dam (Table 1, Fig.
2). Fathead minnows, comprising 23.4% of all fishes
collected in 1985, greatly outnumbered all other
non-native species, none of which exceeded 1%. In
1989 and 1990, fish collections below the dam were
roughly 80% non-native and only 20% native. The
two native species seemingly most affected following impoundment were bluehead sucker and speckled date. Both species formerly shared dominance
among native fishes with flannehnouth sucker and
roundtail chub in both pre- and post-impoundment
collections below the dam. In 1989-1990, speckled
date composed about 2% of all fishes collected below the dam while bluehead sucker accounted for
less than 0.5%. Increased captures of Colorado
squawfish below the dam in 1989-1990 resulted
from escapement of juveniles stocked in the reservoir (Trammel1 1991, Trammel1 et al. 1993).
Non-native red shiner and common carp showed
the most notable increases below the dam (Table 1).
While fathead minnows composed 20-26% of the
fishes collected below the dam in 1989 and 1990, red
shiners outnumbered them two-fold in both years
becoming the most collected species below the
dam. Common carp, scarce in this segment of the
White River prior to impoundment, increased noticeably in both 1989-1990, particularly the incidence of juveniles in seine samples (Trammel1 1991).
As believed in the case of common carp, increased
abundance of black crappie below the dam in 19891990 most likely resulted from increased abundance
of these species in the reservoir. These black crappie young-of-year and juveniles, were taken in seine
or drift net samples (Trammel1 1991).
�235
Holden (1979) considered riverine fishes to include
obligate and facultative rive&e species. He further
divided obligate riverine species into species requiring rivers for all their ecological needs and
those requiring rivers for a portion of their life history. The effect of damming a river on obligate riverine species is generally negative and is a major
cause in the decline of these species (Holden 1979).
Observations made during this study, suggest the
most obligate riverine species, i.e. Colorado squawfish, speckled date and bluehead sucker, were most
affected by impoundment of the White River.
During our study, a single wild Colorado squawfish was captured above the dam following its closure. This adult specimen, captured in 1985, was the
last wild Colorado squawfish verified in the White
River above Taylor Draw Dam. Adult Colorado
squawfish from the White River undertake extensive potamodromous
migrations for spawning in
the Green and Yampa rivers (Martinez2, Tyus 1990).
Martinez* reported the migrations of one adult Colorado squawfish captured near Rangely, Colorado,
in 1983. This fish, recaptured near known spawning
sites in the Yampa River in 1984, was subsequently
caught by an angler in the White River near its original capture site in 1985, thus confirming at least
700 km of upstream and downstream movements in
three rivers (Martinez2). The effect on Colorado
squawfish, formerly resident in the river above the
dam prior to impoundment, becomes obvious. Further, stocking there does not seem a long-term solution to maintaining this species in its historic range
above Taylor Draw Dam (Trammel1 1991, Trammel1
et al. 1993).
The decline in relative abundance of both speckled date and bluehead sucker following impoundment is probably attributable to their obligate riverine life histories. Speckled date, a more lotic adapted species (Minckley 1973, Woodling,’ Sublette et
al. 1990), and bluehead sucker, largely limited to
relatively swift-flowing waters over cobble or gravel (Baxter & Simon 1970, McAda & Wydoski 1983,
Sublette et al. 1990), displayed an affinity for flowing habitats in the White River (Chart 1987). While
their reduced abundance in the reservoir could be
attributed to their lotic preferences, reductions of
these species below the dam in 1989-1990 was not as
readily explained.
Chart (1987) reported speckled date reproduction to be especially high below the dam in 1985. He
suggested that habitat preference of adult speckled
date should preclude competition with the burgeoning fathead minnow population, but young
speckled date would likely face considerable competition from this species. Red shiner, the most
abundant species below the dam in 1989-1990, may
be a serious competitor with native species in the
Colorado River Basin (Holden 1979, Nesler7). The
combined effects of fathead minnow and red shiner
(Karp & Tyus 1990) may have contributed to the reduction of speckled date. Because speckled date
are short-lived (few live beyond 3 years, Sigler &
Sigler 1987), mortality of their young due to competition and lack of recruitment may explain their demise below the dam.
Chart (1987) suggested bluehead suckers in the
lower reaches of the White River in Colorado came
from reproduction by this species in and above the
vicinity of Kenney Reservoir. This belief was substantiated by Lanigan & Berry (1981) who showed
bluehead suckers in the White River in Utah were
scarce, composing less than 0.5% of all fish collected. During our investigation, bluehead suckers
were most abundant above the dam axis from 1983
to 1985. Chart (1987) attributed the reduction in
young-of-year bluehead suckers below the dam in
1985 to poor drift of larvae through the reservoir.
He further reasoned that this loss of supplemental
recruits from upstream spawning areas would result
in the long-term decline of bluehead suckers below
the dam. This mechanism explained the stark reductions of this species below the dam in 1989-1990.
’ Woodling, J. 1985. Colorado’s little fish: a guide to the minnows
and other lesser known fishes in the state of Colorado. Colorado
Division of Wildlife, Denver: 77 pp.
’ Nesler, T.P 1991. Endangered fishes investigations. Job Progress Report, Federal Aid in Fish and Wildlife Restoration Project SE-3, Colorado Division of Wildlife. Fort Collins. 69 pp.
Discussion
Effects on the native fish component
�236
Young-of-year and older juvenile bluehead suckers
dominated seine samples from the White River
from 1983 to 1985 (Martinez’, Chart 1987); seining
was also the principle means of sampling fish in the
river in 1989-1990 (Trammel1 1991).
While evidence is lacking to show roundtail chub
and flannelmouth sucker benefitted from impoundment of the White River, neither should be as adversely affected as bluehead sucker and speckled
date. Roundtail chubs and flannelmouth suckers
continued to be commonly collected in Kenney
Reservoir, although their abundance relative to
numbers of non-native fishes was low. Behnke’predicted roundtail chub would increase following impoundment. Chart (1987) suggested roundtail chub,
unless replaced by further introductions of non-native species, could flourish in Kenney Reservoir.
Chart & Bergersen (1992) indicated Taylor Draw
Dam would not affect flannehnouth suckers in the
White River due to their distribution and movement patterns. Both roundtail chub and flannelmouth sucker occur in reservoirs (Baxter & Simon
1970); both occur in Elkhead Reservoir, an off-stem
impoundment in the Yampa River drainage where
their persistence indicates recruitment has occurred (Martinez unpublished data).
Mountain whitefish and mottled sculpin inhabit
the White River, primarily upstream of Kenney
Reservoir (5~s et al. 1982). Immediate effects of
impoundment on these species appeared negligible
and significant delayed effects are not expected.
Consequences of non-native fishes
Lanigan & Berry (1981) suggested native fishes in
the White River in Utah were being replaced by
non-native species. They believed habitat deterioration and competition were operative in the lower
White River, and were responsible for a pattern of
native fish displacement in other western rivers and
streams. While they demonstrated the relative
abundance of native fishes was greater than that of
non-native species in their uppermost stations near* Behnke, R.J. 1981. Taylor Draw Reservoir: aquatic biology assessment. Western Engineers Inc., Grand Junction. 16 pp.
est to Colorado, non-native species accounted for
80.4% of the fish collected in their middle and lower
stations (Lanigan & Berry 1981). Replacement of
the predominantly native ichthyofauna by non-native fishes in the lower White River in Colorado was
facilitated and certainly greatly accelerated by construction of Kenney Reservoir. Relative abundance
of non-native species in the White River below Taylor Draw Dam in 1989 and 1990 averaged 79.4%;
thus, in less than a decade, the riverine ichthyofauna of the lower White River in Colorado has shifted
from 90% native to 80% non-native species.
All non-native fish species recorded during this
study were formerly known to occur in the White
river drainage, either upstream or downstream of
the study site or in Rio Blanc0 Lake, a shallow, offstem impoundment at RK 243 (Fig. 1) managed for
warmwater sport fishes. Nesler’ listed six non-native species posing the greatest threat to native fishes in the upper Colorado River basin: red shiner,
common carp, fathead minnow, channel catfish,
northern pike, and green sunfish. In addition,
McConnell et a1.3 predicted Kenney Reservoir
would provide highly suitable habitat for common
carp, white sucker and black crappie. While non-native species collected during this investigation, except largemouth bass, had been previously reported
from the White River (@us et al. 1982, Martinez’),
none were formerly dominant in the river in Colorado.
Red shiner was reported by Lanigan & Berry
(1981) and Miller et al? to be the most abundant fish
from their lowermost stations in the White River,
Utah. The combined percentage for red shiner in
these stations was about 66% in 1978 and 1979 (Lanigan & Berry 1981) and 1981 (Miller et a1.5). Formerly composing much lower percentages in the
White River in Colorado prior to impoundment
(Carlson et a1.4,Miller et al.‘), red shiner accounted
for about 47% of all fishes collected in 1989 and
1990. It appears the segment of the White River in
which red shiners dominate has increased by more
than 50% since impoundment.
Common carp and fathead minnow were rare in
the White River in Colorado prior to formation of
Kenney Reservoir (Tyus et al. 1982). Carlson et a1.4
and Miller et al.’ showed neither species accounted
�237
for more than 5% of the fishes collected during
their studies. McConnell et a1.3suggested prevailing
habitat conditions in Kermey Reservoir would favor common carp. While common carp numbers did
not increase as rapidly as expected (Chart 1987) its
numbers in the reservoir did increase and its relative abundance below the dam increased noticeably. We expect the segment of the White River below the dam where common carp and fathead minnow are common will extend downstream in time.
White suckers were reported by Pettus’,” from
the White River near the mouth of Piceance Creek.
These records were questioned by Carlson et al4
because white suckers had not been reported in the
White River by other investigators. Tyus et al.
(1982) also considered the species to be absent in
the White River, however, a single specimen was reported in collections from the White River in Utah
by ERI.” It appears white suckers were virtually absent in the White River prior to impoundment, and
none were found in our river collections. The individuals captured in Kenney Reservoir in 1989-1990
were taken in gill nets by Trammel1 (1991) who
found no evidence of reproduction or recruitment.
Despite this it seems that white sucker abundance
and distribution will increase due to favorable habitat conditions for this species in the reservoir
(McConnell et a1.3).
In addition to concerns about non-native fishes
replacing native species, juveniles of endangered
fishes in nursery backwaters of the Green River in
Utah (Archer & Tyus’“) may be at greater predation
risk if Kenney Reservoir becomes a chronic source
of non-native piscivores. Martinez believed warmwater sport fish escaping from Rio Blanc0 Lake
’ Pettus, D. 1973. Cold-blooded vertebrates of the Piceance
Creek Basin, Rio Blanc0 and Garfield counties, Colorado.
Thorne Ecological Institute, Boulder. 19 pp.
” Pettus, D. 1974. Inventory and impact analysis of fishes, Piceance Creek Basin, Rio Blanc0 and Garfield counties, Colorado. Thome Ecological Institute, Boulder. 13 pp.
” Ecosystem Research Institute (ERI). 1983. Investigation of
fish distribution, habitat, and food preference in the White River, Utah and Colorado for White River Shale Oil Corporation.
Logan. 162 pp.
‘* Archer, D.L. & H.M. Tyus. 1984. Colorado squawfish spawning study, Yampa River. U.S. Fish and Wildlife Service, Salt Lake
City. 34 pp.
(Fig. 1) prior to formation of Kenney Reservoir
would not proliferate in the White River due to the
lack of suitable habitat. However, Kenney Reservoir offers more favorable habitat for these species
and may contribute to their increased abundance
and distribution (Martinez2, Trammel1 1991). Concern about northern pike Esox fucius from Rio
Blanc0 Lake proliferating in the White River as
they did in the Yampa River following their escape
from Elkhead Reservoir was a primary factor warranting isolation of Rio Blanc0 Lake following impoundment of the White River (Martinez2). No
northern pike were collected during our investigation; however, two were caught by anglers in the
White River below Taylor Draw Dam, one each in
1987 and 1990. Anglers also reported catching
northern pike in Kenney Reservoir in 1989-1990
(Trammel1 1991). Behnke’ suggested that this species would flourish in Kenney Reservoir if introduced there; however, no evidence to date indicates
this species has become established in the White
River.
Wiltzius3 reported channel catfish were stocked
in the White River in 1910. Lemons14 stated channel
catfish inhabited the White River in Colorado only
within the lower 32 km from Rangely to the stateline. Habitat suitable for channel catfish in the
White River is poor in comparison to other rivers in
western Colorado (Lemons14). This species was
considered rare throughout the White River (Carlson et a14, Lanigan 8~ Berry 1981, Tyus et al. 1982)
and this continued to be the case during our investigation. Lemons14 found no evidence of reproduction by this species, and only a single young-of-year
specimen was collected near the state line in 1985
(Martinez’).
Behnke’ predicted channel catfish
would increase in Kenney Reservoir, however, the
number of channel catfish collected in the reservoir
decreased during our investigation. Their decline
was most likely due to harvest by anglers and lack of
natural reproduction due to inadequate temper” Wiltzius, W.J. 1985. Fish culture and stocking in Colorado,
1872-1978. Division Report No. 12, Colorado Division of wildlife, Fort Collins. 102 pp.
” Lemons, D.G. 1955. Channel cat study. Project Number 121,
Colorado Game. Fish and Parks Department, Fort Collins. 9 pp.
�238
atures (Martinez
unpublished
data). Unless
stocked, channel catfish should not increase in
abundance in Kenney Reservoir or in the White
River above the reservoir.
Green sunfish were considered rare in the White
River and restricted largely to Utah (5~s et al.
1982). Adult and young-of-year green sunfish were
collected below the dam in 1989-1990 suggesting
this species could spread throughout in the lower
White River. Conditions in Kenney Reservoir
proved favorable for black crappie; this species reproduced successfully in the reservoir and may reproduce in the river immediately below the dam
(Trammel1 1991). Reports of black crappie in the
White and Green rivers near their confluence in
Utah in 1989 (S. Cranney personal communication)
confirmed that its distribution increased greatly beyond that reported by l@ts et al. (1982). Other
warmwater sport fish collected, black bullhead,
bluegill and largemouth bass, are not expected to
increase dramatically, but the reservoir provides
more favorable habitat for them than occurred in
the unimpounded White River.
Large numbers of trout stocked in Kenney Reservoir moved over the dam resulting in as many
trout being harvested in the plunge pool and channels immediately below the dam as in the reservoir
itself. While trout were reported in the White River
as much as 50 km below the dam. few were reported
after springtime suggesting that trout moving
downstream out of the reservoir were caught, had
dispersed widely, or had died. Trout escapement
from the reservoir was presumed innocuous, however, large numbers of trout in the river increased
angling activity that may have increased incidental
catch of Colorado squawfish.
Construction of large main stem dams on the upper Colorado River and its tributaries have contributed to highly altered flow, water temperature, and
sediment transport at the expense of native fishes
(Wydoski & Hammill 1991). Aside from the resulting loss of stream habitat through inundation and
blockage of migration routes due to impoundment
(Wydoski & Hammil1991) Taylor Draw Dam and
Kenney Reservoir imparted comparatively subtle
physical changes to the White River (Wullschleger
1990, Chart & Bergersen 1992). Despite this, our in-
vestigation indicates smaller-scale, main stem impoundments pose a substantial threat to native ichthyofauna by facilitating establishment and proliferation of non-native fishes. Probably the greatest
boon to non-native species resulting from Kenney
Reservoir is that it provides suitable habitat for
their recruitment. It is this ecological benefit to
non-native species that will facilitate their continued proliferation in the White River.
Acknowledgements
Water User’s Association Number 1 provided funding for the early portion of this study and their personnel, G. Trainor, J. Geyler and J. ‘Hoot’ Gibson,
provided valuable support. W. Burkhard and R.
VanBuren, Colorado Division of Wildlife, initiated
this study. A. Martinez identified fish larvae during
the early portion of this study. U.S. Fish and Wildlife
Service, Colorado River Fishery Project, provided
funding, equipment, and assistance in various aspects of these projects. We especially thank
USFWS biologists L. Kaeding, B. Burdick and H.
Tyus. S. Cranney, Utah Division of Wildlife Resources, provided fish distribution and access information during the early portion of this project. We
thank W. Wiltzius, T. Powell, T. Nesler, R. Behnke
and an anonymous reviewer for reviewing drafts of
this paper.
References cited
Baxter, G.T. & J.R. Simon. 1970. Wyoming fishes. Wyoming
Game and Fish Department Bulletin 4, Cheyenne. 168 pp.
Chart, T.E. 1987. The initial effect of impoundment on the fish
community of the White River, Colorado. M. SC.Thesis, Colorado State University, Fort Collins. 112 pp.
Chart, T.E. & E.P. Bergersen. 1992. Impact of mainstream impoundment on the distribution and movements of the resident
flannelmouth sucker (Catostomidae: Catostomus latipinnis)
population in the White River, Colorado. Southw. Nat. 37: 915.
Hickman, T.J. 1983. Effects of habitat alteration by energy resource developments in the Upper Colorado River Basin on
endangered fishes. pp. 537-550. In: V.D. Adams & V.A. Lamarra (ed.) Aquatic Resources Management of the Colorado
River Ecosystem, Ann Arbor Science Publishers, Ann Arbor.
�239
Holden, P.B. 1979. Ecology of riverine fishes in regulated streams
with emphasis on the Colorado River. pp. 57-74. In: J.V. Ward
& J.A. Stanford (ed.) Ecology of Regulated Streams, Plenum
Press, New York.
Holden, P. & C. Stamaker. 1975. Distribution and abundance of
mainstream fishes of the middle and upper Colorado River
basins, 1967-1973. Trans. Amer. Fish. Sot. 104: 217-231.
Karp, CA. & H.M. Tyus. 1990. Behavioral interactions between
young Colorado squawfish and six fish species. Copeia 1990:
25-34.
Lanigan, S.H. & C.R. Berry, Jr. 1981. Distribution of fishes in the
White River, Utah. Southw. Nat. 26: 389-393.
McAda, C.W. & L.R. Kaeding. 1991. Movements of adult Colorado squawfish during the spawning season in the upper Colorado River. Trans. Amer. Fish. Sot. 120: 339-345.
McAda, C.W. & R.S. Wydoski. 1983. Maturity and fecundity of
the bluehead sucker, Catostomus discoboh (Catostomidae),
in the Upper Colorado River Basin, 1975-76. Southw. Nat. 28:
12cl23.
Miller, R.R. 1946. The need for ichthyological surveys of the major rivers of western North America. Science 104: 517-519.
Miller, R.R. l%l. Man and the changing fish fauna of the American Southwest. Papers of the Mich. Acad. of Sci., Arts, and
Let. 46: 365-404.
Minckley, W.L. 1973. Fishes of Arizona. Arizona Game and Fish
Department, Phoenix. 293 pp.
Minckley, W.L. & J.E. Deacon. 1968. Southwestern fishes and
the enigma of ‘endangered species’. Science 159: 1424-1432.
Mullan, J.W., V.J. Starostka, J.L. Stone, R.W. Wiley & W.J. Wihzius. 1976. Factors affecting upper Colorado River reservoir
tailwater trout fisheries. Proceedings of the Symposium and
Specialty Conference in Instream Flow Needs. Amer. Fish.
Sot., Bethesda.
Sigler, W.F. & J.W. Sigler. 1987. Fishes of the Great Basin. University of Nevada Press, Reno. 425 pp.
Stanford, J.A. & J.V. Ward. 1986a. The Colorado River system.
pp. 353-374. In: B.R. Davies & K.F. Walker (ed.) The Ecology
of River Systems, Dr W. Junk Publishers, Dordrecht.
Stanford, J.A. & J.V. Ward. 1986b. Reservoirs of the Colorado
system. pp. 374-383. In: B.R. Davies & K.F. Walker (ed.) The
Ecology of River Systems, Dr W. Junk Publishers, Dordrecht.
Stanford, J.A. & J.V. Ward. 1986~. Fish of the Colorado River
system. pp. 385-402. In: B.R. Davies & K.F. Walker (ed.) The
Ecology of River Systems, Dr W. Junk Publishers, Dordrecht.
Sublette, J.E., M.D. Hatch & M. Sublette. 1990. The fishes of
New Mexico. University of New Mexico Press, Albuquerque.
393 pp.
Trammell, M.A. 1991. Evaluation of Colorado squawfish stocking in Kenney Reservoir, Rangely, Colorado. M. SC. Thesis,
Colorado State University, Fort Collins. 64 pp.
Trammel], M.A., E.P. Bergersen & PJ. Martinez. 1993. Evaluation of an introduction of Colorado squawfish in a main stem
impoundment on the White River. Colorado. Southw. Nat. 38:
362-369.
Tyus, H.M. 1990. Potamodromy and reproduction of Colorado
squawfish in the Green River basin. Colorado and Utah.
Trans. Amer. Fish. Sot. 119: 1035-1047.
Tyus, H.M., B.D. Burdick, R.A. Valdez, C.M. Haynes,T.A. Lytle
& C.R. Berry. 1982. Fishes of the Upper Colorado River Basin:
distribution, abundance, and status. pp. 12-70. In: W.H. Miller,
H.M. T@s KcCA. Carlson (ed.) Fishes of the Upper Colorado
River System: Present and Future. American Fisheries Society, Bethesda.
Tyus, H.M. & C.W. McAda. 1984. Migration, movements and
habitat preferences of Colorado squawfish, Ptychocheih lucius, in the Green, White and Yampa rivers. Colorado and
Utah. Southw. Nat. 29: 289-299.
Vanicek, C.D., R.H. Kramer & D.R. Franklin. 1970. Distribution
of Green River fishes in Utah and Colorado following closure
of Flaming Gorge Dam. Southw. Nat. 14: 297-315.
Wullschleger, J.G. 1990. Initial impacts of an impoundment on
downstream benthic invertebrate fauna. M.Sc. Thesis, Colorado State University, Fort Collins. 106 pp.
Wydoski, R.S. & J. Hamill. 1991. Evolution of a cooperative recovery program for endangered fishes in the upper Colorado
River basin. pp. 123-135. In: W.L. Minckley & J.E. Deacon
(ed.) Battle Against Extinction: Native Fish Management in
the American West. The University of Arizona Press, ‘Btcson.
�
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Subject: Nutrition
Fishery Leaflet No .. 29
Date: October 15, 1956
A Comparison of Hatchery Diets and Natural Food
By: Arthur M. Phillips, Reed S. Nielsen, and
Donald R. Brockway
Most of the ingredients of diets fed to hatchery trou~ -are foreign in the sense
that the fish would seldom receive them in the natural envi;ronment. The composition
of hatchery diets is based largely upon the results of fee:cling trials, and these usually
are judged on the basis of growth, mortality, conversion, and the cost of production.
In recent years definite nutritional deficiencies have been recognized, and supplements
are added to the diet now to prevent the appearance of known nutritional disorders. In
for:rn.lating diets for hatchery fish, little or no attention has been given to the natural
food of trout.
Probably one of the reasons for this lack of study of natural food is the general
belief that hatchery diets are more efficiently converted into fish flesh than are the nat\lral
foods of trout. A r eview of the literature fails, in general, to support this contention.
Hatchery foods now in use will convert at a rate of about 3. 0 pounds of food per pound of
fish. Values for natural foods have been found foat range from 2. 3 to 7 .1. h1 almost
ever y instance wher e the higher values have been reported, underfeeding of the fish is
evident in the experimental design.
Different authors r eport the following varying conversions for scuds,Gammarus:
6. 6, 5. 0 and 3. 9. Other conversions for natural feeds are midge larvae, Chironomus,
4. 4, trout (cannibalism), 2.. 3, and 1r.aggots1 7 .1. The results cited above fail to show
• any great prefer ence for hatchery foods over natural foods in terms of conversion.
If hatchery diets are to be evaluated in terms of natural food, it is necessary to
know both the gener al composition, (fats, proteins, ash, and carbohydrates) and the composition iu torr.-ts of the trace factors ·(minerals and vitamins). For the p ast 2 years,
through the cooperation of several field workers, the Cortland laboratory has r eceived
samples of natural food to be used in analytical studies. This paper may be considered
as a progress report on the work.
As a result of the studies conducted, general analysis shows a great difference
between this particular hatchery diet and the average values for natural food. (Note: -It is probable that the experimental diet used in the study is eve n lower in mineral and
vitamin content than diets now being used by most states). Organisms studied wer e
mayflies, Baetis, stoneflies, Pteronarcys and Acroneuria , caddis flies, Brachycentrus.
black flie s , Simulium, scuds, Gammarus, and aquatic earthworms, Helodrilus. The
hatchery diet contains about half as much water, more than twice as much protein, half
again as much fat, and four times as much ash. The iodine number of the fat of the hatchery food is considerably lower than that of the natural organisms. If chemical content
alone is considered, the conclusion is that hatchery foods are nutritionally superior to
natural foods . This assumption, however, mus t be r e - evaluated in terms of conversion
of natural food into fish flesh . When conversion is considered, the lower chemical content of natural foods points to a more efficient utilization of the materials from natural
food than from the hatchery diet.
(over)
�Page 2.
Fishery Leaflet No. 29
Date: October 15, 1956
-
A comparison of mineral content between natural and hatchery foods. again
indicates that, from the chemist'·s standpoint, the -~tchery diet should be considered
superior to wild food. The hatchery diet is seven ti~es richer in calcium, more than
five times richer in phosphorus, and four times richer in magnesium.
. A comparison with hatchery foods shows that the average values for the vitamin
- ·-· --- -- ·--,,c-o---n-r-te-nt o~nafiiral foods, except in thEf case of r1bofiavfii;- arEnvelloelow the values-that are shown· for the hatchery diet. The riboflavin content of hatchery food was only
slightly higher than that of natural foods. Again it may be concluded that, with reference to nutrition, the natural foods are inferior to the hatchery diet .
. When all of the analytical results are taken into consideration, it may be concluded that, from the point of view of the nutritionist, the hatchery diet is apparently
superior to the natural foods studied. In all but one instance (riboflavin), the chemical
content of the hatchery diet is well above that of the natural foods. As, according to
values in the literature, one should expect similar conversions into fish flesh from both
types of food, it appears logical to believe that the natural food must offer something
that is lacking in the present hatchery:~diets. This could involve many factors--the digestibility of the food, amino acid content of the protein, biological value of the protein,
availability of the factors present, and any numbor of undetermined elements that are
not included in this study.
In the streams there are foods that do have a chemical content similar to that
of the hatchery diet (other fish, for example.)· However, it has been shown by a number
of worker.a that the types or organisms listed (in this study) form 90 to 99 percent of the
-f-ood~by~ut-6--inches·-or--less-in-length.--It,-theref-ore,---becomes apparent that the
diet of wild fish ·during early growth is composed of organisms inferior (according to
present nutritional standards) to the hatchery diets, and yet the fish grow with an efficiency (based on conversion) that is similar to that found in the hatcheries. This would
appear to warrant the making of additional studies along the lines of conversion of natural
food into fish flesh, as well as studies on the various nutritional factors in natural food
organisms.
Abstracted by Gene Cook - from Progressive Fish-Culturist, 1954, #4, pp.153-157
�
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Greenback
Cutthroat Trout
Recovery Plan
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�Greenback
Cutthroat Trout
Recovery Plan
Prepared by:
Greenback Cuffhroat Trout Recovery Team
for
Region 6
U.S. Fish and Wildlife Service
Denver, Colorado
~t4’?e/
DEPUTY R
ional Director
March
1998
�Table of Contents
DISCLAIMER
1
ACKNOWLEDGEMENTS
EXECUTIVE SUMMARY
PART I INTRODUcTION
Historic DistribUtion
Type Specimens
Taxonomy
Current Distribution
Reasons for Decline
Habitat Requirements
Reproduction
Food and Feeding
Size and Growth
Disease and Parasites
Sensitivity to pH
HeavyMetals
Management Practices (Fish Culture, Stocking, Angling)
1
1
4
7
7
PART II RECOVERY
Objective
Stepdown Outline
Narrative Outline
19
19
21
23
.
PART m IMPLEMENTATION
.
11
11
12
12
13
13
38
.
42
LITERATURE CITED
PUBLIC REVIEW
9
10
.
PART IV FIGURES, TABLES, AND APPENDICES
Figure 1. Mature South Platte drainage greenbacks
Figure 2. Historic distribution of greenback cutthroat trout
Figure 3. Comparison of selected parameters for various Colorado subspecies of
0. clarki and rainbow trout
Table 1. Summary of Known Historic Greenback Cutthroat Trout Sites and Stability
of Population. 1970-1997
Table 2. Summary of South Platte Greenback Cutthroat Trout Restoration Projects,
1970-1997
Table 3. Summary of Arkansas River Greenback Cutthroat Trout Restoration Projects,
1970-1997
Table 4. Summary of Greenback Historic Populations, Restoration Projects, Areas
Open to Angling and Stable Populations. 1997
Table 5. Hybrid Populations of Greenback Cutthroat Trout. 1994
Table 6. South Platte Greenback Restoration Projects and Stocking Schedule
Table 7. Arkansas River Greenback Restoration Projects and Stocking Schedule
Table 8. South Platte River Drainage Greenback Research Cutthroat Trout Stocking
Sites. 1994.2007
Table 9. Arkansas River Drainage Research Greenback Cutthroat Trout Stocking
Sites. 1994.2007
Appendix 1. Summary of Recovery History, 1959-1994
43
44
2
3
6
45
46
49
51
52
53
54
55
58
59
�Disclaimer
Recovery plans delineate reasonable actions which are believed to be required to recover and/or
protect the species. Plans are prepared by the U.S. Fish and Wildlife Service, sometimes with the
assistance of recovery teams, contractors, State agencies, and others. Objectives only will be
attained and funds expended contingent upon appropriations, priorities, and other budgetary
constraints. Recovery plans do not necessarily represent the views, official positions, or
approvals of any individuals or agencies, other than the U.S. Fish and Wildlife Service, involved in
the plan formulation. They represent the official position of the U.S. Fish and Wildlife Service
only after they have been signed by the Regional Director, or Director as approved. Approved
recovery plans are subject to modification as dictated by new findings, changes in species status,
and the completion of recovery tasks.
Literature citations should read as follows:
U.S. Fish and Wildlife Service. 1998. Greenback cutthroat trout recovery plan. U.S. Fish and Wildlife
Service, Denver, Colorado.
Additional copies may be purchased from:
Fish and Wildlife Reference Service
5430 Grosvenor Lane, Suite 110
Bethesda, Maryland 20814
(301) 492-6403 or 1-800-582-3421
Thefeefor the plan varies with the number ofpages of the plan.
Illustrations by: Bill Border, Nederland, Colorado.
Layout Design by: Renee Garfias, Bureau of Land Management
�We gratefully acknowledge the dedication of Dr. Robert Behnke for years of service to the greenback
program, and Colorado Trout Unlimited for their interest and funding of greenback restoration projects.
We also acknowledge the Bozeman Fish Cultural Development Center, Saratoga National Fish Hatchery and
Colorado Division of Wildlife Fish Research Hatchery for their work in developing the captive rearing
techniques for South Platte and Arkansas River drainage greenbacks, and to Mr. McAlpine and the U.S.
Army, Ft. Carson, for providing habitat for the early Arkansas River broodstock program. Also, Mr. Jim
Bennett, Colorado Division of Wildlife, for his long service as Team Leader.
The Greenback Cutthroat Trout Recovery Team is also grateful to its consultants who aided in the
preparation of this plan, and former members who aided in the preparation of previous versions of this
plan:
Robin Knox
David Langlois
RoIf B. Nittman
James R. Bennett
Larry E. Harris
Steve J. Puttmann
Douglas Krieger
Rick Anderson
Greg A. Policky
Phillip J. Goebel
Robert Behnke
Leo Gomolchak
Tim Devine
David R. Stevens
John Gold
Thomas L. Warren
Don Prichard
David Gilbert
James W. Mullan
Pat Dwyer
James Hammer
Terry Hickman
Jane Roybal
Patty Worthing
Richard Moore
Bob Stuber
Albert Collotzi
Dave Gerhardt
David Winters
Denny Bohon
Mike Young
Colorado Division of Wildlife
Colorado Division of Wildlife
Colorado Division of Wildlife
Colorado Division of Wildlife
Colorado Division of Wildlife
Colorado Division of Wildlife
Colorado Division of Wildlife
Colorado Division of Wildlife
Colorado Division of Wildlife
Colorado Division of Wildlife
Colorado State University
Colorado Trout Unlimited
National Park Service
National Park Service
Texas A&M University
U.S. Army, Fort Carson
U.S. Bureau of Land Management
U.S. Bureau of Land Management
U.S. Fish and Wildlife Service
U.S. Fish and Wildlife Service
U.S. Fish and Wildlife Service
U.S. Fish and Wildlife Service
U.S. Fish and Wildlife Service
U.S. Fish and Wildlife Service
U.S. Forest Service
U.S. Forest Service
U.S. Forest Service
U.S. Forest Service
U.S. Forest Service
U.S. Forest Service
U.S. Forest Service
Current Greenback Cutthroat Trout Recovery Team Members:
Therese Johnson
Bruce D. Rosenlund
Brenda Mitchell
Gordon Sloane
Tom Nesler
1994-present
1977.present
1981 .present
1989-present
1992-present
National Park Service
U.S. Fish and Wildlife Service
Bureau of Land Management
U.S. Forest Service
Colorado Division of Wildlife
ii
�Executive Sumrnar
Current Species Status: The greenback cutthroat trout (Oncorhynchus clarki stomias) is the
only trout endemic to both the headwaters of the South Platte and Arkansas River drainages.
Although once abundant, their numbers declined in the late 1800’s due to loss of habitat caused
by mining and agriculture, over-harvest, and the introduction of non-native trout species. The
greenback was extirpated from most of its native range by the early 1900’s, and Greene (1937)
considered the subspecies extinct. In 1973, two small populations were confirmed that
represented approximately 2,000 greenbacks in 4.6 km of stream. The subspecies was listed as
“endangered” in 1973, and downlisted to “threatened” in 1978. As a result of recovery efforts,
captive broodstocks were established, non-native trout were removed from suitable habitat,
greenbacks were reintroduced, stable populations were developed and catch-and-release fisheries
were initiated.
Greenback cutthroat trout are present in 62 sites that total 179 hectares (442 acres) of lakes and
ponds and 164 kilometers (102 miles) of stream habitat. Forty seven sites are open to catch-andrelease fishing and 20 populations are considered to be stable. Seventeen stable populations are
located in the South Platte drainage, and three stable populations are located within the Arkansas
drainage. These numbers may change as new projects are accomplished.
Habitat Requirements and Limiting Factors: This species inhabits cold water streams and
cold water lakes with adequate stream spawning habitat present in the spring of the year.
Limiting factors include other spring spawning trout species that hybridize with greenbacks, and
fall spawning species that compete with greenbacks for food and space, combined with overharvest of greenbacks.
Recovery Objective: Delisting.
Recovery Criteria: The goal of this Plan is to restore the greenback cutthroat trout to nonthreatened status within its native range. Delisting of this subspecies is considered to be possible
by the year 2000. This may be accomplished through maintaining at least 20 stable greenback
populations occupying at least 50 hectares (124 acres) of lakes and ponds and 50 kilometers (31
miles) of stream. At least five of the stable populations should occur in the Arkansas drainage.
Actions Needed:
1. Maintain existing populations of greenbacks.
2. Establish or document, 20 stable populations of greenbacks.
3. Establish captive and wild greenback broodstocks within Colorado.
4. Conduct research on greenback angling programs and hatchery programs.
5. Conduct greenback information and education programs.
6. Promote partnerships, and expand efforts to obtain non-agency funding.
7. Prepare a long-term greenback management plan and cooperative agreement.
Date of Recovery: 2000.
Cost of Recovery: $634,000.
iii
�This Recovery Plan for the greenback cutthroat trout (greenback) was developed by the
Greenback Cutthroat Trout Recovery Team, an interagency group of scientists operating under
the sponsorship of the U.S. Fish and Wildlife Service.
The original Greenback Recovery Plan was written in 1978, revised in 1983 and is superseded by
this Plan. This latest edition contains updated information and recovery objectives completed by
researchers since 1973.
The Plan is organized into four sections:
I.
Introduction Historic distribution, type specimens, taxonomy, current distribution,
reasons for decline, habitat requirements, reproduction, food and feeding, size and
growth, disease and parasites, sensitivity to pH, heavy metals, management practices,
fish culture, stocking and angling.
II.
~
Recovery objectives, and tasks considered vital to the successful recovery of
the greenback.
III.
Imnlementation Schedule An itinerary of scheduled recovery tasks assigning agency
responsibility and estimated costs.
IV.
Fi2ures. Tables and AnDendices
-
-
-
We sincerely hope that this document will be used by agencies involved with greenback
cutthroat trout management to coordinate their efforts to most effectively work toward our
common goal.
Revisions of this Plan will occur as often as is feasible and appropriate.
iv
�Part I Introduction
The greenback cutthroat trout,
distribution in the western United States,
(Oncorhynchus clarki stomias, formerly
(Behnke, 1984). The greenback declined so
Salmo clarki stomias), is one of the most
rapidly in the 1800s that the original
colorful subspecies of cutthroats (Figure 1),
and was one of the rarest. At the time of the
distribution of the subspecies is not precisely
enactment of the Endangered Species Act in
1973, only two small historic populations of
original distribution included all mountain and
foothill habitats of the Arkansas and South
greenback cutthroat trout were known to exist
Platte drainages (Figure 2). The greenback
Como Creek and South Fork, Cache La
Poudre River that conformed to the meristics
was known to occur within these drainages at
of the type specimens. These two small
however, little is known of its exact historic
headwater streams of the South Platte River
drainage collectively represented 4.6
lake and stream distribution and the range in
elevation it once occupied. The only other
kilometers of stream habitat and supported
trout thought to have occurred within the
less than 2,000 greenbacks. Since then, seven
greenback’s native range was the yellowfin
additional historic populations have been
identified, five populations in the South Platte
cutthroat (Oncorhvnchus clarki macdonaldi)
River drainage and two populations in the
drainage) in 1889 (Behnke 1979). The
Arkansas River drainage. The historic
yellowfin cutthroat became extinct in the
populations are listed in Table 1.
earl)’ 1900’s.
known. Behnke and Zarn (1976) assumed the
-
lower elevations than it occupies today,
-
collected from Twin Lakes (Arkansas River
Contrary to the common name of the fish, the
Type Specimens
back of the greenback is not especially green
in color. In older age classes (4 years or
According to Behnke (1979), “There is
more), mature males display crimson red
considerable confusion concerning the name
colors along the ventral region during the
stomias in regard to where the original type
spring spawning season, especially in lake
specimens actually came from. It is possible
environments.
that the specimens on which the name is
based were not greenback trout taken from
the South Platte drainage. Cope (1872), in
Historic Distribution
the same publication in which he names
The greenback is native to the headwaters of
S. pleuriticus, named Salmo stomias from
the South Platte and Arkansas river drainages
specimens collected from: “The South Platte
within Colorado and a small segment of the
River at Fort Riley, Kansas.” The South Platte
River drainage does not enter the State of
South Platte drainage within Wyoming. The
greenback and the Rio Grande cutthroat trout
Kansas. In later publications, Cope stated that
(Oncorhynchus clarki virginalis), represent
the easternmost limits of native trout
the -‘type locality” of £ stomias is the Kansas
River at Fort Riley, Kansas.
1
�Figure 1. Mature South Platte drainage greenbacks from stream and lake
environments. Rocky Mountain National Park. 1992.
Mat nrc female greenback with typical non-spawning coloration and spotting pat tern
I roin a small stream environment, Hunters Creek. RMNP
Mature male greenback with typical spawning coloration and spotting pattern from a
lake environment. Bear Lake, RMNP
�Figure 2. Historic distribution of greenback cutthroat trout, (Behnke and Zarn, 1976)
and location of historic sites and stable reproducing populations. 1994.
* Historic populations known prior to 1978
Populations, 1991
El Probable historic range
u
3
�The Kansas River, however, has no native
numerous subspecies or geographic races.
trout. The confusion originated with an Army
Many subspecies undoubtedly are
expedition under the command of Lt. F. T.
Bryant, traveling from Fort Riley, Kansas, to
polyphyletic, having evolved directly from
other subspecies rather than
Fort Bridger, Wyoming, and back again in
(monophyletically) from a centrally localized
1856. A surgeon, Dr. W. R. Hammond,
accompanied the expedition and made natural
stem group. This evolutionary pattern,
history collections; among his collections
were two specimens of cutthroat trout. The
expedition traversed parts of the Kansas,
coupled with the declining abundance of
“pure” inland trout, and extensive
hybridization with introduced species (e.g.
North Platte, South Platte, and Green River
rainbow trout 0. rnykiss), has made it difficult
to unravel the myriad of systematic problems
drainages in Kansas, Nebraska, Wyoming and
within inland 0. clarki (Gold 1977).
Colorado. Cutthroat trout could have been
collected only in the Green River or South
Platte drainages. The problem is that all of the
The taxonomy of the greenback cutthroat
specimens collected on the expedition were
simply labeled ‘Fort Riley, Kansas’ (the
Wernsman (1973), Behnke (1973, 1979), and
terminus of the expedition) and shipped to
the Philadelphia Academy of Sciences, where
Cope later saw the cutthroat trout specimens
trout (0. c. stomias) has been described by
Behnke and Zarn (1976). The following
description of the subspecies is from Behnke
and Zarn (1976):
“Taxonomic criteria for S. clarki stomias
remain tentative due to the extreme
rareness of pure populations and to the
scarcity of ancient museum specimens.
Even so, scale counts (180-230) made from
available specimens consistently exhibit the
highest values of any cutthroat trout, or any
trout in the genus Salmo. It may be
assumed that extremely high scale counts
are characteristic of pure populations of
S. c. stomias, with some suggestion that
those populations native to the South Platte
Basin may show slightly higher counts than
those native to the Arkansas drainage. The
greenback cutthroat trout displays typically
lower numbers of pyloric caeca and
vertebrae than most other subspecies of
clarki, but much overlap occurs in these
characters.
and named Salmo stomias.”
Jordan (1891) redefined stomias and limited
its use to the cutthroat trout native to the
South Platte and Arkansas River drainages.
Jordan also appears to be the first person to
use the common name “greenback” for this
trout in the literature. All cutthroat trout are
currently placed in the genus Oncorhynchus,
with the current scientific name of the
greenback being Oncorhynchus clarki
stomias.
Taxonomy
The cutthroat trout, Oncorhynchus clarki
£
(formerly Salmo clarki), is a prime example of
a polytypic species. Trout referred to as 0.
Salmo clarki stomias undoubtedly derived
via an ancient headwater transfer of the
Colorado River basin to the South Platte
clarki are found in both coastal and inland
streams from Alaska to New Mexico, and
within this range the species has evolved into
4
�River drainage (and then to the Arkansas
River drainage) and for this reason shares
many similarities with the Colorado River
cutthroat. S. c. pleuriticus. The striking
spotting pattern and intense coloration
which can develop in mature fish are the
most diagnostic field characteristics of the
greenback trout. S. c. stomias typically
displays the largest and most pronounced
spots of any cutthroat trout. Round to
oblong in shape, the spots appear
concentrated posteriorly on the caudal
peduncle area. Coloration is similar to that
found in S. c. pleuriticus and tends toward
blood-red over the lower sides and ventral
region. especially in mature males.
Although a genetic basis exists to express
characteristic color patterns, the actual
manifestation of color intensity and pattern
depends upon age, sex, and diet” (see
Figure 1).
phenotypically from ‘essentially pure” to
obvious hybrids. The Colorado Division of
Wildlife (CDOW) has adopted a rating system
developed by Binns (1977) as a means of
rating population purity. Each population is
assigned a letter ranging from A (pure) to C
(obvious hybrids).
Only Type A populations are considered for
recovery purposes in this plan (Tables 1-4).
However, known type B and C greenback
populations (Table 5) are also included in
hopes that information obtained from
research on types A through C populations
will be of value in formulating management
plans for all cutthroat trout subspecies.
A summary of meristic characteristics for
various Colorado subspecies of 0. clarki
(Salmo clarki) are provided in Figure 3.
Although there is a close relationship between
greenbacks and Colorado River cutthroat
trout, recent mitochondrial DNA studies
indicate that both the Arkansas River and
South Platte River greenbacks are more closely
related to each other, than to populations of
Colorado River cutthroat. Greenbacks from
the Arkansas and South Platte River drainages
are nearly identical in DNA fragment patterns
(Proebstel 1993). However, because of the
geographic separation of the drainages,
greenbacks from the two drainages should not
be mixed for restoration purposes.
Since greenback cutthroat trout hybridize with
other species and subspecies of
Oncorhynchus, populations can range
5
�~IQ
Comparison of Selected Parameters for
Various Colorado Subspecies of Salmo clarki and Rainbow Trout
(From Johnson 1976)
Lateral line Scale count
Number
Number
scale count from lateral
Number pyloric Number basibranchial (2 rows above
line to
vertebrae ceaca gill-rakers
teeth
lateral line)
dorsal fin
mean
(range)
mean
(range)
mean
(range)
mean
(range)
mean
(range)
mean
(range)
S. clarki stom,as
60.6
gG reenback
(59-62)
utthroat Trout)’
S. clarki virginalis
61.7
~Rio Grande
tthrt Trout)’
(60-63)
uoa
S. clarkipleuriticus
61.2
(Colorado Cutthroat (60-63)
Trout)’
S. clark, macclonaldi 60.6
~Yellowtin Cutthroat (60-61)
rout)’
S.. cfarkilewisi
61.6
29.4
(24-42)
20.5
(17-22)
195.0
(175-214)
48.0
(46-53)
46.0
19.5
usually
present
(0-15)
7.3
164.0
41.9
(33-59)
35.0
(23-46)
(18-21)
19.0
(16-21)
(146-186)
180.0
(159-202)
(39-47)
43.0
(31-51)
42.0
(32-49)
21.3
(20-22)
(4-12)
usually
present
(0-15)
15.5
(15-16)
161.7
(149-172)
41.3
(38-46)
41.2
20.6
24.0
179.2
40.6
~utthroatTrout)
S. gairdneri
(Rainbow Trout)
(31-51)
55.0
(40-70)
(18-23)
19.0
(18-21)
(9-46)
absent
(161-187)
130.0
(120-140)
(37-46)
27.0
(24-30)
(60-63)
63.0
(62-65)
‘Counts from populations thought to be pure strains and typical of the subspecies.
Spots
F’.
Large,
absent
from head
Medium size
concentrated
posteriorly
Large spots
concentrated
posteriorly
Spots small
irregular
shape
Ii
0
0
‘1
0
Small,
equally
distributed
0
�susceptible to negative influences associated
with 19th century development of Colorado.
Current Distribution
The greenback cutthroat trout currently
Land and water exploitation, mining,
occurs in 61 sites that total 166 hectares of
agriculture, logging, and unregulated fishing
lakes and 165 kilometers of stream habitat in
all took their toll in reducing the numbers and
the upper tributaries of the South Platte and
habitat of endemic trout populations.
Arkansas river drainages. Nine “historic”
However, no action had more long-term
populations remain that have been identified
through recovery efforts conducted since
impacts on the endemic trout subspecies than
the introduction of non-native salmonids
1973. Pure greenbacks have been introduced
into 52 additional streams and lakes within the
which hybridized and competed with native
fishes. Shortly after the turn of the century,
greenbacks had declined to a point that
species historic range (as described in
Objective 2, Part II of the Recovery section).
Greene (1937) believed them to be extinct.
At present, twenty populations (including
The fate of the greenback population native to
both historic and restoration populations) are
Twin Lakes, in the Lake Creek drainage,
believed to be stable self-sustaining
populations (See definition in Part ID, but only
illustrates the effects of subsistence harvest
and stocking of nonnative fish, and typifies
three of these stable populations occur in the
the response of the greenback trout in
Arkansas River drainage. The “historic”
general. According to Behnke (1979), “Twin
Lakes was noted for its abundance of
populations are located in the higher
elevations of the species’ historic range,
greenback trout in the nineteenth century. In
probably because of less habitat disturbance
the 1890’s rainbow trout, brook trout, lake
and less accessibility to humans than occurred
trout (Salvelinus namaj’cush), and Atlantic
in the lower elevations.
salmon were introduced. When juday
Reasons for Decline
sampled Twin Lakes in 1902-1903, rainbow
trout were dominant (Juday 1906). Although
Fate of Historic Populations
Juday collected specimens of greenback trout
Four cutthroat trout subspecies are known to
(some of these were identified as hybrids
have existed in Colorado when European
when examining Juday’s specimens at the
settlers first arrived: greenback cutthroat trout,
National Museum), he found no “yellowfin”
cutthroat trout. The greenback disappeared
yellowfin cutthroat trout, Rio Grande
cutthroat trout, and the Colorado River
cutthroat trout. The yellowfin cutthroat
from Twin Lakes shortly thereafter. Twin
occurred in the upper Arkansas River drainage
fishery.”
Lakes is now primarily noted for its lake trout
in Twin Lakes, the Rio Grande cutthroat
occurred in the Rio Grande drainage, and the
Introduction of Non-native Fish
Colorado River cutthroat occurred in the
The major factor in the decline of the
greenback cutthroat trout was the
Colorado River drainage. Unfortunately, all
four cutthroat trout subspecies proved quite
introduction of non-native salmonid species
7
�(rainbow trout, brook trout, brown trout and
year earlier sexual maturation by brook trout
Yellowstone cutthroat trout), within the South
Platte and Arkansas River drainages.
and through larger brook trout young-of-theyear (YOY). Brook trout spawn in the fall.
The 1800’s began with the greenback cutthroat
Their fry emerge from the redds much earlier
as the dominant salmonid of these two
in the year than do the spring spawning
drainages. However, the arrival of the railroad
and the emergence of fish culture combined to
greenbacks, and the YOY brook trout can be
make large numbers of fish eggs and fry readily
first October. In Hidden Valley Creek, Rock)’
available and transportable in a relatively short
Mountain National Park (RMNP), YOY brook
period of time. The greenback’s failure to
respond to early fish culture practices soon led
trout (65 mm) and YOY greenbacks (35 mm)
30 mm longer than YOY greenbacks by their
to other fish species, such as brook trout and
are usually found in the shallow stream habitat
by October and appear to compete for food
rainbow trout, being reared and stocked
and space during winter minimum flows.
throughout the greenback’s limited native
range.
Fausch and Cummings (1986), found brook
trout juveniles to occupy more energetically
favorable positions than greenbacks in stream
habitats when the two were found in sympatry
Hybridization
Greenbacks hybridize readily with rainbow
trout and other subspecies of cutthroat.
within Hidden Valley Creek, RMNP, and
Several hybridized populations known to occur
dominant over juvenile greenbacks (probably
in Colorado are shown in Table 5.
due to their larger size). However, Fausch and
indicated that brook trout juveniles were
Cummings found aggression between adult
Corn petition
(>150 mm) brook trout and greenbacks to be
Brook Trout. The ability of brook trout to
minimal.
displace a pure greenback population was
dramatically demonstrated by events in Black
Hollow Creek, Arapaho/Roosevelt National
Although brook trout dominate greenbacks and
Forest. Brook trout were removed from this
represent 60%-90% of the fish population in
small montane stream in 1967 prior to
Black Hollow and Hidden Valley Creeks,
greenback hybrids and Colorado River
restocking with 50 pure greenback cutthroat
cutthroats have successfully co-existed for over
40 years and/or dominate (50% to 90% of fish
trout, which later established a reproducing
population. However, in 1973, two brook
trout were found above the barrier, and by
1977, electrofishing for more than one mile
numbers) over brook trout within Lake-of-
above the barrier produced only brook trout
Mountain National Park (RMNP). Greenbacks
(Behnke and Zarn 1976, 1979).
have also demonstrated that they can invade
dense brook trout populations in some
The mechanism by which brook trout displace
circumstances, such as in the North Fork of
the Big Thompson River. Greenbacks were
Glass, Thunder Lake and Willow Creek, Rocky
greenbacks is not thoroughly understood.
However, in colder habitats, it probably
introduced into a fishless habitat above an unnamed falls on the upper North Fork of the Big
includes an advantage gained through a one
8
�Thompson River, RMNP in 1970, and
Angler Harvest
established a reproducing population. By
1986, greenbacks had drifted downstream,
The removal of adult greenbacks by anglers,
and represented 14.5 percent of the fish over
greenbacks, especially when non-native
salmonids were present. Cutthroat trout are
may have had a negative impact upon
50 mm in length in the stream section from
Lost Falls to the unnamed falls. In this
more easily caught than other species.
Removal of the older, larger greenbacks might
section, brook trout did not exceed 280 mm
in length, though greenbacks reached 304
favor brook trout, which reproduce at smaller
mm.
sizes and younger ages. Changes in fishing
regulations in effect since 1982 within RMNP
Arkansas River greenbacks in Lytle Pond (U.S.
that limited the harvest of non-native
Army, Ft. Carson) successfully coexist with
brook trout, with brook trout numbers
cutthroats and Colorado River cutthroat to
two fish over 250 mm, and catch-and-release
declining. However, spawning habitat at Lytle
only for greenbacks, appears to be allowing
pond is less favorable in the fall than in the
for the downstream expansion of cutthroats
spring, and may provide greenbacks with a
into brook trout populations in some streams
competitive advantage over brook trout at this
within RMNP (North Fork of the Big
location.
Thompson River, North Inlet and North St.
Vram). However, in other areas, (Ouzel,
Brown trout. Wang (1989) observed the
behavior and competition of yearling South
Hidden Valley, George and Cornelius Creeks)
Platte greenbacks and brown trout in an
populations of greenbacks despite no legal
indoor stream aquarium. Brown trout were
found to be more aggressive than equal-sized
angler harvest of greenbacks.
brook trout continue to expand into
greenbacks. Brown trout even outcompeted
greenbacks that were 1.27 times longer and
Habitat Requirements
1.69 times heavier. Slow current combined
Habitat requirements of greenback cutthroat
with dim light significantly increased attack
trout appear little different from other species
frequency of brown trout on greenbacks. Few
of trout. Bulkley (1959) gathered information
greenback restoration projects involve former
brown trout habitat. However, the dominance
on age, growth, food habits, and movement of
a slightly hybridized population in the
of brown trout over greenbacks (as indicated
headwaters (3,200 m) of the Big Thompson
by Wang’s study) is evident in George and
River, Rocky Mountain National Park (RMNP).
Cornelius Creeks, where brown trout appear
Nelson (1972) provided data on age, growth,
to be displacing greenbacks (Steve Puttmann,
Colorado Division of Wildlife, pers. comm.
and fecundity of a dense, unexploited, and
slightly hybridized greenback population in
1991).
Island Lake, Boulder Creek watershed.
Restoration efforts should be directed to
habitats that are capable of supporting a
9
�minimum of 20 kg/ha of fish. Habitats
Reproduction
occupied by non-native trout will require their
removal prior to the introduction of
Spawning is generally initiated in the spring
greenbacks to prevent hybridization and
to the influence of elevation on water
competition.
temperatures, greenbacks in Lytle Pond on Ft.
when water temperatures reach SC-8C. Due
Carson (1,889 in) spawn by early April,
Stable reproducing populations of greenbacks
greenbacks in Hunters Creek (2,896 m) spawn
in Colorado are rarely found above timberline
in mid-June, and greenbacks in Upper
Hutcheson Lake (3,402 m) spawn by mid-July.
since cold water temperatures do not allow
for sufficient time for spring spawning,
hatching and establishment of fry during the
Although greenbacks are spring spawners,
older greenback males in high elevation
short ice-free period. Currently, the highest
known elevation of a long-term reproducing
streams (Hunters Creek and the headwaters of
the North Fork of the Big Thompson River
population is the Upper Hutcheson Lake
within RMNP), were observed to be in
spawning colors and running milt in mid-
population at 3,402 m. Due to the availability
of surplus greenbacks, experimental
September.
introductions are being conducted in high
elevation fishless waters to document the
Although Como Creek greenbacks can
produce eggs at age 2 in the hatchery, females
effect of elevation as a limiting factor on
greenbacks. Two timberline lakes that were
in small subalpine streams within Colorado
stocked with non-native cutthroats in RMNP,
appear to mature after their third to fourth
summer of life when they reach lengths of
but became fishless after the termination of
the non-native fish stocking, were
approximately 180 mm.
subsequently stocked with native greenbacks.
In one of these lakes (Lake Odessa at 3,048
The fecundity of seven females from Island
in), greenbacks spawned from late June to
Lake (Type B), averaging 270-i-mm in length,
early July and established a reproducing
had a mean value of 299 eggs per fish (Nelson
population. Greenbacks stocked in the other
lake, Crystal Lake (3,511 m) spawned by mid-
1972). Como Creek greenbacks (Type A) held
at the USFWS Fish Technology Center (FTC) at
July, but survival past the egg stage was not
Bozeman, Montana, produced 1.5 eggs per
gram of female weight for 2-year-old
documented through 1995.
greenbacks weighing 254 grams, and 1.4 eggs
The lower elevation limit of greenback
per gram of female weight for 3-year-olds
survival is not known. However, greenbacks
stocked in a low elevation lake (1,889 m) on
weighing 357 grams (Dwyer 1981).
Fort Carson, Colorado, have survived and
In the Big Thompson River (Forest Canyon),
attained a size of 2.0 kg. Future experimental
RMNP at an elevation of approximately 3,200
stocking should involve lower elevation
projects to determine greenback survival in
low elevation habitats, and in association with
m, Bulkley (1959) observed slightly
hybridized (Type B) greenback fry emerging
on August 26.
native non-salmonid forage species in low
elevation habitats.
10
�Food and Feeding
while the yellowfin cutthroat (now extinct)
attained a size of 10-12 pounds.”
Jordan (1891) mentioned that 0. c. stomias
fed on invertebrates when held in the
Leadville NFH, but were reluctant to accept
Nonetheless, the size and growth of
fish flesh as food. Bulkley (1959) reported
greenbacks varies, based upon the elevation
that the slightly hybridized greenbacks in
and population size. In small headwater
Forest Canyon, RMNP (3,200 in), fed upon
terrestrial organisms during the summer,
habitats, the greenback has attained a
relatively large size of 356-380 mm as
observed in the headwaters of the South Fork,
primarily adult Hymenoptera and adult
Diptera. Fausch and Cummings (1986) found
Cache La Poudre River, where it is much
greenbacks in Hidden Valley Creek, RMNP
larger than most brook trout in similar habitat.
(2,690 in), fed opportunistically on a wide
variety of organisms. In Hidden Valley Creek,
In September 1981, 40 pure (type A) Cascade
analysis of greenback stomach contents
Creek greenbacks were transferred to the
fishless 0.4 ha Lytle Pond at an elevation of
revealed that terrestrial invertebrates
1,889 in to establish a wild broodstock.
comprised a relatively constant proportion of
the diet through September, but the
Although none of these greenbacks exceeded
proportion of terrestrial invertebrates in the
250 mm in September 1981, one male attained
diet declined rapidly in October as
temperatures declined. None of the stomachs
a total length of 510 mm and a weight of 2.00
kg by November 1983. Studies of tagged
greenbacks in Lytle pond have shown a 79 mm
contained YOY greenbacks.
and 410 g increase for male greenbacks, and a
The stomach of an 1.19 kg pure (type A)
86 mm and 315 g increase for pre-spawning
Cascade Creek greenback, illegally taken from
Lytle Pond, Fort Carson contained a 114 mm
females from April 1991 to April 1992.
tiger salamander G4mystoma tigrinurn) in
The growth rate of adult greenbacks at higher
1982. Variations in the Arkansas darter
population that co-exists with the greenbacks
elevations can be much lower depending on a
variety of factors including population density.
in Lytle pond indicate that greenbacks eat
This is demonstrated by two alpine lakes in
these native darters, although this observation
has not been confirmed by stomach analysis of
RMNP (Sandbeach and Pear) where the nonnative trout population had been removed.
The lakes were stocked with 161 mm
the greenbacks.
greenbacks at the rate of 22.7 to 26.0 kg/ha on
June 30, 1989. After 10 weeks, the fish
Size and Growth
increased in length by an average of 57 mm
Behnke (1979) stated that, “Historically, it
(range 47-68 mm). Both populations began to
appears that the greenback seldom attained a
large size. About 1-2 pounds seems to be
spawn by 1990, with growth averaging only
typical maximum size given by old timers. In
Twin Lakes, Colorado, during the late 1800’s.
the greenback did not exceed a foot in length,
September 1991, and 16 mm for Pear from
20 mm for Sandbeach from September 1989 to
September 1989 to July 1991.
11
�performed by the USFWS, Fish Disease
Tag studies conducted on the Hunters Creek
historic population, indicated that growth for
Control Center, Fort Morgan, Colorado.
six greenbacks (178-252 mm in length),
averaged only 6 g from June 1988 to June
1989, with no measurable change in length.
Due to the concern over the recent
Hunters Creek is 2,896 in in elevation, and has
cerebralis) to Colorado, experiments were
a large (118 kg/ha) stable fish population that
is used for egg collections and is closed to
conducted on the response of greenbacks to
whirling disease at the USFWS, National Fish
fishing.
Heath Research Laboratory, in conjunction
introduction of whirling disease (Myxobolus
with the Colorado Division of Wildlife. The
Disease and Parasites
experimental exposure of two to three month
old greenbacks to a light exposure of whirling
The first modem fish pathology work on wild
disease (Myxobolus cerebralis), indicated that
greenbacks was conducted prior to the
transfer of 64 Como Creek greenbacks to the
greenbacks produced 7.5 times less M
USFWS, Fish Technology Center in 1977.
three months, and 15.6 times less spores than
Fecal material, ovarian fluid and seminal fluid
rainbows after six months. However, infected
from 78 Coino Creek pre-and post-spawning
greenbacks failed to show any viral activity
greenbacks weighed about 45% less than the
infected rainbows, with greenback mortalities
when inoculated onto susceptible tissue
26% to 32%, compared to 3 percent to 4
cultures. One moribund greenback collected
percent for infected rainbows. These results
from Como Creek on June 22, 1977, had
numerous Gyrodactylus spp. and Glossatella
indicate that although greenbacks showed no
cerebralis spores than rainbow trout after
overt signs of infections (skeletal deformities
spp. covering the body, with Hexamita spp.
and tail chasing), mortalities for infected
and Crepidostomumfarionis within the
greenbacks were higher than for infected
rainbow trout. Mortalities of unexposed
intestinal tract. Although bacteria were
present within the kidney, they were
controls were one percent for both species
(Markiw 1990).
nonobligate to salmonids. Following the
transfer of the Como Creek greenbacks to the
FTC, 11 greenbacks were lost within six
Sensitivity to pH
months. Examination of these fish revealed no
viral activity, and no clinical bacterial
Research conducted by Woodward, Farag,
infection was found although Pseudomonas
Little, Steadman, and Yancik (1991), indicated
that the threshold concentration on
spp. and Aeromonas hydrophilia were
isolated. Additional non-lethal fish disease
greenbacks in the absence of aluminum was
samples (fecal, seminal fluid, ovarian fluid)
collected from Hunters Creek, Upper
pH 5.0. However, adverse effects were
observed at pH 6.0 when 50 ug/I of aluminum
was present. Greenback alevin and swim-up
Hutcheson Lake and South Fork of the Poudre
River from 1983 to 1996, found no viral
larva were found to be more sensitive to acidic
activity and no obligate fish bacterial
infections. Fish diagnostics work was
pH and elevated aluminum than eggs and
embryos. However, growth of greenbacks was
12
�not reduced at low pH. as was observed in
Snake River and Yellowstone cutthroats.
cutthroat trout did not adapt well to captive
rearing, and local citizens were so displeased
Reduced pH is a concern, because most of the
with the hatcher~’ spawning traps in Twin
historic greenback populations and greenback
Lakes that they were blown out with
restoration projects are located in alpine
habitats that are susceptible to acid
dynamite” (Tulian 1896). The availability of
precipitation.
adaptable to hatchery rearing, and the large
other species (brook and rainbow trout) more
scale availability of Yellowstone cutthroat (0.
c. bouvier,) from Yellowstone Lake, led to the
Heavy Metals
abandonment of the greenback by earls’ fish
culturists as a source of trout for stocking
Bard Creek was a fishless inontane stream that
was known to have elevated levels of heavy
purposes.
metals due to past mining activity.
Experimental stocking of greenbacks into the
A second attempt to rear greenbacks at the
fishless habitat of Bard Creek indicated that
Leadville National Fish Hatchery was
attempted in 195~ ~nd 1958 using 50 slightly
greenbacks stocked at over 25 mm in length
will survive to maturity and spawn despite
hybridized greenbacks from the Big
elevated concentrations of heavy metals.
Thompson River in Forest Canyon, RMNP, and
However, eggs from mature fish deposited by
26 pure greenbacks from the now extirpated
late June did not survive to the fall in Bard
Albion Creek population. This project was
Creek. As Woodward found with low pH and
abandoned due to fish mortality in the
elevated aluminum levels, the swim-up and
alevin stages may be the most sensitive to
hatchery and asynchronous maturation of the
remaining males and females. The project
terminated with the stocking of the surviving
elevated levels of heavy metals.
broodstock into Florence Creek, Uinta and
Management Practices
Ouray Indian Reservation, Utah. The
greenbacks in Florence Creek were almost
Fish Culture
totally displaced by brook trout by 1978.
Although the stocking of cultured nonnative
salmonids almost resulted in the extinction of
South Platte Draina2e Broodstock. As part of
the greenback, the greenback was one of the
the Recovery Plan, another attempt to rear
earliest fish to be reared in Federal hatcheries.
South Platte drainage greenbacks was initiated
In 1889, the Leadville National Fish Hatchery
in 1977, with the transfer of 64 Como Creek
greenbacks to the USFWS, Fish Culture
was established near Leadville Colorado, and
some of its original objectives were to rear
Development Center, Bozeman Montana.
greenbacks and yellowfins. Both subspecies
were obtained from waters adjacent to the
This broodstock initially encountered the same
hatchery and moved by wagon to the hatchery
problems with asynchronous maturation of
to be used as broodstock. Eggs of both
subspecies were taken from Twin Lakes.
males and females, the loss of males due to
However, the greenback and yellowfin
captive situation. In 1978, males produced
fungus, and the failure to accept feed in a
13
�milt in April and May, but the females matured
Creek, Hunters Creek and the Poudre River.
in July and August. Asynchronous maturation
In 1990, about 200 eggs were collected from
problems were overcome by allowing water
temperatures to decline to near 2 C, then
Upper Hutcheson Lake. Fish were produced
from all areas except the Poudre River, and
allowing the temperature to rise again in the
eggs were collected again from the Poudre
spring. Fungus was controlled with malachite
River in July 1992. Eggs were collected from
green. The use of variable temperatures and
the CDOW Experimental Hatchery broodstock
malachite green allowed for successful
in 1991 and 1992, with problems of
spawning, with 160,000 fry shipped to
Colorado from 1981 to 1988. Milt from wild
asynchronous spawning experienced during
1992. Malachite green could not be used to
greenbacks from Como Creek, Hunters Creek,
Hidden Valley Creek and the Poudre River was
control fungus in 1992, and all the 1989 year
class of broodstock did not survive past the
also collected and used to fertilize ova from
spawning season.
Bozeman females (Dwyer and Rosenlund,
1988). This action also helped enhance the
Arkansas Draina2e Broodstock. The Greenback
Recovery Plan also calls for development of an
genetic diversity of the broodstock. An
attempt was also made to establish a Poudre
River greenback broodstock at the Saratoga
Arkansas River greenback broodstock. To
NFH in 1984 and 1985. Eggs collected in
1984 did not survive, but 47% of the eggs
Cascade Creek were introduced into MeAlpine
collected in 1985 survived to swim-up. None
Carson Army Base). In 1984, eggs were
of the young accepted feed, and all died.
Interestingly, eggs from the Poudre River
collected from the greenbacks spawning in
McAlpine Pond and in Lytle Pond and were
population required much less time to develop
sent to Saratoga NFH. Fry and catchable-sized
greenbacks were produced at Saratoga NFH
develop this broodstock, greenbacks from
Pond (privately owned) and Lytle Pond (on Ft.
and hatch than did those of the greenbacks
from the Arkansas River drainage’s Cascade
from 1987 through 1992. Due to FWS
funding problems and the predominance of
Creek at the Saratoga NFH. At 8 C, eggs from
the Poudre River fish required only 16 days to
reach the eyed egg stage and 32 days to hatch,
old adults within the Saratoga broodstock, the
compared to 29 days to the eyed stage and 39
days to hatch for eggs from Cascade Creek (J.
transferred from Saratoga NFH to the CDOW
Hammer, Saratoga NFH, personal
establishment of the new broodstock at the
communication).
CDOW Experimental Hatchery, 3,200 eggs
from South Apache Creek and 10,000 eggs
Arkansas River broodstock program was
Experimental Hatchery. To facilitate
New South Platte and Arkansas greenback
broodstocks were initiated at the CDOW
Experimental Hatchery at Ft. Collins to
replace the aging and unfunded USFWS
broodstocks. During 1989, a total of 5,419
eggs were collected from Bear Lake, Como
14
�Como Creek. Unfortunately, colonization of
Leadville National Fish Hatchery Egg
Collection, Circa 1890
the habitat was slow and genetic diversity was
impaired due to the limited numbers of fish
from
stocked. These prol~lems also undermined
Saratoga NW were shipped to the
(1)0W Experimental Hatchery in 1992.
confidence in the abilit~ to establish fishable
Following the collection of eggs at the
p~ptIl~ttioi1s. The captive broodstock programs
~verc initiated to allow imre rapid
Saratoga NFH in 1992. the remaining
greenbacks at Saratoga NFH were lost due to
establishment of new populations, to protect
water problems at the hatchery.
the small historic populations from over
utilization as broodstock sources, and to allow
for genetic management. The captive
broodstock program produced enough
Stocking
greenback fry t( ) support stocking within each
restoration site for at least three consecutive
A wide range of stocking rates and methods
-
have been used to re-introduce greenbacks
nto historic habitats. Farl~ methods usually
~‘ears. This multi-year stocking facilitated
involved stocking low numbers (64 to 84) of
establishment of several year classes within
adult and sub-adult greenbacks into renovated
the new restoration sites, and, by using milt
from different historic populations to fertilize
habitats during the fall of the year. Only small
numbers of greenbacks were stocked due to
the hatchery eggs, enhanced the genetic
the limited number of fish available from
diversity of the reestablished populations.
15
�.
Initially. stocking rates for hatchery fry were
but severely impacted the abundance and
distribution of the subspecies during the
2,500 fry/ha per year in fishless lakes, and
1800’s. Wiltzius quoted Bell (188’) “The fish
1.666 fry,/1 .0 km per year in fishless streams,
with each area to be stocked for three
is so easily caught. it is so unwary and
consecutive years. These rates were believed
confiding, that the fish in a moderate-sized
to be necessary to compensate for the stress
and mortality of 12 hours of trucking required
stream can be taken out in one season with a
hook and line and a grasshopper. Without the
to move the fish from Bozeman, Montana to
modern hereditary instincts of self-
Ft. Collins, Colorado, followed by final
stocking by horseback or helicopter.
preservation, apparently, it cannot hold its
own against the fisherman”. As part of the
However, the stocking rates for fry in lakes
recovery program, studies on the performance
were found to be excessive, and were reduced
to 1,000 fry/ha per year. The reduced
of greenbacks in sport fishing management
stocking rate facilitated increased growth rates
and the production of catchable size fish
of these studies are described below:
within four years.
South Platte draina2e. mixed-trout fisheries
In September 1973, brook trout and longnose
Stocking of sub-adult (161 mm) greenbacks in
suckers were removed from Hidden Valley
June 1989 facilitated more rapid
reestablishment of fishable populations, and
Creek, RMNP, using antimycin. This was
allowed these areas to be reopened to angling
from Como Creek in October 1973. The
greenbacks established a reproducing
areas have been conducted since 1982. A few
followed by the stocking of 82 greenbacks
the following year. However, there were
logistical problems in transporting the larger
fish (over 386 total kg of fish) into inaccessible
population in both ponded (beaver ponds)
and non-ponded stream habitats: but by 1976,
alpine lakes within the RMNP. To resolve
brook trout were once again collected in
these problems, helicopter fire buckets
Hidden Valley. Brook trout numbers
aerated with oxygen were used to transport
the fish. These lakes were stocked at the rate
continued to increase in the beaver pond
habitats within the creek through 1981 even
of 18.5 to 36 kg of fish/ha. This same
with the removal of brook trout by fyke nets.
technique was used on the Rock Creek
By the end of 1981, it was feared that brook
trout would soon displace greenbacks in the
drainage, above the Leadville National Fish
Hatchery in 1991. Stocking in the Rock Creek
beaver ponds if a more efficient method of
drainage used larger greenbacks (234 mm),
brook trout removal could not be found. As an
and allowed the area to immediately be
reopened to catch-and-release angling.
alternative to the expensive netting program,
an experimental angling program (catch-andrelease for greenbacks and catch-and-kill for
brook trout) was opened on August 1, 1982.
Angling
Angling was limited to barbless artificial lures
As with most subspecies of cutthroat trout,
the greenback is easily caught by sport
only, and a daily possession limit of 18 brook
trout of which 10 must be 203 mm or less in
anglers. This feature makes the greenback a
length.
good fish for catch-and-release fisheries today,
16
�Prior to the start of the experimental Hidden
Valley angling program, fyke nets were set
ranged from 17 to 12 fish per hour on
National Forest and RMNP waters in the
throughout the beaver ponds. Greenbacks
period from 1990 to 1993.
were captured at an overall ratio of one
greenback to every three to four brook trout
captured; however the ratio varied between
Arkansas River draina2e. The first catch-andrelease greenback fishery in the Arkansas
ponds from 1:1 to 1:50. During the first week
River drainage opened at the 0.4 ha Lvtle Pond
of fishing in 1982, anglers fishing in the
beaver ponds caught an average rate of 0.86
on Ft. Carson in 1989. A limit of 25 annual
greenback permits are sold at a cost of $20.00
greenbacks and 0.40 brook trout per hour. In
for this pond. Prior to obtaining a greenback
1983, anglers caught an average of 0.78
greenbacks per hour and 0.25 brook trout per
permit, all greenback anglers are required to
hour during the first week of angling. This
permit, a Colorado State fishing permit and
attend a Ft. Carson safety briefing. Angler
hold a $10.00 Ft. Carson general fishing
demonstrated that although greenbacks were
the minority of the fish in the ponds, they
represent the majority of the fish caught.
success, satisfaction and experience was
measured by a self-conducted creel census.
Fifteen percent of the greenbacks captured in
In this census anglers ranked themselves as
fyke nets during September 1983 exhibited
visible damage attributed to angler’s hooks.
“experienced” anglers, and indicated the
following angler success and satisfaction:
It was hoped that anglers would keep all
brook trout caught, but interviewed anglers
reported releasing 60 percent of all brook
trout caught in 1982 and 1983. and 45-100%
of all brook trout caught from 1984-1993.
Although anglers must release all greenbacks,
as mans’ as seven percent of the greenbacks
were kept due to mistaken identification of
subspecies in 1986.
South Platte draina2e. ureenback-only
fisheries. Several lakes and streams within the
Roosevelt National Forest and RMNP are open
to catch-and-release angling for greenbacks
(see Tables 1-4). Greenback biomass in
restoration projects is usually greater tinder
catch-and-release regulations than that found
under the previous catch-and-kill regulations.
Angler success rates for greenbacks ranged
from 0.3 to 6.4 fish per hour in streams within
RMNP in the period from 1986-1989, and
17
�Fort Carson Creel Census, 1990-1991
Year
Average
Fish/Hour
Length
1990
1.52
307mm
72
78
81
1991
0.47
353mm
52
77
100
% AnglersLength
Satisfied with:
Number
Overall
Program
As in RMNP, about 16% of the fish examined showed some signs of hooking or hooking damage.
Although brook trout were present in Lytle Pond, none were reported caught in the 1990-1991
creel census. This again demonstrates the greater susceptibility to angling exhibited by
greenbacks.
18
�The purpose of this plan is the reestablishment of pure greenback cutthroat trout to population
levels where the subspecies will not likely become extinct throughout all or a significant portion
of their historic range. Overall, an ecosystem management approach will be used, with special
considerations for impacts to listed species, other native species, water quality and public use.
For a summary of previous recovers’ accomplishments and activities, please see Appendix 1.
Objective
THE OBJECTIVE OF THE GREENBACK CUTTHROAT TROUT RECOVERY PLAN IS THE REMOVAL OF THIS SUBSPECIES
FROM THE LiST OF THREA TENED AND ENDANGERED SPECIES. THIS SUBSPECIES WILL BE CONSIDERED RECOVERED
WHEN 20 STABLE GREENBACK CUTTHROAT TROUT POPULATIONS ARE DOCUMENTED REPRESENTING A MINIMUM OF
SO HECTARES OF LAKES AND PONDS AND 50 KILOMETERS OF STREAM HABITAT WITHIN ITS NATIVE RANGE. A
MINIMUM OF FIVE OF THESE POPULA TIONS WILL EXIST IN THE ARKANSAS RIVER DRAINAGE. ONCE RECOVERY
OBJECTIVES HAVE BEEN MET, A LONG RANGEMA NAGEMENT STRATEGY WILL BE IMPLEMENTED FOR THE CONTINUED
RESTORA TION OF THE SPE~1ES.
For delisting purposes, a stable self-sustaining greenback cutthroat trout population is defined as
a population of greenbacks that maintains a minimum of 22 kilograms of greenbacks per hectare
of habitat through natural reproduction. The population should contain a minimum of 500
adults (individuals greater than 120 mm in total length), and represent a minimum of two year
classes within a five-year period that are established through natural reproduction. A minimum
of 120 breeding pairs (240 adult fish) was considered necessar~’ to maintain genetic diversity
within a population (Leary, pers corn), and the team has set a minimum of 50() adults as
necessary to insure maximum genetic diversity for each wild greenback population. Twenty
stable reproducing populations. along with the above population criteria, are needed to quantify
an adequate population to meet the stated recoverx’ objectives. This strategy distributed into two
separate drainages (the Arkansas and the South Platte), will provide a minimtim viable population
goal that can be monitored and maintained.
A population of greenbacks cannot be considered stable unless the population is separated by
physical or biological barriers from other salmonids. Although fall-spawning trout species will
not hybridize with greenbacks, the presence of brook trout and brown trout is not considered to
be conducive to stable greenback populations. Fall-spawning species will most likely displace
greenbacks. or prevent the greenbacks from meeting the requirements for biomass and
reproduction.
10
�Highly glaciated drainages, with multiple hanging valleys, can contain more than one stable selfsustaining population. However, each stable population should contain at least two hectares of
habitat that is separated by barriers to upstream fish migration. Each stable population within a
drainage must meet the previously stated requirements for biomass, population size and
reproduction.
The locations the team has selected for recovery sites have concentrated on headwater streams
and high elevation lakes. These sites provide the most likely sites for successful recovery of this
species due 1) to presence of barriers; 2) ease of removing non-native fish; 3) inaccessibility
which reduces problems with reintroduction of non-native species; and 4) the fact that existing
remnant populations were discovered in headwater habitats. As the recovery progresses, both
larger and lower elevation habitats may be renovated.
Previous editions of the Greenback Cutthroat Trout Recovery Plan identified recovery actions
that have resulted in significant improvements in the status of the greenback. Twenty stable
populations now exist, however only three stable populations occur in the Arkansas River
drainage. Two major actions that need to be accomplished before the species can be delisted
are:
1.
—.
The establishment of two additional stable populations in the Arkansas River
drainage and
The preparation of a long-term management plan and a cooperative
management agreement for greenback cutthroat trout to guide management
of the greenback after delisting.
20
�Stepdown Outline
1. Maintain or enhance all known Type A greenback cutthroat trout populations and their
habitats.
1.1.
1.2.
1.3.
1.4.
Conduct population and habitat monitoring.
Enhance or restore habitat.
Maintain stream barriers.
Prevent introduction of non-native species.
1.5.
Promote sound land and water use guidelines.
1.6.
Enforce regulations.
2. Establish or document the existence of 20 stable populations of pure (Type A) greenback
cutthroat trout within the subspecies’ historic range.
2.1. Conduct surveys for historic populations.
2.2.
Prepare and maintain a list of candidate habitats.
2.3.
Consult with land owners and management agencies.
2.4.
Prepare habitats listed in Tables 6 and 7 for reintroduction.
2.41.
Conduct habitat manipulation.
2.42. Construct or improve barriers.
2.5.
2.43. Remove all non-native salmonids.
Introduce pure (Type A) greenback cutthroat trout.
2.51.
Use appropriate stocking rates for fish from wild populations.
2.52.
Use appropriate stocking rates for larval hatchery fish.
2.6
2.7.
Monitor and document the success of each introduction.
Annually update greenback cutthroat trout population status
3. Establish hatchery and wild populations of pure (Type A) greenback trout for broodstock.
3.1.
3.2.
Establish a South Platte River wild broodstock.
Establish an Arkansas River wild broodstock.
3.3.
Establish captive broodstocks.
3.31.
3.32.
Collect and utilize milt from wild populations.
Establish South Platte River and Arkansas River greenback broodstocks at
Colorado Division of Wildlife hatcheries.
3.33. Prepare reports on the status of the hatchery program.
3.34. Provide fish culture information necessary for the development of the long-term
management plan and cooperative agreement.
�4. Document response to angler pressure, stocking rates, fish diseases, fishing regulations, and
native non-salmonids.
4.1
Assess mixed greenback/non-native salmonid recreational fisheries under a
variety of harvest regulations.
4.2.
Implement catch-and-release greenback fisheries programs on public lands.
4.3.
Complete research on fish diseases, stocking, and angling programs.
4.4.
Complete research on stocking of greenbacks into waters with native non- salmonids,
or, introduce native non-salmonids to greenback projects.
5. Conduct an information and education program.
5.1.
5.2.
Encourage information and education programs.
Promote interagency cooperation and understanding of recovery activities whenever
possible.
5.3.
Present current activities at professional and public meetings.
5.4.
Promote watchable greenbacks programs.
5.5.
5.6.
Promote the adoption of the greenback as the Colorado State Fish.
Prepare a greenback display.
6. Promote partnerships with conservation groups and explore alternative management and
funding strategies.
6.1.
Increase the use of non-traditional agency funds and private funds.
6.2.
6.3.
Market art work.
Produce a greenback brochure.
7. Prepare a long-term management plan and cooperative management agreement for the
greenback cutthroat trout.
7.1.
Prepare a long-term management plan
7.2.
Prepare a cooperative agreement
22
�Narrative Outline of Greenback
Cutthroat Trout Recovery Plan
1. Maintain or enhance all known
Type A greenback cutthroat trout
populations and their habitats.
Type A greenback populations are those that are considered to be genetically pure. Other
populations (Type B-C) are believed to have varying degrees of hybridization with non-native
trout species. All known Type A populations and their habitats u’ill need to be maintained to
ensure the continued health and survival ofgreenback populations. This will involve regular
censusing ofpopulations, restoration and enhancement of habitat, and maintenance of
stream barriers.
1.1.
Conduct nonulation and habitat monitorin2. All streams that contain populations of
pure (Type A) greenback trout should be censused at least once every 3 years.
Numbers, age and condition of fish, and condition of the habitat should be evaluated.
The presence of any non-native species or habitat degradation should be noted and
appropriate management action taken.
1.2.
Enhance or restore habitat. ‘When necessary and appropriate, restore habitat quality
that is below its potential through physical manipulation of the damaged habitat using
sound land and water management practices.
23
�1.3.
Maintain stream barriers. Stream barriers are essential to prevent invasions of
undesirable fish into the habitat of greenback cutthroat trout. Natural barriers should
be inspected periodically for their effectiveness and stability. Although natural
barriers are strongly preferred, artificial barriers may be constructed when necessary
and should be inspected regularly for needed repairs.
1.4.
Prevent the introduction of non-native soecies. It is extremely important to prohibit
the introduction of non-native fish into greenback cutthroat trout habitat. Such
introductions foster competition and hybridization. Increased public education as
described in Objective 5 will help to meet this objective.
1.5.
Promote sound land and water use guidelines. Promote and support mining, grazing,
logging, and agricultural and silvicultural techniques that do not adversely affect the
greenback cutthroat trout habitat. The establishment and maintenance of buffer strips
along streams should be encouraged to help protect habitat from human and livestock
impacts. The land use practices listed below should be reviewed to ensure that they
are not negatively affecting greenback populations:
a. Grazing practices.
b. Maintaining riparian vegetation.
c. Silvicultural practices.
d. Mining activities.
e. Instream flow maintenance.
f. Water diversion and reservoir operations.
g. Road construction.
1.6.
Enforce re2ulations. Following the development of special angling regulations (see
Task 4.0) or habitat closures, strict enforcement by the Colorado Division of Wildlife,
Forest Service, Bureau of Land Management, Rocky Mountain National Park, Fish and
Wildlife Service, U.S. Army, Ft. Carson and U.S. Air Force, Air Force Academy is
necessary to ensure that the populations are protected from overharvest.
24
�2
2. Establish or document the existence of 20 stable populations of pure
(Type A) greenback cutthroat trout within the subspecies’ historic range.
In order to meet the recovery goalfor delisting the subspecies, the existence of 20 stable
populations ofpure (Type A) greenback populations, representing a minimum of 50 hectares
of lakes and ponds and 50 kilometers ofstream habitat which has a minimum biomass of 22
km/ha, will need to be established or documented within the subspecies historic range. A
minimum offive populations will be in the Arkansas River drainage.
This Task has largely been completed, with 20 stable populations documented, representing
53.9 hectares of lake habitat and 50.7 kilometers of stream habitat, Table 4. However, only
three stable populations currently exist within the Arkansas River drainage.
Thus, the major task that needs to be accomplished under this revision of the Greenback
Cutthroat Trout Recovery Plan is the documentation of at leastfive stable reproducing
populations within the Arkansas River drainage (see Tables 3 and 4).
2.1.
Conduct surveys for historic ponulations. Continue to search systematically for
historic populations of greenback cutthroat trout that may still exist within its historic
range. Verify such populations by field collections and analysis by qualified
taxonomists.
2.2.
Prenare and maintain a list of candidate habitats. Prepare and maintain a list of
candidate aquatic habitats that delineates areas that could, with or without
25
�modification, support populations of pure (Type A) South Platte and Arkansas River
greenback cutthroat trout. A list of candidate habitats has been developed (see Tables
6 and 7). These tables will need to be updated as new habitat areas are identified. The
selection of candidate aquatic habitats is based upon the following criteria:
1. Presence of barriers.
2. Ease of removing non-native fish.
3. Water temperature of 5-8C by earlyJuly.
4. Adequate water flows.
5. Ability to sustaln more than 500 adult fish and 22 kg/ha of biomass.
6. Ability to sustain reproduction.
2.3.
Consult with landowners or a2encies responsible for land mana2ement of candidate
~
Determine if the establishment of a greenback cutthroat trout population in a
candidate area would be compatible with landowner or agency management goals.
2.4.
Prepare habitats listed in Tables 6 and 7 for reintroduction. Carry out remedial actions
necessary and appropriate to make candidate waters listed in Tables 6 and 7 suitable
for the introduction of pure (Type A) greenback cutthroat trout. Aquatic habitats that
have been selected for the introduction of greenbacks may be lacking in some phase
of preferred or essential habitat requirements. Special emphasis should be given to
Arkansas River projects (Table 7), since only three stable reproducing populations
currently exist in this drainage.
2.41. Conduct habitat manioulation. If necessary and appropriate, enhance candidate
habitat to restore pool/riffle ratios, riparian vegetation, spawning habitat, water
quality and protection from excessive disturbance.
2.42.
Construct or imorove barrier(s). Although natural fish migration barriers are
preferred, some areas may require the construction of artificial barriers or
improvement of existing barriers.
2.43. Remove all non-native salmonids. Use piscicides to remove all non-native
salmonids from the candidate habitats. Review the success of this removal and
repeat the application of piscicides, if necessary. Special emphasis should be
given to completing removal of non-native salmonids in candidate habitats
within the Arkansas River drainage. Allow treated habitats to remain fishless for
a minimum of 6 months prior to proceeding with the reintroduction of
greenbacks and other native fish (Task 2.5).
26
�2.5.
Introduce nure (Tvoe A) 2reenback cutthroat trout. Introduce pure (Type A)
greenback cutthroat trout into the candidate waters using the greenbacks most
representative of the drainage being stocked. Greenback cutthroat trout populations
introduced within the South Platte drainage (Table 6) should be established with trout
from Como Creek, South Fork of the Cache La Poudre River, Hunters Creek, Upper
Hutcheson Lake, their descendants, or from yet to be determined Type A South Platte
populations.
Greenback cutthroat trout populations established within the Arkansas drainage (Table
7) should be established with trout from Cascade Creek, South Fork Apache Creek,
their descendants, or from yet to be determined Type AArkansas River populations.
2.51. Use anorooriate stocking rates for fish from wild nonulations. Stocking rates
for greenbacks from wild populations should be 240-500 sub-adults or adults per
site, with 500 being the most desirable number. Removal of any greenbacks
from pure (type A) populations will require approval from the Service and from
responsible management agencies.
2.52.
Use anoropriate stocking rates for larval hatchery fish. Annual stocking rates
for hatchery fry should be 1,000, 25mm fish per hectare of lake and 1,000,
25mm fish per 1.6 km of stream. Areas should be stocked for three consecutive
years following the removal of non-native fish to maximize heterozygosity and
the establishment of multi-year class populations capable of supporting
recreational fisheries.
2.6.
Monitor and document the success of each introduction of 2reenbacks into candidate
waters. Greenback trout reintroduction projects should be examined annuallyfor the
first 3 years following stocking and then once every two to three years until the
candidate water meets its management goal and meets the criteria defining stability.
Monitoring and reporting of each project’s success will be the responsibility of the
lead agency on the project.
2.7.
Annually undate 2reenback cutthroat trout nonulation status. Prepare annual
updates of the list of historic populations (Table 1), the restoration projects (Tables 2
and 3), the summary of total greenback populations (Table 4), list of hybrid
populations (Table 5), the candidate list of restoration projects (Tables 6 and 7),
and the list of research stocking projects, (Tables 8 and 9).
�3. Establish hatchery and
wild populations of pure
(Type A) greenback
cutthroat trout for
broodstock.
Efforts will be pursued to establish greenback trout
populations in captivity and to ident~fy wild
greenback populations that can be used as
broodstock to support the establishment of
additional greenback populations
u’ithin the subspecies’ historic range.
3.1.
Establish a South Platte River wild
broodstock. Establish/maintain at least one
lake/stream environment within the South Platte River drainage to function as a wild
broodstock source. These broodstocks can also constitute one or more of the 20 stable
populations under Task 2.0. This Task has been completed; wild greenback
populations in Como Creek, Hunters Creek, Bear Lake and Upper Hutcheson Lake are
identified as suitable egg sources. Zimmerman Lake was renovated in 1995, and will
serve as a wild broodstock lake.
3.2.
Establish an Arkansas River wild broodstock. Establish one lake/stream environment
within the Arkansas River drainage to function as a practical wild broodstock source.
This broodstock may constitute one or more of the 20 stable populations under Task
2.0. This task has been completed. Eggs have been collected from Lytle Pond on Ft.
Carson, from South Apache Creek and Boehmer Reservoir.
3.3.
Establish cantive broodstocks. Demonstrate the successful use of a hatchery
propagation program at the USFWS, Bozeman Fish Technology Center, (FTC)
Bozeman, Montana, using pure (type A) greenback cutthroat trout. Movement of
greenback fry and milt between Bozeman FTC and restoration sites in Colorado will
be done in accordance with current State and Federal fish disease policies and good
fisheries management practices. Use greenback fry from this source to reintroduce
greenbacks into candidate habitats as outlined in Task 2.4.
28
�In addition to the Bozeman program, another successful hatchery program
demonstrated at the Saratoga NFH in Wyoming. Both of these greenback ha
programs ended in 1992. Ahatchery program at the CDOW Experimental I-I
was initiated in 1989.
3.31. Collect and utilize milt from wild nopulations. Collect and utilize milt
wild populations of pure (Type A) greenbacks for fertilization of hatchi
to minimize genetic drift within the hatchery. This task has been comj
milt from Hidden Valley Creek, Como Creek, Poudre River and Hunters
have been used since 1982.
3.32. Establish South Platte River and Arkansas River 2reenback broodstocks at
Colorado Division of Wildlife hatcheries. These broodstocks will be base
mixture of historic populations within their respective drainages.
Eggs from historic populations of South Platte greenbacks were shipped ~
CDOW experimental hatchery in 1989, 1990 and 1992. Eggs from the Sar
NFH and South Apache Creek were shipped to the CDOW Experimental
Hatchery in 1992. Greenback eggs and fry have been produced at the
Experimental Hatchery, but fungus infections have eliminated a substantial
number of the mature broodstock, now that malachite green cannot be use~
the control of fungus on hatchery fish. Recently, raceways have been cover
to provide shade, with the shading of raceways appearing to greatly reduce
fungus problems.
3.33. Preoare renorts on the status of the hatchery Dro2ram. Annual reports have
been prepared by each hatchery operating a greenback broodstock.
3.34. Provide information necessary for develooment of a lone-term manaeement ol
and coonerative aereement. The Bozeman FTC and the CDOW Experimental
Hatchery should prepare a report which addresses management topics
pertinent to the long-term management plan discussed in Task 7.0, and provide
additional information detailing hatchery aspects of managing greenbacks.
�4. Document
response
to angler
pressure,
stocking rates,
fish diseases,
fishing
regulations, and
native non-salmonids.
N-
Prior to delisting, at least
one population of
pure greenback cutthroat
trout will be open to
angling, using special
regulations, over a period ofyears
to adequately document the
subspecies’ response to angling pressure and other
factors. Angling for greenbacks is authorized under 50
CFR 17.44 ~D.
4.1.
Assess a mixed greenback/non-ET1 w53 343 m195 343 lSBT
native salmonid recreational
fisheries under a variety of harvest
re2ulations. This task is completed. A mixed brook trout-greenback cutthroat trout
fishery exists within the beaver pond habitat of Hidden Valley Creek, RMNP. This area
was opened to artificial lure catch-and-kill angling for brook trout and catch-andrelease angling for greenbacks to determine if such special regulations give a
competitive edge to greenbacks. This angling program did not result in a significant
long-term improvement in the Hidden Valley greenback population, although it may
have slowed the decline of the greenback population.
4.2.
Imolement catch-and-release 2reenback fisheries oro~rams on public lands. This
task is completed. Areas opened to catch-and-release fishing are listed in Tables 1-4.
Monitoring is needed in these areas to determine angler success rates and population
status. The purpose of this task is to allow sport fishing for greenbacks, and therefore
engender public support for further reintroductions of greenbacks, without impacting
the stability of greenback populations.
30
�.
4.3.
Comolete research in fish diseases. stocking. and an~lin~ resolutions. Research on fish
diseases, stocking, and angling programs will be conducted using surplus captive
reared greenbacks to explore their response to a wide range of habitat types, estimated
fish diseases, angler pressures, and appropriate angling regulations. Research stocking
sites are listed in Tables 8 and 9.
4.4.
Comolete research stockin2 of 2reenbacks into waters with native non-salmonids.
or. introduce native non-salmonids to 2reenback oroiects. The purpose of this
research is to evaluate the opportunity for greenbacks and other native non-salmonids
to coexist, and to provide information on survivability of greenbacks in lower elevation
waters. One project has been completed at Lytle Pond, U.S. Army, Ft. Carson,
Colorado. In this project, Arkansas darters were released in 1980, into an area
occupied by greenbacks. Both species have coexisted since 1980. Other proposed
projects include evaluation of greenback survival with white suckers and creek chubs
in Monument Creek and Crow Creek. However, due to the proximity of these streams
to urban areas and the increased potential for harm to any introduced greenbacks from
increased human intrusion, these projects may have to be completed after delisting to
prevent conflicts due to the current listed status of the subspecies.
31
�5. Conduct an information
and education program.
An information and education
program is needed to promote
public support. This program
should explain the goal,
objectives, recovery activities,
and public fishing programs for
the greenback cutthroat trout.
proerams. Make
newsworthy activities
available to media outlets,
particularly when these
activities mark the completion
of objectives of the Recovery Plan.
These activities include the opening
of lakes and streams to sport
fishing, local hatchery greenback
activities, and watchable fish programs. Public understanding and support of
propagation, reintroduction, and angling management needs, as discussed in Tasks 2, 3
and 4 of this Plan, will promote efforts to recover the greenback cutthroat trout.
5.2.
Promote interaeencv cooPeration and understandin2 of recovery activities. Whenever
possible, efforts should be made to promote interagency cooperation and
understanding of activities needed for recovery of the greenback cutthroat trout. This
should include sponsoring interagency coordination meetings, preparing agency
reports and publications, and providing cooperative funding of recovery efforts.
5.3.
Present current recovery activities at professional and public meetin2s. This should
include papers presented at American Fisheries Society and Wildlife Society meetings,
and to interested public groups, such as Trout Unlimited, The Nature Conservancy and
the National Wildlife Federation.
5.4.
Promote watchable greenback programs. Programs to provide viewing opportunities
for the public to view greenback trout and their habitats should be promoted
throughout watchable greenback programs. This should include viewing areas during
the spawning season, and programs such as the boardwalk at the Hidden Valley beaver
ponds, RMNP.
32
�5.5.
Promote the adoption of the 2reenback as the Colorado State Fish. Colorado Trout
Unlimited supports this proposal, and has taken a lead role in contacting
representatives to sponsor a bill. This task was completed in 1994.
5.6.
Prenare a 2reenback disolay. Develop a greenback display for use in public relations
and education programs describing the history, biology, and ecology of greenback
cutthroat trout and of sympatric native species. This task was completed in 1993.
�6. Promote partnerships with conservation groups and explore
alternative management and funding strategies.
6.1.
Increase the use of non-traditional a~encv funds and private funds. Explore
opportunities to increase funds available for completion of greenback recovery
programs, by using non-traditional or private sources, such as inter-agency funding,
challenge grants, and Fish American funding of restoration work.
6.2.
Market art work. Produce art work based upon greenbacks that promote public
awareness and support for the recovery of the subspecies. Market art work such as a
limited edition greenback print, postcards and shirts to produce funds for greenback
restoration activities. This task has been completed.
6.3
Produce a greenback brochure. Produce a greenback brochure with funding from
Colorado Trout Unlimited. This task has been completed.
34
�7. Prepare a long-term management plan and cooperative management
agreement for the greenback cutthroat trout.
Prior to delisting the greenback cutthroat trout, a long-term management plan and
cooperative agreement for the management of greenback cutthroat trout will need to be
prepared. Thisplan should be approved and utilized by allparticipating agencies (Colorado
Division of Wildlqe, US. Bureau of Land Management, US. Forest Service, US. Fish and
Wildlife Service, and National Park Service) having proprietorship over the populations of
type A and B greenbacks.
The 1992 Amendments to the Endangered Species Act require delisted species to be monitored
for a period offive years following their delisting. A monitoring program describing how the
greenback will be monitored after delisting u’ill be included in the long-term management
plan.
7.1.
Prenare a lon2 term-manauement plan. A management plan should be prepared
that will incorporate all the information obtained through completion of the recovery
plan tasks. All agencies will need to maintain records on their recovery activities and
provide pertinent information in development of the management plan. The purpose
of this management plan is to ensure that adequate regulatory mechanisms and
management programs remain in existence after delisting to ensure that adequate
populations of greenback cutthroat trout are maintained. The plan will need to
provide pertinent biological and management information on the greenback for use itt
maintaining greenback populations. It must identify how populations will be
monitored to document the status and condition of populations and habitats, and
should identify conditions that would warrant relisting the greenback. The plan
35
�should also address interagency cooperation and agency responsibilities and
cooperative agreements established under Task 7.2. The plan should be developed
before the delisting of the greenback is proposed. The plan should be reviewed and
approved by all parties with jurisdiction over greenback trout populations before the
greenback is delisted. The plan should be written based on the following outline:
I. Life History and Ecology
a. Habitat requirements
b. Reproduction
c. Food preference
d. Community ecology
e. Fish diseases
II. Present Status of Greenbacks
a. Brief history of recovery
b. List of current Type A and B populations
c. Criteria for stable populations
III. Management Goals and Objectives
a. Conservation Management
1. Future population goal and objectives
2 Population monitoring
3. Isolated population concern/action
4. Genetic monitoring of wild population
5. Habitat
6. Future populations (Metapopulations)
.
7. Impacts
b. Recreation/Public Use
1. Quality fisheries
2. Limited harvest fisheries
3. Protected areas
4. Watchable fisheries programs
5. Aquatic education programs
IV. Maintenance
a. Habitat management guidelines
1. Resource management activities
2. Habitat improvement structures
U-36
�b. Species Management
1. Broodstock maintenance
2. Stocking
3. Angling regulations
4. Methods for removing non-natives
a) with greenbacks present
b) for new sites
V. Implementations Strategies
List of activities, dates, and responsibilities
7.2.
Prenare a cooperative a2reement. Cooperative management agreements should be
prepared to define the role of the management agencies in maintaining populations
of pure greenback cutthroat trout established or documented under Task 2.0 of this
Plan. This agreement will need to be approved and signed by all involved management
agencies with greenback populations on areas under their jurisdiction. Review of this
cooperative agreement and an evaluation of the status of the subspecies can be
reviewed at interagency coordination meetings.
P
37
�The Implementation Schedule that follows outlines actions and costs for the recovery program.
It is a guide for meeting the objective and tasks outlined in Part II of the plan. This schedule
indicates the general category for implementation. recovery plan tasks, corresponding outline
numbers, task priorities, duration of tasks (-‘ongoing”) denotes a task that, once begun should
continue on an annual basis, the responsible agencies, and estimated costs. These actions, when
accomplished should bring about the recovery of the greenback cutthroat trout and protect its
habitat. Tasks will only be completed and funds expended contingent upon appropriations,
priorities, and other budgetary constraints that apply to each agency or organization.
Priority I - All actions that are absolutely essential to prevent the extinction of the subspecies.
Priority 2 - All actions necessary to maintain the subspecies’ current population status.
Priority 3 - All other actions necessary to provide for full recovery of the subspecies.
Agency Abbreviations Used in Implementation Schedule and Tables:
ARNF
Arapaho Roosevelt National Forests
CCBLM
- Canon City District of BLM
CDOW
- Colorado Division of Wildlife
CTh
- Colorado Trout Unlimited
-
DOD
FS
BLM
-
Department of Defense (Fort Carson)
U.S. Forest Service
Bureau of Land Management
FWS
-
U.S. Fish and W~ildlife Service
P&SINF
-
Pike & San Isabel National Forests
Priv
-
Private property
RMNA
-
Rocky Mountain Nature Association
RMNP
-
Rocky Mountain National Park
-
-
Fish Abbreviations Used in Tables:
Brook Trout
BKT
-
GBC
RBT
-
Greenback Cutthroat Trout
Rainbow Trout
BNT
-
Brown Trout
-
Other Definitions:
On-going, task or action which will need to be conducted on a regular basis throughout the
Recovery program.
38
�PART Ill - IMPLEMENTATION SCHEDULE FOR RECOVERY OF THE GREENBACK CUTTHROAT TROUT FROM 1995 TO 2000
Number
—
Priority
Task Description
Task
Duration
1
—
~~Cost
—
—
~~Cost
EWS
—
FS
—
BLM
—
RMNP
——
5 0
40 0
Comments
Estimates (X $1,000)
I
DOD
—
RMNA
—
CTU
—
1 1
1
Conduct population and
habitat monitoring
Ongoing
1 2
1
Enhance or restore habitat
Ongoing
Costs will be determined as needs are
identified.
1 3
I
Maintain stream barriers
Ongoing
Costs will be determined as needs are
identified.
1 4
1
Prevent introduction of non-
Ongoing
Will be conducted as part of ongoing agency
programs.
I 5
1
Promote sound land and
Ongoing
5.0
1 6
1
Enforce regulations
Ongoing
5.0
SUBTOTAL
30.0
TASK I - Maintainlenhance known populations
20 0
10 0
12.0
10.0
8.0
1.0
5.0
5.0
Maintain list of candidate
habitats
Ongoing
5.0
5.0
2.3
3
Consult with landowners
and agencies
Ongoing
5.0
—
10.0
2.41
3
Manipulate habitat of
reintroduction areas
Ongoing
2.42
3
Improve barriers in
reintroduction areas
Ongoing
2.43
3
Remove non-native
salmonids in reintroduction
areas.
Ongoing
2.51
3
Use stocking rates for wild
populations
Ongoing
Ongoing
0.0
0.0
0.0
152.0
Agencies will need to maintain and update the
list as necessary.
5.0
5.0
5.0
50
Some costs cannot be determined until needed
projects are identified.
Costs cannot be determined until projects are
identified.
5.0
—
Monitor success of
~reeohack reintroductions
Will be conducted as part of ongoing agency
programs.
2.0
3
3
5.0
5.0
2.2
2.6
5.0
40.0
Ongoing
Ongoing
Will be conducted as part of ongoing agency
programs.
50.0
Survey for historic
populations
Use stocking rates for larval
hatchery fish
5.0
10.0
3
3
5.0
22.0
2.1
2.52
5.0
30 0
50.0
—
15.0
Will be conducted as part of ongoing agency
ro rams.
—
Will be conducted as part ofongoing agency
programs.
5.0
5.0
2.0
25.0
15 0
�Ti~k
Nutitber
Prtorit~
2 ~
Task Description
pulatioit ~
rirceirback
Annually update
I~
TASK 2 — Esahlish document 2)) stable populations
Task
Ditrait 0
Cost Estimates X $1 (XX))
Comments
R
Ongiinv
EWS
CS
BLM
RMNP
CDOW
DDOD
RMNA
SUBTOTAL
30.))
4)1 0
t30
95.0
5X.l)
0.0
0.0
CCTU
0.1)
236.0
3.1
3
Establish South PIitte Riser
complete
Involved agencies will riced to conduct regular
3.2
3
s~ Id broodstock
Establish Arkaosas River
broodsrock
cuttiplete
nionitorin of the wild hroodstock 0 ulations.
Involved agencies will iieed to conduct regular
ttm(itlttoring of the wild broodstoc k populations-
3.31
3
Collect tuilt front ss Id
populations
()ttgoritg
51)
5.))
3.32
3
Establish broodstocks at
CDOW hatcheries
Oiteoiire
6)11)
15.))
Work will be acconipl shed by C DOW w jilt
funding friim tither involved agencies.
3.33
3
Prepare reports oii statu5 01
hatchery priterant
Ongoing
5.))
Will be cotiducred as part of hatchery
programs.
3.34
3
Provide information ftir
long—tertit tttaiiagenicrir plait
arid cooperative aereement
I sear
1 .1)
1 (1
I .11
1 .1)
I .11
SUBTOTAL
1.0
66.0
1.0
26.0
21.0
1(3.0
5.1)
TASK 3 - Establish PO ularions for broodstocks
21).))
Tit be completed prit r to spec ies deli suite
0(1
4.1
3
Assess mixed recreation
fisheries
complete
4.2
3
Implement catch-and-release
programs on public lands
complete
4.3
3
Coniplete research stocking.
angline resulatitins, etc.
Otigoing
1(1.))
4.4
3
Complete research stiucking
ofgreenbacks into waters
with native non-salmonids
Ongoing
5.0
TASK 4 - Document response to angler pressure. etc. SUBTOTAL
15.))
0.))
(1.1)
1(1.1)
5.0
5.1)
5.0
5.0
5.0
5.0
5.0
5.0
5.1
3
Encourauc l&E programs
Oneoin~
5.2
3
Promote interagency
cotiperation
Ongoing
5.3
3
Present recovery
information at meetines
Ongoing
0.0
0.0
5.0
115.0
Additional costs will be incurred iii later years
as restitratitin projects are identified.
1).))
1)))
35.1)
Will be conducted as part ol unitoitig atmericy
pr(ierautts.
5.))
5.0
5.0
5.))
5.0
5.))
Will be cirtiducted as part if otigoing ageticy
prorirarits.
�Task
Priority
Number
[____
Task Description
Task
F
F
—~ Cost Estimates
—
(X $1,000)
—.
R
t___________
Duration
FFWS
F FS
—
BLM j —
RMNP
—
I—.—
RMNA
RMNA
CTU
—
5.4
3
greenbackwatchable
Promote
programs
Ongoing
5.5
3
Promote adoption of
greenback as Colorado State
fish,
Complete
5.6
3
Prepare a traveling
greenback display
Complete
6.1
3
Increase use of non
traditional agency and public
funds
Ongoing
6.2
3
Market art work
On oin
6.3
3
Produce a greenback
brochure
complete
~
TASK 6 - Promote partnershi s and altemative fundin UBTOTAL
j
.
2 years
1 year
agreement
TASK 7 - Prepare a long-term management plan
TOTAL
—
SUBTOTAL
Will
programs.
be conducted as part of ongoing agency
Accomplished with sponsorship by CTU.
Funding provided by FS & BLM.
1
TASK 5 - Croduct an information/education program SUBTOTAL
Prepare a long term
management
plan
Prepare a cooperative
—
CDOW j —
DOD
1 Comments
10.0
10.0
—
10.0
10.0
10.0
10.0
0.0
0.0
60.0
Part of agency programs
2.0
1.0
—
1.0
Accomplished with assistance from CDOW,
BLM, FS, & FWS.
0.0
20
00
00
0.0
0.0
1.0
1.0
4.0
3,0
—1.0
3.0
—1 0
30
—1 0
30
3.0
1.0
3.0
—
1.0
To be completed prior to delisting.
1 0
3.0
—1.0
—
—
—
—
—
be part ofongoing agency programs.
To be completed prior to delisting. Costs will
4.0
60
4 0
40
4.0
4.0
1.0
5.0
32.0
90.0
146 0
38 0
195 0
138.0
19.0
2.0
6.0
634.0
�LITERATURE CITED
Behnke. R. J. 1973. The greenback cutthroat trout Salmo clarki stomias.
Status report. U.S. Fish and Wildlife Service. Albuquerque. New Mexico.
Behnke, R. j. and M. Zarn. 1976. Biology and management of threatened and endangered
western trout. USDA Forest Service, Rocky Mountain Forest and Range Experimental Station.
General Technical Report RM-28.
Behnke, R. J. 1979. Monograph of the native trouts of the genus Salmo of western North
America. U.S. Fish and Wildlife Service, Denver. Colorado.
Behnke, R.J. 1984. Greenback cutthroat trout, Salino clarki stomias. Trout.
Binns, N. A. 1977. Present status of indigenous populations of cutthroat
trout, Salmo clarki in southwest Wyoming. Wyoming Game and Fish Department. Cheyenne.
Fish Technical Bulletin 5.
Bulkley, R. V. 1959. Report on 1958 fishery studies in Rocky Mountain
National Park. Bureau of Sport Fisheries and Wildlife, Logan. Utah.
Cope. E. D. 1872. Report on the reptiles and fishes obtained by the
naturalists of the expedition. U.S. Geological Survey Wyoming: 432-442.
Dwyer, W P. 1981. Greenback cutthroat trout broodstock annual report for
1981. USFWS, Fish Cultural Development Center. Bozeman. Montana.
Dwyer. WP., and B.D. Rosenlund. 1988. Role of fish culture in the
reestablishment of greenback cutthroat trout. American Fisheries Society Symposium 4:75-80
Fausch. K.D.. and T.R. Cummings. 1986. Effects of brook trout competition on
threatened greenback cutthroat trout.
Gold. J. T. 1977. Proposal for the morphological analysis of S. c. stomias
and S. c. pleuriticus populations. Texas A&M University, College Station.
Greene, W. 5. 1937. Colorado trout. Colorado Museum of Natural History
Popular Series No. 2.
Johnson, j. F. 1976. Status of endangered and threatened fish species in
Colorado. USD1, BLM Technical Note 280.
Jordan. D. 5. 1891. Report on explorations in Colorado and Utah during the
summer of 1889 with an account of the fishes found in each of the river basins examined.
Bulletin U.S. Fish Commission, 9:1-40.
Juday, C. 1906. A study of Twin Lakes, Colorado, with special consideration
of the foods of the trouts. Bulletin U.S. Bureau of Fisheries, 26:147-178.
Os~fC
42
�Markiw, M.E. 1990. Unpublished letter to Colorado Division of Wildlife.
USFWS, National Fish Health Research Laboratory, Kearnesyville. WV.
Nelson. W 5. 1972. An unexploited population of greenback trout. Colorado
Division of Wildlife. Fort Collins, CO.
Proebstel, D. 1993. Genetic variability of greenback cutthroat trout
(Oncorhvnchus clarki stomias): as determined by analysis of meristic characters and restriction
fragment length polymorphisms of mitochondrial DNA. Unpublished report. Department of
Fishery and Wildlife Biology, Colorado State University. Fort Collins. 10 pp.
Rosenlund, B.D. and D.R. Stevens. Use of antimycin for the restoration of
greenback and Colorado River cutthroat trout within the Leadville National Fish Hatchery and
Rocky Mountain National Park. In press.
Stuber, R.J., B.D. Rosenlund, and JR. Bennett. 1988. Greenback cutthroat
trout recovery program: management overview. American Fisheries Society Symposium 4:70-74.
Tulian, E.A. 1896. Annual report of the operations at the Leadville station
for the year ending 30 June 1896. Leadville National Fish Hatchery, Leadville, CO.
Wang, L. 1989. Behavior and microhabitat competition of brown trout and greenback cutthroat
trout in an artificial stream. Masters thesis, Montana State l.Jniversity. Bozeman.
Wernsman, G. 1973. Systematics of native Colorado trout. Master’s thesis.
Colorado State University, Fort Collins.
Wiltzius, W J. 1985. Fish culture and stocking in Colorado, 1872-1978.
Colorado Division of Wildlife. Fort Collins, CO
Woodward, D.F.. A.M. Farag, E.E. Little, B. Steadman and R. Yancik. 1991.
Sensitivity of greenback cutthroat trout to acid pH and elevated aluminum. Transactions of the
American Fisheries Society 120:34-42
PUBLIC REVIEW
This recovery plan was made available to the public for comments as required by the 1988
amendments to the Endangered Species Act of 1973. The public comment period was
announced in the Federal Register 29 April 1993, and closed 28 June 1993. Press releases were
sent to the print media.
During the public comment period, five letters were received. The comments provided in these
-~
-~
letters have been considered, and incorporated as appropriate. Comments that address recovery
tasks that are the responsibility of an agency other than the U.S. Fish and Wildlife Service have
been sent to that agency as required by the 1988 amendments to the Act. The recovery plan was
prepared in 1993, updated to reflect current population status through 1997, signed and printed
in 1998.
43
�C
tv,
44
�Table 1
Summary of Known Historic Greenback Cutthroat Trout Sites and Stability of Pooulation. 1970-1997.
LOCATION
HABITAT
km
ha
CRITERIA
Survey
Kg/Ha
>500
——
COMMENTS
GBC
Other species
Repro-
present
Stable as of
L~L.
South Platte Drainage
Como Creek, ARNE
29
1991
46.0
Y
Y
N
Y
hunters Creek. RMNP
20
1996
118.0
Y
Y
N
Y
lip. hutch. Lake, RMNP
0S
30
1997
50.0
Y
Y
N
Y
Open to C&R angling
Mid. hutch. Lake, RMNP
02
1 7
1990
50.0
Y
Y
N
Y
Open to C&R angling
SUBTOTAL South Platte Drainage -stable
56
4 7
S.F. Poudre R.. ARNF, RMNP
1 7
1991
17.8
N
Y
N
N
Population is improving
U
20
1990
Unk
N
Y
N
N
Vetyfewfish
Tarryall Creek, near Boreal Pass. private
20
1991
Unk
I
I—
Unk
BKT
N
Below rivate minin claims.
SUBTOTAL South Platte Drainage
II 3
1995
38.3
Y
Y
N
Y
1995
127 1
N
Y
rHa ueCreek,RMNP
47
Arkansas River Drainage
Cascade Creek, P&SINF
2.8
S. Apache Creek, P&SINF, Priv, CCBLM
12.2
—
a.
SUBTOTAL Arkansas Drainage
15.0
0
TOTAL
26.3
4.7
3900 GBC estimate
�“ahle
.——
2. Summary of South Platte Greenback Cutthroat Trout Restoration Projects, 1970-1997.
LOCATION
HABITAT
STOCKED
km
ha
1.7
1.0
1970
2.6
1989
4.5
CRITERIA
Survey
date
COMMENTS
Kg/Ha
>500
fish
GBC
Reprod
non
Other species
present
Stable as of
last survey
62.0
Y
Y
N
Y
Opened to C&R angling, 1990.
GBC to 400mm
1993
55.0
Y
N
N
1975-1987
1991
50.0
Y
Y
N
Y
No angling due to heavy use of lake
trail.
Stable Habitats
N.F. Thompson
Creek,
RMNP
NF Thompson
Ck, above 3274
m
Lake Louise
Bear Lake, RMNP
0.1
Williams Gulch, ARNF
2.0
1981-1982
1993
84.0
Y
Y
N
Y
Closed to angling
E.& W. Forks Sheep Creek
ARNF
11.2
1982-1987
1993
67.0
Y
Y
N
Y
Opened to C&R angling, 1988.
Fern Lake
Fern Creek, RMNP
1.4
3.7
1982-1984
1991
45
24
N
N
Y
Y
N
N
Y
Opened to C&R angling, 1986.
Odessa Lake, RMNP
0.2
4.5
1984-1989
1993
27.0
Y
Y
N
Y
Opened to C&R angling in 1987.
Lawn Lake, and
inlet below Big Crystal Lake,
RMNP
0.9
9.5
1984-1986
1992
60.0
Y
Y
N
Y
Opened to C&R angling in 1988.
Roaring River, RMNP
6.5
1984-1986
1991
81.0
Y
Y
N
Y
Opened to C&R angling, 1991.
Lower Hutch. Lake and
outlet stream above 3048 m, RMNP
1.0
1.7
1986-1991
1991
138.0
Y
Y
N
Y
Opened to C&R angling in 1991.
Pear Lake, RMNP
1.2
6.1
1989-1990
1991
80.0
Y
Y
N
Y
Opened to C&R angling in 1991.
Sandbeach Lake, RMNP
0.1
4.0
1989-1990
1992
69.0
Y
Y
N
Y
Opened to C&R angling, 1991.
Cony Creek, RMNP
3.5
1989-1990
1996
25
Y
Y
N
Y
Opened to C&R angling, 1991.
Spruce Lake. RMNP
03
1.5
1991-1992
1995
60.0
Y
Y
N
Y
0
SUBTOTAL - Stable Habitat
30.1
39.1
1.6
2.5
1973
1989
50.0
BKT
P
Brook trout dominate beaver pond
habitat. Opened to angling 1982.
ned to C&R an lin
1993.
Potentially Stable Habitats
Hidden Valley Creek,
and beaver ponds
RMNP
�LOCATION
hABITAT
km
STOCKED
ha
—
Sur
vey
Kg/Ha
Idate!
—
West Creek, above West Creek
Falls, RMNP
2.4
1979-1987
1996
May Creek,
ARNF
1.7
1980-1987
1994
50.0
Ouzel Creek above Ouzel Falls,
RMNP
4.7
1981-1983
1991
Ouzel Lake and
Stream below Bluebird Lake,
RMNP
1.4
2.6
1981-1983
Lost Lake
N.F. Big Thompson Creek,
above Lost Falls,RMNP
3.0
3.7
Loomis Lake and Pond, RMNP
0.4
Zimmerman Reservoir, ARNF
—
1>500
j fish
CRITERIA
r—
GBC
Reprod
—
tion
—
COMMENTS
J Other species
present
Stable as of
last survey
I____
Y
N
P
N
Y
N
P
34-229
Y
Y
BKT
P
Opened to C&R angling, 1986.
1996
69.0
Y
Y
Y
P
Opened to C&R angling, 1986.
1987-1989
1987-1990
1993
1993
30.0
15.0
Y
Y
Y
Y
Y
Y
P
P
Opened to C&R angling, 1990.
1.5
1991-1992
1995
28
Y
N
N
P
Opened to C&R angling, 1993.
0.4
4.6
1996
1997
N
P
Opened to C&R angling, 1997.
Husted Lake, RMNP
0.1
4.1
1991
1993
N
P
Open to C&R angling, 1995
Dream Lake, RMNP
0 1
2.2
1997
1997
N
P
Open to C&R angling. 1998.
SUBTOTAL - Puten~ial1y Stable
Habitats
15.8
21.2
—
—
Unstable Habitats
Black Hollow, ARNF
5.2
1981-1983
1994
8.5
N
N
BKT, RBT
N
Hourglass Creek. ARNF
2.0
1981-1982
1992
0
N
N
N
N
Bard Creek, ARNF
6.1
1982-1986
1994
43.0
Y
N
N
N
Cornelius Creek, ARNF
6.9
1983-1985
1993
5.0
N
N
BKT. BNT
N
Opened to C&R angling, 1988.
Population declining due to competition
with exotics. Unsuccessful project.
George Creek, ARNF
12.7
1983-1985
1993
3.6
N
Y
BKT, BNT
N
Opened to C&R angling, 1988.
Population declining due to competition
with exotics. Unsuccessful project.
Unsuccessful project. GBC no longer
present.
Opened to C&R angling. 1993. No
reproduction due to heavy metals.
Maintained as GBC fishery through
stocking.
�LOCATION
Big Crystal Lake, RMNP
HABITAT
km
ha
02
10 0
N. Fork Jackson Creek, P&SINF
Bruno Gulch. P&SINF
STOCKED
9.0
Lily Lake, RMNP
CRITERIA
COMMENTS
Survey
date
Kg/Ha
>500
fish
GBC
Reprodnon
Other species
present
Stable as of
last survey
1984-1986
1995
114.0
Y
N
N
N
High elevation experimental population
opened to C&R angling, 1990. No
reproduction documented. Still under
evaluation.
0.3
1985-1987
1991
2.0
N
N
BKT
N
BKT dominate, opened to standard
regulations., 1993. Unsuccessful
project.
1.4
1986-1990
1991
8.0
N
N
BKT
N
No reproduction due to heavy metals.
Opened to standard regulations.. 1993.
Unsuccessful project.
6.8
1980-1992
1997
Y
N
N
N
Experimental fisheries, maintained by
stocking.
1986-1988
1993
N
Y
BKT
N
Unsuccessful project.
Pennock Creek, ARNF
8 0
SUBTOTAL - Unstable Habitats
50 1
18 5
TOTAL - South Platte Basin
96 0
78 8
9.4
�Table 3. Summarv of Arkansas River
LOCATION
““~‘-“
Cutthroat Trout Restoration Projects. 1970-1997.
HABITAT
km
STOCKED
CRITERIA
ha
Survey
date
Kg/Ha
>500
fish
GBC
Reproduction
COMMENTS
Other species
present
Stable as of
last survey
N
Y
Ci~ofCoSpringswatersupply
Closed to angling.
Stable_Habitats
Boebmer Res.,
Ci CoS rin s
10.1
SUBTOTAL - Stable populations
0.0
10.1
Lytle pond
—
0.4
Lytle inlet
1.0
19851989
1996
I 200
I
I Y
I
I Y
I
1981-1993
1994
50.0
N
Y
BKT, DART
P
Opened to C&R angling 1989.
I
Potentially Stable Habitats
Ft. Carson
LAKE FORK
COMPLEX,
P&SINF
ROCK CREEK
COMPLEX
Leadville NFH
& P&SINF
Duck Pond
1.7
Virginia Lake,
1.2
1987-1990
1991
20.0
N
Y
N
P
Open to C&R angling, 1990 and
harvest, 1993.
Timberline
Lake,
10.1
1987-1990
1991
20.0
Y
Y
BKT
N
BKT2S% of population above 3200m.
Open to angling, 1990.
Timberline Inlet
0.4
1987-1990
LakeForkCr.
& 3 lks. Trib.
48
1987-1996
1991
35.0
Y
Y
BKT
N
Zac Bog,
1 0
1987-1990
1991
35 0
Y
Unk
N
P
35
1991-1996
1995
200
U
U
—
Unk
N
P
Opened to C&Rangling, 1991.
Rainbow Lake,
Open to C&R angling, 1990.
Native Lake. and
inlet/outlet
1 0
2 3
1991-1996
1995
12 0
U
Y
BKT
P
Opened to C&R angling, 1991.
Swamp Lake &
outlet
11
—
2 5
1991-1992
1994
10 0
U
U
—
Y
BKT
U
BKT only in stream below the lakes by
1995
Rock Creek
58
1991-1996
5 0 35 0
—
22 1
U
U
U
U
Y
BKT
U
Opened to C&R angling, 1991.
Y
BKT
U
Elk Creek
1 2
1991-1996
1994
—
1995
Cascade Creek
09
1991-1992
1993
37 9
U
Y
N
U
Bog Creek
0 3
1991
1991
Unk
Unk
Unk
BKT
Unk
—
�LOCATION
HABITAT
km
STOCKED
ha
Greenhorn Creek
P&SINF
3.2
1988-1989
Sayres Gulch, P&SINF
2.4
1996
Mason Reservoir, CCS
4.8
Hunt Lake Basin, PS&NF
2.4
Newlin Creek, P&SINF
2.4
North Apache Creek
2.4
SUBTOTAL Potentially Stable populations
35 1
CRITERIA
Sur
vey
date
[Kg/Ha
1>500
fish
1995
65.0
Y
GBC
Reproduction
Y
COMMENTS
I Other species
present
N
Stable as of
last survey
P
Fishless area prior to 1988. No
reproduction, until 1994. Uncertain
spawning habitat. Poor habitat
conditions. May conduct habitat
improvement project in the future.
P
Fishless stream prior to 1996.
55.0
P
Treated in 1996
8.5
P
Treated in 1997
1997
P
Fislsless stream prior to 1997
1996-1997
P
Fishless stream prior to 1996
85 2
Unstable Habitats
Cottonwood Creek
P&SINF
SUBTOTAL - Unstable nonulations
Open to angling
�Table 4. Summary of Greenback Historic Populations, Restoration Projects. Areas Open to Ansline and-- Stable Populations. 1997.
TYPE OF POPULATION
I
N1tM~FR
I
T-t~FTAD~V
I
VII CTh~T~n(
SOUTH PLATTE RIVER DRAINAGE
Restoratiots Projects
Historic Populations
South Platte Summary
Total Restoration Projects
33
78.8
96.0
Open to Angling
31
74.3
93.9
Stable Restoration Projects
13
39.1
30.1
Total Historic Populations
7
4.7
11.3
Open to Angling
2
4.7
0.0
Stable Historic Populations
4
4.7
5.6
Total Populations
40
83.5
107.3
Open to Angling
33
79.0
93.9
Stable Populations
17
43.8
35.7
Total Restoration Projects
20
95.3
41.5
Open to Angling
14
21.7
25.3
Stable Restoration Projects
1
10.1
0.0
Total Historic Populations
2
0.0
15.0
Open to Angling
0
0.0
0.0
Stable Historic Populations
2
0.0
15.0
Total Populations
22
95.3
56.5
Open to Angling
14
21.7
25.3
Stable Populations
3
10.1
15.0
Total Populations
62
178.8
163.8
Open to Angling
47
100.7
119.2
Stable Populations
20
53.9
50.7
ARKANSAS RIVER DRAINAGE
Restoration Projects
Historic Populations
Arkansas Summary
GRAND TOTAL
�Table 5. Hybrid Ponulations of Greenback Cutthroat Trout. 1994.
SITE NAME/DRAINAGE
RIVER DRAINAGE
TYPE B POPULATlONS~ Essentially pure, with a trace of influence from other s tin s awnin trout s
Arkansas River
South Platte River
OWNERSHIP
cies:
South Fork of the Arkansas River
Arkansas River
P&SINF
Strawberry Creek
Huerfano River
P&SINF
Dutch Creek
Hue rfano River
P&SINF
Dee Creek
Huerfano River
P&SINF
Island Lake
Boulder Creek
City of Boulder
Still awaiting DNA analysis
Goose Lake
Boulder Creek
City of Boulder
Still awaiting DNA analysis
Forest Canyon
Big Thompson River
RMNP
Caddis Lake
Fall River
RMNP
Sawmill Creek
Poudre River
ARNF
Roaring Creek
Poudre River
ARNF
TYPE C POPULATIONS: Good representatives of greenback stock, both with noticeable influences from other spring spawning trout species:
South Platte River
COMMENTS
Rabbit Creek
N.F. Poudre River
Private
transplant of Forest Canyon greenbacks
�Table 6. South Platte Greenback Restoration Projects and Stocking Schedule. Includes year proposed for renovation (R), year and number of greenback fry to be stocked, and year to open to catch-and-release
(C&R) angling based upon the stocking of fry. 1995-2007.
SITE
Habitat
km
Sandbeach Creek, RMNP
199
-ha
J
1996
1999
Liz
1.5
Ilidden Valley Creek, RMNP
2.5
1.6
Mummy Pass Creek, RMNP
2000
~20~
~2002
2003
R
2000
2000
2000
C&R
R
1500
1500
1500
C&R
R
1600
1600
1600
C&R
R
1000
1000
1000
C&R
1.0
2004
j2005
2006
J2007]
Poudre Lake, RMNP
30
R
5000
5000
5000
C&R
Lake Hajyaha, RMNP
6.3
R
6300
6300
6300
C&R
R
1500
1500
1500
C&R
R
2000
2000
2000
C&R
R
3700
3700
3700
C&R
R
5800
5800
5800
R
2000
2000
R
6700
R
1500
11,500
16,000
1.5
Hague Creek, RMNP
1.0
Black Lake, RMNP
3.7
Willow Creek, RMNP
5.0
Cow Creek, RMNP
2.0
Thunder Lake and
l~ion Creek. RMNP
SUMMARY
6.7
1.5
]15.1
[222
J~~0
to
110
15,100
118,900
20.900
1115,800
2,000
13,700
119,500
�Table 7. Arkansas River Greenback Restoration Projects and Stocking Schedule. Includes year proposed for renovation (R), year and number of greenback fry to be stocked, and year to open to catch-andrelease (C&R~ anelirie based upon the stocking of greenback adolts* and fry. 1995-2007.
________
________
_________
________
________
________
________
_________
SITE
f..2~ta
1...........j 1995
J1998
11999
2000
12001
R
6000
6000
6000
R
2.7
5.2
—
—
1996
3.2
*
N. Apache Creek, P&SINF
1.9
1000
Cottonwood Creek. P&SINF
6.4
1000
Turkey Creek, P&SINF
9.7
Stanley Canyon Creek. W.
Monument Creek
6.0
Severly Creek
Graneros Creek
1.6
4.8
SUMMARY
- stock from S. Apache
12003
3000
3000
3000
R
2000
2000
2000
R
2500
2500
2500
7000
7000
]7,500
17,500
2004
~2005
2006
12007
1000
3
Lake Fork Creek
Timber Lake
~2002
—
Greenhorn Creek, P&SINF
Stanley Canyon Res
1997
R
7000
10
141.5111310
9
9
12,~
Il,~
J~
Jl3,~]l3,~[20,500
[~ 110 :10
101
�.
~lablc8. South Platte River Drainage Greenback Research Cutthroat Trout Stocking Sites. 1995-2007
SITE
1995
{1996
1997
1998
JI~
12000
2001
~2002
J2003
—
U—
ULiii
—
——
S—
—
111
—
——
2004
U—
2005
J2~
2007
—
—it—
—
ROCKY MOUNTAIN NATIONAL_PARK______
Lily Lake
—~
Arrowhead Lake
Subtotal, RMNP
6.8
500
500
1500
14.8
21.6
12000
I 2,500
I
12000
2,500
12000
2,500
—
——
— ~.
—
—
[500
1
1500
1~____
s001
500
j__
2000~
] 2,500
1
12000
I 2,500
1
I
12000
J 2,500
1
J
——
—
——
——
—
. —
—
500
500
2000
1 25001
PRIVATE PROPERTY:
~Mancbesterl.ake
Subtotal, Private
I....i5.0
()015.O~5001I500T0I010I0I0~0I0L0T0
—
—
—
——
——
—
10]
—
——
U—
—
——
——
——
—
PIKE & SAN ISABEL NATIONAL FOREST/ ARAPAHO & ROOSEVELT NATIONAL FOREST., FORMER CDOW CENTRAL REGION
Upper Diamond
Lake
2.4
600
600
600
600
600
600
600
600
600
600
600
600
600
North Iceberg Lake
4.0
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
Heart Lake
6.9
1700
1700
1700
1700
1700
1700
1700
1700
1700
1700
1700
1700
1700
Upper Crater Lake
3.4
850
850
850
850
850
850
850
850
850
850
850
850
850
IceLake
4.9
1100
1100
1100
1100
1100
1100
1100
1100
1100
1100
1100
1100
1100
Caroline Lake
3.5
850
850
850
850
850
850
850
850
850
850
850
850
850
Ethel Lake
2.0
500
500
500
500
500
500
500
500
500
500
500
500
500
Silver Dollar Lake
7.5
1850
1850
1850
1850
1850
1850
1850
1850
1850
1850
1850
1850
1850
Dorothy Lake
6.5
2400
2400
2400
2400
24.00
24430
2400
2400
2400
2400
2400
2400
2400
Bob Lake
3 4
1275
1275
1275
1275
1275
1275
1275
1275
1275
1275
1275
1275
1275
King Lake
46
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
14(10
Deep Lake
20
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
7.3
900
900
900
900
900
900
900
900
900
900
900
900
900
Frozen Lake
2.8
500
500
500
500
500
500
500
500
500
500
500
500
500
Shelf Lake
34
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
Abyss Lake
—
�SITE
ha
—
1995
—
1996
11997
11998
l~
I2~
2001
J2002
•2003
2004
12005
2006
2007
Upper Roosevelt
Lake
07
450
450
450
450
450
450
450
450
450
450
450
450
450
ByronLake
Il
300
300
300
300
300
300
300
300
300
300
300
300
300
Lower Roosevelt
Lake
06
450
450
450
450
450
450
450
450
450
450
450
450
450
Upper Chicago
Lake
4.0
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
Upper Bear Track
Lake
1.8
500
500
500
500
500
500
500
500
500
500
500
500
500
Bard Creek
6.1
5000
5000
5000
5000
5000
5000
5000
5000
5000
5000
5000
5000
5000
7&9
24,625
24,625 11 24,625 I 24~25
24,625
2’~625
24,625
24,625
24,625
24,625
I2~~
24,625
24,625]
SUBTOTAL
I~~I
ARAPAHO ROOSEVELT NATIONAL F~~3~ORMER CDOW NE REGION
Upper Agnes Lake
1 2
300
300
300
300
300
300
300
300
300
300
300
300
300
UpperCarey Lake
16
400
400
400
400
400
400
400
400
400
400
400
400
400
ClearLake
40
500
500
500
500
500
500
500
500
500
500
500
500
500
Iceberg Lake
24
600
600
600
600
600
600
600
600
600
600
600
600
600
Island Lake
5 7
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
Kathleen Lake
1 2
400
400
400
400
400
400
400
400
400
400
400
400
400
Lower Longs Lake
0 8
200
200
200
200
200
200
200
200
200
200
200
200
200
Upper Longs Lake
08
200
200
200
200
200
200
200
200
200
200
200
200
200
Rock Hole Lake
24
600
600
600
600
600
600
600
600
600
600
600
600
600
Rolfs Lake #1
6.4
1600
1600
1600
1600
1600
1600
1600
1600
1600
1600
1600
1600
1600
RolfsLake#2
4.4
1100
1100
1100
1100
1100
1100
1100
1100
1100
1100
1100
1100
1100
Upper Roxy Ann
Lake
1.6
400
400
400
400
400
400
400
400
400
400
400
400
400
Ruby Jewel Lake
1.6
400
400
400
400
400
400
400
400
400
400
400
400
400
Seven Lakes #1
5.6
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
14.00
Slip Lake
1.2
300
300
300
300
300
300
300
300
300
300
300
300
300
�12004
_____
12005
ha
SITE
Snow
Lake
Habitat
1995
L...,.......j691
1700
1996
1~I
SUBTOTAL
TOTAL
]O.0]
7
1998
1999
12000
12001
2002
2003
11 500
—
[T7~~J
U—
2””
199
1700
1700
478
—
11 500
U—
11500
—
11,500
—
11,500
—
11,500
—
11,500
—
11,500
—
151.5
1 41,325
40,825
41,325
40.825
40,825
40,825
40,825
11,500
——
11,500
—
11,500
—
1700]
11,500
—
40,825 I 40,825
40,825
40,825
40,825
�.
Table 9.
~
~
~‘~‘
SITE
1995
US ARMY, FORT CARSON:
Fort Carson
21
J 40,000
Air Force Academy
26
51,000
Subtotal US ARMY
{2003
Drainaae Research Greenback Cutthroat Trout Stocking Sites. 1995-2007
-
J 0.0
—
47.0
—
91000
——
~
-
1996
j1997
11998
1999
~2000
2001
2002
—
-—
-—
—
—
—
—
40,000
J 40,000
40,000
40,000
40,000
40.000
40,000
40.000
40
000
40,000
51,000 J 51,000
51,000
51,000
51,000
51,000
51,000
51,000
51,000
51,000151,000
51,000
91,000 I 91,000 I 91,000
—
——
——
] 91,000
—
1 91,000
—
91,000
——
91,000
—
91,000
—
91,000
—
91,000
1 91,000
—
91,000
—
40.000
~2004
200~
2006
2007
-—
PIKE & SAN ISABEL NATIONAL FOREST/ SOUTHEAST REGION, CDOW:
Little Dry Lake
1.6
400
400
400
400
400
400
400
400
400
400
400
400
400
Middle Dry Lake
2.4
600
600
600
600
600
600
600
600
600
600
600
600
600
UpperDryLake
1.2
300
300
300
300
300
300
300
300
300
300
300
300
300
Kroenke Lake
12.1
3000
3000
3000
3000
3000
3000
3000
3000
3000
3000
3000
30(10
3(100
Arthur Lake
2.4
600
600
600
600
600
600
600
600
600
600
600
600
600
Upper Hancock Lake
2.8
700
700
700
700
700
700
700
700
700
700
700
700
7(10
Grassy Lake
2.4
600
600
600
600
600
600
600
600
600
600
600
600
600
Lower Venerable Lake
3.6
900
900
900
900
900
900
900
900
900
900
900
900
900
Upper Venerable Lake
2.0
500
500
500
500
500
500
500
500
500
500
500
500
50(1
Horn Lake
9.7
2400
2400
2441)0
2400
2400
2400
2400
2400
2400
2400
2400
2400
2400
NorthHornLake
1.2
300
300
300
300
300
300
300
300
300
300
300
300
300
Lower Macey Lake
3.6
900
900
900
900
900
900
900
900
900
900
900
900
900
South Macey Lake
5.7
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
12(10
West Macey Lake
4.9
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2(100
20(1(1)
[55.6
1114400
114400
[14400
1114400
114400
[14400
114400
[14400
114400
114400
114400
114400
1114400!
102.6 1 105400
I 105400
105400
J 105400
1 105400
1 105400
1 10540g
[SUBTOTAL
10.0
TOTAL
1 0.0
105400 I 105400 1 105400 [ 105400
105400
105400
�Appendix 1. Summary of Reovery History, 1959-1994.
Recovery History
Conservation efforts started in 1959. and have resulted in considerable accomplishments in the
preservation of the greenback. Additional detail of some subjects discussed in this recovers’
history can be found in Part I.
Recovery. 1959 to 1972. Prior to the enactment of the Endangered Species Act, conservation
efforts commenced in 1959, when greenback trout from the headwaters of the Big Thompson
River in Forest Canyon of Rocky Mountain National Park (RMNP) were stocked into Fay Lakes of
the Park after removal of non-native trout with rotenone. A greenback population was not
establish in Fay Lakes, but the descendants established a reproducing population in Caddis Lake.
Unfortunately, the Forest Canyon population was later classified as slightly hybridized with
Yellowstone cutthroat trout, therefore both the Forest Canyon and Caddis Lake greenback
populations are now classified as B populations (see Table 5).
Analysis of all specimens obtained prior to 1970 indicated only two pure populations, one in
Como Creek, an isolated tributary of North Boulder Creek, Boulder County, and one in the very
headwaters of the South Poudre River, above a barrier falls in Larimer County.
In 1967, a cooperative project between the FS, Colorado Cooperative Fishery Unit and the
CDOW resulted in the removal of brook trout above a barrier on Black Hollow Creek and the
introduction of Como Creek greenbacks. Unfortunately, brook trout were reestablished, and
displaced the greenback population. However, a 1971 transplant of 50 Como Creek greenbacks
into the fishless headwaters of the North Fork of the Big Thompson River, RMNP, was successful
and resulted in the establishment of a stable greenback population by the early 1980’s.
Recovers’. 197~-1975. With the enactment of the Endangered Species Act in 1973. the greenback
was classified as Endangered.
Hidden Valley Creek in RMNP was treated to remove brook trout, and greenbacks were
introduced in 1973. In 1975, brook trout were removed and greenbacks were introduced into
Bear Lake in RMNP. This population is considered to be stable.
Recovery. 1976-1982. A Recovery Plan was completed in 1977, and an Arkansas River population
of pure greenbacks was confirmed in 2.8 km of Cascade Creek. The Recovery Team
recommended downlisting the subspecies to allow for angling opportunities and to assist in
habitat acquisition. The Federal classification of the greenback changed from endangered to
threatened in 1978.
A total of 64 adult and sub-adult Como Creek greenbacks were shipped to the FWS, Bozeman
Fish Cultural Development Center, Montana, to establish a captive South Platte broodstock in
1977. This project was successful, with 630 greenback sub-adults and 16,579 greenback fry
stocked into restoration projects in the South Platte River drainage in 1981. Milt from wild South
~
59
�Platte populations was taken from wild populations and shipped to Bozeman by 1982. The
taking of milt from wild fish was originally used to compensate for asychronization of males and
females at the hatchery, and later to improve heterozygosity of the captive stock due to the small
number of fish available to found the broodstock.
Semi-wild Arkansas River broodstocks were initiated in 1980 and 1981 at McAlpine Pond
(private) and Lytle Pond ( U.S. Army, Ft. Carson).
Since restoration projects could now be restocked with greenbacks at the rate of 1000 fry/ha, and
the areas opened to catch-and-release fishing within four years, restoration projects increased.
Restoration projects were completed, and greenbacks were stocked into Black Hollow (second
restoration), May Creek, Hourglass Creek, Williams Creek, Sheep Creek, and Bard Creek on the
Arapaho/Roosevelt National Forest lands, and into West Creek, Ouzel Lake and Ouzel Creek and
Fern Lake and Fern Creek within RMNP.
Hidden Valley Creek in RMNP opened to catch-and-release fishing for greenbacks and catch-andkill for brook trout in August of 1982.
Recovery. 198~-1986. A new Recovery Plan was completed in 1983 that capitalized upon the
successes of the broodstock programs and the chemical techniques for removing non-native fish
species.
This recovery plan identified an objective for delisting the subspecies upon
establishment of 20 stable reproducing populations. The plan identified six recovery goals.
Achievements for these goals are described below:
1. Protect Historic Ponulations and Stable Populations. New historic populations were
confirmed in Hunters Creek and the Hutcheson Lakes in RMNP (see Table 1). These historic
populations probably were established by transfers of greenbacks above natural barriers in the
late 1800’s.
2. Establish 20 Stable Populations. Using the South Platte broodstocks, greenbacks were
introduced into George Creek, Cornelius Creek, Pennock Creek and Bruno Gulch within
Arapaho/Roosevelt and Pike National Forests, and into Odessa Lake, Lawn Lake, Roaring River
and Big Crystal Lake, Rocky Mountain National Park. Within the Arkansas River drainage,
Cascade Creek greenbacks were introduced in Cottonwood Creek and Boehmer Reservoir and
exotic fish were removed from Virginia Lake, Timberline Lake, Zac Bog and Lake Fork Creek
within the Pike/San Isabel National Forests.
3. Establish Wild and Cantive Broodstocks. Poudre River greenback eggs were shipped to the
Saratoga NFH, Wyoming in 1985. The Poudre River greenbacks hatched, but did not accept feed
and all died. Milt from the Poudre River fish was later shipped to Bozeman to increase the
heterozygosity of the South Platte broodstock.
Cascade Creek/Lytle Pond greenback eggs were shipped to the Saratoga NFH in 1984. The
Cascade Creek (Arkansas River) stock was established, and sub-adults and fry were shipped to
Colorado to restock restoration projects by 1987.
60
�4. Document Resoonse to An~lin~. In addition to the Hidden Valley fisheries, Ouzel Lake and
Ouzel Creek, and Fern Lake and Fern Creek, Rocky Mountain National Park, opened to catch-andrelease angling for greenbacks in 1986.
5. Increase I&E Program. In 1984, the Recovery Team was awarded the Colorado National
Wildlife Federation Researcher of the Year Award in recognition of the success of the greenback
recovery program.
6. Lone Range Management Plan. To be completed upon delisting of the subspecies.
Recovery 1987-1994. Had the pre-1987 pace of restoration work continued, it would have been
possible to completely delist the greenback by 1990-1992. Unfortunately, Section 6 funding for
CDOW recovery activities and FWS funding of FWS activities did not extend past 1986.
Reorganization of the FWS and the CDOW compounded funding problems, and resulted in no
greenback restoration projects completed outside of Rocky Mountain National Park and the
Leadville National Fish Hatchery since 1987. Problems with fish control permits further
complicated the problem of completing restoration projects.
The recovery plan was revised and public reviewed in 1993, and used the six goals established in
the 1983 Recovery Plan. (This plan was updated, signed and printed in 1998).
1. Protect Historic Populations and Stable Ponulations. New historic populations were
confirmed in South Apache Creek (Leary, 1987) in the Arkansas River drainage, and in Upper
Hague Creek in the South Platte River drainage (see Table I). Tarryall Creek in the South Platte
River drainage has a small greenback population that is believed to be historic. Additional
genetic research is being conducted on this population. A site near Rollinsyille, also in the South
Platte River drainage, needs to be evaluated as a possible historic population.
2. Establish 20 stable nonulations. Due to funding problems, restoration projects were limited
to Rocky Mountain National Park and the Rock Creek drainage above the Leadville National Fish
Hatchery (NFH). In the South Platte drainage, Rocky Mountain National Park restoration
projects conducted through 1990, included Lost Lake, North Fork Big Thompson River, Husted
Lake, Lower Hutcheson lake, Pear Lake, Conev Creek, Sandbeach Lake, Loomis Lake and Spruce
Lake. No additional South Platte restoration projects were completed from 1991 through 1994.
In the Arkansas River drainage, the occurrence of a fish disease, introduced by infected nonnative salmonids, within the watershed of the Leadville NFH resulted in the removal of fish from
this area in August 1990. This was accomplished with funding from Colorado Trout Unlimited,
Texaco Foundation and with assistance from the Forest Service and Colorado Division of
Wildlife. 20.4 ha of lakes and ponds and 10.3 km of stream habitat in the Rock Creek drainage
above the Leadville NFH was restocked with catchable greenbacks from the Saratoga NFH in June
1991, and immediately opened to catch-and-release fishing. No additional Arkansas restoration
projects were completed from 1991 through 1994.
�3. Establish Wild and CaDtive Broodstocks. Due to the expense of maintaining native Colorado
fish in National Fish Hatcheries in Wyoming and Montana. and the limited use of these fish
outside of Rocky Mountain National Park. the decision was made to abandon these stocks as soon
as they could be replicated within Colorado. Activities at these hatcheries were funded by the FS
and BLM, while their function was transferred to the CDOW Experimental Hatcher~’. Ft. Collins,
Colorado.
Eggs were collected from Hunters Creek, Upper Hutcheson Lake. Bear Lake and the Poudre River
in 1989, from Upper Hutcheson Lake in 1990, and the South Fork of the Poudre in 1992 to begin
a new CDOW South Platte broodstock at Ft. Collins. Eggs were taken from the 1989 year class in
1991, with 447 greenbacks surviving to December 1991. Malachite green could not be used to
control fungus in 1992, and the entire 1989 year class of greenback broodstock was lost.
Attempts were made to start a CDOW Arkansas broodstock at Ft. Collins by collecting eggs from
Cascade Creek in 1991. However, the Cascade Creek egg collection was not successful. In 1992,
3,200 eggs were collected from South Apache Creek. In addition to South Apache Creek eggs,
10,000 eggs were shipped from the Saratoga NFH to Ft. Collins in August 1992. These two
groups of eggs led to the successful establishment of an Arkansas River drainage greenback
broodstock. Due to problems associated with construction at the Saratoga NFH in 1992, the
majority of their adult Arkansas greenback broodstock was lost, and the Saratoga program was
terminated by September 1992.
4. Resnonse to An~linQ. Within Arapaho/Roosevelt National Forest, catch-and- release fishing for
South Platte greenbacks opened in Sheep Creek, Cornelius Creek and George Creek. Within
Rocky Mountain National Park, Odessa Lake. Lawn Lake, Roaring River, Big Crystal, Lost Lake,
North Fork Big Thompson River, Lower Hutcheson Lake, Pear Lake, Sandbeach Lake and Cone)’
Creek opened to catch-and-release angling by 1990. Spruce and Loomis Lakes opened to catchand-release angling by 1993.
Catch-and-release fishing for Arkansas River greenbacks is allowed on Ft. Carson, and in the Pike
National Forest at Virginia Lake, Timberline Lake, Zac Bog, Lake Fork Creek, Rainbow Lake,
Native Lake, Swamp Lakes and Rock Creek above the Leadville NFH by 1991.
5. Imnrove I&E Programs. The team increased its involvement with conservation groups,
particularly Colorado Trout Unlimited (CTU). The CTh partnership resulted in increased
educational opportunities due to CTh publications and chapter meetings, and a funding
partnership for the greenback restoration work above the Leadville NFH. Work was also initiated
with school groups and Colorado Trout Unlimited by 1991, to make the greenback the Colorado
State Fish. In 1994, the greenback replaced the non-native rainbow trout as the official Colorado
State Fish.
6. Lon2 Ran2e Mana2ement Plan. To be completed upon delisting of the subspecies.
‘~-
62
~
-
�
https://cpw.cvlcollections.org/files/original/e815eab05cb92bbefe5990258e848d22.pdf
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PDF Text
Text
Herpetological
Review
Gape Width: An Alternative to Snout–Vent
Length for Characterizing Anuran Size
KEVIN B. ROGERS
Aquatic Research Group, Colorado Division of Wildlife
P.O. Box 775777, Steamboat Springs, Colorado 80477, USA
e-mail: kevin.rogers@state.co.us
�Herpetological Review, 2009, 40(4), 416–418.
© 2009 by Society for the Study of Amphibians and Reptiles
Gape Width: An Alternative to Snout–Vent
Length for Characterizing Anuran Size
KEVIN B. ROGERS
Aquatic Research Group, Colorado Division of Wildlife
P.O. Box 775777, Steamboat Springs, Colorado 80477, USA
e-mail: kevin.rogers@state.co.us
Snout–vent length (SVL) is the most frequently used metric
to describe the size of anurans captured in the field (Hammerson
1999; Stebbins 2003). In addition to taxonomy and systematics,
SVL has been commonly used in a wide variety of studies including
those on age (e.g., Kellner and Green 1995; Schroeder and Baskett
1968), growth (e.g., Quinn and Mengden 1984; Ritke et al. 1991),
demography (e.g., Miller 1977; Van Gelder and Rijsdijk 1987),
fecundity (e.g., Quinn and Mengden 1984; Reading 1986; Tejedo
1992), mate selection (e.g., Arak 1988; Marco et al. 1998; Olson
et al. 1986; Reading 1991), and locomotion (e.g., Daugherty and
Sheldon 1982; Navas et al. 1999). Despite the pervasive use of
SVL, little has been published on the precision and accuracy of
this metric (Blouin-Demers 2003). Users may have recognized the
limitations of SVL, but continued to acquire this metric presumably
because of its ease of use and lack of a robust alternative. Measuring mass has become increasingly popular as a metric to describe
size (Alvarez and Nicieza 2002; Carey 1978), but its properties
have also not been well studied and can be more difficult to obtain
in the field. Inadequacies in SVL are a direct result of the inherent
malleability in the anurans being studied, as amphibian vertebral
columns are somewhat flexible (Fellers et al. 1994). Unlike fish
where measurements between researchers on the same individual
yield functionally equivalent results (Anderson and Neumann
1996), measurements on frogs appear to be highly variable (K.
Rogers, personal observation). Perhaps measurement of more rigid
structures that are still clearly defined and easy to isolate would
provide more consistent results. This study seeks to quantify variation in SVL measurement as well as that in some alternative metrics
expected to be more reproducible between researchers.
Methods.—This study examined 100 animals representing three
different year classes from nine lots of the Boreal Toad (Anaxyrus
boreas boreas) brood stock housed at the Colorado Division of
Wildlife’s Native Aquatic Species Restoration Facility (NASRF)
in Alamosa, Colorado. Husbandry practices at NASRF sought to
emulate conditions found in the wild where possible and generally
followed Scherf-Norris et al. (2002). Brood stock was reared in
captivity from eggs collected in the wild. Animals were maintained
on a normal circadian pattern with photoperiod matching ambient
conditions. Tanks were maintained at a minimum temperature of
20°C, ranging up to 26°C on hot summer afternoons, with a UVA
basking light available in each tank. Boreal Toads were fed 3-week
old crickets powdered with nutrient supplements (Scherf-Norris
et al. 2002) and hibernated from October 1 through May 1 at
5°C in four environmental chambers subdivided into hibernacula
that could house up to five individuals each (Scherf-Norris et al.
2002).
Metrics used in this study were obtained by passing animals
416
FIG. 1. Gape width measurements were taken with a digital caliper
from the corners of each Boreal Toad’s mouth.
down an assembly line of six biologists who each measured the
SVL, length of the tibiofibula (TF), width of the gape (GW; Fig.
1), and mass for every toad. Lengths were measured in mm with
digital calipers, while mass (g) was obtained with digital balances
tared before each measurement. An ANOVA was used to evaluate
differences between readers. The coefficient of variation (CV)
between readers for each Boreal Toad was also calculated, and a
mean CV for all 100 toads for each body metric was determined.
Differences between mean CVs were also evaluated with an
ANOVA followed by Bonferroni’s multiple comparison test with
simultaneous 95% confidence intervals.
Results.—There was considerable variation between readers (P
= 0.029) in the average SVL calculated for all 100 toads measured
(Fig. 2). In fact, measurements varied by as much as 30% of the
calculated mean SVL for a given toad, with a mean of 12% (95%
CI from 11–13%). Significant variation occurred between readers
measuring TF as well (P = 0.035). Differences between biologists
were not evident for GW (P = 0.081) or mass (P > 0.999).
Coefficients of variation were greatest for SVL and TF and least
for mass (Fig. 3). Gape width did provide significantly more precision than SVL and TF, but not mass. As captive Boreal Toads used
in this study were of known age, correlation of the various metrics
with age was possible. Animal age ranged from 16–40 months. All
metrics were positively correlated with age, with highly significant
regressions (P < 0.001). However, mass was least predictive with
an r2 = 0.76. SVL and TF were intermediate, while GW showed
the highest correlation with age (r2 = 0.85; Fig. 4)
Discussion.—Variation in mean SVL measurements was considerable, and potentially a function of how aggressively Boreal
Toads were handled during the measurement process. Body parts
easily isolated for measurement produced consistent results, while
those that required holding the animal in uncomfortable positions
induced movement, and therefore more measurement error. It was
expected that measurements of body parts less flexible than the
anuran vertebral column would be more reproducible between
readers. It was surprising therefore that the TF measurement was
Herpetological Review 40(4), 2009
�no better than SVL for repeatability as the tibiofibula bone is rigid
and should have yielded more consistent results. Perhaps subject
movement induced by the awkward holding position required to
measure TF played a role in the relatively large mean coefficient
of variation seen for this metric (Fig. 3). GW was significantly
less variable between readers. In fact this assessment is probably
conservative, as much of the variation observed was due to contributions from only one of six biologists (Fig. 2). Consistency in
GW measurement was facilitated by mouth corners being well
defined and easily located by most readers. In addition, Boreal
Toads could be held in a comfortable position while acquiring this
FIG. 3. Mean coefficient of variation (CV) calculated from 100 CVs
generated across six biologists for snout–vent length (SVL), tibiofibula
length (TF), gape width (GW), and mass with associated 95% confidence
intervals. Bars sharing the same bold line below the x-axis are not
significantly different (α = 0.05).
dimension; reducing writhing that can complicate measurement of
SVL and TF. This benefit was also conferred to measurement of
mass. It was also not surprising that mass was the most repeatable
measure used in this study, as it is the least subject to interpretation
as implemented here with top-loading digital scales. Mechanical
tube scales commonly used in field surveys might introduce additional measurement variation, but mass will remain a valuable
metric for describing Boreal Toad size.
Perhaps the most useful aspect of measuring the width of
the gape is that in addition to being very repeatable between
measurers, it gave the tightest correlation with age over the
size ranges examined here—a function that mass was not able
to consistently achieve. While condition or plumpness of an
individual can greatly affect the mass of a Boreal Toad, it often
FIG. 2. Average snout–vent length (mm), average tibiofibula length
(mm), average gape width (mm), and average body mass (g) for 100
Boreal Toads measured by each of six biologists (A–F) with associated
standard errors.
FIG. 4. Mean values for gape width (mm) and mass (g) calculated across
biologists as a function of toad age.
Herpetological Review 40(4), 2009
417
�has little to do with age. GW on the other hand is intimately tied to
the animal’s more rigid cranial dimensions. Though others have
documented a poor relationship of SVL or mass to age in sexually
mature amphibians (Halliday and Verrell 1988; Reading 1991;
Wake and Castanet 1995), cranial dimensions in the first several
years of a Boreal Toads life appear to more closely reflect age of
the individual than mass, at least in the captive Boreal Toads used
in this study. Although environmental conditions at NASRF were
matched to ambient conditions, the steady diet furnished to these
captive Boreal Toads might have provided for more consistent
growth than would be realized in the wild. An additional study on
known age wild Boreal Toads would be required to confirm the
tight link between gape width and age in natural populations.
Indeed, for many analyses where only a rough index of size is
required, SVL is probably adequate even with variation between
readers. Certainly some of this variation can be mitigated if the
same biologist acquires all of the readings. However, if precision
is critical to the outcome of the study, or if a metric that is
more closely correlated with age is required, then using GW is
recommended.
Acknowledgments.—My gratitude is extended to J. Logan (B), T.
Banulis (C), J. Eichler (D), T. Jungwirth (E), and C. Fetkavich (F) who
indulged my desire to explore an alternative, and took a day to measure
toad parts along with D. Schnoor for shuttling toads to the assembly
line. The staff at NASRF is thanked for maintaining the population
of adult toads that make this sort of study possible. M. Mahoney
provided a thorough review that greatly improved the manuscript. All
applicable institutional animal care guidelines were followed during the
implementation of this project.
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Herpetological Review 40(4), 2009
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Herpetological
Review
Detecting Batrachochytrium dendrobatidis in the
Wild When Amphibians Are Absent
JOEL G. WIXSON
and
KEVIN B. ROGERS*
Aquatic Research Group, Colorado Division of Wildlife
P.O. Box 775777, Steamboat Springs, Colorado 80477, USA
*Corresponding author; e-mail: kevin.rogers@state.co.us
��Herpetological Review, 2009, 40(3), 313–316.
© 2009 by Society for the Study of Amphibians and Reptiles
Detecting Batrachochytrium dendrobatidis in the
Wild When Amphibians Are Absent
JOEL G. WIXSON
and
KEVIN B. ROGERS*
Aquatic Research Group, Colorado Division of Wildlife
P.O. Box 775777, Steamboat Springs, Colorado 80477, USA
*Corresponding author; e-mail: kevin.rogers@state.co.us
Once common in the southern Rocky Mountains of North
America, sharp declines in Boreal Toad (Anaxyrus boreas boreas)
populations precipitated their listing as a state endangered species
in Colorado, USA (Loeffler 2001) and consideration for listing
under the Endangered Species Act (U.S. Fish and Wildlife Service
2005). The amphibian chytrid fungus (Batrachochytrium dendrobatidis, hereafter Bd) has been implicated in these declines (Livo
2000; Muths et al. 2003; Scherer et al. 2005). Interest in reintroducing A. b. boreas into historical habitats (Loeffler 2001) has spurred
the need to develop a test for the presence of Bd. Reintroduction
efforts are time consuming and costly, and their success may hinge
on the occurrence of Bd at a potential site. As such, it is imperative that disease status be considered when evaluating potential
reintroduction efforts.
Currently our ability to detect Bd at a site relies on resident amphibians being present, yet they are not at many promising potential
reintroduction locations. Since Bd can persist at a location even in
the absence of amphibian species (Longcore et al. 1999; Rowley
et al. 2007; Speare et al. 2001), we suspect that amphibians may
not be the only host, and that infection can be maintained through
other alternate hosts or environmental reservoirs. We hope that
by testing these non-amphibian sources, the Bd status at potential
reintroduction sites can be evaluated. Rowley et al. (2007) did not
detect Bd in retreat sites of rain forest stream frogs, while Lips et
al. (2006) did find Bd DNA on stream boulders but not in filtered
water samples. Others have detected Bd in filtered water samples
(Kirshtein et al. 2007; Walker et al. 2007), but their approaches
do not always perform well in waters carrying high organic loads
that rapidly clog filters (Cossel and Lindquist 2009) or cause PCR
inhibition (Kirshtein et al. 2007). Our initial efforts toward finding
alternative Bd hosts focused on insects, because they are readily
available and chytrid fungi can degrade chitin, a component of
aquatic insect exoskeletons (Johnson and Speare 2003; Powell
1993). These early surveys were unable to confirm the presence of
Bd in samples of Dytiscidae, Coenagrionidae, Hydrophilidae, or
Notonectidae from two ponds known to harbor the fungus (Rogers
et al. 2004). Samples of Corixidae, algae, snails, and clams taken
from a third pond with infected Boreal Chorus Frogs (Pseudacris
maculata) were also negative for Bd DNA (Rogers and Wood
2005). In an effort to establish a more rigorous examination of
potential alternate hosts, we initiated a study to explore the feasibility of using sentinel cages and fish following reports that Bd
could be found on the scales of Fathead Minnows (Pimephales
promelas) that were exposed to Bd in the laboratory (R. Retallick,
pers. comm., GHD, Australia). Feathers and keratin were included
Herpetological Review 40(3), 2009
313
�in this field study as well when others demonstrated the ability to
culture Bd on sterile duck feathers (Johnson and Speare 2005) or
1% keratin agar (Piotrowski 2004) in vitro.
Methods.—Sentinel experiments were conducted in both a midelevation site in the town of Steamboat Springs, Colorado, and a
high elevation site on the Grand Mesa, Colorado after the spring
thaw in 2005 when prevalence of Bd infection was greatest (K.
Rogers, unpubl. data). This occurred in May for the low elevation
site in Steamboat Springs, and in July for the high elevation sites
on the Grand Mesa. Bd presence at both sites was confirmed by
swabbing resident P. maculata following Livo (2004). DNA was
extracted from the samples using a standard spin column protocol.
All sample DNA preparations were assayed for the presence of
the Bd ribosomal RNA Intervening Transcribed Sequence (ITS)
region by 45 cycle single-round PCR amplification (Annis et al.
2004) that was modified for greater specificity and sensitivity at
Pisces Molecular, Boulder, Colorado.
Cages (0.125 m3) were constructed of 4 × 4 cm pine boards
and 3 mm mesh to house sentinel animals. Cages were deployed
in water less than 60 cm deep, and secured to the bottom with
metal stakes. A protective hardware cloth (25 mm mesh) was attached to the outside of each cage to protect them from predators.
Sentinel fish were sampled for Bd at 1, 3, 7, and 14 days following
introduction to the cages, and mortalities were noted. Fish were
swabbed on their right flanks one day after exposure. After 3, 7
and 14 days of exposure, 10 fish of each species from each pen
were euthanized with MS-222, then swabbed, scraped, and fin
clipped. A cotton swab (Puritan cotton-tipped applicators, VWR
International, West Chester, Pennsylvania), was stroked 20 times
unidirectionally across the left flank of each sentinel fish, then
preserved in 70% ethanol (Livo et al. 2004) for subsequent PCR
screening. The skin scrapes followed a similar protocol but used
a sharpened wooden dowel (Livo 2004). Paired and caudal fins
were removed and preserved in 70% ethanol.
In addition to sampling sentinel fish, six mallard (Anas platyrhynchos) flank feathers were taped together at the stalk and suspended
in the surface film with a string attached to the outside of the cage.
A feather was collected on each sampling day by clipping the exposed end of the feather and placing the complete piece in a 2-mL
microcentrifuge tube containing 70% ethanol, then processed with
the same PCR procedure.
The first study was conducted in a small temporary springflooded pond (Trafalger Pond) next to the Yampa River within
the city limits of Steamboats Springs, Colorado (2051 m elev.;
40.47445°N, 106.83017°W). Skin swabs from 20 resident adult P.
maculata collected during the breeding season suggest this pond
has harbored Bd since at least 2004 (30% prevalence, K. Rogers,
unpubl. data). Thirty Rainbow Trout (Oncorhynchus mykiss), 30
P. promelas, and 30 Goldfish (Carassius auratus) were used as
sentinel fish in each of four cages spread throughout the pond, in
addition to six Mallard flank feathers suspended outside of each
cage.
The second study was conducted in the Kannah Creek drainage
on the Grand Mesa near Grand Junction, Colorado (3268 m elev.;
39.04420°N, 108.02992°W). Dozens of small ponds in this drainage are home to robust populations of P. maculata. Ponds with
perennial water also support Tiger Salamanders (Ambystoma tigrinum). Bd was first detected in this drainage in 2003 in P. maculata
314
collected from a 1.0 ha pond (Pond 4) used in this study (Rogers
and Banulis 2004). One cage with 30 P. promelas was deployed in
each of two additional 0.5 ha ponds, hereafter referred to as Lands
End and Cow Camp. Pond 4 received two cages, each with 30 P.
promelas. Six Mallard flank feathers were installed outside of each
of the four cages. In addition, we explored baiting Bd with pure
keratin (VWR International, West Chester, Pennsylvania). Keratin
tea bags were constructed from paper coffee filters, cut in half
and sewed together. Five bags were fastened to each cage with 3
g of keratin per bag. A bag was removed from each cage on every
sampling occasion, and a portion of the contents preserved in 70%
ethanol. Skin swabs from 20 adult P. maculata were collected from
each of these three ponds the day after this 14-day experiment to
evaluate the prevalence of Bd in 2005.
Results.—In an effort to reduce assay costs in the first study, only
the feathers collected at 1, 3, 7, and 14 days following exposure
along with fish skin swabs collected one day following exposure
on O. mykiss and three days following exposure on P. promelas
and C. auratus were submitted for analysis. None of these 16
feather samples or 120 fish samples suggested that Bd was present.
Because the ability to use sentinel organisms at this site did not
appear promising and processing samples was costly, the remaining samples were archived.
In the second study, despite a substantial number of Bd-positive
samples from the P. maculata collected at the end of our experiment
(prevalence of Bd ranging from 25–30% in all three ponds), only
six of 350 fish swab, scrape, and fin samples were Bd positive.
These included five swabs collected one day after exposure on P.
promelas in Cow Camp and a single swab from Lands End, also
collected one day after exposure that returned a very weak positive
signal. None of the fish swabs, scrapes, or fin clips collected 3, 7,
or 14 days after exposure yielded positive results. Feathers and raw
keratin were equally ineffective, as all 32 samples failed to register
any evidence of Bd over the course of the experiment.
Discussion.—Caged fish, feathers, and keratin were ineffective at sampling Bd in ponds known to have amphibians with the
disease. Although swabbing the flanks of P. promelas exposed for
one day in a Bd-positive environment yielded Bd-positive results,
fish sampling was clearly much less sensitive than sampling P.
maculata in the same environment. The fact that the majority of
the positive results came from the single cage at Cow Camp, and
that positives were found after only one day of exposure but not
after a week or two weeks makes the use of P. promelas as sentinel organisms problematic. Rather than Bd actually infecting the
host, this suggests that the cage was fortuitously deployed in an
area with Bd zoospores, and that they simply adhered to the fish
when sampled on that first day. Chytrid spores have a short-lived
free-swimming stage that only lasts about 24 hrs before encysting
(Piotrowski et al. 2004). Even with this 24 hr active period the
spore can only swim 2 cm (Piotrowski et al. 2004). Thus we may
have simply been lucky in our placement of the Cow Camp cage
in particular. There does not appear to be any particular affinity by
the zoospores toward P. promelas, as subsequent samples revealed
no indication of Bd presence. Given the inconsistent nature of the
results, it is doubtful that using sentinel P. promelas would be a
viable approach for screening potential amphibian reintroduction
sites for the presence of the fungus. Although sentinel fish have
been used to test for pathogens like whirling disease (Koel et al.
Herpetological Review 40(3), 2009
�2006; Thompson et al. 1999), the construction and deployment of
cages remains labor intensive, particularly in sites that are difficult
to access. This is an additional consideration, given the apparently
low sensitivity of P. promelas as a sentinel to detect Bd.
Because the majority of positive samples came from the same
cage on the same day, contamination of the samples is a concern.
The frog samples used to confirm the presence of the fungus were
collected following the experiment, and stored in a different location making them an unlikely source of contamination. Using
latex gloves between samples, and sterilizing equipment with an
open flame further minimized contamination risk. Contamination
occurring in the original source stock of P. promelas was also
ruled out, as most positive signals came from a single cage, and
only early in the study. Samples collected after 3, 7, and 14 days
were all Bd-negative.
Given that others have been successful growing chytrid fungi on
a 1% keratin agar (Piotrowski et al. 2004) or on feathers (Johnson
and Speare 2005) in vitro, we were surprised that none of the
keratin or feather samples yielded a positive PCR result. It was
suggested that perhaps the Bd fungus did not colonize the interior
of the keratin bags, but rather just the outside, which was not
sampled. Subsequent tests using agar-impregnated swabs rolled
in raw keratin however also failed to bait in Bd following three
days of exposure (K. Rogers, unpubl. data).
If Bd has a patchy distribution in a pond environment, it would
be difficult to sample with fixed organisms or objects. A more
effective approach would be to release amphibians targeted for a
reintroduction effort, then subsequently collecting survivors the
following year to sample for Bd. Using a non-tethered organism
allows the target to move through the environment as it would following a repatriation effort, encountering pathogens along the way.
Repatriation efforts require the ability to produce large numbers of
offspring for subsequent release; a portion of this captive production could be used to assay potential field sites for Bd. If a captive
broodstock is not available, fertilized eggs could be secured from
the wild, washed to minimize risk of Bd transfer, then raised to the
larval stage for release (Rogers and Banulis 2004). This approach
requires that target amphibians be produced during pilot studies
prior to implementing full repatriation efforts to determine the
suitability of potential translocation sites.
Acknowledgments.—Our gratitude is extended to C. Slubowski who
shepherded the sentinel cages on the Grand Mesa and helped collect
samples. F. B. Wright III is thanked for assisting with sample collection
and providing many helpful ideas. We also appreciate the time of G. and
J. Wixson who supplied the necessary tools and advice in building the
cages. Substantial improvements to the manuscript were provided by D.
Olson, J. Rowley, and an anonymous reviewer. All applicable institutional
animal care guidelines were followed during the implementation of this
project.
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Herpetological Review 40(3), 2009
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American Fisheries Society Symposium 9:49-64. 1991
Interactions of Zooplankton, Mysis relicta, and Kokanees in
Lake Granby, Colorado
PATRICK J. MARTINEZ
Colorado Division of Wildlife, 317 West Prospect, Fort Collins, Colorado 80526. USA
ERIC P. BERGERSEN
U.S. Fish and Wildlife Service. Colorado Cooperative Fish and Wildlife Research Unit'
Room 201 Wagar Building, Colorado State University. Fort Collins, Colorado 80523, USA
Abstract. In studies of zooplankton and kokanees Oncorhynchus nerka in Lake Granby,
Colorado, conducted from 1981 to 1983, we investigated the suspected role of introduced Mysis
relicta in the decline of the kokanee sport fishery and egg take. Mysis relicta entered surface waters
at night and preyed on zooplankton, except when summer temperatures above 14°C excluded it
from the epilimnion and created a temporary refuge for cladocerans. We attributed the disappearance of hypolimnetic Daphnia longiremis to predation by mysids, and the virtual elimination of
Daphnia pulex (once the preferred item in the kokanee diet) to the effects of intense selective
predation by abundant M. relicta and to kokanee overstocking. Daphnia galeata mendotae,
historically the most abundant daphnid, has replaced D. pulex as the principal item in the kokanee
diet. Premysid populations of Daphnia spp. appeared by late May and peaked by late July, whereas
postmysid populations appeared in late June and peaked in late August or early September. Mysis
relicta appeared more frequently in stomachs of large kokanees ( 21)0 mm in total length) and
sometimes contributed substantially to the biomass of the kokanee diet. However, actual numbers
of mysids and their frequency of occurrence in individual kokanee stomachs remained low. The
disappearance or persistence of Daphnia spp. in other Colorado waters containing mysids appears
to be explained by thermal conditions. It is clear that the introduced M. relicta has not adequately
substituted for the diminished daphnid populations that were used heavily by planktivorous fishes.
Mysis relicta has been introduced in many
western lakes and reservoirs (Gosho 1975), including 50 in Colorado (Martinez and Bergersen
1989), to enhance forage bases for coldwater fish.
Its establishment in Kootenay Lake, British Columbia (Sparrow et al. 1964), and the subsequent
increased growth of kokanees Oncorhynchus
nerka (Northcote 1972a, 1972b), provided impetus
for further mysid introductions to benefit kokanee
(Rieman and Falter 1981; Leathe and Graham
1982; Brown 1984).
Unfortunately, kokanees have not responded as
positively in other lakes where M. relicta has been
established as they did in Kootenay Lake. The
deleterious effects of introduced mysids on daphnid populations have caused kokanee population
declines in Lake Tahoe, California—Nevada (Morgan et al. 1978), Pend Oreille Lake, Idaho (Rieman and Falter 1981), and Whitefish Lake, Montana (G. Anderson and D. Domrose, Montana
Department of Fish, Wildlife, and Parks, unpublished), and poor kokanee growth in Dillon Reservoir, Colorado (Nelson 1981).
Kokanees in Lake Granby, Colorado, have
supported a major sport fishery and served as the
source of several million eggs annually. In the late
1970s, the numbers of kokanees harvested and
eggs collected declined considerably (Table I).
Sealing and Bennett (1980) attributed the declines
to predation by lake trout Salvelinus namaycush,
reservoir drawdown that reduced survival of kokanee fry, overstocking of kokanees, and the
negative effect of introduced mysids on daphnid
populations.
The loss of all Daphnia spp. in Lake Granby
would be detrimental to the kokanee sport fishery
and to the statewide stocking program dependent
on the lake's kokanees for eggs (Nelson 1981).
The objective of this study was to determine the
interactions of zooplankton, M. relicta, and kokanees in Lake Granby.
Study Area
Lake Granby is 160 km northwest of Denver
near the headwaters of the Colorado River (Figure
I). Constructed in 1949, the impoundment is a
major source of irrigation water for northeastern
Colorado via transmountain water diversion. It
has a surface area of 2,938 hectares, a depth of
61 m, a mean depth of 22.6 m, and 64.4 km of
'The Unit is jointly sponsored by the U.S. Fish and
Wildlife Service, the Colorado Division of Wildlife, and
Colorado State University.
49
�50
MARTINEZ AND BERGERSEN
TABLE 1.-Summary of Lake Granby kokanee fishery statistics, 1975-1987 (Sealing and Bennett 1980; Martinez
and Wiltzius 1991).
Year
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
Total
fishing
hours•
(thousands)
•
Kokanee
Number
stocked°
(millions)
Boat
harvest'
(thousands)
1.4
1.3
1.8
1.7
1.2
1.3
1.1
1.0
1.0
1.0
0.9
0.5
0.5
69
45
43
23
21
228
171
131
151
130
126
141
141
135
137
99
75
16
39
44
24
16
5
3
Spawning
fund
(thousands)
Egg
take'
(millions)
Mean total length
of spawners
(mm)
88
29
30
11
32
33
104
134
154
149
80
37
39
10.1
1.9
5.5
2.4
4.6
6.8
16.4
12.3
10.2
13.0
6.8
4.0
6.1
330
378
399
394
356
295
312
306
304
295
269
274
287
*Includes effort expended by both boat and shore anglers.
°All stocked kokanee were fry until 1981. Larger sizes have been stocked experimentally in recent years.
'Includes all fish species; however, boat anglers caught kokanees primarily.
°Number of mature kokanees estimated to ascend the Colorado River.
'Numbers of kokanee eggs artificially stripped and fertilized at the Colorado River spawn-taking site.
shoreline at maximum elevation of 2,524 m above
mean sea level. It is subject to wide surface-level
fluctuation and can be drawn down as much as
28.7 m (Timm and Seeley 1970). In past investigations, the reservoir has been classified as oligotrophic (PHS 1963), oligomesotrophic (Timm
and Seeley 1970), mesoeutrophic (USEPA 1977),
and mesotrophic (Nelson 1982).
Mysis relicta, which was introduced in Lake
Granby in 1971 (Finnell 1977), developed a relatively dense population by 1978 (Nelson 1981).
Five fish species in addition to kokanee are abundant in Lake Granby: rainbow trout Oncorhynchus mykiss, brown trout Salmo trutta, lake trout,
longnose sucker Catostomus catostomus, and
white sucker Catostomus commersoni. Less common species are cutthroat trout Oncothynchus
clarki, brook trout Salvelinus fontinalis, johnny
darter Etheostoma nigrum, and mottled sculpin
Coitus bairdi.
Methods
Crustacean zooplankton was sampled in the
entire water column at a single deep station and
down to 10 m at several shallow stations (Figure
1). Midday samples were collected at monthly
intervals from June to December. In l983, samples were collected only once (deep station on 27
August) to confirm findings of the previous years.
From June to October 1982, diel samples (midday,
dusk, darkness, and dawn) were collected at the
deep station to monitor vertical movements of
zooplankton.
Quantitative collections of zooplankton were
made with an opening-closing Clarke-Bumpus
metered plankton sampler (0.12-mm-aperture netting) towed obliquely through the water column in
nonoverlapping strata of 5, 10, and 20 m. While
being towed, the sampler was opened at the
stratum upper limit, lowered to the stratum lower
limit, and then closed during retrieval at the
stratum upper limit. Qualitative collections also
were made through the ice at the deep station in
January, March, and April 1982 by drawing a
Wisconsin plankton net (0.12-mm-aperture netting) upward through the entire water column.
We periodically monitored the contribution of
daphnids to Lake Granby from surrounding impoundments from June to December 1982 by
collecting samples with a Clarke-Bumpus sampler
held in the current of major inlets near their
confluences with the reservoir.
Diel vertical distributions of M. relicta and
kokanees were recorded with an echo sounder in
1982. Soundings were taken concurrently with our
diel zooplankton sampling at the deep station
from June to September.
The relative abundance of M. relicta in shallow
water (3-7 m) was determined at monthly intervals from June to December 1982. Midday samples were collected at stations 1-6 (Figure 1) with
�51
MYSIDS IN LAKE GRANBY
N
Colorado
Granby -4. River
Pump
Canal
Colorado
Study
7
• Area
( Denver
7Continental
Divide
Willow
Creek-se
Canal
olorado
River
1.0km
1-1
Arapaho
Creek
FIGURE 1.—Lake Granby, Colorado, showing sampling stations. Stations A (deep) and a, b, c, and d (shallow) are
sampling sites for crustacean zooplankton; stations 1-6 are shallow-water sites used for epibenthic trawling for
Mysis relicta. Broken line in inset denotes Continental Divide.
an epibenthic trawl fitted with 0.71-mm-aperture
netting (Gregg 1976).
Kokanees were captured with a large midwater
trawl (mouth 6-m square) towed just after dark in
June, August, and October 1982 and in July,
August, and October 1983, at depths of 10-20 m
(Martinez and Wiltzius 1991). More than 1,400
stomachs were collected for food analyses. Gill
nets were occasionally set overnight to collect
kokanees in 1981 (N = 63) and 1982 (N = 119) for
cursory examination of stomach contents to compare with other food data.
Water temperature and dissolved oxygen were
measured on zooplankton sampling dates at the
deep station in 1981 and 1982. Dissolved oxygen
in water samples taken at 0, 5, 10, 20, 30, 40, and
50 m was measured by the Winkler method.
Mysids were removed from Clarke-Bumpus
samples before the crustacean zooplankton was
counted. Total counts of all species in three 1-mL
aliquots were made in a Sedgwick-Rafter counting chamber. Copepod nauplii were not counted.
In random subsamples, mysids were measured to
the nearest 1.0 mm and zooplankters to the nearest 0.01 mm.
The consumption of zooplankton by mysids
was studied by examining pooled stomach contents of 20-60 adult M. relicta each month from
June to December 1982. Three to five stomachs
were teased open into a Palmer-Maloney counting cell and all zooplankters were identified and
counted. Ingested rotifers appeared to remain
intact; cladocerans and copepods were identified
by specific structures; Bosmina longirostris by the
antennules, Daphnia galeata mendotae by the
postabdominal claw, and Diacyclops bicuspidatus
thomasi2 by the urosome.
Mysids in kokanee stomachs were picked out
and counted. Intact mysids were measured to the
nearest 1.0 mm. An average length of ingested
mysids was determined for estimating dry weight
from a length-weight equation established for M.
2Called Cyclops bicuspidatus thomasi by other authors.
�52
MARTINEZ AND RERGERSEN
relicta in Lake Tahoe by Morgan (1979). After the
mysids were removed, the remaining stomach
contents were pooled, by date, for kokanees in
10-mm-length categories. The number of zooplankters in a pool was estimated by counting all
individuals in three l-mL aliquots in a SedgwickRafter chamber. Average lengths of zooplankters
were used to calculate wet weights from established length—weight equations (Edmondson
1971). Dry weight was estimated by multiplying
wet weights by 0.1 (Rieman and Bowler 1980).
Once the numbers and dry weights of zooplankters were estimated, stomach contents with large
numbers of insects were filtered and dried at 60°C
for 12 h. After these materials were weighed, the
calculated zooplankton dry weight in the dilution
was subtracted from the dried sample weight to
estimate the dry weight of insects in the pooled
samples.
Abundance and Distribution of Zooplankton,
Mysis relicla, and Kokanees
Daphnid Population Changes
Studies conducted by Finnell and Reed (1969)
and Nelson (1971) focused on three daphnids
eaten by fish: Daphnia longiremis, D. pulex, and
D. g. mendotae. Finnell and Reed reported that
the daphnid population, in order of abundance,
was composed of D. g. mendotae, D. pulex, and
D. longiremis. Finnell and Reed (1969) and Nelson (1971) showed that D. longiremis was most
abundant below 10 m, D. pulex was concentrated
above 9-10 m, and D. g. mendotae was concentrated above 10 m. Maximum densities (number
per liter) reported by Nelson (1971) from 1%3 to
1965 were 18.4 for D. g. mendotae, 16.7 for D.
longiremis, and 3.9 for D. pulex.
The composition of the Lake Granby daphnid
community changed after the introduction of M.
relicta. Daphnia longiremis, which formerly appeared in the kokanee diet (Finnell and Reed
1969), was not seen during the current study.
Nelson (1971) suggested that predation on this
species may have been slight because it was small
(0.48-1.26 mm long; modal peaks at 0.61 and 0.81
mm) and concentrated in deep water. Although D.
pulex was extremely rare during our study, it was
once the species most heavily used by kokanees,
composing 85% of all organisms ingested in 1965
and 92% in 1966 (Finnell and Reed 1969).
Seasonal Zooplankton Densities
Daphnia g. mendotae and Bosmina longirostris
essentially composed the cladoceran community
during our study. Both appeared in small numbers
by late June. Although bosminids outnumbered
daphnids in July in 1981 and 1982, daphnids
surpassed bosminids for the rest of the year
(Table 2). Daphnia g. mendotae flourished in all
years of our study and its density peaked from late
August to early September (Martinez 1986).
Daphnia ptdex, which appeared in October and
November 1981 and in October and December
1982, never exceeded a mean density of 0.1/L
(Martinez 1986). L. M. Finnell (Colorado Division
of Wildlife, unpublished report) reported small
numbers of cladocerans and copepods in Lake
Granby in May and indicated that zooplankton
concentrations in the upper strata peaked by late
June or early July. He noted peak cladoceran
numbers in July or August. Nelson (1971) suggested that densities of daphnids were greatest
from late July to early August. Apparently, the
seasonal abundance of daphnids in Lake Granby
shifted after the establishment of mysids, as was
reported for cladocerans in Pend Oreille Lake by
Rieman and Bowler (1980), Rieman and Falter
(1981), and Bowles et al. (1986). These investigators also reported seasonal shifts in abundance of
B. longirostris. Unfortunately, no similar comparisons can be made for Lake Granby because
historical data on bosminid abundance are lacking. The highest daphnid density seen during our
study, in November 1982 (Table 2), may or may
not have reflected typical population dynamics of
D. g. mendotae in Lake Granby; however, it
showed that substantial numbers of daphnids persisted in the presence of an established mysid
population.
The cyclopoid copepod Diacyclops bicuspidaIns thomasi was the most abundant crustacean
zooplankter seen throughout our study (excluding
nauplii), and was present in all collections (Table
2). It was virtually the only crustacean zooplankter in samples collected through the ice (Martinez
1986). The calanoid copepod Diaptomus nudes,
rare throughout our study, appeared to be best
represented from October to December (Martinez
1986).
Temporal and Spatial Distribution
Generally, all species of zooplankton were most
abundant at depths above 10 m. Typically, Daphnia g. mendotae was concentrated above 10 m
with peak densities above 5 m. Nelson (1971)
found this species concentrated above 10-13 m in
other Colorado lakes and reservoirs. The greatest
density of D. g. mendotae observed in the main
lake during our study exceeded 60/L at 0-5 m at
�MYSIDS IN LAKE GRANBY
53
TABLE 2.-Mean midday densities of dominant crustacean zooplankton above 10 m in Lake Granby, 1981 and
1982.
Density (number/L) of
Date
1981
Jun 18
Jul 7
Aug 23
Sep 6
Sep 26
Oct 18
Nov 21
Dec 20
1982
Jun 1-2
Jun 28-29
Jul 27-28
Sep 3-4
Oct 10-11
Nov 14
Dec 4
Number of
samples
alumina
langimstris
Daphnia
galeaia
mendatae
2
2
7
7
7
7
7
5
<0.1
29.5
14.4
10.6
5.4
1.9
3.0
0.5
<0.1
0.8
38.0
31.7
17.3
6.4
18.3
3.6
12
12
12
12
12
12
8
<0.1
1.2
16.4
4.3
1.8
6.0
1.1
<0.1
<0.1
3.1
27.7
14.1
64.9
9.9
the deep station in November 1982. Daphnia
pulex, when present, showed no distinct distribution pattern; however, Finnell and Reed (1969)
and Nelson (1971) found this species occasionally
more abundant at depths of 5-20 m than at 0-5 m.
Diacyclops b. thomasi occurred in all strata and
was the most abundant crustacean below 10 m.
Diaptomus nudus, which rarely exceeded a density of 0.2/L, was most abundant above 20 m
(Martinez 1986).
Diet-stratified sampling in 1982 did not clearly
demonstrate vertical migrations by zooplankton.
Although densities within the same stratum differed among the four diel sampling periods (daylight, dusk, darkness, and dawn), the strata may
not have been narrow enough to define vertical
movements (Martinez 1986). Finnell and Reed
(1969) did not observe diet vertical distribution
trends in Lake Granby daphnids. In nearby Grand
Lake, Pennak (1944) found no vertical migrations
of Diacyclops b. thomasi and only moderate diet
vertical movement (5.8 m) of Daphnia longispina.
Diet movements of M. relicta were clearly
evident. Changes in mysid densities in the water
column were closely correlated with echograms of
mysid distributions (Martinez 1986). Typically,
mysids were near the bottom or in deep water
during daylight and migrated upward at night. At
dawn, they returned to deep water. These downward migrations were rapid. Echograms indicated
that the M. relicta population, pelagic at 10-20 m
before dawn, descended to 40-50 m within 15-20
min. The upward migration at dusk appeared to be
slower, requiring 30-40 min regardless of the
Daphnia
pules
<0.1
<0.1
<0.1
<0.1
<0.1
Diacyclops
bicuspidatus
Ihamast
Diaptomus
audios
34.8
70.7
31.5
24.4
12.1
11.0
68.5
50.4
<0.1
<0.1
<0.1
<0.I
0.1
0.4
<0.1
3.5
9.7
23.2
29.3
19.0
38.5
46.6
<0.1
<0.1
<0.1
0.3
0.6
0.1
vertical distance. These rates were similar to
those reported by Rybock (1978) for ascents (48
m/h) and descents (100 m/h) of M. relicta in Lake
Tahoe.
Finnell and Reed (1969) reported that kokanees
in Lake Granby occupied the upper 9 m by day
and migrated downward at night, when they concentrated between 9 and 18 m. Observations of
kokanee movements during our study differed
slightly. Echograms showed that kokanees were
primarily above 10 m by day but occurred down to
20 m. They began descending at dusk, were
concentrated between 10 and 20 m at night, and
returned into surface waters at dawn (Figure 2).
Crustacean zooplankton appeared to be the
organisms least affected by seasonal changes in
iimnological conditions. However, water circulation during the fall turnover distributed zooplankters (usually concentrated in the upper 10 m)
throughout the water column.
The vertical extent of the diet mysid migration
appeared to be restricted by temperature. Mysis
relicta occurs in cold water, down to -2°C
(Holmquist 1963), and has a strong preference for
waters less than 14°C (Morgan 1979; Pennak
1989). It can withstand temperatures up to 20°C
only through very gradual acclimation (Holmquist
1959; Smith 1970; DeGraeve and Reynolds 1975).
Although M. relicta can endure high temperatures
for short periods, DeGraeve and Reynolds (1975)
demonstrated that mortality increased rapidly at
temperatures above 13°C.
Mysids in Lake Granby did not enter surface
waters when thermal stratification developed and
�54
MARTINEZ AND DERGERSEN
0
10
•
•
• • •
•
•
•
.
•
7
•
•
•
•
KOKANEE
30
l
MYSIS
•
/
>- 20
40-
•
•
•• •
•
• "j/.
./• 1
•
•••
•
. • • •• „
I
50
0
I0
I— 20-
•
•
•
•
Z
— 30-
I
40-
I
Temperature
— —Disolved
Oxygen
50
,
JUN 27
5
10
15
JUL 28
20
0
5
10
15
20
0
5
SEP 3
10
15
0
2.5
5.0
1114/11
20
10.0
TEMPERATURE (°C)
2.5
5.0 • 7.5
10.0
0
2.5
5.0
7.5
10.0
7.5
DISOLVED OXYGEN (mg/ L)
FIGURE 2.—Diurnal and nocturnal echogram depictions of vertical distribution of kokanees and Mysis relicta in
Lake Granby at station A on 27 June, 28 July, and 3 September 1982. Solid line shows temperature profile; dotted
line shows dissolved oxygen profile.
epilimnetic temperatures exceeded 14°C (Figure
3). As the epilimnion thickness increased, the
upward limit of the vertical migration of M. relicta
progressed downward. Beeton (1960) demonstrated not only that light was the most important
factor governing timing of these vertical migrations, but that high epilimnetic temperatures were
important in limiting vertical distribution. When
thermal stratification was pronounced in Lake
Granby during late July to mid-September,
mysids were effectively excluded from the upper
10-11 m of the reservoir. It appeared that most of
the population did not enter the upper water
column where temperatures exceeded I4°C. Similarly, Rieman and Falter (1981) found that M.
relicta in Pend Oreille Lake was seasonally isolated from the upper 10 m of the water column in
August and September by increasing thermal
stratification.
Mysis relicta also requires well-oxygenated wa-
ter and can tolerate conditions of less than 2 mg/L
for only short periods (Juday and Birge 1927;
Brownell 1970; Sandeman and Lasenby 1980).
Despite its ability to reduce oxygen consumption
as ambient temperatures and oxygen concentrations decrease, it remains intolerant of oxygen
below 2-3 mg/L (Sandeman and Lasenby 1980).
Declining ,dissolved oxygen in Lake Granby
during late summer and fall was correlated with
both vertical and horizontal movements of the
mysid population. Hypolimnetic oxygen depletion
began soon after the spring turnover. By late
August or early September, dissolved oxygen
below 40 m fell to less than 2 mg/L and the entire
mysid population was suspended off the bottom
(Figure 2). This avoidance of hypoxic conditions
by mysids was evident in stratified Clarke—Bumpus net collections and in echograms (Martinez
1986). By October, dissolved oxygen concentrations at depths greater than 20 m fell below 2 mg/L
�55
MYSIDS IN LAKE GRANBY
n Kokanee
containing
mysids
JUN 15-17
11+
1+
n=229
w
fr
co
O
20 60 100 140 180 220 260 300 340 380
Length Imml
FIGURE 3.—Kokanee length-frequencies and occurrences of
Mysis relicta in kokanee stomachs in Lake Granby,
1982.
(Martinez 1986). Instead of suspending in the
water column above 20 m, most of the mysid
population moved horizontally in the reservoir.
They were scarce or absent in stratified zooplankton samples (Martinez 1986), absent in pelagic
echogram records, and very abundant in epibenthic
trawl collections taken in water 3-7 m deep (Table
3). Horizontal migrations of mysids from deep to
shallow water in response to low dissolved oxygen in deeper portions of lakes have been documented by other investigators (Tattersal and Tattersal 1951; Holmquist 1959; Lasenby 1971;
Morgan and Threlkeld 1982). In Lake Granby, M.
relicta reappeared in open-water zooplankton
samples below 20 m by late November, after fall
turnover had replenished dissolved oxygen in
deeper waters (Martinez 1986). Lasenby (1971)
reported similar timing for the return of mysids to
the depths of Stony Lake, Ontario, after the fall
turnover. The abundance of M. relicta in inshore
areas appeared to diminish as ice formation began
in December (Table 3).
The persistence of large numbers of mysids in
shallow water at station 1 (Table 3) may be
�MARTINEZ AND BERGERSEN
56
TABLE 3.-Occurrence of Mysis relicta in shallow
water (3-7 m) in Lake Granby in 1982. A = abundant; P
= present; 0 = absent. Stations are shown in Figure 1.
Station
Date
Jun I
Jun 27
Jul 274
Sep 3
Oct 10
Nov 14
Dec 4
A
A
0
A
A
2
3
4
5
6
A
P
A
P
P
0
0
0
A
A
A
Ice
A
A
0
A
A
P
P
0
0
0
0
0
0
A
A
A
A
P
P
0
0
0
0
explained by age composition. Station 1 was in a
large, relatively shallow part of the reservoir
(Figure 1). All mysids collected in epibenthic
trawls in this area during summer were young of
the year. The summer occurrence of predominantly juvenile mysids in deeper water near station 1 was also noted by W. C. Nelson (Colorado
Division of Wildlife, personal communication).
Morgan and Threlkeld (1982) described horizontal
migrations of newly hatched juvenile mysids into
shallow water during summer in Lake Tahoe and
nearby lakes. Juvenile mysids appeared less sensitive to light and temperature (Gosho 1975),
which would explain their tolerance of summer
conditions in shallower waters.
Water temperatures also appeared to influence
the vertical distribution of kokanees. Generally,
kokanees migrated to the lake surface during the
day and to deeper waters at night (Finnell and
Reed 1969). From late July to early September,
when surface water temperatures were highest,
kokanees did not appear to enter the upper few
meters of water in the reservoir during daylight
(Figure 2). Water temperatures at 0-3 m often
exceeded 18°C during this period. This observation of kokanees avoiding near-surface waters
was consistent with Brett's (1971) finding that the
natural occurrence of the anadramous, conspecific sockeye salmon is limited to temperatures at
or below 18°C, despite its ability to tolerate 24°C.
Similarly, Finnell and Reed (1969) found kokanees in Lake Granby to be most abundant at
depths of 4.5-13.5 m during the day from late July
to mid-September. Because kokanees lived in the
upper 20 m of the reservoir, oxygen depletion
probably had no direct effect on their distribution.
Trophic Relations of Zooplankton,
Mysis relicta, and Kokanees
Zooplankton in Mysid Diet
In June and July, rotifers (primarily Kellicottia
longispina and a few Keratella cochlearis) composed the bulk of the zooplankters in the mysid
diet (Table 4). The large rotifer Asplanchna sp.,
which appeared to be abundant in spring and early
summer, was not detected in mysid guts. Either it
was not eaten or we failed to recognize its parts
among other zooplankton fragments. Rybock
(1978) found positive selection for K. longispina
by M. relicta in Lake Tahoe; however, Cooper
and Goldman (1980) and Langeland (1981) showed
that mysids fed on larger prey when available. As
TABLE 4.-Numbers and percentages (in parentheses) of zooplankton prey in pooled stomach contents of Mysis
relicta (10-18 mm long) collected in Lake Granby, 1982.
Date and sample size
Prey type
Jun l•
N 49
Bosmina
longirostris
Jun 2T
N .= 46
Jul 27•
N = 62
Aug 11°
N 35
Sep 3•
N = 28
Oct 116
N = 25
Nov 14°
N = 30
Dec 4°
N= 20
2
(0.5)
143
(23.7)
238
(52.8)
37
(60.7)
12
(21.8)
IS
(26.9)
4
(16.0)
58
(12.9)
21
(34.4)
37
(67.2)
9
(16.0)
'5
(20.0)
32
(57.1)
16
(64.0)
Daphnia
galeata
mendotae
Diacyclops
bicuspidatus
thomasi
27
(4.5)
6
(1.3)
149
(33.0)
Kellicottia
longispina
345
(98.0)
334
(90.8)
424
(70.3)
Keratella
cochlearis
7
(2.0)
32
(8.7)
9
(1.5)
3
(5.5)
3
(4.9)
"Mysis relicta from Clarke-Rumpus collections.
°Mysis relicta from epibenthic trawl collections.
`Mysis relicta from Clarke-Rumpus and epibenthic trawl collections combined.
3
(5.5)
�57
MYSIDS IN LAKE CRANBY '
TABLE 5.-Frequency of occurrence of food items in stomachs of kokanees collected at night with a midwater
trawl in Lake Granby, 1982 and 1983.
Date
1982
Jun 15-17
Aug 11-13
Oct 5-6
1983
Jul 11-12
Aug 23-24
Oct 13
Number (%) of food items
Number of
kokanees
captured
Number of
stomachs
examined
Crustacean
zooplankton"
249
353
326
229
345
322
201 (87.8)
343 (99.4)
294 (91.4)
88 (38.4)
50 (14.5)
276
354
72
273
353
71
264 (96.7)
351 (99.4)
62 (87.3)
250 (91.6)
17 (4.8)
8 (11.3)
Insects°
0
Mysis
relkta
Number (%)
of empty
stomachs
42 (18.3)
172 (49.9)
52 (17.7)
4 (1.7)
12 (4.4)
84 (23.8)
17 (23.9)
2 (0.7)
I (0.2)
5 (7.0)
0
4 (1.2)
"Includes Bosmina longirostris, Daphnia galeata mendotae, Daphnia palm Diacyclops biatspidatus thomasi, and Diaptomus
nudus; however, not all species were consumed on all dates.
b lneludes chironomids (pupae and adults) and hypmenopterans (ants).
cladoceran abundance and their consumption by
mysids increased in August, fewer rotifers were
eaten. Although rotifer densities were not determined, rotifers appeared to be relatively abundant
throughout the open-water season. As cladoceran
numbers diminished in late fall, K. longispina
again became prevalent in the mysid diet (Table
4).
Daphnia spp. and Bosmina spp. are preferred
prey of M. relicta (Lasenby and Langford 1973;
Langeland 1981; Lasenby and Furst 1981), but
daphnids are preferred over other zooplankters
(Grossnickle 1978; Cooper and Goldman 1980).
Bosmina longirostris, appearing before Daphnia
g. mendotae in early summer in Lake Granby,
also appeared earlier in mysid stomachs and continued to be eaten in relatively large numbers for
the rest of the year (Table 4). Even after July,
when daphnids were more numerous at all depths,
mysids in Lake Granby appeared to select B.
longirostris as preferred prey. Daphnia g. mendotae was abundant and was eaten by mysids in
August and September, but it did not compose the
highest percentage of ingested zooplankters until
October. Although B. longirostris and D. g. mendome were most abundant above 10 m, both
occurred in deeper water and were available to M.
relicta even during summer when it was isolated
from surface waters.
Despite its abundance and occurrence at all
depths, few Diacyclops bicuspidatus thomasi appeared in mysid stomachs (Table 4). Lasenby
(1971) found that mysids in Stony Lake also fed
almost exclusively on cladocerans in summer,
even in the presence of abundant copepods.
Lasenby and Fiirst (1981) suggested that mysids
eventually would feed on copepods if cladoceran
numbers remained low. Diaptomus nudus was not
found in mysid guts, perhaps because of its scarcity, although mysids elsewhere have shown low
(Grossnickle 1978) to negative (Rybock 1978) selection for Diaptomus spp.
Kokanee Food Habits
Kokanees in Lake Granby fed on crustacean
zooplankton and insects (chironomid pupae and
larvae and ants). Only a few rotifers and a single
small kokanee were seen in kokanee stomachs.
Crustacean zooplankton (cladocerans and copepods) appeared in 87-99% of the kokanee stomachs examined during all sampling periods (Table
5). The frequency of insect occurrence in kokanee
stomachs ranged widely among the six sampling
dates-from 0 to almost 92%. Mysis relicta occurred in 4-50% of the kokanees. The incidence of
empty stomachs was low, ranging from 0 in July
1982 to 7% in October 1983.
The use of Bosmina longirostris, Diacyclops
bicuspidatus thomasi, and insects by kokanees in
Lake Granby was greatest in spring and early
summer. Relatively few B. longirostris appeared
in kokanee stomachs and (partly because of their
small size) they contributed little to the biomass of
the kokanees' diet (Table 6). Although D. b.
thomasi was eaten by kokanees during all sampling periods, it contributed most to the diet
biomass early in the year (Table 6). In Lake
Chelan, Washington, Brown (1984) reported
heavy, selective use of Bosmina spp. by kokanees. In Pend Oreille Lake, Bosmina spp. was
an important kokanee food during spring and
early summer, but it was little used when cyclopoids were extremely abundant (Rieman and
Bowler 1980). Finnell (unpublished) reported
heavy consumption of copepods and light use of
aquatic and terrestrial insects by Lake Granby
�58
MARTINEZ AND BERGERSEN
TABLE 6.-Numbers and dry weight (mg) of food items in pooled stomach contents of age-0, age-1, and age-2
kokanees collected at night with a midwater trawl in Lake Granby, 1982 and 1983. N is the number of stomachs with
food.
Date
Food
item*
Age 0
Age 1
Weight
Number
1982
Jun 15-17
75)
33
105
89
1
5
138
(N = 70)
191,034
1,356
80
1
3.720
16
14
67
39
262
(N = 217)
449,048
3,188
132
8,381
37
233
1,111
1,114
7.613
267
2
(N = 99)
117.244
3,113
1,278
17
(N = 186)
538.897
5,874
3,750
21
1.865
11,827
1
15
145
(N = IS)
300
1,460
8,423
437
2
3
46
1,926
(N = 235)
2,523
18
2.707
6
135,253
730
1.205
5,311
298
47
(N= 65)
145,810
1,341
1,420
7
3
13
14
89
(N= 18)
3,598
37
130
1,230
26
8
35
(N = 250)
640,880
5,896
3,030
15
27
119
227
1,440
(N = 43)
2,615
27
215
1,860
39
12,518
133
1,051
29
Daphnia
Diacyclops
Mysis
24,526
327
Daphnia
Bosmina
Diacyclops
Insects
Mysis
120
188
2.710
33
Daphnia
Diacyclops
Insects
Mysis
11,795
40
7
Daphnia
Diacyclops
Diaptomus
Insects
Mysis
160
200
2
1
5
4
22
25
(N= 58)
(N = 33)
= 21)
(N = 37)
Aug 23-24
Oct 13
109
1
31
(N
Weight
(N = 65)
605
2
31,241
172
2,995
628
265
1,586
Daphnia
Bosmina
Diacyclops
Insects
Mysis
1983
Jul 11-12
Number
12
384
448
191
5,998
22
Oct 5-6
Age 2
Weight
(N = 85)
4,718
69,873
94
32
Bosmina
Diacyclops
Insects
Mysis
Aug 11-13
Number
5)
43
273
Insects include chironomids (pupae and adults) and hymenopterans (ants).
kokanees in early spring. In contrast, during the
earliest sampling periods in 1982 and 1983, insects
composed the bulk of the biomass ingested by
kokanees of all ages (Table 6). Because of the
comparatively large size of insects, relatively few
made up a large percentage of the diet biomass.
Daphnia g. mendotae was the most used food
of kokanees of all sizes after July, usually outnumbering all other organisms combined. Information on diet obtained from kokanees captured
in gill nets also showed this (Martinez 1986).
Clearly, the species composition of the kokanee
diet has changed since Finnell and Reed (1969)
reported that D. pulex was the most heavily used
and preferred food of Lake Granby kokanees in
the 1960s. Kokanee preference for daphnids is
well documented (Rieman and Bowler 1980;
Leathe and Graham 1982; Vinyard et al. 1982). As
one of the larger crustacean zooplankters in the
reservoir, D. g. mendotae also contributed significantly to the kokanees' diet biomass (Table 6).
The limited use of Daphnia pulex and Diaptomus nudus, the largest limnetic entomostracans,
was probably due to their scarcity. Diaptomus
nudus was absent from all kokanee stomachs
examined except in October 1983, when it appeared in the stomachs of 1- and 2-year-old kokanees (Table 6). Large numbers of Daphnia
pulex were found in the stomachs of 12 kokanees
collected in a gill net on December 4, 1982. The
net was set in the vicinity of zooplankton sampling station A (Figure I). Zooplankton samples
collected nearby at station A on the same day
contained high densities of Daphnia g. mendotae
and very few Daphnia pulex. These observations
corroborate the strong selection for Daphnia
�MYSIDS IN LAKE GRANBY
pulex by kokanees in Lake Granby reported by
Finnell and Reed (1969), even when the density of
this daphnid is very low.
59
predation. Because this cladoceran occurred in
the hypolimnion (Finnell and Reed 1969), it was
available to M. relicta as prey. Threlkeld et al.
(1980) and Morgan et al. (1981) suggested that
Use of Mysids by Kokanees
cladoceran species inhabiting deep water in lakes
Although other food items were seasonally im- typically disappear after mysids are introduced.
Because daphnids were concentrated above 10
portant to kokanees, there was no distinct peak in
m,
they were spatially separated from M. relicta
use of mysids. They appeared in nearly 50% of the
for
nearly 2 months (late July to mid-September).
kokanee stomachs examined in August 1982 (Th.;
This
seasonal exclusion of mysids from surface
ble 6), and some stomachs contained mysids
almost exclusively, but overall, few kokanees fed waters provided a thermal sanctuary for daphon them. Only 29% (N = 896) of the stomachs nids. Threlkeld et al. (1980) and Morgan et al.
examined contained mysids in 1982 and 16% (N = (1981) stressed the importance of thermal refugia
697) in 1983. Rieman and Bowler (1980) found M. in the coexistence of daphnids and mysids, and
recta in 19-23% of the kokanee stomachs exam- they proposed such refugia as the principal mechanism that allows cladocerans to persist in lakes
ined in Pend Oreille Lake in 1977-1978.
Rieman and Bowler (1980) reasoned that the containing natural mysid populations.
Temporal shifts in the development of daphnid
contribution of mysids to the kokanee diet was
populations
have been attributed to intense selecless than such percentages indicated. Mysis
tive
predation
by mysids (Rieman and Falter
relicta typically is not available to kokanees dur1981). A similar pattern was evident in Lake
ing the day (when kokanees often feed). If stomachs for food analysis came from kokanees col- Granby in the spring when mysids inhabited the
lected just after dusk, the samples would tend to entire water column during their vertical migraoverrepresent the actual contribution of mysids to tion and, in the upper strata, preyed selectively on
the daily kokanee ration (Rieman and Bowler daphnids at night, severely depressing numbers of
1980). Because kokanees in Lake Granby feed daphnids and inhibiting population development.
diurnally (Finnell and Reed 1969) and the stom- As the thermal refuge developed in the summer,
achs examined in this study were from kokanees the daphnid population recovered rapidly and
collected just after dusk, the same bias probably attained premysid densities, despite the presence
applies. In the gut samples, M. relicta appeared to of fewer species (Figure 5).
The importance of a thermal refuge in limiting
be the last item ingested, which further supports
mysid
predation on epilimnetic daphnids is further
this contention.
supported
by the scarcity of Daphnia spp. in
As with insects, mysids (because they are large)
Grand
Lake,
Dillon Reservoir, and Lower Twin
contributed substantially to the biomass of the
Lake
(Table
7).
These waters formerly contained
were
kokanee diet, even when comparatively few
ingested. Overall, however, the numbers of in- thriving populations of daphnids and also supgested mysids were low. Individual kokanees ported kokanee fisheries. Because Daphnia spp.
contained up to 176 mysids, but most contained became scarce after M. relicta was established,
only 1-5 (Martinez 1986). There appeared to be a these lakes are no longer managed for kokanees.
trend in Lake Granby toward higher mysid use by The stocking of juvenile rainbow trout has been
larger ( �200 mm) kokanees (Figures 3 and 4). discontinued in Dillon Reservoir because the trout
This trend was reported also for kokanees in Lake was suspected of competing with stunted koTahoe (Morgan et al. 1978) and Pend Oreille Lake kanees for extremely limited cladoceran forage
(Rieman and Bowler 1980). The smallest kokanee (Stuber et al. 1985)—a situation apparently aggrato contain mysids during this study was 87 mm vated by a dense mysid population.
Thermal conditions appear to be the most imlong. Rieman and Bowler (1980) reported M.
portant factor in the coexistence of daphnids and
relicta in kokanees as short as 40-45 mm.
introduced mysids. In Colorado waters, where
low epilimnetic temperatures allow M. relicta to
and
Interactions of Daphnids, Mysids,
enter surface waters almost year-round, daphnids
Kokanees
can be expected to become scarce (Nester 1986).
Daphnids versus Mysids
Although surface temperatures exceed 14°C in
The disappearance of Daphnia longiremis in Grand and Lower Twin lakes (Table 7), subsurLake Granby probably was caused by mysid face water temperatures are lower, and the short-
�60
MARTINEZ AND BERGERSEN
20
n Kokanee
JUL 11-12
0+
1+
II+
containing
mysids
10
n = 273
20
AUG 23-24
0
1+
0+
Y 10
0
II+
n =353
20
OCT 13
0+
1+
10-
n = 71
20
i
610 100 1d0 180 220 260 300 340 1 380
Length imml
F IGURE 4.—Kokanee length-frequencies and occurrences of Mysis relicta in kokanee stomachs in Lake Granby,
1983.
ness of the warmwater period apparently does not
exclude mysids long enough to allow daphnid
populations to develop. In Lake Granby, where
mysids are excluded from surface waters for
nearly 2 months, daphnids persist.
The small numbers of M. relicta in Green
Mountain Reservoir suggest that thermal regimes
also may be important in establishing dense mysid
populations. Green Mountain Reservoir does not
stratify pronouncedly in summer (Table 7); instead, because of the reservoir's low retention
time, water temperatures decrease gradually from
top to bottom (Nelson 1981). Such thermal conditions apparently are not conducive to proliferation
of M. relicta, because most of the reservoir exceeds 14°C during summer. Nelson (1981) suggested that inflow-outflow conditions in Green
Mountain Reservoir did not favor development of
a mysid population. This appears to have held
true in the 15 years following the M. relicta
introduction in the reservoir, where it is now rare
to absent and daphnids remain abundant (Table
7).
Daphnia g. mendotae remained the dominant
�MYSIDS IN LAKE GRANBY
30-
Pre - Mysis
61
D. g. mendotae
D. longiremis
D. putex
20-
0
_a 30-,
E
Post- Mysis
z
Z 2010-
A
M
J
J
A
S
O
N
D
J
FIGURE 5.—Trends in composition and abundance for three species of Daphnia before and after the establishment
of Mysis relicta in Lake Granby.
cladoceran in Lake Granby after mysids fed on
the daphnid population. Rieman and Falter (1981)
wrote that it replaced D. thorata as the dominant
daphnid after M. relicta became established in
Kootenay and Pend Oreille lakes. These investigators suggested that the helmet spikes of D. g..
mendotae gave it a survival advantage over
round-helmeted D. thorata. Because M. relicta
must seize and manipulate larger prey for ingestion (Cooper and Goldman 1980), the helmet
spikes might foil mysid attacks by impeding such
manipulation. This feature alone, which can develop in several Daphnia species including D.
longiremis (Zaret 1980), is not sufficient to avert
mysid predation—as evidenced by the disappearance of the spike-forming species in several Col-
orado lakes. It may, however, preserve greater
numbers of D. g. mendotae, whose populations
can rebound more quickly once mysid predation
is curbed by thermal stratification.
Typically, D. ptdex was concentrated above 10
m in Lake Granby (Finnell and Reed 1969; Nelson
TABLE 7.—Comparison of Mysis relicta introduction dates and current status, mean August temperature profiles,
and current status of daphnid populations in five Colorado lakes.
Species
and
variable
Mysis relicta
Year introduced
Status 1983'
Water temperature MP
Surface
10-m depth
20-m depth
40-m depth
Daphnia spp.
Status 1983'
Lake
Granby
Grand
Lake
Green
Mountain
Reservoir
Dillon
Reservoir
Lower
Twin
Lake
1971
A
1969
A
1974
RA
1970
A
1962
A
18
15
9
8
15
10
7
5
16
16
14
12
14
13
16
13
8
A
RA
A
RA
'A abundant; RA = rare to absent.
°Temperature data for all lakes except Lower Twin Lake are from Nelson (1981).
6
RA
�62
MARTINEZ AND BERGERSEN
1971) and should have received the same sanctuary in warm surface waters enjoyed by D. g.
mendotae. That it did not indicates selective fish
predation was responsible for the suppression of
D. pulex numbers.
Daphnids versus Kokanees
The' virtual elimination of D. pulex in Lake
Granby probably was among the chief causes of
the kokanee fishery's decline. Ironically, the scarcity of D. pulex in 1981-1983 apparently resulted
from intense kokanee predation that followed
kokanee overstocking. Despite its addition to the
reservoir from surrounding impoundments (Martinez 1986), D. pulex has been unable to recolonize the reservoir.
Suppression of particular daphnid species,
however, depends not only on selective removal
of larger members of the population, but on
whether the fish consume both mature and immature forms (Galbraith 1967). If fish feed primarily
on mature daphnids, adequate numbers of reproducing females usually survive to sustain the
population; this tends not to be the case if fish
consume immature as well as mature daphnids
(Galbraith 1967). Obviously, size at maturity becomes an important factor in the capacity of
different daphnid species to withstand fish predation. Daphnia g. mendotae typically matures at
about 1 mm and D. pulex at 2 mm (Zaret 1980). In
Lake Granby, kokanees preyed primarily on D. g.
mendotae longer than 1 mm, whereas most of the
D. pulex in kokanee stomachs were shorter than 2
mm (Martinez 1986). Consistent with Galbraith's
(1967) findings, D. pulex appeared unable to sustain a viable population when faced with intense
predation by kokanees.
This suppression of D. pulex implies that the
rate of kokanee predation on limnetic daphnids
has increased since the kokanee harvest and egg
take went into decline in the late 1970s. At that
time, larger kokanees appeared in fishermen's
creels and in spawning runs. In the early 1980s,
the Lake Granby kokanee fishery was characterized by low harvest of small kokanees and record
numbers of smaller and older spawners (Table 1).
Brown (1984) reported a negative relation between mean size of kokanees and angler catch
rate. This negative relation seemingly developed
in Lake Granby (Martinez and Wiltzius 1991). The
reduced catch rate and harvest meant that thousands of kokanees were not removed by fishermen and remained in the lake. These trends
toward smaller kokanees, lower harvests, and
numerous spawners led to stunting due to over-
stocking (Martinez and Wiltzius 1991). Stunting
undoubtedly increased intraspecific competition
between all age-classes of kokanees that rely on •
the same pelagic foods. It seems reasonable to
presume that this competition intensified predation on all available prey, particularly on preferred items.
Daphnia g. mendotae may have an additional
survival advantage over D. pulex because of its
extreme transparency, which conceivably protects it from sight-feeding kokanees. Transparency in zooplankton is believed to be an effective
adaptation against sight-feeding predators (Kerfoot 1980). Nelson (1971) suggested that D. g.
mendotae may have been protected from fish
predation by its ability to produce small, helmeted
morphs during summer. Both helmeted and unhelmeted forms occurred in Lake Granby during
our study. Possibly transparency and smaller
morphs both contributed to the persistence of D.
g. mendotae by making detection by kokanees
more difficult.
Mysids versus Kokanees
It appears that the decline of the Lake Granby
kokanee fishery can be attributed to changes in
the daphnid populations resulting from the joint
effects of intense selective predation by introduced mysids and overabundant kokanees, particularly kokanees. Although thermal conditions
allow daphnids to persist in the reservoir, the
temporal shift of the daphnid population may
effectively shorten the season of optimum kokanee growth. Kokanees now appear to grow only
during a 2-month period from late August to late
October (W. J. Wiltzius, Colorado Division of
Wildlife, personal communication).
Because kokanee growth is strongly density
dependent (Goodlad et al. 1974; Leathe 1984),
stunting of the kokanee population before Mysis
became established could have been easily corrected by a reduction in stocking rate. However,
the postmysid situation may be more complex. It
does not appear that the inclusion of other zooplankton, insects, or even M. relicta in the kokanee diet has adequately compensated for the
diminished daphnid forage. The reduction in annual growth may mean that the reservoir can no
longer support the kokanee density that produced
exceptional kokanee fishing (Table 1).
Martinez and Wiltzius (1991) noted an increased frequency of occurrence of M. relicta in .
Lake Granby kokanees and rainbow trout in September 1981. Because hypolimnetic oxygen became depleted by August (Martinez 1986), many
�r
MYSIDS IN LAKE GRANBY
mysids may have been trapped between hypoxic
conditions in deeper waters and high temperatures in the epilimnion, which could have increased their availability to the fish.
Despite the trend toward higher use of mysids
by larger kokanees, the consumption of M. relicta
in populations containing more large kokanees
would probably remain low. Simply put, M.
relicta typically is available to kokanees only at
night when the fish cease feeding (Finnell and
Reed 1969; Doble and Eggers 1978). Myth relicta
has not enhanced kokanee growth in Lake Granby
and probably will not benefit kokanees in other
Colorado lakes where it has become established.
Acknowledgments
We thank Wes Nelson, Bill Wiltzius, Jake Bennett, and Clee Sealing of the Colorado Division of
Wildlife for their involvement and cooperation in
this study. We gratefully acknowledge Anita Martinez and Beverly Klein for their assistance in
producing this manuscript.
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MARTINEZ AND BERGERSEN
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tionships between ambient oxygen concentration,
1981. Impact of introduced populations of Mysis
temperature, body weight, and oxygen consumprelicta on zooplankton in oligotrophic subalpine
tion for Mysis relicta (Malacostraca:Mysidacea).
lakes. Internationale Vereinigung fur theoretische
Canadian Journal of Zoology 58:1032-1036.
und angewandte Limnologie Verhandlungen 21:
Sealing, C., and G. Bennett. 1980. Middle Park reser339-345.
voir studies. Final Report. Colorado Division of
Morgan, M. D., and S. T. Threlkeld. 1982. Size depenWildlife, Federal Aid Project F-40-D, Grand Juncdent horizontal migration of Mysis relicta. Hydrotion.
biologia 93:63-68.
Smith, W. E. 1970. Tolerance of Mysis relicta to therMorgan, M. D., S. T. Threlkeld, and C. R. Goldman.
mal shock and light. Transactions of the American
1978. Impact of the introduction of kokanee (OncoFisheries Society 99:418-422.
rhynchus nerka) and opossum shrimp (Mysis
Sparrow,
R. A. H., P. A. Larkin, and R. A. Rutherglen.
relicta) on a subalpine lake. Journal of the Fisheries
1964. Successful introduction of Mysis relicta
Research Board of Canada 35:1572-1579.
Lover! into Kootenay Lake, British Columbia.
Nelson, P. C. 1982. Aquatic macrophytes of Shadow
Journal of the Fisheries Research Board of Canada
Mountain Reservoir, Grand Lake, and Lake
21:1325-1327.
Granby, Colorado. Master's thesis. Colorado State
Stuber, R. J., C. Sealing, and E. P. Bergersen. 1985.
University, Fort Collins.
Rainbow trout returns from fingerling plantings in
Nelson, W. C. 1971. Comparative limnology of ColoDillon Reservoir, Colorado, 1975-1979. North
rado-Big Thompson Project reservoirs and lakes.
American Journal of Fisheries Management 5:471Final Report. Colorado Division of Wildlife, Fort
474.
Collins.
Tattersall, W. M., and 0. S. Tattersall. 1951. The BritNelson, W. C. 1981. Large lake and reservoir limnologish Mysidacea. Ray Society, London.
ical studies. Pages 6-8 in 0. B. Cope, editor. Colorado Fisheries Research Review 1978-1980. Colo- Threlkeld, S. T., J. T. Rybock, M. D. Morgan, C. L.
Folt, and C. R. Goldman. 1980. The effects of an
rado Division of Wildlife, Fort Collins.
introduced invertebrate predator and food resource
Nesler, T. P. 1986. Mysis-gamefish studies. Job Progvariation on zooplankton dynamics in an ultraoligress Report. Colorado Division of Wildlife, Federal
otrophic lake. Pages 555-568 in W. C. Kerfoot,
Aid in Fish and Wildlife' Restoration, Project
editor. Evolution and ecology of zooplankton comF-83-R, Fort Collins.
munities. University Press of New England, HanNorthcote, T. G. 1972a. Kootenay Lake: man's effects
over, New Hampshire.
on the salmonid community. Journal of the FisherTimm, C. M., and C. M. Seeley. 1970. A survey of
ies Research Board of Canada 29:861-865.
water quality conditions in Grand Lake, Shadow
Northcote, T. G. I972b. Some effects of mysid introMountain Lake, and Lake Granby, and their tribuduction and nutrient enrichment on a large oligtaries. U.S. Department of the Interior, Federal
otrophic lake and its salmonids. Internationale
Water Quality Administration, Pacific Southwest
Vereinigung fOr theoretische und angewandte LimRegion, San Francisco.
nologie Verhandlungen 18:1096-1106.
USEPA (U.S. Environmental Protection Agency). 1977.
Pennak, R. W. 1944. Diurnal movements of zooplankWater quality study-Grand Lake, Shadow Mounton organisms in some Colorado mountain lakes.
tain Lake, Lake Granby, Colorado, 1974. USEPA,
Ecology 25:387-403.
EPA-908/2-77-002, Denver.
Pennak, R. W. 1989. Fresh-water invertebrates of the
Vinyard, G. L., R. W. Drenner, and D. A. Hanzel.
United States, 3rd edition. Wiley, New York.
1982. Feeding success of hatchery-reared kokanee
PHS (Public Health Service). 1963. Physical and chemsalmon when presented with zooplankton prey.
ical stratification in two high altitude reservoirs of
Progressive Fish-Culturist 44:37-39.
the Colorado River Basin. U.S. Department of
Zaret, T. M. 1980. Predation and freshwater communiHealth, Education and Welfare, Public Health Serties. Yale University Press, New Haven, Connectvice, Denver.
icut.
Rieman, B. E., and B. Bowler. 1980. Trophic ecology of
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8b1829b40a2c057d0b36c8e665b46778
PDF Text
Text
Jesse M. Lepak, Ph. D.
Colorado Parks and Wildlife
317 West Prospect Rd. Fort Collins, CO 80526
Phone: (970) 472-4432
Email: Jesse.Lepak@state.co.us
Education
2008
Ph.D., Cornell University, Natural Resources. Fishery science, resource
policy and management, and cellular and molecular medicine concentrations.
(Advisor: C. Kraft, Committee: P. Bowser, E. Cooch, B. Knuth, L. Rudstam)
2004
M.S., Cornell University, Natural Resources.
(Advisor: C. Kraft, Committee: E. Cooch, N. Hairston, Jr.)
2001
B.S., University of Wisconsin-Madison, Biology, Zoology, and Biological
Aspects of Conservation. (Mentor: J. Kitchell)
Appointments
2023 - present
Aquatic Research Scientist IV, Colorado Parks and Wildlife.
(Supervisors: G. Schisler)
2022 - 2023
Research Associate, Colorado State University Cooperative Fish
and Wildlife Research Unit (Supervisor: D. Winkelman)
2021 - 2022
Aquatic Research Section Technician, Colorado Parks and Wildlife
(Supervisors: A. Hansen and G. Schisler)
2017 - 2020
Great Lakes Fisheries and Ecosystem Health Specialist, New York
Sea Grant (Supervisor: M. Austerman)
2016 - present
Adjunct Biologist, Biodiversity Research Inst (Director: Dr. D. Evers)
2010 - 2015
Aquatic Research Scientist IV, Colorado Parks and Wildlife.
(Supervisors: M. Jones and G. Schisler)
2011 - 2016
Affiliate Faculty Member, Department of Fish, Wildlife, and
Conservation Biology, Colorado State University. (Department
Head: K. Wilson)
2008 - 2010
Postdoctoral Researcher, Department of Fish, Wildlife, and
Conservation Biology, Colorado State Univ. (Advisor: B. Johnson)
2004 - 2008
Graduate Research Assistant (Ph.D.), Natural Resources, Cornell
University. (Advisor: C. Kraft)
2001 - 2004
Graduate Research Assistant (M.S.), Natural Resources, Cornell
University. (Advisor: C. Kraft)
2001
Research Assistant, Cornell, Natural Resources, Adirondack
Fishery Research Program (Advisor: C. Kraft)
Page 1 of 26
�Refereed publications
In press: Lepak, J.M., Hansen, A.G., Johnson, B.M., Battige, K., Cristan, E.T.,
Farrell, C.J., Pate, W.M., Rogers, K.B., Treble, A.J., and Walsworth, T.E. Four
decades of change: cyclical multi-trophic level responses to an introduced forage
fish. Fisheries.
2024
1)
Lepak, J.M., Pate, W.M., Cadmus, P., Hansen, A.G., Gallaher, K.D., Silver, D.B.
Response of an invasive aquatic crustacean to the fish toxicant rotenone. Lake
and Reservoir Management. 40(3):330-337.
2)
Hansen, A.G., Lepak, J.M., Gardunio, E.I., Eyre, T. 2024. Evaluating harvest
incentives for suppressing a socially-valued, but ecologically-detrimental, invasive
fish predator. Fisheries Management and Ecology.
https://doi.org/10.1111/fme.12699
2023
3)
Lepak, J.M., Hansen, A.G., Cristan, E., Williams, D., Pate, W.M. 2023. Rainbow
smelt (Osmerus Mordad) influence on walleye (Sander vitreus) recruitment
decline: mtDNA evidence supporting the predation hypothesis. Journal of Fish
Biology. https://doi.org/10.1111/jfb.15523.
4)
Lepak, J.M., Johnson, B.M., Hooten, M.B., Wolff, A., and Hansen, A.G. 2023.
Predicting Sport Fish Mercury Contamination in Heavily Managed Reservoirs:
Implications for Human and Ecological Health. PLoS ONE. 18(8): e0285890.
https://doi.org/10.1371/journal.pone.0285890.
5)
Hansen, A.G., Miller, M.W., Cristan, E.T., Farrell, C.J., Winkle, P., Brandt, M.,
Battige, K., and Lepak, J.M. 2023. Gill net catchability of walleye (Sander vitreus):
are provincial standards suitable for estimating adult density outside the region?
Fisheries Research. 266: 106800. https://doi.org/10.1016/j.fishres.2023.106800
2022
6)
Hansen, A.H., Cristan, E.T., Moll, M.M., Miller, M.W., Gardunio, E.I., and Lepak,
J.M. 2022. Factors influencing early growth of juvenile tiger trout stocked into
subalpine lakes as biocontrol and to enhance recreational angling. Fishes. 7:342.
DOI: 10.3390/fishes7060342.
7)
Cristan, E.T., Hansen, A.G., and Lepak, J.M. 2022. Effects of ethanol
preservation on larval and fingerling walleye and gizzard shad body size. North
Page 2 of 26
�American Journal of Fisheries Management. 42:874-881. DOI:
10.1002/nafm.10773.
8)
Lepak, J.M., Hansen, A.G., Hooten, M.B., Brauch, D., and Vigil, E.M. 2022. Rapid
proliferation of the parasitic copepod, Salmincola californiensis (Dana), on
kokanee salmon, Oncorhynchus nerka (Walbaum), in a large Colorado reservoir.
Journal of Fish Diseases. 45:89-98.
2021
9)
Adams. J.V., Birceanu, O., Chadderton, W.L., Jones, M.L., Lepak, J.M.,
Selheimer, T.S., Steeves, T.B, Sullivan, W.P., and Wingfield, J. 2021. Trade-offs
between suppression and eradication of sea lampreys from the Great Lakes.
Journal of Great Lakes Research. 47(Suppl. 1):S782-S795.
2005-2020
10) Anders, K., Sethi, S.A., Duskey, E., Lepak, J.M., Rice, A., Estabrook, B., K.
Fitzpatrick., George, E., Mary-Quay, B., Paufve, M., Perkins, K., and Scofield, A.,
2020. Seasonal habitat use indicates depth may mediate the potential for trophic
impacts of invasive round goby in inland lakes. Freshwater Biology. 65:13371347.
11) Taylor, M.S., Driscoll, C.T., Lepak, J.M., Josephson, D.C., Jirka, K.J., and Kraft,
C.E. 2020. Temporal trends in fish mercury concentrations in an Adirondack Lake
managed with a continual predator removal program. Ecotoxicology.
https://doi.org/10.1007/s10646-019-02156-5.
12) Wolff, B.A., Johnson, B.M., and Lepak, J.M. 2017. Changes in sport fish mercury
concentrations from food web shifts suggest partial decoupling from mercury
loading in two Colorado reservoirs. Archives of Environmental Contamination and
Toxicology. 72:167-177.
13) Kopack, C., Broder, E.D., Fetherman, E.R., Lepak, J.M., and Angeloni, L.M.
2016. The effect of a single pre-release exposure to conspecific alarm cue on
post-stocking survival of three strains of rainbow trout (Oncorhynchus mykiss).
Canadian Journal of Zoology. 94:661-664.
14) Lepak, J.M., Hooten, M.B., Eagles-Smith, C.A., Tate, M.T., Lutz, M.A., Ackerman,
J.T., Willacker, J.J. Jr., Evers, D.C., Wiener, J.G., Flanagan Pritz, C., and Davis,
J. 2016. Assessing potential health risks to fish and humans using mercury
concentrations in inland fish from across western Canada and the United States.
Science of the Total Environment. 571:342-354.
Page 3 of 26
�15) Eagles-Smith, C.A., Ackerman, J.T., Willacker, J.J., Tate, M.T., Lutz, M.A., Fleck,
J., Stewart, A.R., Wiener, J.G., Evers, D.C., Lepak, J.M., Davis, J., and Flanagan
Pritz, C. 2016. Spatial and temporal patterns of mercury concentrations in
freshwater fishes across the Western US and Canada. Science of the Total
Environment. 568:1171-1184.
16) Eagles-Smith, C.A., Wiener, J.G., Eckley, C, Willacker, J.J., Evers, D.C., MarvinDiPasquale, M., Obrist, D., Fleck, J., Aiken, G., Lepak, J.M., Jackson, A.K.,
Webster, J., Stewart, A.R., Davis, J., Alpers, C., and Ackerman, J.T. 2016.
Mercury in western North America: a synthesis of environmental contamination,
fluxes, bioaccumulation and risk to fish and wildlife. Science of the Total
Environment. 568:1213-1226.
17) Jackson, A., Evers, D.C., Eagles-Smith, C.A., Ackerman, J.T., Willacker, J.J.,
Elliott, J.T., Lepak, J.M., VanderPol, S.S., and Bryan, C.E. 2016. Mercury risk to
avian piscivores across the western United States and Canada. Science of the
Total Environment. 568:685-696.
18) Willacker, J.J., Eagles-Smith, C.A., Lutz, M.A., Tate, M.T., Ackerman, J.T, and
Lepak, J.M. 2016. The influence of reservoirs and their water management on
fish mercury concentrations in Western North America. Science of the Total
Environment. 568:739-748.
19) Vigil, E., Christianson, K., Lepak, J.M., and Williams, P. 2016. Temperature
effects on hatching and viability of juvenile gill lice; Salmincola californiensis.
Journal of Fish Diseases. 39:899-905.
20) Fetherman, E.R., Lepak, J.M., Brown, B., and Harris, D.J. 2015. Optimizing
triploid Walleye production using pressure shock treatment. North American
Journal of Aquaculture. 77:471-477.
21) Kopack, C., Broder, E.D., Lepak, J.M., Fetherman, E.R., and Angeloni, L.M.
2015. Behavioral responses of a highly domesticated, predator naïve rainbow
trout to chemical cues of predation. Fisheries Research. 169:1-7.
22) Johnson, B.M., Lepak, J.M., and Wolff, B.A. 2015. Effects of prey assemblage on
mercury bioaccumulation in a piscivorous sport fish. Science of the Total
Environment. 506-507:330-337.
23) Hargis, L.N., Lepak, J.M., Vigil, E.M., and Gunn, C. 2014. Prevalence and
intensity of the parasitic copepod (Salmincola californiensis) on kokanee salmon
(Oncorhynchus nerka) in a Colorado reservoir. SW Naturalist. 59:126-129.
24) Pate, W.M., Johnson, B.M., Lepak, J.M., and Brauch, D. 2014. Management for
coexistence of Kokanee and trophy Lake Trout in a montane reservoir. North
American Journal of Fisheries Management. 34:908-922.
Page 4 of 26
�25) Lepak, J.M., Cathcart, C.N., and Stacy, W.L. 2014. Tiger muskellunge predation
upon stocked sport fish intended for recreational fisheries. Lake and Reservoir
Management. 30:250-257.
26) Fetherman, E.R., and Lepak, J.M. 2013. Back-calculation of capture probability
and estimating gear efficiency using known population abundances. Fisheries
Research. 147:284-289.
27) Lepak, J.M., Kraft, C.E., and Vanni, M.J. 2013. Clupeid response to stressors: the
influence of environmental factors on thiaminase expression. Journal of Aquatic
Animal Health. 25:90-97.
28) Lepak, J.M., Cathcart, C.N., and Hooten, M.B. 2012. Otolith weight as a predictor
of age in kokanee salmon (Oncorhynchus nerka) from four Colorado reservoirs.
Canadian Journal of Fisheries and Aquatic Sciences. 69:1569-1575.
29) Lepak, J.M., Hooten, M.B., and Johnson, B.M. 2012. The influence of external
subsidies on diet, growth and Hg concentrations of freshwater sport fish:
implications for fisheries management and the development of fish consumption
advisories. Ecotoxicology. 21(7):1878-1888.
30) Stacy, W.L., and Lepak, J.M. 2012. Relative influence of prey mercury
concentration, prey energy density and predator sex on sport fish mercury
concentrations. Science of the Total Environment. 437:104-109.
31) Lepak, J.M., Fetherman, E.R., Pate, W.M., Craft, C.D. and Gardunio, E.I. 2012.
An experimental approach to determine esocid prey preference in replicated pond
systems. Lake and Reservoir Management. 28:224-231.
32) Lepak, J.M., Kinzli, K.D., Fetherman, E.R., Pate, W.M., Hansen, A.G., Gardunio,
E.I., Cathcart, C.N., Stacy, W.L., Underwood, Z.E., Brandt, M.M., Myrick, C.M.,
and Johnson, B.M. 2012. Manipulation of growth to reduce sport fish mercury
concentrations on a whole-lake scale. Canadian Journal of Fisheries and Aquatic
Sciences. 69(1):122-135.
33) Josephson, D.C., Robinson, J.M., Lepak, J.M., and Kraft, C.E. 2012. Rainbow
trout performance in food-limited environments: Implications for future
assessment and management. Journal of Freshwater Ecology. 27(2):159-170.
34) Pate, W.M., Stacy, W.L., Gardunio, E.I., and Lepak, J.M. 2011. Collaborative
research between current and future fisheries professionals: facilitating AFS
subunit participation. Fisheries. 36(9):458-460.
35) Lepak, J.M., Robinson, J.R., Josephson, D.C., and Kraft, C.E. 2009. Changes in
mercury bioaccumulation in apex predators in response to removal of an
introduced competitor. Ecotoxicology. 18:488-498.
Page 5 of 26
�36) Lepak, J.M., Shayler, H.A., Kraft, C.E., and Knuth, B.A. 2009. Mercury
contamination in sport fish in the Northeastern United States: Considerations for
future data collection. BioScience. 59:174-181.
37) Lepak, J.M. and Kraft, C.E. 2008. Alewife mortality, condition, and immune
response to prolonged cold temperatures. Journal of Great Lakes Research.
34:134-142.
38) Lepak, J.M., Kraft, C.E., Honeyfield, D.C., and Brown, S.B. 2008. Evaluating the
effect of stressors on thiaminase activity in alewife. Journal of Aquatic Animal
Health. 20:63-71.
39) Lepak, J.M., Kraft, C.E., and Weidel, B.C. 2006. Rapid food web recovery in
response to removal of an introduced apex predator. Canadian Journal of
Fisheries and Aquatic Sciences 63:569-575.
40) Warren, D.R., Sebestyen, S.D., Josephson, D.C., Lepak, J.M. and Kraft, C.E.
2005. Acidic groundwater discharge and in situ egg survival in lake spawning
brook trout (Salvelinus fontinalis) redds. Transactions of the American Fisheries
Society 134:1193-1201.
Non-refereed publications
•
•
Lepak, J.M., Hansen, A.G., Walsworth, T.E., Pate, W.M., and Farrell, C.J. 2024.
Lake and Reservoir Research. Colorado Parks and Wildlife. Annual Report, Fort
Collins, CO, USA.
Hansen, A.G., Lepak, J.M., Pate, W.M., and Farrell, C.J. 2023. Coldwater lake
and reservoir research. Colorado Parks and Wildlife. Annual Report, Fort Collins,
CO, USA.
•
Lauber, T.B., Lepak, J.M, Connelly, N.A., Schroeder, B., Stedman, R.C. Knuth,
B.A., and Furgal, S.L. 2022. Stakeholder and manager responses to the Lake
Huron Chinook Salmon fishery collapse: Informing future decision making.
Center for Conservation Social Sciences Publ. Series 22-3. Dept. of Nat.
Resources. and the Environ., Coll. Agric. and Life Sci., Cornell Univ., Ithaca, NY.
•
Hansen, A.G., Lepak, J.M., Cristan, E.T., Pate, W.M., and Farrell, C.J. 2022.
Coldwater lake and reservoir research. Colorado Parks and Wildlife. Annual
Report, Fort Collins, CO, USA.
Hansen, A.G., Lepak, J.M., Cristan, E.T., Pate, W.M., and Farrell, C.J. 2021.
Coldwater lake and reservoir research. Colorado Parks and Wildlife. Annual
Report, Fort Collins, CO, USA.
•
•
Fetherman, E.R., Lepak, J.M., and Harris, D.J. 2015. Optimizing triploid walleye
production in Colorado. Colorado Parks and Wildlife White Paper.
Page 6 of 26
�•
Lepak, J.M. 2014. Annual Lake and Reservoir Research Report. Colorado Parks
and Wildlife. Annual Report, Fort Collins, CO, USA.
•
Lepak, J.M. 2013. Annual Lake and Reservoir Research Report. Colorado Parks
and Wildlife. Annual Report, Fort Collins, CO, USA.
•
Lepak, J.M. 2012. Annual Lake and Reservoir Research Report. Colorado Parks
and Wildlife. Annual Report, Fort Collins, CO, USA.
•
Lepak, J.M. and Johnson, B.M. 2010. Bioaccumulation of mercury in aquatic
food webs: integrating research and management towards remediation. Colorado
Division of Wildlife Report.
•
Lepak, J.M. and Johnson, B.M. 2010. Predictors of mercury contamination in
Colorado reservoirs: implications for improving the protection of human health.
Colorado Division of Wildlife Report.
•
Lepak, J.M., Johnson, B.M., and Vieira, N.K. 2010. Bioaccumulation of mercury
in aquatic food webs: integrating research and management towards
remediation. Colorado Department of Public Health and Environment Report.
•
Lepak, J.M. and Johnson, B.M. 2010. Predictors of mercury contamination in
Colorado reservoirs: implications for improving the protection of human health.
Colorado Department of Public Health and Environment Report.
•
Lepak, J.M. 2005. Intruders in Cayuga Lake: The hidden dangers of introduced
fish. Cayuga Lake Watershed Network News. Interlaken, NY.
•
Fitzsimons, J., Brown, S., Fodor, G., Williston, B., Brown, L., Moore, K., Barrows,
R., Kraft, C.E., Lepak, J.M., Honeyfield, D.C., and Tillitt, D. 2004. Factors
influencing alewife thiaminolytic activity. In Great Lakes Fishery Trust Report.
Professional highlights
•
40 peer-reviewed publications, and 11 non-peer-reviewed publications, reports
and popular news articles. Aspects of my work have been featured in multiple
radio, newspaper, popular press and television outlets such as Northern
Colorado Public Radio and the Denver Post.
•
100+ oral and poster presentations for a combination of public, state, federal, and
private audiences. Of these, 8 received awards as the best professional or
student presentations at state or regional professional meetings.
•
Obtained and administered over $2 million research dollars including funds from
the National Science Foundation, Disney Conservation Fund, Colorado
Department of Public Health and the Environment, Cornell Provost’s Diversity
Page 7 of 26
�Fellowship and the Species Conservation Trust Fund for Native Fish (fish
disease section).
•
Responsible for statewide lake and reservoir research for Colorado Parks and
Wildlife (2010-2015). Led interdisciplinary research with academic, federal, and
state personnel to address controversial and emerging issues facing fisheries
managers and policy makers. My findings informed conservation decisions,
health risk policy development, and fisheries and water management.
•
Colorado-Wyoming American Fisheries Society’s Outstanding Mentor of the Year
in 2013 and mentor/supervisor/co-advisor/committee member to a combination of
8 research associates and graduate students as affiliate faculty at Colorado State
University in the Department of Fish, Wildlife, and Conservation Biology.
•
3 publications through the direct collaboration with members of Colorado State
University’s Student Subunit of the American Fisheries Society (AFS), one of
which was entitled, “Collaborative research between current and future fisheries
professionals: facilitating AFS subunit participation” in the AFS journal Fisheries.
•
Served on the Technical Advisory Committee (2011-2015, 2021-current)
developing fish consumption advice for Colorado anglers and their families.
Encouraged appropriate fish consumption and rapid communication of
monitoring results due to potential for fast change in fish mercury concentrations.
•
Member of the Western North American Mercury Synthesis, an international
group of experts characterizing mercury contamination in western North America
(~9 million km2) to identify areas of concern and potential mechanisms to mitigate
the effects of environmental mercury contamination on fish, wildlife, and humans.
•
Rapidly reduced mercury concentrations in contaminated sport fish (mature
northern pike) by up to 50% over the course of ~50 days by providing alternate
forage (low mercury, high calorie) in the form of stocked rainbow trout.
•
Member of the New York State Invasive Species Advisory Council, the Lake
Ontario Sport Fishing Promotion Council (advisor: 2017-2020), and Commercial
Fisheries Advisor for Lake Ontario to the U.S. Section of the Great Lakes
Fisheries Commission. These entities provide information to anglers and other
stakeholders for decision-making and to managers for setting policies/quotas.
•
In fall 2017, Dr. Lepak was an instructor for a graduate course at Cornell
University (NTRES 6940; advanced research methods in fisheries and aquatic
science) focused on improving round goby assessments. We used videography
to evaluate numbers, biomass, and habitat use of round goby in a recently
invaded lake in the Great Lakes watershed. Nine students were enrolled and
~35 individuals were involved (e.g., guest lectures, sampling, data collection and
analysis, etc). Also mentored 3 interns in conjunction with the course. A
Page 8 of 26
�manuscript entitled “Seasonal habitat use indicates depth may mediate the
potential for trophic impacts of invasive round goby in inland lakes” was
submitted and accepted to the journal Freshwater Biology.
•
Interacted with thousands of fisheries stakeholders including anglers, charter
captains, bait and tackle shop owners, commercial anglers, county officials,
NGOs, promotions and marketing personnel, state and federal agencies,
university faculty and students, and the general public on topics including the role
of Sea Grant in coastal communities, New York fisheries, lakes Ontario and Erie
predator-prey interactions, invasive species, and food web
alteration/perturbation.
•
Represented the Great Lakes Aquaculture Collaborative at the World
Aquaculture Society Conference in New Orleans (March 2019). This
collaborative effort includes partners from the eight Great Lakes’ states working
together to advance aquaculture initiatives in the area. Presented, “Barriers to
New York Aquaculture with a focus on the Great Lakes basin: can we plan
initiatives and grow the industry?”
•
Developed and/or redesigned a variety of outreach and education materials for
use throughout the Great Lakes basin in NY, MI, WI, IN, and IL for large
audiences consisting of researchers, anglers, and charter captains, and for more
targeted groups like the Adirondack League Club, the Silver Lake (PA) Lake
Association, Colorado Conservation Officers, Monroe County Fisheries Advisory
Board, and the Eastern Lakes Ontario Salmon and Trout Association.
Students and professional mentoring
•
2019 fall semester: mentoring 1 graduate and 1 undergraduate student from the
State University of New York-Oswego (lake sturgeon conservation).
•
2018 spring semester: mentoring 2 undergraduate interns at Cornell University in
conjunction with data collected during NTRES 6940; advanced research methods
in fisheries and aquatic science.
•
2017 fall semester: mentored 3 undergraduate interns at Cornell University in
conjunction with NTRES 6940; advanced research methods in fisheries and
aquatic science.
•
Estevan Vigil: 2018 M.S.. Colorado Cooperative Fish and Wildlife Research Unit
(Co-advised with Dr. Dana Winkelman). The current and potential impacts of the
parasitic copepod Salmincola californiensis on cutthroat trout.
•
Kyle Christianson. 2017 M.S., Department of Fish, Wildlife, and Conservation
Biology, Colorado State University (Committee member with Dr. Brett Johnson).
Page 9 of 26
�Distribution and persistence of introduced Mysis diluviana across the Colorado
landscape.
•
Christopher Kopack: 2015-2016 Research Associate. Department of Biology,
Colorado State University (Mentoring with Dr. Lisa Angeloni). Using
environmental enrichment to increase post-stocking survival of hatchery reared
native and sport fishes.
•
Estevan Vigil: 2014-2015 Research Associate. Colorado Cooperative Fish and
Wildlife Research Unit (Mentoring with Dr. Dana Winkelman). Distribution and
impacts of gill lice (Salmincola californiensis) in Colorado.
•
Brian Wolff: 2013-2014 Research Associate. Department of Fish, Wildlife, and
Conservation Biology, Colorado State University (Mentoring with Dr. Brett
Johnson). Characterizing bioaccumulation of mercury in sport fish: informing
TMDL development and modeling mitigation strategies in Front Range
(Colorado) reservoirs.
•
Michael Avery: 2014. Research Associates. Department of Fish, Wildlife, and
Conservation Biology, Colorado State University (Mentoring with Dr. Ken
Wilson). Statewide aquatic sound and navigation ranging (SONAR).
•
Devin Olsen: 2014. M.S. Department of Fish, Wildlife, and Conservation Biology,
Colorado State University (Committee member with Dr. Brett Johnson). Arctic
char (Salvelinus alpinus) can enhance fisheries in reservoirs with trophic
constraints.
•
William Pate: 2013. M.S. Department of Fish, Wildlife, and Conservation Biology,
Colorado State University (Committee member with Dr. Brett Johnson). Optimal
management strategies for multi-use recreational fisheries: coexistence of lake
trout and kokanee in western waters.
•
Kristoph Kinzli, Eric Fetherman, William Pate, Adam Hansen, Eric Gardunio,
Nathan Cathcart, William Stacy, Zachary Underwood, and Mandi Brandt. 2012.
Led this group of American Fisheries Society students in a one-year project
culminating in the publication of, “Manipulation of growth to reduce sport fish
mercury concentrations on a whole-lake scale. Canadian Journal of Fisheries
and Aquatic Sciences. 69(1):122-135”.
•
While with Colorado Parks and Wildlife, Dr. Lepak supervised over 20 technician
positions over the course of 5 years. Also worked with over a half dozen
volunteers. More than 95% of these individuals as well as the co-advised
graduate students have moved on to positions or appointments in fisheries.
Page 10 of 26
�Teaching experience
•
Guest lecturer. State University of New York-Oswego Great Lakes
Environmental Issues course (fall semester 2019). Food web shifts and
responses in sport fish mercury concentrations and lake sturgeon conservation.
•
Instructor. Cornell University, NATRES 6940 (fall semester 2017) Contemporary
research methods in fisheries and aquatic sciences. Round goby invasion
ecology and impacts in the Great Lakes Basin.
•
Guest Instructor. State University of New York-Oswego 7th grade summer
class. August 2017. Fish and Food Web of Lake Ontario.
•
Guest lecturer. Front Range Community College (Freshwater Ecology), 2011 –
2014, 2023. Introduction to the use of stable carbon and nitrogen isotopes and
mercury as indicators of energy and contaminant cycling in ecosystems.
•
Guest instructor. Colorado State University (Introduction to Fishery Biology),
2009. Fisheries management to reduce mercury bioaccumulation in populations
of Colorado walleye.
•
Guest lecturer. Colorado State University (Fisheries Science), 2008. Topics on
changes in food webs and mercury bioaccumulation in response to removal of an
introduced piscivore in an Adirondack ecosystem.
•
Teaching assistant. Led laboratory and field exercises, discussion and review
sections, and presented guest lectures. Developed and graded assignments and
exams for Natural Resources 311 (Fish Ecology). Cornell University, 2007.
•
Teaching assistant. Led laboratory and field exercises, class instruction and
discussions and guest lectures and graded exams for Natural Resources 210
(Field Biology). Cornell University, 2006.
•
Teaching assistant. Led bi-weekly discussion sections, graded research papers
and developed student grades for Natural Resources 201 (Environmental
Conservation). Cornell University, 2006.
•
Guest lecturer. Cornell University, Natural Resources 311 (Fish Ecology), 2003
- 2006. Topics on changes in food webs and mercury bioaccumulation in
response to removal of an introduced piscivore in an Adirondack ecosystem.
•
Guest lecturer. Cornell University, Natural Resources 210 (Field Biology), 2002
- 2003. Topics on stream and food web ecology.
Page 11 of 26
�Funding obtained and administered totaling: $2,117,560
•
2023-2025 Colorado Parks and Wildlife’s Senior Aquatic Biologist contribution to
report describing Gizzard Shad in Colorado: $40,000
•
2023-2024: Colorado Parks and Wildlife’s lake and reservoir food web ecology
and sport fish research budget (Lepak): $50,000
•
2021: Species Conservation Trust Fund (Tiger Muskellunge), $361,000
•
2019: Great Lakes Fisheries Commission human dimensions research grant:
$138,251
•
2019: FFO NOAA-OAR-SG-2019-2005963 – Advanced Aquaculture
Collaborative Programs: Sub-award on a proposal led by Minnesota Sea Grant:
$40,433
•
2018: Disney Conservation Foundation: $47,400
•
2018: Cornell Program Work Team small grant: $2,000
•
2018: Mussel Stopper LLC Gift in Kind: $1,500
•
2018: New York Sea grant Program Development funding: $4,410
•
2014-2015: Colorado Parks and Wildlife’s lake and reservoir food web ecology
and sport fish research budget: $50,703
•
2014: Species Conservation Trust Fund for Native Fish (fish disease), $256,000
•
2013-2014: Colorado Parks and Wildlife’s lake and reservoir food web ecology
and sport fish research budget: $129,556
•
2013: Species Conservation Trust Fund for Native Fish (fish disease), $78,620
•
2012-2013: Colorado Parks and Wildlife’s lake and reservoir food web ecology
and sport fish research budget: $129,685
•
2012: NADP/MDN site CO97 (US Forest Service, Federal) Gift in Kind, $24,000
•
2012: Colorado Department of Public Health and Environment, $2,000
•
2012: Northern Water Conservancy District “Gift in Kind” 2012, $176,824
•
2012: Fort Collins Utilities Gift in Kind, $31,878
•
2012: Quicksilver Scientific Gift in Kind, $1,875
•
2012: Colorado Department of Public Health and the Environment, $286,353
•
2011-2012: Colorado Parks and Wildlife’s lake and reservoir food web ecology
and sport fish research budget: $129,262
Page 12 of 26
�•
2010-2011: Colorado Parks and Wildlife’s lake and reservoir food web ecology
and sport fish research budget: $32,671
•
2009: Colorado Department of Public Health and the Environment, $25,488
•
2009: Colorado Division of Wildlife Gift in Kind, $27,000
•
2009: Quicksilver Scientific Gift in Kind, $1,250
•
2007: National Science Foundation-DIGG, $11,085
•
2007: CEBAM Analytical Gift in Kind, $4,230
•
2007: Cornell Provost’s Diversity Fellowship, $10,000
•
2006: Biogeochemistry and Environmental Biocomplexity small grant, $3,984
•
2006: Kieckhefer Adirondack Fellowship, $5,000
•
2005: Biogeochemistry and Environmental Biocomplexity small grant, $3,720
•
2004: Environmental Research Grant, Center for the Environment, $3,880
•
2003: Kieckhefer Adirondack Fellowship, $2,500
•
2002: Kieckhefer Adirondack Fellowship, $5,000
Selected Presentations
•
Lepak, J.M. Characterizing lake and reservoir ecosystems: simple and complex
models. Invited Lecture: Front Range Community College. Fort Collins, CO. Apr.
2024.
•
Brandt, M., Hansen, A.G., and Lepak, J.M. Converting to the North American
Standard: Evaluation of CPW vs. AFS Gill Nets. Colorado Parks and Wildlife
Northeast Biodays. Apr. 2024.
•
Lepak, J.M. Tiger Muskellunge update, College Lake comparison, Grand Lake
mesocosms. Colorado Parks and Wildlife Coldwater Reservoir Meeting. Virtual.
Feb. 2024.
•
Lepak, J.M. Lake and Reservoir Research Projects. Colorado Parks and Wildlife
Aquatic Section Meeting. Feb. 2024.
•
Brandt, M., Hansen, A.G., and Lepak, J.M. Converting to the North American
Standard: Evaluation of CPW vs. AFS Gill Nets. Colorado Parks and Wildlife
Aquatic Biologist Summit. Feb. 2024.
•
Lepak, J.M. Manipulation of sport fish growth to reduce mercury bioaccumulation
on a whole-system scale. Invited Lecture (Dr. R. Razavi): Syracuse University,
Syracuse, NY. Feb. 2024.
Page 13 of 26
�•
Walsworth, T.E., Hansen, A.G., and Lepak, J.M. Untangling drivers of cyclic
walleye dynamics. 2024 Utah Chapter of the American Fisheries Society. Feb.
2024.
•
Lepak, J.M. Characterizing lake and reservoir ecosystems: simple and complex
models. Invited Lecture: Front Range Community College. Fort Collins, CO. April
2023.
•
Lepak, J.M., Hansen, A., Winkelman, D., Ewert, J., Eyre, T. Sterile tiger
muskellunge (Esox lucius x E. masquinongy) as undesirable fish species control
agents. Colorado Parks and Wildlife Coldwater Lake and Reservoir Annual
Meeting. Remote. Feb. 2023.
•
Lepak, J.M., Winkelman, D., Hansen, A., Ewert, J., Eyre, T. Sterile tiger
muskellunge (Esox lucius x E. masquinongy) as undesirable fish species control
agents. Colorado State University Cooperative Fish and Wildlife Research Unit
annual review. Fort Collins, CO. May 2023.
•
Lepak, J.M. Manipulation of sport fish growth to reduce mercury bioaccumulation
on a whole-system scale. Invited Lecture (Dr. R. Razavi): Syracuse University,
Syracuse, NY. Feb. 2023.
•
Lepak, J.M. Collaborative Research with Lake Ontario Charter Captains: King
Salmon Movement and Behavior in Lake Ontario. Joint National American
Fisheries and Wildlife Societies Meeting. Reno, Nevada. Sept. 2019.
•
Lepak, J.M. Lake Ontario CSMI Discussion: Sharing Ideas and Contributions for
Outreach Materials. Lake Ontario CSMI Planning Meeting. Buffalo, New York.
June 2019 (session Chair).
•
Lepak, J.M. Lake Ontario CSMI Discussion: Sharing Ideas and Contributions for
Outreach Materials. International Association for Great Lakes Research Meeting.
Brockport, New York. June 2019 (session co-Chair).
•
Lepak, J.M. Understanding angler response to barotrauma in Lake Erie yellow
perch. International Association for Great Lakes Research Meeting. Brockport,
New York. June 2019.
•
Lepak, J.M. Barriers to New York Aquaculture with a focus on the Great Lakes
basin: can we plan initiatives and grow the industry? World Aquaculture Society
Conference. New Orleans, Louisiana. March 2019
•
Lepak, J.M. Understanding angler response to barotrauma in Lake Erie yellow
perch. American Fisheries Society Annual Meeting. Poughkeepsie, New York.
Feb. 2019.
Page 14 of 26
�•
Lepak, J.M. New York Sea Grant and Great Lakes Fisheries: Past, present, and
future. Midwest Fish and Wildlife Conference. Cleveland, Ohio. Jan. 2019
(Session co-Chair).
•
Lepak, J.M. Sethi, S.A., Rice, A., Andres, K., Duskey, E., Estabrook, B.,
Fitzpatrick, K., George, E., Marcy-Quay, B., Perkins, K., Paufve, M., and
Scofield, A. A New York Sea Grant perspective: King salmon, round goby, and
fisheries in Lake Ontario. Finger Lakes Research Conference. Geneva, New
York. Jan. 2019.
•
Lepak, J.M. Fisheries pathways and projects. SUNY-ESF Student Chapter of the
American Fisheries Society. Syracuse, New York. Nov. 2018.
•
Watkins, J., Perle, C., Lepak, J.M., and Rudstam, L. Tracking Chinook Salmon in
Lake Ontario Using Tagging Technology. Natural Resources Seminar Series.
Cornell University. Ithaca, New York. Oct. 2018.
•
Lepak, J.M. Sea Grant, salmon, and goby. Eastern Lake Ontario Salmon and
Trout Association Meeting. Syracuse, New York. Sept. 2018.
•
Lepak, J.M., Watkins, M., and Perle, C. Communicating Research to Charter
Captains: King Salmon Movement and Behavior in Lake Ontario. International
Association for Great Lakes Research Meeting. Toronto, Ontario, Canada, June.
2018 (Session co-Chair).
•
Watkins, J, Perle, C., Lepak, J.M., and Rudstam, L. Tracking diel foraging
behavior of Chinook Salmon in Lake Ontario using pop-off satellite archival tags.
International Association for Great Lakes Research Meeting. Toronto, Ontario,
Canada, June. 2018.
•
Lepak, J.M. Take pride in your perch! Practice ethical and sustainable angling
when handling yellow perch suffering from barotrauma. International Association
for Great Lakes Research Meeting. Toronto, Ontario, Canada, June. 2018.
•
Sethi, S.A., Lepak, J.M., Rice, A., Andres, K., Duskey, E., Estabrook, B.,
Fitzpatrick, K., George, E., Marcy-Quay, B., Perkins, K., Paufve, M., and
Scofield, A. Characterizing the ecological niche of invasive round goby in inland
lakes. International Association for Great Lakes Research Meeting. Toronto,
Ontario, Canada, June. 2018.
•
S.A. Sethi, Lepak, J.M., Rice, A., Andres, K., Duskey, E., Estabrook, B.,
Fitzpatrick, K., George, E., Marcy-Quay, B., Perkins, K., Paufve, M., and
Scofield, A. The role of invasive Round Goby in the Great Lakes basin: habitat
use and standing stock biomass in a recently invaded deep inland lake. New
York American Fisheries Society Meeting. Cooperstown, New York, Feb. 2018.
Page 15 of 26
�•
Lepak, J.M., Bunting-Howarth, K., and Focazio, P. The Great Lakes Cooperative
Science and Monitoring Initiative (CSMI): Lake Ontario. New York Chapter of the
American Fisheries Society Meeting. Cooperstown, New York, Feb. 2018.
•
Lepak, J.M. Barotrauma in Lake Erie yellow perch: take pride in your perch.
Poster presentation New York American Fisheries Society Meeting.
Cooperstown, New York, Feb. 2018.
•
Sethi, S.A., Lepak, J.M., Rice, A., Andres, K., Duskey, E., Estabrooks, B.,
Fitzpatrick, K., George, E., Marcy-Quay, B., Perkins, K., Paufve, M., and
Scofield, A. Characterizing the ecological niche of invasive round goby in Cayuga
Lake. Finger Lakes Research Conference. Geneva, New York, November 2017.
•
Lepak, J.M. Barotrauma in Lake Erie yellow perch: take pride in your perch.
Poster presentation at the National American Fisheries Society Meeting. Tampa,
Florida. August 2017.
•
Lepak, J.M. Barotrauma in Lake Erie yellow perch: take pride in your perch.
Poster presentation at the Great Lakes Sea Grant Network Meeting. Cleveland,
Ohio. June 2017.
•
Lepak, J.M. Rapid food web shifts and subsequent changes in sport fish mercury
concentrations. Hobart and William Smith Colleges, Finger Lake Institute Aquatic
Seminar Series, Geneva, New York. October 2016.
•
Lepak, J.M. Ecological risks to fish from environmental mercury contamination:
examples from the United States. Costa Rica Workshop on Monitoring Mercury
in Fish and Birds. University of Costa Rica, San Jose, Costa Rica, April 2016.
•
Lepak, J.M. Consumption advisories and management to maximize benefits of
consuming fish and minimize risks. Costa Rica Workshop on Monitoring Mercury
in Fish and Birds. University of Costa Rica, San Jose, Costa Rica, April 2016.
•
Lepak, J.M. Food web shifts and subsequent changes in mercury concentrations
of sport fish. American Fisheries Society Student Chapter Meeting. Cornell
University, Ithaca, New York, November 2015.
•
Eagles-Smith, C., Marvin-DiPasquale, M., Evers, D., Eckley, C., Wiener, J.,
Fleck, J., Ackerman, J., Aiken, G., Davis, J., Drevnick, P., Geesey, G., Jackson,
A., Lepak, J.M., Obrist, D., Stewart, R., Webster, J., Weiss-Penzias, P., and
Willacker, J. Western North American Mercury Synthesis (WNAMS): a multidisciplinary, tri-national assessment of the climate, landscape, and land use
controls on mercury risk to ecological and health across western North America.
Society of Environmental Toxicology and Chemistry. Salt Lake City, Utah. Nov.
2015.
•
Lepak, J.M. Lake and Reservoir Research Progress. Annual Colorado Parks and
Page 16 of 26
�Wildlife Aquatic Biologist Meeting. Cripple Creek, Colorado. Jan. 2015.
•
Lepak, J.M., Eagles-Smith, C., Marvin-DiPasquale, M., Sunderland, E., and
Weiner, J. Spatiotemporal differences in food web structure and resulting
mercury contamination in sport fish. Western Division American Fisheries Society
Annual Meeting. Mazatlan, Mexico. April 2014 (awarded Western Division AFS
travel grant to attend and present as the professional representative for
Colorado).
•
Vigil, E., and Lepak, J.M. Temperature Effects on Hatching and Viability of
Juvenile Gill Lice. Poster presentation. Western Division American Fisheries
Society Annual Meeting. Mazatlan, Mexico. April 2014.
•
Broder, E.D., Kopack, C., Lepak, J.M., Fetherman, E.R., and Angeloni, L.M.
Chemical cues of predation induce anti-predator behavior in naïve rainbow trout:
implications for training hatchery-reared fish. Poster presentation. Western
Division American Fisheries Society Annual Meeting. Mazatlan, Mexico. April
2014.
•
Johnson, C., Johnson, B.M., Lepak, J.M., Burckhardt, J., and Neebling, T. Use
of Summer Profundal Index Netting to Estimate Lake Trout Abundance in
Wyoming and Colorado Waters. Colorado-Wyoming American Fisheries Society
Annual Meeting. Laramie, Wyoming. Mar. 2014. (C. Johnson presenter).
•
Vigil, E., and Lepak, J.M. Gill lice in Colorado. Colorado-Wyoming American
Fisheries Society Annual Meeting. Laramie, Wyoming. Mar. 2014. (E. Vigil
presenter)
•
Vigil, E., and Lepak, J.M. Temperature effects on hatching and viability of
juvenile gill lice. Poster presentation. Colorado-Wyoming American Fisheries
Society Annual Meeting. Laramie, Wyoming. Mar. 2014. (Best Professional
Poster Award; E. Vigil presenter).
•
Kopack, C., Broder, E.D., Lepak, J.M., Fetherman, E.R., and Angeloni, L.M.
Chemical cues of predation induce anti-predator behavior in naïve rainbow trout:
implications for training hatchery-reared fish. Poster presentation. ColoradoWyoming American Fisheries Society Annual Meeting. Laramie, Wyoming. Mar.
2014. (C. Kopack presenter).
•
Christianson, K., Lepak, J.M., Treble, A., Myrick, C., and Swigle, B. Evaluating
and enhancing trophy largemouth bass opportunities in Colorado. ColoradoWyoming American Fisheries Society Annual Meeting. Laramie, Wyoming. Mar.
2014. (C. Christianson presenter).
•
Fetherman, E.R., Lepak, J.M., Kopack, J., Broder, E.D., and Angeloni, L.M.
Chemical cues of predation induce anti-predator behavior in Hofer rainbow trout:
Page 17 of 26
�implications for training hatchery-reared fish. Great Plains Fishery Workers
Workshop. Fort Collins, Colorado. Feb. 2014. (E. Fetherman presenter).
•
Vigil, E., and Lepak, J.M. There is a Louse in the House. Great Plains Fishery
Workers Workshop. Fort Collins, Colorado. Feb. 2014. (E. Vigil presenter).
•
Christianson, K., Lepak, J.M., Treble, A., Myrick, C., and Swigle, B. Evaluating
and enhancing trophy largemouth bass opportunities in Colorado. Great Plains
Fishery Workers Workshop. Fort Collins, Colorado. Feb. 2014. (C. Christianson
presenter).
•
Christianson, K., Lepak, J.M., Treble, A., Myrick, C., and Swigle, B. Evaluating
and enhancing trophy largemouth bass opportunities in Colorado. Colorado State
University Student Chapter of the American Fisheries Society Meeting. Fort
Collins, Colorado. Feb. 2014. (C. Christianson presenter).
•
Lepak, J.M., and B.M. Johnson. Northern Water Conservancy District. Nutrient
balance restoration. Berthoud, Colorado. Feb. 2014.
•
Kopack, C., Broder, E.D., Lepak, J.M., Fetherman, E.R., and Angeloni, L.M.
Front Range Student Ecological Symposium. Chemical cues of predation induce
anti-predator behavior in naïve rainbow trout: implications for training hatcheryreared fish. Poster presentation. Fort Collins, Colorado. Feb. 2014. Best Student
Poster Award. (C. Kopack presenter).
•
Lepak, J.M. Fisheries Research from Two Different Perspectives: Science and
Art. Colorado State University Student Chapter of the American Fisheries Society
Meeting. Fort Collins, Colorado. Nov. 2013.
•
Lepak, J.M. Fisheries Management to remediate mercury contamination in sport
fish. Environmental Protection Agency, Region 9 Mercury Seminar. Sep. 2013.
International online attendance.
•
Eagles-Smith, C., Evers, D., Marvin-DiPasquale, M., Weiner, J., Ackerman, J.,
Aiken, G., Alpers, C., Cline, C., Dassuncao, C., Davis, J., Eckley, C., Elliott, J.,
Flanagan, C., Fleck, J., Gustin, M., Jackson, A., Jaffe, D., Johnson, P.,
Krabbenhoft, D., Lepak, J.M., Luengen, A., Morris, K., Siitari, K., Steffen, A.,
Stewart, R., Sunderland, E., Turnquist, M., Villatoro, F., Webster, J., Wilson, A.,
and Wright, G. Mercury Cycling, Bioaccumulation, and Risk across Western
North America: a landscape scale synthesis. Invited poster presentation.
International Conference on Mercury as a Global Pollutant. Edinburgh, Scotland.
Jul. to Aug. 2013 (C. Eagles-Smith presenter).
•
Eagles-Smith, C., Marvin-DiPasquale, M., and Lepak, J.M. Western North
American Mercury Synthesis. Western North American Mercury Synthesis
Webinar. April 2013.
Page 18 of 26
�•
Lepak, J.M., and Avery, M. Proposed hydroacoutsic survey: 2013. Annual Dillon
Reservoir Research Meeting. Fort Collins, Colorado. April 2013.
•
Lepak, J.M. Summary of the 32nd International Kokanee Salmon Workshop in
Fort Collins, CO. Northern Water Conservancy District Meeting. Berthoud,
Colorado. Feb. 2013.
•
Lepak, J.M., Hargis, L., Vigil, E., and Gunn C. 32nd Experiences with Gill Lice in
Colorado Kokanee Salmon populations. International Kokanee Salmon
Workshop. Fort Collins, Colorado. Feb. 2013. (J.M. Lepak: meeting organizer).
•
Pate, W.M., Johnson, B.M., Lepak, J.M., and Brauch, D. Strategies for multi-use
recreational fisheries: coexistence of lake trout and kokanee in western waters.
32nd International Kokanee Salmon Workshop. Fort Collins, Colorado. Feb. 2013.
(W. Pate presenter).
•
Hargis, L., Lepak, J.M., Vigil, E., Gunn, C. Prevalence and Intensity of the
Parasitic Copepod (Salmincola californiensis) on Kokanee Salmon
(Oncorhynchus nerka) in a Colorado reservoir. 32nd International Kokanee
Salmon Workshop. Fort Collins, Colorado. Feb. 2013. (L. Hargis presenter).
•
Lepak, J.M., Cathcart, C.N., and Stacy, W. Tiger muskellunge predation on
stocked sportfish intended for recreational fisheries. CO-WY American Fisheries
Society Meeting. Fort Collins, Colorado. Feb. 2013. (Best Professional Paper
Award).
•
Olsen, D., Johnson, B.M., and Lepak, J.M. The Arctic char (Salvelinus alpinus)
of Dillon Reservoir, Colorado: an evaluation of their present status and future
management possibilities. Colorado-Wyoming American Fisheries Society
Meeting. Fort Collins, Colorado. Feb. 2013. (Best Student Paper Award; D.
Olsen presenter).
•
Hargis, L., Lepak, J.M., Vigil, E., Gunn, C. Prevalence and Intensity of the
Parasitic Copepod (Salmincola californiensis) on Kokanee Salmon
(Oncorhynchus nerka) in a Colorado reservoir. Poster presentation. ColoradoWyoming American Fisheries Society Meeting. Fort Collins, Colorado. Feb. 2013.
(Best Professional Poster Award; E. Vigil presenter).
•
Marvin-DiPasquale, M., Eagles-Smith, C., Eckley, C., Evers, D., and Lepak, J.M.
Western North American Mercury Synthesis. Delta Tributaries Mercury Council
Meeting. Sacramento, California. Feb. 2013. (M. Marvin-DiPasquale presenter).
•
Avery, M., and Lepak, J.M. Status of hydroacoustic studies in Colorado. HTI
SONAR workshop. Dutch John, Utah. June 2012 (M. Avery presenter).
•
Lepak, J.M. Managing sport fish in Colorado. District Wildlife Manager Meeting.
Gunnison, Colorado. May 2012.
Page 19 of 26
�•
Lepak, J.M. Progress on Kokanee Salmon Research. Annual Colorado Parks
and Wildlife Kokanee Salmon Meeting. Buena Vista, Colorado. Feb. 2012.
•
Lepak, J.M. Progress on Lake and Reservoir Research Priorities. Annual
Colorado Parks and Wildlife Aquatic Biologist Meeting. Fort Collins, Colorado.
Jan. 2012.
•
Pate, W.M., Johnson, B.M., Brauch, D., and Lepak, J.M. Boom-and-bust lake
trout-kokanee fisheries: turning runaway consumption into sustainable fisheries
for both species. Western Division American Fisheries Society Meeting. Jackson,
Wyoming. Mar. 2012. (W. Pate presenter).
•
Lepak, J.M., and Cathcart, C.N. Otolith weight as a predictor of age in kokanee
salmon (Oncorhynchus nerka). Western Division American Fisheries Society
Meeting. Jackson, Wyoming. Mar. 2012.
•
Lepak, J.M. Manipulation of sport fish growth to reduce mercury bioaccumulation
on a whole-lake scale. National American Fisheries Society Meeting. Seattle,
Washington. Sept. 2011.
•
Lepak, J.M. Manipulation of sport fish growth to reduce mercury bioaccumulation
on a whole-lake scale. Colorado-Wyoming American Fisheries Society Meeting.
Fort Collins, Colorado. Feb. 2011. (Best Professional Paper Award).
•
Stacy, W, and Lepak, J.M. Relative importance of growth, prey energy density
and prey mercury content in determining walleye mercury concentrations.
Midwest American Fisheries Society Meeting. Brookings, South Dakota. Jan.
2011 (W. Stacy presenter).
•
Stacy, W., Lepak, J., Kinzli, K., Fetherman, E., Pate, W., Hansen, A., Gardunio,
E., Cathcart, C. and Underwood, Z. Manipulation of sport fish growth to reduce
mercury bioaccumulation on a whole-lake scale. Colorado-Wyoming American
Fisheries Society Student Colloquium. Moscow, Idaho. Dec. 2010 (W. Stacy
presenter).
•
Lepak, J.M. Mercury bioaccumulation in Brush Hollow Reservoir: lessons from
research. Colorado Department of Public Health and Environment Mercury
Workshop. Denver, Colorado. Dec. 2010.
•
Kraft, C.E., Chiotti, J.A., Jirka, K.K., Josephson, D.C., Lepak, J.M., Robinson,
J.M., Weidel, B.C., and Zipkin, E.F. Long-term ecosystem and population
responses to the large-scale removal of a dominant non-native piscivore from
lake ecosystems. Annual American Society of Limnology and
Oceanography/North American Benthological Society Meeting. Santa Fe, New
Mexico. June 2010 (C. Kraft presenter).
Page 20 of 26
�•
Lepak, J.M., and Johnson, B.M. Bioaccumulation of mercury in aquatic food
webs: integrating research and management towards remediation. Colorado
Division of Wildlife Senior Aquatic Staff Meeting. Kremmling, Colorado. May
2010.
•
Fialko, K.N., Lepak, J.M., and Johnson, B.M. A comparison of chronometric
structures for aging walleye: peculiar bias in spine-derived ages from a Front
Range reservoir. Colorado State University Honors Undergraduate Research
Program Poster Session. Fort Collins, Colorado. April 2010 (K. Fialko
presenter).
•
Lepak, J.M., Pate, W.M., Cathcart, C.N., Fetherman, E.R., Kinzli, K.D., Brandt,
M.M., Stacy, W.L., Underwood, Z.E., Gardunio, E.I., and Hansen, A.G.
Manipulation of sport fish growth to reduce mercury bioaccumulation on a wholelake scale. Poster presentation. Colorado-Wyoming American Fisheries Society
Meeting. Laramie, WY. April 2010.
•
Lepak, J.M., Johnson, B.M., and Vieira, N.K.M. Potential influence of fisheries
management on mercury concentrations in Colorado sport fish. Colorado
Division of Wildlife invited presentation. Fort Collins, Colorado. Mar. 2010.
•
Lepak, J.M., Pate, W.M., Cathcart, C.N., Fetherman, E.R., Kinzli, K.D., Brandt,
M.M., Stacy, W.L., Underwood, Z.E., Gardunio, E.I., and Hansen, A.G.
Manipulation of sport fish growth to reduce mercury bioaccumulation on a wholelake scale. Poster presentation. Western Division American Fisheries Society
Meeting. Salt Lake City, Utah. Mar. 2010. (Best Student Poster Award; E.
Fetherman presenter).
•
Lepak, J.M., Johnson, B.M. and Vieira, N. Bioaccumulation of mercury in aquatic
food webs: integrating research and management towards remediation. Joint
meeting of the Colorado Department of Public Health and the Environment and
the Environmental Protection Agency. Denver, Colorado. June 2009.
•
Lepak, J.M., Pate, W.M., Cathcart, C.N., Fetherman, E.R., Kinzli, K.D., Brandt,
M.M., Stacy, W.L. and Underwood, Z.E. Manipulation of sport fish growth to
reduce mercury bioaccumulation on a whole-lake scale. Poster presentation.
Western Division American Fisheries Society Meeting. Albuquerque, New
Mexico. May 2009.
•
Lepak, J.M. College Lake: management to reduce mercury concentrations in top
predators. Zoology Club Meeting. Colorado State University. Fort Collins,
Colorado. Mar. 2009.
Page 21 of 26
�•
Lepak, J.M., Johnson, B.M. and Vieira, N. Factors affecting bioaccumulation of
mercury in sport fish in Colorado reservoirs. Colorado-Wyoming American
Fisheries Society Meeting. Loveland, Colorado. Feb. 2009.
•
Lepak, J.M., Pate, W.M., Cathcart, C.N., Fetherman, E.R., Kinzli, K.D., Brandt,
M.M., Stacy, W.L. and Underwood, Z.E. Manipulation of sport fish growth to
reduce mercury bioaccumulation on a whole-lake scale. Poster presentation.
Colorado-Wyoming American Fisheries Society Meeting. Loveland, Colorado.
Feb. 2009.
•
Lepak, J.M. A pathway to fisheries research: project example and career advice.
American Fisheries Society Student Chapter Meeting. Colorado State University.
Fort Collins, Colorado. Oct. 2008.
•
Lepak, J.M. Changes in methylmercury bioaccumulation in an apex predator in
response to removal of an introduced piscivore. Department of Fish, Wildlife and
Conservation Biology. Colorado State University. Fort Collins, Colorado. Sep.
2008.
•
Lepak, J.M. Addressing negative anthropogenic and environmental impacts in
aquatic systems: A food web perspective. Natural Resources Seminar Series.
Cornell University. Ithaca, New York. Nov. 2007.
•
Lepak, J.M., Robinson J.R., Warren, D.W., Josephson, D.C. and Kraft, C.E.
Changes in mercury bioaccumulation in apex predators in response to removal of
an introduced piscivore. National American Fisheries Society Meeting. Lake
Placid. New York. Sept. 2006.
•
Lepak, J.M. and Kraft, C.E. Evaluating the effects of environment and stressors
on thiaminase expression in alewife and gizzard shad. Poster Presentation.
Department of Natural Resources Graduate Student Association Annual Meeting.
Cornell University, Ithaca, New York. Jan. 2006.
•
Lepak, J.M. and Kraft, C.E. Evaluating the effects of environment and stressors
on thiaminase expression in alewife and gizzard shad. Poster Presentation. New
York Sea Grant Review. Cornell University, Ithaca, New York. 2006.
•
Lepak, J.M. and Kraft, C.E. 2006. Effects of environment and stressors on
thiaminase levels in alewife. American Fisheries Society Annual New York
Chapter Meeting. Utica, New York. Feb. 2006.
•
Lepak, J.M., and Kraft, C.E. Evaluating the effects of environment and stressors
on thiaminase expression in alewife. Early Mortality Syndrome Meeting. Ann
Arbor, Michigan. Sep. 2005.
•
Lepak, J.M. Introduced species: Possibility of native recovery. Trout Lake
Seminar Series. Trout Lake Field Station, Sayner, Wisconsin. July 2005.
Page 22 of 26
�•
Lepak, J.M., and Kraft, C.E. Stable isotope measurements as indicators of diet
shifts in a lake trout population in an oligotrophic Adirondack lake. National
American Fisheries Society. Quebec City, Quebec. Aug. 2003.
•
Lepak, J.M., and Kraft, C.E. Stable isotope measurements as indicators of diet
shifts in a lake trout (Salvelinus namaycush) population in an oligotrophic
Adirondack lake. Natural Resources Seminar Series. Cornell University. Ithaca,
New York. April 2003.
•
Lepak, J.M., and Kraft, C.E. Stable isotope measurements as indicators of diet
shifts in a lake trout (Salvelinus namaycush) population in an oligotrophic
Adirondack lake. Department of Natural Resources Symposium. Cornell
University. Ithaca, New York. Jan. 2003 (honorable mention).
•
Lepak, J.M., and Kraft, C.E. Stable isotope measurements as indicators of diet
shifts in a lake trout (Salvelinus namaycush) population in an oligotrophic
Adirondack lake. Department of Ecology and Evolutionary Biology Symposium.
Cornell University. Ithaca, New York. Jan. 2003.
•
Lepak, J.M., and Kraft, C.E. Stable isotope measurements as indicators of diet
shifts in a lake trout (Salvelinus namaycush) population in an oligotrophic
Adirondack lake. New York American Fisheries Society Annual Meeting.
Canandaigua, New York. Jan. 2003 (Best Student Paper Award).
•
Lepak, J.M., and Kraft, C.E. Stable isotope measurements as indicators of diet
shifts in a lake trout population in an oligotrophic Adirondack lake. Canadian
Conference for fisheries Research. Ottawa, Ontario. Jan. 2003.
Honors and awards
•
Western Division American Fisheries Society’s Travel Award. Professional
representative for Colorado. 2014.
•
Colorado-Wyoming American Fisheries Society’s Best Professional Poster
Award (Coauthor: 2014).
•
Front Range Student Ecological Symposium’s Best Student Poster Award
(Coauthor: 2014).
•
Colorado-Wyoming American Fisheries Society’s Outstanding Mentor of the Year
Award. 2013.
•
Colorado-Wyoming American Fisheries Society’s Best Professional Poster
Award (Coauthor: 2013).
•
Colorado-Wyoming American Fisheries Society’s Best Professional Paper Award
(Lead author: 2013).
Page 23 of 26
�•
Colorado-Wyoming American Fisheries Society’s Best Student Paper Award
(Coauthor: 2013).
•
Colorado-Wyoming American Fisheries Society’s Best Professional Paper Award
(Lead author: 2011).
•
Western Division American Fisheries Society Meeting Best Student Poster
Award (Coauthor: 2010).
•
New York American Fisheries Society Best Student Paper Award. (Lead author:
2003).
Selected collaborators (previous and current)
•
Genesee Charter Boat Association
•
Lake Ontario Sport Fish Promotional Council
•
Eastern Lake Ontario Salmon and Trout Association
•
New York State Department of Environmental Conservation
•
Sea Grant Programs: Ohio, Lake Champlain, Illinois-Indiana, Michigan,
Wisconsin, Pennsylvania, Florida
•
Douglaston Salmon River Run
•
US Geological Survey, Oswego Field Office
•
Monroe County Fishery Advisory Board
•
Adam Hansen (Colorado Parks and Wildlife)
•
Richard Stedman (Cornell Center for Conservation Social Science)
•
Nancy Connelly (Cornell Center for Conservation Social Science)
•
Bruce Lauber (Cornell Center for Conservation Social Science)
•
Jim Watkins (Cornell University)
•
Josh Ackerman (United States Geological Survey)
•
Lisa Angeloni (Colorado State University)
•
Kevin Bestgen (Larval Fish Laboratory, Colorado State University)
•
Jean Marie Boyer (Hydros Consulting)
•
David Buck (Biodiversity Research Institute)
•
Jay Davis (San Francisco Estuary Institute)
•
Charley Driscoll (Syracuse University)
Page 24 of 26
�•
Collin Eagles-Smith (United States Geological Survey)
•
Chris Eckley (United States Environmental Protection Agency)
•
David Evers (Biodiversity Research Institute)
•
Adam Hansen (Colorado Parks and Wildlife)
•
Collin Farrell (United States Fish and Wildlife Service)
•
Eric Fetherman (Colorado Parks and Wildlife)
•
Christine Hawley (Hydros Consulting)
•
Natalia Ivone Sandoval Herrera (University of Costa Rica)
•
Brett Johnson (Colorado State University)
•
Daniel Josephson (Cornell University, Little Moose Field Station)
•
James Kitchell (University of Wisconsin; Professor Emeritus)
•
Barbara Knuth (Cornell University, Center for Conservation Social Science)
•
Aimee Konowal (Colorado Department of Public Health and Environment)
•
David Krabbenhoft (United States Geological Survey)
•
Mark Marvin-DiPasquale (United States Geological Survey)
•
Freylan Mena Torres (National University of Costa Rica)
•
Kristy Richardson (Colorado Department of Public Health and Environment)
•
Jason Robinson (New York State Department of Environmental Conservation)
•
George Schisler (Colorado Parks and Wildlife)
•
María del Mar Solano Trejos (Ministry of the Environment, Costa Rica)
•
Kim Sparks (Cornell University Stable Isotope Laboratory)
•
Robin Stewart (United States Geological Survey)
•
Esther Vincent (Northern Colorado Water Conservancy District)
•
Dana Warren (Oregon State University)
•
Brian Weidel (United States Geological Survey)
•
James Weiner (University of Wisconsin-La Crosse)
•
Sarah Wheeler (Colorado Department of Public Health and Environment)
•
Dana Winkelman (Colorado Cooperative Fish and Wildlife Research Unit)
Page 25 of 26
�Service and memberships
•
United States Advisor: Great Lakes Fisheries Commission (Lake Ontario
commercial and sport fisheries), 2018-2020
Member: New York Invasive Species Advisory Council, 2017-2020
•
Member: Lake Erie Percid Management Advisory Group, 2018-2020
•
Member: American Fisheries Society, Parent Society, 2001-present
•
Member: American Fisheries Society, Colorado Chapter, 2023-present
•
Colorado-Wyoming Co-Chair of the Continuing Education Committee, 2011 to
2015
•
Member: North American Lake Management Society, intermittently
•
Peer reviews for journals and institutions including:
•
• Canadian Journal of Fisheries and Aquatic Sciences
• Ecology Letters
• Fishes
• Biology
• Aquaculture, Fish, and Fisheries
• Ecotoxicology
• Environmental Protection Agency
• International Journal of Environmental Research and Public Health
• North American Journal of Fisheries Management
• San Francisco Estuary and Watershed Science
• Transactions of the American Fisheries Society
• United States Geological Survey
• National Park Service
• Pennsylvania Sea Grant
• Minnesota Sea Grant
• Illinois-Indiana Sea Grant
• Wisconsin Sea Grant
• Lake Champlain Sea Grant
• Michigan Sea Grant
Page 26 of 26
�
https://cpw.cvlcollections.org/files/original/4929bd884c4df963c409f83e72d9694a.pdf
e2c39e14c7408eea01ba3a10b8acfc8e
PDF Text
Text
Kemp-Breeze State Wildlife Area Habitat Project, Colorado River
Site Assessment and Conceptual Design Report
Prepared by
Colorado Parks and Wildlife
Eric E. Richer, Aquatic Research Scientist
Matt C. Kondratieff, Aquatic Research Scientist
Jon Ewert, Aquatic Biologist – Area 9
Eric R. Fetherman, Aquatic Research Scientist
Dan A. Kowalski, Aquatic Research Scientist
Tracy Kittell, Capital Development Design Supervisor
June 1, 2019
�1.
Table of Contents
Project Description .................................................................................................................. 2
2.
Site Overview .......................................................................................................................... 4
3.
4.
2.1
Habitat Project .................................................................................................................. 4
2.2
Kemp-Breeze State Wildlife Area Habitat Project .......................................................... 5
Site Assessment ....................................................................................................................... 6
3.1
Watershed Description ..................................................................................................... 6
3.2
Hydrology......................................................................................................................... 8
3.3
Hydraulics ...................................................................................................................... 12
3.4
Geomorphology.............................................................................................................. 15
3.5
Biology ........................................................................................................................... 21
Conceptual Design ................................................................................................................ 23
4.1
Project Elements ............................................................................................................. 23
4.2
Design Criteria ............................................................................................................... 26
4.3
Design Methods.............................................................................................................. 28
5.
Project Schedule .................................................................................................................... 31
6.
Project Budget ....................................................................................................................... 31
7.
References ............................................................................................................................. 33
Appendix A - Site Assessment
Appendix B - Hydrologic Data
Appendix C - HEC-RAS Model Configuration and Results
Appendix D - Fishery Information
Appendix E - Conceptual Design
1
�1. Project Description
The Upper Colorado River Habitat Project (Habitat Project) was developed in coordination with
the Municipal Subdistrict, Northern Colorado Water Conservancy District (Subdistrict) and
Denver Water to address concerns raised by Colorado Parks and Wildlife (CPW) and other
stakeholders regarding conditions of the aquatic ecosystem in the Colorado River downstream of
Windy Gap Reservoir (Subdistrict 2011). CPW, formerly the Colorado Division of Wildlife
(CDOW), documented declines in populations of Salmonfly (Pteronarcys californica), which was
historically a major source of food for trout in the Colorado River (Nehring et al. 2011). Mottled
Sculpin (Cottus bairdii) are a native fish that are important food sources for trout, occupy similar
habitat niches as Salmonflies, and have also shown population declines. Riffle habitats below
Windy Gap Reservoir were altered by changes in flow regime, water depletions, sedimentation,
and armoring of the channel bed (Nehring et al. 2011). Trout populations between Windy Gap and
Kremmling have also declined. In particular, Rainbow Trout (Oncorhynchus mykiss) populations
in the Colorado River have decreased significantly due to the prevalence of whirling disease, which
has been exacerbated by favorable conditions for whirling disease within Windy Gap Reservoir.
The goal of the Habitat Project is to design and implement a stream restoration program to improve
the existing aquatic environment in the Colorado River from the Windy Gap Diversion to the lower
terminus of the Kemp-Breeze State Wildlife Area (SWA) by returning the river to a more
functional system considering current and future hydrology. The large-scale Habitat Project
includes a study area of approximately 16.7 miles (Figure 1), but Phase 1 of the project will focus
on habitat restoration for a 1.5-mile reach within the Kemp-Breeze SWA (Appendix A). The
Kemp-Breeze project is being used as funding match for a Natural Resources Conservation Service
(NRCS) Regional Conservation Partnership Program (RCPP) award received by Trout Unlimited
for the Colorado River Headwater Project (CRHP). The CRHP includes three separate projects:
the Kemp-Breeze habitat project, a bypass project around Windy Gap Reservoir to restore fish
passage and sediment transport, and the Irrigated Lands in Vicinity of Kremmling (ILVK) project.
To fulfill requirements for the NRCS RCPP grant, the Kemp-Breeze project will be implemented
within a five to six year timeframe that began in 2017.
The objective of this report is to provide an initial site assessment and conceptual design for Phase
1 of the habitat project that will be implemented on the Kemp-Breeze SWA. Goals and objectives
for the Kemp-Breeze SWA Habitat Project are summarized in Table 1.
2
�Figure 1. Location map for the greater Upper Colorado River Habitat Project reprinted from Municipal Subdistrict (2011a).
3
�Table 1. Goals and objectives for the Kemp-Breeze SWA Habitat Project on the Colorado River.
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Project Goals
Improve sediment transport processes
Improve floodplain connectivity
Restore and enhance riparian corridors
Improve habitat for Mottled Sculpin and Salmonflies
Improve the quality and diversity of trout habitat
Restore benthic macroinvertebrate populations
Objectives
Increase sediment transport capacity and competence by manipulating channel dimensions
Decrease the prevalence of fine sediment and reduce embeddedness within riffle habitats
Increase the frequency of flushing flow events in riffle habitats under the future flow regime
by manipulating channel dimensions
Activate floodplains with a frequency of 1-3 years under the future flow regime
Increase the density of native riparian vegetation along streambanks and floodplains to
increase flood resilience and improve wildlife habitat
Increase the density of Mottled Sculpin and Salmonflies within the project reach
Increase trout population biomass (lbs/acre) and quality (# of fish > 14”/acre)
Increase Rainbow Trout reproduction (fry density) and recruitment (adult density)
Increase habitat suitability and diversity for Rainbow Trout, Brown Trout, and Mottled
Sculpin by improving instream hydraulics
Increase the abundance, distribution, and diversity of benthic macroinvertebrates
2. Site Overview
General site descriptions for the greater Habitat Project and the Kemp-Breeze SWA are provided
below. The Kemp-Breeze SWA Habitat Project is considered Phase 1 of the greater Habitat
Project.
2.1 Habitat Project
The greater Habitat Project extends from the Windy Gap dam to the downstream boundary of the
Kemp-Breeze SWA (Figure 1). This project encompasses 16.7 miles of river, of which 9.3 miles
is privately owned and 7.4 miles is available for public access, mainly through SWAs. Upstream
of the town of Hot Sulphur Springs, land status is dominated by private ownership while
downstream of Hot Sulphur Springs the river is mostly public. A core concept that plays a
dominant role in defining habitat deficiencies is the fact that the channel in this section of the
Colorado River was defined by historic flows of a greater magnitude than typically occurs now.
For example, peak flows for the Fraser River at Winter Park have decreased by ~50% while peak
flows for the Colorado River near Granby have decreased by ~95%. Hydrologic alteration has also
4
�affected baseflows in the upper Colorado River, which are spread across an extremely wide and
shallow channel exhibiting very high width-to-depth (W/D) ratios. In many places, these wide
riffles are so shallow that they may create seasonal barriers to fish movement. Reduced flows have
also decreased sediment transport capacity, while sediment supplies have decreased due to the
construction of channel-spanning dams on the main stem and tributaries of the Colorado River.
In addition to the effects of reservoirs and transbasin diversions on hydrology and sediment, there
are several large irrigation diversions on this section of the Colorado River. Some of the structures
are poorly designed, essentially “push-up dams” that require irrigators to rebuild the diversions
with heavy equipment after high water years. In addition, the larger ditches are known to entrain
fish but the impact of this entrainment is not well studied. Therefore, the overall Habitat Project
should consider the systematic modernization of diversion structures so they are rebuilt in a more
permanent design that allows for fish passage and sediment transport, while reducing maintenance
needs and frequency of disturbance to the channel. Strategies for preventing fish entrainment into
ditch systems should be examined as well.
2.2 Kemp-Breeze State Wildlife Area Habitat Project
Phase 1 of the greater habitat project will focus on stream restoration in the Kemp-Breeze SWA.
This initial project will provide guidance for future phases of the larger habitat project on the upper
Colorado River. The upper section of the Kemp-Breeze SWA is privately owned to the midline of
the channel on river right, and public property to the midline on river left. The Williams Fork
River, the largest tributary in the study area, joins the Colorado River midway through this section
and contributes significant flows to the river, at times doubling the flow. Water in the Williams
Fork is released from the bottom of Williams Fork Reservoir two miles upstream from the
confluence. As a result, the Williams Fork has a beneficial cooling effect on temperatures in the
Colorado River during the summer and fall. Conversely, the project reach remains open and
relatively free of anchor ice during the winter compared to reaches upstream of the Williams Fork.
The reach upstream of the Williams Fork confluence displays major habitat deficiencies and would
likely benefit greatly from habitat improvements. This is one of the warmest reaches on the
Colorado River and can suffer from critically high temperatures during drought and baseflow
periods. Habitat work that narrows and deepens the channel could have a moderating effect on
these high-temperature episodes by reducing surface area exposed to solar radiation and increasing
floodplain connectivity. However, CPW has not received landowner permission to implement the
habitat project on the upper mile of the Kemp-Breeze SWA. Therefore, the upstream extent of the
Kemp-Breeze SWA habitat project will begin at the “Parshall Hole” (UTM: 399,201 E; 4,435,354
N) and end at the lower boundary of the SWA (UTM: 396,785 E; 4,435,236 N). The length of the
project reach is approximately 1.5 miles, and CPW is the sole property owner for the entire extent
of the proposed reach. Site maps for the Kemp-Breeze SWA are included in Appendix A.
5
�The Parshall Hole is one of the most heavily fished locations in Grand County, in part because
inputs from the Williams Fork River results in the water staying open through most of the winter
while the majority of the river elsewhere is covered in ice and snow. The Breeze Bridge roughly
bisects the section of river contained in the Kemp-Breeze SWA. The reach between the Parshall
Hole and Breeze Bridge is probably the most-heavily fished section of the Colorado River in Grand
County. Habitat conditions in this reach could be described as moderately degraded relative to the
other reaches discussed in this report. Riffles in this reach appear to be moderately embedded and
are over-wide at base flows. During seasonal low flows, the river spreads across these riffles and
becomes extremely shallow. Thalweg definition and targeted channel narrowing through point-bar
and pool enhancement and other techniques would benefit this reach. If riffle de-armoring proves
successful, the riffles in this reach are good candidates for that treatment as well.
The Colorado River downstream of Breeze Bridge is lower quality habitat than the reach above
the bridge. In particular, the 1,400-ft section towards the bottom of the SWA contains a single long
riffle in which the habitat is almost entirely featureless. At baseflows this section is likely a barrier
to fish movement as the water spreads across an extremely wide channel (>150 ft) at a depth of
only a few inches. Immediately below the Breeze Bridge is a push-up dam that diverts water into
the Williams Ditch, which is used to irrigate hay meadows downstream of the SWA. Downstream
of the Williams Ditch, there is an older habitat project consisting of alternating “barbs” which
provide thalweg definition and tend to hold a higher density of fish. However, immediately
downstream of each barb structure are warm, shallow depositional zones with deep accumulations
of fine sediment, which could serve as Tubifex tubifex worm habitat that perpetuates whirling
disease infection in downstream trout populations.
3. Site Assessment
Watershed characteristics, hydrology, channel hydraulics, geomorphology, and biology were
investigated and summarized below. Site assessment maps, photo points, and historical aerial
imagery for the Kemp-Breeze SWA are presented in Appendix A.
3.1 Watershed Description
The USGS Stream Stats application was used to derive basin characteristics for the project reach
(Appendix B). The contributing area for the Colorado River at the lower terminus of the KempBreeze SWA is 1,160 square miles. Average annual precipitation is 25.2 in and runoff is primarily
driven by snowmelt. The elevation ranges from 7,490-14,259 ft, with an average elevation of 9,665
ft. The basin is 52% forested and only 1% of the basin is classified as developed (urban) based on
the 2011 National Land Cover Dataset. The upstream drainage network consists of the Colorado
River and its primary tributaries, including the Fraser River, Willow Creek, and the Williams Fork.
There are numerous reservoirs upstream of the project reach that alter hydrology and sediment
6
�Figure 2. Watershed map for the Colorado River at the Kemp-Breeze SWA.
7
�supply, including Shadow Mountain Reservoir, Lake Granby and Windy Gap Reservoir on the
Colorado River, Willow Creek Reservoir, and Williams Fork Reservoir (Figure 2). The reservoirs
are part of the Colorado-Big Thompson (CBT) project and Moffat collection system, which divert
water from the Colorado and Fraser rivers under the continental divide via the Adams and Moffat
tunnels, respectively, to municipalities and agricultural lands along the Colorado Front Range. The
Windy Gap and Moffat Firming Projects plan to divert additional water from the upper Colorado
River watershed, which led to the development of the habitat project as mitigation for the firming
projects. Additional information on the upper Colorado River, including the project reach, is
available in the Grand County Stream Management Plan (Tetra Tech 2010).
3.2 Hydrology
Methods- Historic, current, and future hydrology were evaluated in support of the site assessment
and conceptual design for the Kemp-Breeze SWA project. The USGS Stream Stats application
was used to characterize various hydrologic metrics for historical or “unaltered” conditions.
Average daily discharge and peak annual discharge data were obtained for various stream gages
throughout the watershed. The Indicators of Hydrologic Alteration (IHA) software application was
used to analyze current hydrology at the Colorado River Near Parshall stream gage, which is
located just upstream of the Breeze Bridge in the middle of the project reach. Finally, the Moffat
Firming Project Environmental Impact Statement (EIS) was used to obtain hydrologic data for
both current and future hydrology based on modelled outputs from PACSM (ACOE 2014). Note
that the future hydrology reported in the Moffat EIS accounts for the effects of both the Moffat
and Windy Gap firming projects.
Data sources used for analysis of daily, monthly, and annual averages are listed below:
USGS Stream Stats application (regional regression equations) – “unaltered” conditions
Colorado River near Parshall stream gage (1996-2018) – current conditions
PACSM Model Output for Current Conditions (1946-1991) – current conditions
PACSM Model Output for Alternative 1a – future conditions
Due to different periods of analysis, hydrologic data were compared across the various data sources
when possible. Average annual, monthly, and daily flow statistics were calculated and compared
to summarized values reported in the Moffat EIS (ACOE 2014). The USGS Stream Stats
application uses regional regression equations to estimate flow statistics and is considered to
represent “unaltered” hydrology for this analysis. Although there is high uncertainty regarding the
accuracy of Stream Stats results, including estimates of unaltered hydrology is important for
understanding the potential effects of hydrologic alteration on geomorphology and channel
evolution. Current conditions were derived from observed data at the Colorado River near Parshall
stream gage for 1996-2018 and compared to current conditions from the PACSM model for 19461991. Flow magnitude and variability were also evaluated during critical periods for early-life
stages of trout (Nehring and Andersen 1993). Future conditions are based on the Alternative 1a
scenario (the “preferred alternative”) reported in the Moffat EIS.
8
�Flood-frequency analysis was used to investigate peak flows for “unaltered”, current, and future
conditions. Data sources used for flood frequency analysis are listed below:
USGS Stream Stats application (regional regression equations) – “unaltered” conditions
Colorado River near Parshall (1992-2018), logarithmic regression – current conditions
Colorado River near Parshall (1992-2018), IHA – current conditions
PACSM Model Output for Current Conditions (1946-1991) – current conditions
PACSM Model Output for Alternative 1a – future conditions
Results- Average monthly and annual flows for “unaltered”, current, and future conditions are
compared in Table 2. Summary statistics for daily discharge values at the Colorado River near
Parshall stream gage are presented in Figure 3.
Table 2. Average monthly and annual flows (cfs) for “unaltered”, current, and future conditions
from various data sources and summary periods for the Colorado River below the Williams Fork.
Source
Period
October
November
December
January
February
March
April
May
June
July
August
September
Annual
Stream Stats
Unaltered
287
228
197
191
179
234
696
1,990
2,260
794
357
294
608
Parshall Gage
Current (1996-2018)
269
222
178
167
166
215
429
956
1,446
654
381
301
449
PACSM
Current (1946-1991)
270
231
186
192
174
212
376
478
802
583
355
290
346
PACSM
Future (Alt 1a)
268
229
185
191
173
212
374
470
729
554
352
287
335
Average flows and flow variability as the coefficient of variability (CV) during critical early lifestages for Brown Trout and Rainbow Trout are presented in Figure 4. In general, flows are higher
in magnitude and more variable during early life-stages for Rainbow Trout when compared to
Brown Trout. The results from flood-frequency analysis are presented in Table 3 and Figure 5.
The most recent stream flows data (1992-2018) results in larger magnitude flows for the same
return intervals when compared to the PACSM data for current hydrology (1946-1991). This
indicates that the past 27 years were wetter than the preceding 46 years, which could be explained
by the different periods of record or a changing climate. Reconciling the differences in current
hydrology (1946-1991 vs. 1992-2018) will be important for identifying optimal channel
dimensions for the restoration project. The IHA output, Stream Stats report, and select PACSM
outputs are included in Appendix B.
9
�Average Daily Discharge (cfs)
6,000
5,000
4,000
(A)
Max
Average
Min
3,000
2,000
1,000
0
1-Oct 1-Nov 1-Dec 1-Jan 1-Feb 1-Mar 1-Apr 1-May 1-Jun 1-Jul 1-Aug 1-Sep
Average Daily Discharge (cfs)
2,500
2,000
1,500
(B)
Q3
Median
Q1
1,000
500
0
1-Oct 1-Nov 1-Dec 1-Jan 1-Feb 1-Mar 1-Apr 1-May 1-Jun 1-Jul 1-Aug 1-Sep
Average Daily Discharge (cfs)
1,800
1,600
1,400
(C)
Average
Median
1,200
1,000
800
600
400
200
0
1-Oct 1-Nov 1-Dec 1-Jan 1-Feb 1-Mar 1-Apr 1-May 1-Jun 1-Jul 1-Aug 1-Sep
Figure 3. (A) Maximum, average and minimum daily discharge values, (B) quartiles for daily
discharge values, and (C) comparison of the average and median daily discharge values for the
Colorado River near Parshall stream gage, 1996-2018.
10
�Average Discharge (cfs)
1,600
1,400
1,200
(A)
Brown Trout
Rainbow Trout
1,000
800
600
400
200
0
Flow Variability as CV
1.00
0.80
(B)
Brown Trout
Rainbow Trout
0.60
0.40
0.20
0.00
Spawning
Incubation
Hatching
Emergence
Figure 4. (A) Average daily discharge values and (B) discharge variability as the coefficient of
variation (CV) for the Colorado River near Parshall stream gage (1996-2018) during spawning,
incubation, hatching, and emergence early life stages for Brown Trout and Rainbow Trout. Dates
for early life stage periods were taken from Nehring and Andersen (1993).
Table 3. Flood-frequency results for “unaltered”, current, and future conditions from various data
sources and summary periods for the Colorado River below the Williams Fork. All values are in
cubic feet per second (cfs). RI = Return Interval.
Data Source
Stream Stats
RI (years)
Unaltered
1.01
1.5
2
5
10
25
50
100
2,605
3,114
3,410
4,760
5,780
6,390
7,680
8,630
Parshall Gage
Parshall Gage
- IHA
PACSM
PACSM
Current
(1992-2018)
590
1,290
1,800
3,425
4,654
6,279
7,509
8,738
Current
(1992-2018)
461
1,360
2,112
3,730
4,641
5,638
7,081
8,198
Current
(1946-1991)
458
958
1,083
2,875
3,750
5,208
6,235
7,285
Future
(Alt 1a)
396
917
1,000
2,542
4,083
6,083
7,029
8,264
11
�Peak Discharge (cfs)
10,000
9,000
Future: Alternative 1a
8,000
Current: 1946-1991
7,000
Current: 1992-2018
6,000
Current-IHA: 1992-2018
5,000
Unaltered: Stream Stats
4,000
3,000
2,000
1,000
0
1.01
1.5
2
5
10
Return Interval (years)
25
50
100
Figure 5. Flood-frequency results for “unaltered”, current, and future conditions from various data
sources and summary periods for the Colorado River below the Williams Fork.
3.3 Hydraulics
Methods- Channel hydraulics affect sediment transport, channel morphology, and the quality of
instream habitat. To investigate channel hydraulics for existing conditions, a one-dimensional (1D)
hydraulic model was configured using HEC-RAS v5.0.3 (ACOE 2016). Existing channel and
floodplain morphology were surveyed with a Trimble GNSS surveying system. Additional
bathymetry points were surveyed with SonTek ADP HydroSurveyor within the wetted channel.
The baseline survey was conducted during October 15-19, 2018. Pebble counts and photo points
were also conducted during the baseline survey. Flows at the Colorado River near Parshall stream
gage ranged from 175-226 cfs during the survey, and a flow value of 188 cfs was selected for
model calibration. Ten flow values were selected for analysis of existing conditions with HECRAS based on the current hydrology (1992-2018; Table 4). Hydraulic conditions at the Breeze
Bridge were modeled using the Yarnell method for low flows, a coefficient for twin-cylinder piers
without a diaphragm, and the Pressure and/or Weir method for high flows (ACOE 2016). A scour
analysis was not performed for the bridge but should be considered during the next design phases.
The bridge modeling approach may also need to be revisited.
To calibrate the model for existing conditions at baseflow, Manning’s n was varied between 0.0450.061 within the active channel to minimize the difference between surveyed and modeled water
surface elevations (WSE) across all HEC-RAS cross-sections. For the calibration flow, a
Manning’s n value of 0.061 resulted in the minimum difference between survey and modeled
12
�WSE, with a median difference of 0.01 ft and a range of -0.16-0.67 ft. This Manning’s value is
relatively high but is within the range of expected values (0.040-0.070) for mountain streambeds
that consist of cobbles and large boulders (ACOE 2016). As Manning’s n is known to decrease as
stage increases (Chow 1959), n values were varied vertically in HEC-RAS based on flow.
Manning’s n for the bankfull flow was estimated using methods outlined in Rosgen (2008) and a
high flow Manning’s n of 0.035 was selected from a range of published values (ACOE 2016).
Roughness values for other flow profiles were interpolated between the selected baseflow,
bankfull, and high flows values. The variation in Manning’s n with flow for the stream channel is
presented in Table 5, while Manning’s n values for overbank areas are presented in Table 6.
Table 4. Discharge values (Q) selected for analysis of existing conditions with HEC-RAS.
Discharge records from the Colorado River near Parshall stream gage were used to select all
profiles.
Profile
1
Q (cfs)
170
2
250
3
480
4
5
6
7
8
9
10
950
1300
1950
3150
4750
6000
7500
Description and Data Source
Baseflow; Average daily discharge records (1996-2018)
Average flow during Brown Trout spawning period;
Average daily discharge records (1996-2018)
Average flow during Rainbow Trout spawning period;
Average daily discharge records (1996-2018)
Average flow during May; Average daily discharge records (1996-2018)
1.5-year return interval; Peak flow records (1992-2018)
2-year return interval; Peak flow records (1992-2018)
5-year return interval; Peak flow records (1992-2018)
10-year return interval; Peak flow records (1992-2018)
25-year return interval; Peak flow records (1992-2018)
50-year return interval; Peak flow records (1992-2018)
Table 5. The variation in Manning’s n values with discharge (Q) for the active channel used for
analysis of existing conditions with HEC-RAS.
Profile
1
2
3
4
5
6
7
8
9
10
Q (cfs)
170
250
480
950
1300
1950
3150
4750
6000
7500
Description
Baseflow (calibrated)
Brown Trout spawn
Rainbow Trout spawn
May average
1.5-year (calculated)
2-year
5-year
10-year (estimated)
25-year
50-year
13
Manning’s n
0.061
0.059
0.055
0.046
0.039
0.038
0.037
0.035
0.035
0.035
�Table 6. Manning’s n values for overbank area used in HEC-RAS model configuration for existing
conditions. All values were taken from Table 3-1 in ACOE (2016).
Description
Earthen ditch with some grass and weeds
Hay pasture with high grass
Wetland with scattered brush
Riparian area with willows
Riparian area with cottonwood trees and willows
Manning’s n
0.030
0.035
0.065
0.075
0.095
Results- Results from the hydraulic model can be used to characterize existing conditions and
inform restoration design. Results for existing conditions will be compared to hydraulic models
for the preliminary design once completed to evaluate changes in hydraulic variables. Hydraulic
variables, such as depth and velocity, can also be used to investigate habitat suitability for target
species. The estimated bankfull flow of 1,300 cfs was used to summarize channel hydraulics for
the project reach for all cross-sections, riffles, and pools in Table 7. Hydraulic variables are
described in the HEC-RAS manual (ACOE 2016). The HEC-RAS model configuration and
outputs for existing conditions, including survey layout, flow profiles, cross-sections, and
complete results, are presented in Appendix C.
Table 7. Summarized HEC-RAS results for the estimated bankfull flow of 1,300 cfs for all crosssections, riffle cross-sections, and pool cross-sections within the Kemp-Breeze SWA. Average
values are reported followed by the standard deviation in parentheses. Velocity, Froude #,
hydraulic radius, total stream power, and shear stress are reported for the active channel.
Hydraulic Variable
Energy Slope
Friction Slope
Velocity (ft/s)
Area (sq-ft)
Width (ft)
Depth (ft)
Width/Depth
Froude #
Hydraulic Radius (ft)
Total Stream Power (lb/ft*s)
Shear Stress (lb/sq-ft)
Dimensionless Shear Stress
n
All Cross-Sections
0.0033 (±0.0023)
0.0031 (±0.0011)
3.79 (±0.49)
349 (±42)
143 (±17)
2.48 (±0.46)
61 (±18)
0.43 (±0.10)
2.52 (±0.51)
1.86 (±1.08)
0.47 (±0.17)
0.017 (±0.006)
69
Riffle Cross-Sections
0.0040 (±0.0027)
0.0034 (±0.0010)
3.97 (±0.48)
333 (±35)
148 (±15)
2.26 (±0.31)
68 (±17)
0.47 (±0.10)
2.27 (±0.30)
2.18 (±1.24)
0.53 (±0.18)
0.020 (±0.007)
41
Pool Cross-Sections
0.0021 (±0.0010)
0.0025 (±0.0010)
3.44 (±0.35)
383 (±38)
137 (±18)
2.84 (±0.45)
50 (±14)
0.36 (±0.07)
2.89 (±0.51)
1.27 (±0.45)
0.36 (±0.09)
0.013 (±0.003)
14
Energy and friction slopes were both greater in riffle locations compared to pools, as would be
expected. Average velocity was as also high in riffles compared to pools, and average riffle
velocity agrees the with the national average for bankfull flows of 4 ft/s. Given the lower velocity,
cross-section area was greater in pools compared to riffles. However, the average width in pool
cross-sections at the bankfull flow was lower than the width at riffle cross-section. This diverges
from the expected morphology for natural river channels, where pools are typically wider than
14
�riffles. For example, Soar and Thorne (2001) reports than maximum pool width is typically 1.35
times the bankfull width in riffles for Rosgen B stream types. Results from hydraulic modeling
also indicate that W/D is very high (68) in riffle locations and across the entire reach (61). W/D
ratios are even higher at low flows (i.e., 170 cfs), with average values of 136 for riffle crosssections 115 for all cross-sections. Dimensionless shear stress was calculated using a D50 sediment
size of 80 mm, the hydraulic radius for the channel, and the energy slope for the bankfull flow of
1,300 cfs (Table 7). The resultant values (0.020 ± 0.007) indicate that there is likely inadequate
shear stress at 1,300 cfs to mobile the D50 sediment size in riffle locations. Critical dimensionless
shear stress was estimated at 0.032 using the Wilcock and Kenworthy (2002) method for bedload
transport, and values for cobble substrate can be as high as 0.052-0.054 (Julien 1998). These results
indicate that the project reach is over wide and has low sediment transport capacity with its current
form and altered flow regime.
3.4 Geomorphology
Methods- To support assessment of geomorphology, the project reach was broken into four distinct
reaches. Reaches were identified from riffle crest locations based on a combination of geomorphic
characteristics and design constraints. Reach breaks and descriptions are provided in Table 8. Data
from topographic surveys were used to evaluate the longitudinal profile and cross-section
morphology for individual reaches and the entire project reach. The longitudinal profile was used
to investigate stream channel and water surface slopes, bedform diversity, and pool-to-pool
spacing. Note that the longitudinal profile follows the channel thalweg, whereas the HEC-RAS
profile follows the stream centerline. Therefore, the stationing for HEC-RAS cross-sections does
not align with the stationing from the longitudinal profile. Two riffle cross-sections were selected
within each reach to characterize channel dimensions, including W/D ratios and entrenchment
ratios. Cross-sections 6367.85 and 5910.06 were selected for Reach 1, 5130.32 and 4513.76 were
selected for Reach 2, 3980.46 and 3402.19 were selected for Reach 3, and 1677.02 and 7.86 were
selected for Reach 4.
Pebble counts were conducted in three locations using various methods. First, representative and
active-bed pebble counts were conducted in three locations using methods outlined in Rosgen
(2006). As traditional pebble counts can underestimate the proportion of fines, a grid-frame
method was also used at two of the active-bed locations (Bunte and Abt 2001). Geomorphic
characteristics were used to classify stream morphology with two different classification methods
(Rosgen 1994; Montgomery and Buffington 1997). We should note that classification systems
typically apply to natural stream systems and that the project reach has been altered by decades of
flow alteration and reduced sediment supply. Regardless, geomorphic characteristics and
classifications are useful for comparing morphology between reaches and identifying strategies
for restoration.
15
�Table 8. Reach descriptions including thalweg stationing (start and end) and relative restoration
priority for geomorphic characterization of the Colorado River though the Kemp-Breeze SWA.
Reach
Start
End
1
8,655 ft
5,698 ft
2
5,698 ft
4,521 ft
3
4,521 ft
2,981 ft
4
2,981 ft
57 ft
Priority
Description
The reach starts at the Parshall Hole and extends to
the first riffle crest upstream of the Breeze Bridge.
Moderate Island formation suggests that the reach is tending
towards aggradation. The reach has relatively good
habitat diversity compared to other reaches.
The reach extends from the riffle upstream of the
Breeze Bridge to the first riffle crest below the
Williams Diversion. The reach is characterized by
Moderate
infrastructure, including the bridge, the Colorado
River near Parshall stream gage, and the Williams
Diversion.
The reach extends from the first riffle crest
downstream of the Williams Diversion to the first
riffle crest below the location of previous habitat
work completed during the 1980s or 1990s. The
High
previous work consists of the downstream facing
“barbs” constructed from native or imported
alluvium. The barbs create large backwater areas
downstream of each structure that provide little to no
beneficial habitat for target aquatic species.
The lowermost reach starts below the barb section and
extends to the last riffle crest in the project reach. The
upper section of this reach includes a very steep riffle
and long pool. Below the pool, there is a long
High
featureless riffle that provides little to no trout habitat.
The bottom of the reach enters a highly-confined
valley bounded by high terraces and very little
adjacent floodplain.
Effective discharge is the channel-forming discharge that transports the largest fraction of the bed
material load (Biedenharn et al., 2000). For a preliminary investigation into sediment transport
within the project reach, effective discharge was estimated for three cross-sections (5910.06,
3402.19, and 1676.02) using results from the HEC-RAS model and pebble counts. Effective
discharge was analyzed using current hydrology (1996-2018) and the Wilcock and Kenworthy
(2002) bed-load transport method. Results from the HEC-RAS model were also used to
characterize shear stress in the channel, total stream power in the channel, and the W/D for all
cross-sections and flow profiles. Effective discharge was also reported in the Moffat EIS (ACOE,
2014) and select figures have been included in Appendix B. Finally, historical aerial images
(Appendix A) were obtained for the project reach and used to assess changes in geomorphology.
16
�Results- All results from geomorphic characterization are presented in Table 9. Reach 1 had the
highest bed form diversity (50% pool) and lowest sinuosity, which is counterintuitive but
highlights the importance of island formation on habitat complexity. There is large island complex
above Reach 1 that creates a deep, compound pool (the Parshall Hole) where the island channels
converge. Historical aerial images indicate that this island complex has been present since at least
the 1930s (Appendix A). Historical images from 1938 suggest that there was a large alluvial fan
at the confluence of the William Fork and Colorado River, which is located upstream of the island
complex above the Parshall hole. Williams Fork Reservoir was completed in 1938, and the historic
alluvial fan has become vegetated since the sediment supply from the Williams Fork was disrupted
by the reservoir. Island formation in Reach 1 is evident in 1946 and more recent imagery indicates
that islands have become larger and more vegetated through time. Convergence pools are located
downstream of the islands, and channels around the island provide diverse habitat that supports
juvenile and fry life stages of trout.
Table 9. Geomorphic assessment results for project reaches on the Kemp-Breeze SWA. Rosgen
classification was based on Rosgen (1994) while the M/B classification was based on Montgomery
and Buffington (1997). Note: “PR” = pool riffle and “PB” = plane bed.
Variable
Bankfull Area (sq-ft)
Bankfull Width (ft)
Bankfull Mean Depth (ft)
Bankfull W/D
Entrenchment Ratio
Reach Length (ft)
Sinuosity
Water Surface Slope
Streambed Slope
D50 Particle Class
Rosgen Classification
M/B Classification
Percent Riffle
Percent Pool
Pool Spacing Range (ft)
Pool Spacing Range/Width
Mean Pool Spacing (ft)
Mean Pool Spacing/Width
Reach 1
361
154
2.3
66
1.3
2,954
1.05
0.0031
0.0029
Cobble
F3/B3c
PR
50%
50%
426-534
2.8-3.5
492
3.2
Reach 2
387
145
2.6
56
1.4
1,177
1.09
0.0026
0.0031
Cobble
F3/B3c
PB/PR
73%
27%
638
4.4
588
4.1
Reach 3
434
151
2.9
52
1.4
1,540
1.23
0.0020
0.0019
Cobble
F3/B3c
PB/PR
77%
23%
332-708
2.2-4.7
513
3.4
Reach 4
413
172
2.4
72
1.2
2,924
1.09
0.0030
0.0027
Cobble
F3
PB/PR
65%
35%
2,110
12
1,462
8.5
All Reaches
399
155
2.6
61
1.3
8,652
1.11
0.0030
0.0029
Cobble
F3/B3c
PB/PR
63%
37%
332-2,110
2.1-13.6
661
4.3
Reach 2 is characterized by infrastructure, including a stream gage, bridge, and diversion structure.
This infrastructure has a controlling influence on geomorphology in Reach 2. Both pools in Reach
2 are associated with infrastructure, with one pool below the Breeze Bridge and the other pool
below the Williams diversion structure. Reach 3 had the lowest slope and highest sinuosity. The
“barb” treatments in this reach are responsible for the increased sinuosity. However, the barbs have
17
�not resulted in the formation of pools, as Reach 3 had the lowest pool percentage (23%) of all
reaches. Reach 4 is characterized by two large, compound pools separated by a long featureless
riffle. Results from pebble counts are presented in Table 10 and Figure 6. Pebble counts indicate
that the dominant sediment size is small cobble (64-128 mm). All of the reaches ranged from
entrenched to moderately entrenched, resulting in Rosgen classifications of F3 or B3c (Rosgen
1994). Reach 1 appears to have pool-riffle morphology, but all other reaches have a mixed
morphology of pool-riffle and plane bed (Montgomery and Buffington 1997). However, the effects
of infrastructure in Reach 2 and the barb treatments in Reach 3 have affected channel morphology,
as have the altered hydrology and sediment supply.
Table 10. Sediment classification for different sites and methods within the Kemp-Breeze SWA.
Reach
1
3
4
All
Site
Method
PC1
PC1A
PC1A
PC2
PC2A
PC2A
PC3
PC3A
All
Representative
Active Bed
Grid Frame
Representative
Active Bed
Grid Frame
Representative
Active Bed
All
Particle Size (mm)
D16
D50
D84
59
136
240
60
114
170
31
79
136
0.13
121
252
8
78
157
16
80
143
48
124
215
66
120
195
41
114
203
n
100
100
336
100
100
100
100
100
1036
W/D ratios were very high, ranging from 52-66 at the select cross-sections that were included in
analysis of geomorphology. The average W/D for Rosgen B3, C3, and F3 stream types is 19, 33,
and 38, respectively (Rosgen 1996). The high W/D indicates that the channel lacks the capacity to
move sediment, especially when cumulative impacts of the flow alteration are taken into account.
Results from the effective discharge analysis are presented in Figures 7-8. The effective discharge
for all three cross-sections was 4,447 cfs, which has a return interval of 9-years. Effective discharge
values reported in the Moffat EIS utilized numerous sediment transport equations and ranged from
1,627-5,612 cfs for current conditions, and 1,244-5,612 for future conditions (Appendix B).
Bankfull discharge is typically assumed to have a return interval of 1.5-2.0 years in unaltered
Colorado mountain streams, and the effective discharge typically occurs within 20% of the
bankfull discharge (Torizzo and Pitlick, 2004). The magnitude of effective discharge estimates
relative to the 1.5-year flood further illustrates the lack of sediment transport capacity in the project
reach. Furthermore, bedload transport does not initiate until flows reach approximately 2,000 cfs
(Figure 8; Appendix B), which is 54% higher than the current bankfull flow estimate of 1,300 cfs.
As hydrology cannot be restored, channel narrowing is the primary means to improve sediment
transport capacity and associated aquatic habitats.
18
�% Cumulative (Finer Than)
100%
90%
80%
70%
(A)
Representative
Riffle: Active Bed
Riffle: Grid Frame
60%
50%
40%
30%
20%
10%
0%
0.01
0.1
1
10
100
1000
10000
% Cumulative (Finer Than)
100%
90%
80%
70%
Representative
Riffle: Active Bed
Riffle: Grid Frame
(B)
60%
50%
40%
30%
20%
10%
0%
0.01
0.1
1
10
100
1000
% Cumulative (Finer Than)
100%
90%
Representative
80%
Riffle: Active Bed
10000
(C)
70%
60%
50%
40%
30%
20%
10%
0%
0.01
0.1
1
10
Particle Size (mm)
100
1000
10000
Figure 6. Results from representative, active-bed, and grid-frame pebble counts within (A) Reach
1, (B) Reach 3, and (C) Reach 4.
19
�0.06
Station 5910
Effectiveness (tons/day)
0.05
Station 3402
Station 1676
0.04
0.03
0.02
0.01
0.00
0
1,000
2,000
3,000
Q (cfs)
4,000
5,000
6,000
Figure 7. Effective discharge results for three HEC-RAS cross-sections within the Colorado River
on the Kemp-Breeze SWA.
70
Station 5910
60
Station 3402
Qs (tons/day)
50
Station 1676
40
30
20
10
0
0
1,000
2,000
3,000
Q (cfs)
4,000
5,000
6,000
Figure 8. Bed load transport rates (Qs) for three HEC-RAS cross-sections within the Colorado
River on the Kemp-Breeze SWA.
20
�3.5 Biology
Trout Populations
CPW conducts annual fish population surveys on the project reach using raft electrofishing, and
survey data for this station extends back to 1981. Overall fish population densities remain high,
although the quality of the fishery, as measured by the density of fish greater than 14” total length
(TL), has experienced a slow but steady decline. The prevalence of whirling disease has resulted
in a shift towards a Brown Trout-dominated fishery over the past two decades. The latest Fishery
Management Report for the Kemp-Breeze SWA includes a summary of the fishery and is included
in Appendix D.
Mottled Sculpin
Sculpin are an ecologically important part of freshwater ecosystems because they can occur in high
densities in depauperate coldwater mountain streams (Adams and Schmetterling 2007).
Additionally, sculpin can exert a large influence on aquatic food webs through their diverse trophic
positions. The Mottled Sculpin (Cottus bairdii) is common in coldwater western Colorado streams
where they occur in sympatry with important sport and native trout species. Mottled Sculpin prefer
cool, high gradient mountain streams with cobble habitat and are rarely found in stream reaches
where substrate is embedded with silt (Sigler and Miller 1973; Woodling 1985; Nehring et al.
2011). As such, their habitat preferences for cobble substrate and high quality riffle-run habitat
make Mottled Sculpin a good ecological indicator of stream health (Adams and Schmetterling
2007; Nehring et al. 2011).
Dams are known to drastically alter river habitat and have many diverse effects on fish and
invertebrate habitat and populations (Ward and Stanford 1979). Dams can radically alter stream
temperature and substrate composition, which are considered primary influences of sculpin habitat
suitability (Scott and Crossman 1973). In the upper Colorado River basin, stream reaches below
many dams and water projects have reduced density of Mottled Sculpin (Nehring et al. 2011).
Mottled Sculpin were common in the main stem Colorado River before Windy Gap Reservoir was
built, but are rare or absent after construction (Erickson 1983; Nehring et al. 2011). A survey
conducted in 1975-1976 on the Colorado River before Windy Gap Reservoir was constructed
documented Mottled Sculpin at all sampling sites (Dames and Moore 1977). In 2010, sculpin
density in the upper Colorado River was 15 times higher at sites upstream of impoundments than
downstream (Nehring et al. 2011). This study attributed the decline of Mottled Sculpin to habitat
and flow changes associated with Windy Gap Reservoir. Surveys conducted by CPW in 2013
confirmed these patterns, finding that sculpin were common upstream of impoundments on the
upper Colorado River, but rare or absent downstream (Kowalski 2014). No Mottled Sculpin were
detected on the Kemp-Breeze SWA during adult population or fry surveys in 2018. The last
documented observation of sculpin within the Kemp-Breeze SWA was reported in 1998. Restoring
connectivity around Windy Gap Reservoir and addressing habitat limitations associated with flow
and sediment regimes should improve conditions for this important native fish in the upper
Colorado River.
21
�Benthic Macroinvertebrates
Dams are known to drastically alter river habitat and have many diverse effects on aquatic
invertebrates (Ward and Stanford 1979). Those effects can be large and result in long-term changes
to invertebrate communities (Vinson 2001). In the upper Colorado River basin, previous studies
documented a dramatic change of the aquatic invertebrate community following construction of
Windy Gap Reservoir and that these changes may be associated with flow alterations (Nehring et
al. 2011). The diversity of aquatic invertebrates below Windy Gap Reservoir declined by 38%
from 1980 to 2011. Nineteen species of mayflies, four species of stoneflies, and eight species of
caddisflies have been extirpated from the sampling sites since 1982. In addition to the temporal
changes in the invertebrate community, there was a spatial pattern of increasing diversity
downstream of Windy Gap Reservoir that indicated current effects of the reservoir on invertebrate
habitat and communities. Sensitive species including Drunella grandis, Pteronarcella badia, and
Pteronarcys californica were reduced or eliminated from sites close to Windy Gap Reservoir and
replaced by tolerant species including Ephemerella sp, Baetis sp, and Hydropsyche sp.
CPW surveyed benthic macroinvertebrates within the Kemp-Breeze SWA in 2018, and
preliminary results indicate that invertebrate density was relatively low compared to other sites.
The Breeze Bridge site had the lowest multimetric index (MMI) score of seven sites in the upper
Colorado River. The Breeze Bridge site also had relatively low numbers EPT taxa, which includes
desirable species of Mayflies, Stoneflies, and Caddisflies. Restoring connectivity in the upper
Colorado River and addressing habitat limitations associated with the flow and sediment regimes
should improve conditions for, and the diversity of, benthic macroinvertebrates in the Colorado
River.
Salmonflies
The Salmonfly (Pteronarcys californica), or Giant Stonefly, is a large aquatic invertebrate that can
reach high densities in some Colorado rivers. These invertebrates play an important ecological role
as grazers in stream systems and can be extremely important for stream dwelling trout as a food
resource. Nehring (1987) reported that P. californica was the most common food item in trout
diets in the Colorado River, comprising 64-75% of the mean stomach content over the four-year
study. Because of their high biomass and hatching behavior, Salmonflies also play an important
role in supplementing terrestrial food webs and riparian communities with stream-derived nutrients
(Baxter et al. 2005; Walters et al. 2018). While ecologically important, the Salmonfly has relatively
specific environmental requirements and is considered intolerant of disturbance (Erickson 1983;
Fore et al. 1996). Salmonflies are sensitive to habitat alterations in part because of their lifespan,
as they are one of the longest-lived aquatic insects in the Nearctic (DeWalt and Stewart 1995).
Although they were once common in the upper Colorado River (USFWS 1951; Dames and Moore
1977; Erickson 1983), the abundance of Salmonflies has declined, especially downstream of
Windy Gap Reservoir where flow alterations associated with trans-mountain water diversions are
greatest (Nehring et al. 2011). This pattern has been observed in other rivers. Richards (2000)
22
�documented six to eight times lower density of Salmonflies downstream of a reservoir compared
to upstream and found a negative correlation between their density and substrate embeddedness.
Habitat alterations associated with water development projects seem to have reduced habitat
quality for Salmonflies in the upper Colorado River. CPW has been investigating habitat
preferences for P. californica in Colorado rivers to guide the restoration of sites where this
important native invertebrate species has been reduced in range and numbers. Preliminary results
from this study indicate that high densities of P. californica stoneflies occurred at riffle sites with
very low fine sediment, a low W/D ratio, low cobble embeddedness and a large D50. Model
predictions for the top four habitat variables over a range of Salmonfly densities in Colorado are
presented in Table 11. These variables should be used to inform the design of riffle habitats for the
Kemp-Breeze habitat project.
Table 11. Model results of important habitat variables for a range of Salmonfly densities observed
in three Colorado Rivers.
Relative Density
Moderate Density (Q1)
Median Density
Average Density
High Density (Q3)
Maximum Density
Exuvia/m²
20.3
48.4
95.8
147.0
352.7
% Fines
12.6
9.5
6.0
3.0
0.0
D50 (mm)
64.2
103.8
149.5
187.4
295.0
% Embeddedness
35.6
27.1
17.2
9.1
0.0
Width/Depth
68.4
54.2
37.7
24.2
<24.2
4. Conceptual Design
The conceptual design for the Kemp-Breeze SWA habitat project was developed using the project
elements, design criteria, and design methods outlined below. Plan sheets for the conceptual design
are presented in Appendix E. These elements, criteria, and methods should be developed further
during the preliminary (60%) and final (90%) design stages.
4.1 Project Elements
The following project elements were used to develop the conceptual restoration design and will
provide guidance for development of the preliminary (60%) and final (90%) designs.
Channel Narrowing
Improved sediment transport capacity will be targeted through restoration treatments that focus on
channel narrowing. Current and future hydrology should be considered when developing proposed
channel dimensions. Sediment transport in riffles should be targeted to address habitat deficiencies
in these locations for Mottled Sculpin, Salmonfly, and other benthic aquatic organisms. Channel
narrowing can be achieved through a variety of treatments, including fill with native alluvium and
large woody material. Narrowing could also be achieve by creating roughened, depositional areas
that will accumulate sediment over time. Island and side-channel development should also be
considered as a means to narrow the channel and improve habitat diversity. Developing islands
23
�should also result in the formation of convergence pools downstream of islands that will provide
holding habitat for adult trout. Channel narrowing treatments should be considered a high priority
for the habitat project.
Riffle Habitats
Restoration of interstitial habitat at riffle locations may require some means of mechanical
disturbance to release fine sediments that have accumulated in the hyporheic zone. Creating and
maintaining interstitial habitat in riffles will be critically important for the restoration of Mottled
Sculpin, Salmonfly, and other benthic aquatic organisms in the Colorado River. Various treatments
have been used to clean spawning gravels for salmonids, including mechanical and hydraulic
methods that utilized a bulldozer, “riffle sifter”, or “gravel Gertie” (Cramer 2012). These
techniques are intensive and have typically been applied on a relatively small scale. Therefore,
they should be considered experimental and monitored to determine their effectiveness. Improving
sediment transport at riffle locations will be critically important for maintaining restored riffle
habitats. Flushing flows should be incorporated into the project design to address the maintenance
of hyporheic habitat in riffle locations. Improving riffle habitats may also increase prey resources
and spawning habitat, which should have a beneficial effect on the trout fishery. Riffle treatments
should be considered a high priority for the habitat project, but applied judiciously given their
potential cost, uncertain sustainability, and experimental nature.
Bedform and Habitat Diversity
Habitat conditions for Brown Trout, Rainbow Trout, and Mottled Sculpin are a primary
consideration for design development. Improving bedform diversity should increase habitat
complexity and benefit different fish species and life stages. In particular, pool development would
be beneficial for much of the project reach. Existing pools appear to have formed from various
processes, including convergence of multiple channels below islands, contraction scour where
channel width decreases substantially in an upstream riffle, and lateral scour on the outside of
meander bends. Pocket pools behind habitat features, such as boulders or logs, also have beneficial
effects on habitat diversity.
Developing side channels that remain connected during low flows can provide valuable rearing
habitat for trout fry and juvenile life stages. Placement of spawning gravels at strategic locations
(i.e., glides) should also improve trout habitat. However, creating conditions that support the
deposition of spawning gravels through natural process would provide long-term benefits for
spawning habitat and fish populations. Improving floodplain connectivity will provide trout
refugia under high flow conditions. Narrowing and re-shaping channel dimensions will provide
better trout refugia during low flow conditions, improve routing of fine sediment, improve
conditions for aquatic invertebrates and sculpin, improve or maintain trout spawning gravels,
locally reduce surface area exposed to solar radiation and associated water temperatures, and
improve conditions for fish passage at depth-limited riffle habitats. Improving bedform and habitat
diversity is considered a high priority.
24
�Riparian Vegetation
Establishing riparian vegetation along stream banks will improve the resilience of the system to
respond to extreme conditions, such as floods or fires. Improving vegetation cover within riparian
corridors will also benefit wildlife, including moose and deer. Channel narrowing activities will
also improve floodplain connectivity, creating favorable conditions for establishment and growth
of riparian vegetation. Establishing riparian vegetation is critically important for channel stability.
Restoration projects are considered most vulnerable to erosion following construction. As such,
bank stabilization measure may be needed to protect the newly established channel from
accelerated erosion until riparian vegetation can become established. CPW recommends
transplanting existing streambanks (i.e., sod mats and willow transplants) from their current
location to the edge of new channel. If additional stabilization measures are needed, bioengineering
treatment should be used so that riparian vegetation will become the dominant control on bank
stability over time. Establishing riparian vegetation along the new stream channel is a high priority
for the project.
Large Woody Material
Large woody material should be incorporated within the active channel to enhance fish habitat by
increasing complexity and providing instream cover. Treatments that incorporate large woody
material include engineered logjams, toe wood, log vanes, and habitat logs. Engineered logjams
should emulate a natural logjam, which is a crowded mass of logs within or adjacent to a stream
channel. Logjam treatments should be used on side channels to provide grade control and improve
habitat complexity. Engineered logjams can also be placed at the head of islands or other areas
where sediment deposition is desirable, but should not be placed within the active channel in a
manner that creates a hazard to boaters. Toe wood is a treatment that places large woody material
at the bank toe on the outside of meander bends to stabilize streambanks while riparian vegetation
is established. Toe wood treatments can also be used to create fish habitat in the form of undercut
banks and enhanced habitat complexity. Log vanes can also be used to stabilize streambanks and
provide fish habitat by reducing near-bank shear stress. Habitat logs should be placed in the tail
out of pools and anchored with boulders or native alluvium to provide cover for fish. Given the
potential cost associated with harvesting and transporting large woody material, these treatments
should be considered a moderate priority for the project.
Habitat Boulders
Habitat boulders can consist of a single or multiple boulders grouped together to provide velocity
refuge and cover for fish. This habitat treatment can be applied in riffles as groups of random
boulders, which is often considered beneficial for Rainbow Trout, or within the tail out of pools to
provide cover for trout. These treatments are considered low risk with a moderate benefit on fish
habitat. The use of habitat boulders is considered a lower priority for the project.
Diversion Structure
The Williams Ditch (WDID 5100956) is located just downstream of the Breeze Bridge. The ditch
has a 1.5 cfs water right for irrigation purposes that was appropriated on 4/1/1907 and adjudicated
on 8/3/1991. The existing diversion results in fine sediment deposition upstream of the structure.
25
�Replacing the existing push-up dam with a constructed riffle or cross-vane diversion structure
would improve sediment transport, reduce maintenance needs, and reduce the frequency of
channel disturbance associated with maintenance activities. Incorporating a sediment sluice into
the head gate could also alleviate some issues with fine sediment deposition. The diversion has
been included in the design at the conceptual level, but additional outreach is needed to determine
if the diversion should be included in the next design phases. Fish entrainment in the irrigation
ditch also warrants further consideration to determine if a fish screen would be beneficial and
feasible. Given the potential costs associated with reconstruction diversion structure and/or
screening of the irrigation ditch, incorporating the diversion structure into the habitat project is
considered a lower priority.
4.2 Design Criteria
The following criteria were used to develop the conceptual restoration design and will provide
guidance for development of the preliminary (60%) and final (90%) designs.
Channel Narrowing
Channel narrowing activities should be designed to achieve an effective discharge that
occurs within 20% of the bankfull discharge (Torizzo and Pitlick, 2004).
The channel should be designed to achieve flushing flows that mobilize the D50 sediment
size in riffle locations with a frequency of 1-2 years.
Secondary and tertiary channels should be utilized to convey flood flows to ensure that the
streambanks and bed within the primary channel do not experience excessive shear stress
that results in accelerated erosion.
Proposed channel dimensions should place the channel on a trajectory toward dynamic
equilibrium based on future hydrology and sediment supply.
Riffle Habitats
Riffle de-armoring (or gravel cleaning) techniques should be investigated in select
locations. Criteria for the depth of gravel cleaning will need to be developed. Monitoring
and evaluation will be important to determine the feasibility, effectiveness, and
sustainability of these treatments. The placement of imported cobble material in riffle
locations should also be considered as an alternative to riffle de-armoring.
For riffles designed to restore high densities of P. californica, channel morphology, flow
regime, and land use activities should be managed so riffle habitat has fine sediment <3%,
cobble embeddedness <9%, median particle size >187 mm, and low W/D ratios between
24-38, if possible. As stream habitat variables are interrelated, design criteria should be
looked at holistically. Local conditions that will produce a dynamic but stable channel that
is in balance with sediment and flow regimes at that site should always be considered. In
generally, habitat for Salmonflies can be optimized with a channel design that focuses on
narrow, high gradient riffles with large cobble that will reduce fine sediment deposition
and cobble embeddedness.
26
�Bedform and Habitat Diversity
The proportion of pool habitat should be increased to improve bedform diversity. For
natural channels with slopes <3%, the optimal range for percentage of pool habitat is 4050% (CSQT SC, 2019). Specific targets for percentage pool need to be developed further,
but the assessment of Reach 1 indicates that 50% pool results in improved fish density
compared to Reaches 2-4.
Secondary channels around islands should be designed to achieve target depths, velocities,
and substrate size to provide optimal habitat for trout fry. Conditions for optimal fry habitat
are presented in Appendix D.
Convergence pools should be developed downstream of islands, contraction scour pools
should be developed downstream of riffles, and lateral scour pools should be developed on
the outside of meander bends.
The location for placement of spawning gravels should be identified during design
development. Glides are often considered an ideal place for the placement of spawning
gravels. Class A spawning gravels for Brown Trout range from 1-7 cm and Class B
spawning gravels range from 0.3-<1 and >7-10 cm (Raleigh et al., 1986). Developing
conditions that facilitate the deposition of spawning gravels through natural processes
should also be addressed in the next design phases.
Riparian Vegetation
Riparian vegetation should consist of native species, including but not limited to willows,
sedges, and rushes. Cottonwood galleries should also be targeted for development or reestablishment to improve shading and instream temperatures.
Sod mat transplants, willow transplants, willow planting, willow stakes, and riparian
seeding should be prioritized for vegetation treatments. Areas that are high priority for
vegetation treatments should be identified to focus resources on those areas. Natural
revegetation processes may be considered for lower priority areas, but the potential for
colonization of invasive plant species should also be considered when developing the
revegetation plan.
Bioengineering treatments should be used for bank stabilization in accordance with
guidelines, such as those outlined in Living Streambanks: a Manual for Bioengineering
Treatments for Colorado Streams (Giordanengo et al. 2016).
Natural landscaping materials, such as coir or jute erosion-control products, are preferred
over synthetic landscaping fabrics.
Large Woody Material
Engineered logjams, toe wood, log vanes, and habitat logs should be anchored using natural
materials, such as boulders or native alluvium.
Recently cut or pushed over conifers are preferred for structures constructed from large
woody material. All parts of the tree should be utilized in large wood structures, including
the rootwad, stems, and brush. Cottonwood trees are present on site and would naturally
recruit to the river channel, but cottonwood trees should only be used in large wood
27
�
structure if they are structurally sound. Cottonwood trees that no longer structurally sound
may be used as fill.
Toe wood treatments should be used on the outside of meander bends when feasible to
provide bank stability and improved trout habitat.
Habitat Boulders
Habitat boulders should be placed as a single boulder or in groups of clusters at elevations
that range from ½-bankfull to bankfull to provide velocity refuge and cover across a range
of flows. The majority of boulders should be placed at the lower end of the target elevation
range, but some boulders should be set at higher elevations to provide velocity refuge and
cover during higher flows. Boulders should be placed in manner than appears natural and
should not be placed in locations that accelerate bank erosion.
Footers should be used to support boulders to minimize the risk of settling and movement,
which can results in loss of habitat quality near the structure.
Boulders that are encountered during site excavation or grading should be harvested and
used for habitat treatments.
Diversion Structure
The reconstructed diversion structure should deliver the full decreed water right during the
irrigation season.
The new structure should reduce maintenance needs and the frequency of reconstruction.
Design flows for the diversion structure will need to be identified during future design
phases.
The new diversion structure should be constructed from boulders and native alluvium
without the use of grout or concrete. Concrete and grout may be used for the construction
of the new head gate and fish screen if those project elements are included in the final
design.
Target fish species and life stages for fish screening will need to be identified if the screen
is included as an element of the final design.
A sediment sluice should be considered for incorporation into the head gate structure to
help manage sedimentation upstream of the structure.
4.3 Design Methods
The following methods were used to develop the conceptual restoration design and will provide
guidance for development of the preliminary (60%) and final (90%) designs. Design methods that
need to be developed further during the next design phases were noted as such.
Channel Narrowing
Hydraulic geometry was used to develop conceptual channel dimension based on current
and future hydrology using equations from Torizzo and Pitlick (2004). Preliminary results
28
�
from hydraulic geometry are presented in Table 12. Conceptual dimension for typical
cross-sections are presented in Appendix E.
Methods from Soar and Thorne (2001) were used to develop conceptual pool dimensions
based on typical riffle dimensions (Appendix E).
Conceptual channel dimensions need to be validated and refined based on sediment
transport measurements and/or models to ensure that sediment transport and floodplain
activation targets are achieved. Note that CPW deployed PIT-tagged tracer rocks during
the spring of 2018 to support investigation of sediment transport at three riffle locations.
The design of channels around islands should consider hydraulic and sediment size
recommendations for Rainbow Trout fry in Appendix D.
Other island complexes in upper Colorado River should be considered for design analogs.
The cut/fill balance should be evaluated to determine if fill materials can be sourced on site
or if materials will need to be imported. A cost/benefit analysis may be necessary to
determine if fill materials should be excavated and sorted on site or imported. The location
of excavation areas will need to be identified and validated during the next design phases.
Two-dimensional (2D) hydraulic modeling is strongly recommended to evaluate sediment
transport, flow splits around islands, and floodplain activation.
Scour analysis should also be performed for the Breeze Bridge to evaluate the potential
effects of channel narrowing on structural integrity.
Table 12. Results from preliminary hydraulic geometry calculations based on equations published
by Torizzo and Pitlick (2004). Note that existing conditions are reach averages from the
geomorphology assessment. Wbkf = bankfull width; hbkf = bankfull mean depth; τ*50 =
dimensionless shear stress.
Design Flow
Existing Conditions
Q2.0 (Historic)
Q1.5 (Historic)
Q2.0 (Current)
Q2.0 (Future)
Q1.5 (Current)
Q1.5 (Future)
Q2.0 (PACSM, Alt 1a)
Q1.5 (PACSM, Alt 1a)
Q (cfs)
-3,400
3,100
1,800
1,660
1,300
1,240
1,000
920
Wbkf (ft)
155
138
131
96
92
80
78
69
66
hbkf (ft)
2.6
3.3
3.3
2.8
2.8
2.6
2.6
2.4
2.4
Slope
0.0030
0.0023
0.0025
0.0032
0.0033
0.0038
0.0038
0.0043
0.0045
τ*50
-0.036
0.037
0.039
0.040
0.041
0.041
0.042
0.043
Riffle Habitats
Methods for riffle de-armoring will be investigated to assess feasibility, effectiveness, and
cost-benefit.
Incipient motion analysis for the D50 sediment size will be conducted at riffle locations to
evaluate flushing flows for proposed channel dimensions under current and future
hydrology. Flushing flows are defined as flows that move the D50 sediment size in riffles
with a frequency of 1-2 years.
29
�
Proposed channel dimensions and substrate size for riffle habitat should be evaluated
against habitat preferences for Salmonflies (Table 11) and Mottled Sculpin (Persinger
2003).
2D hydraulic modeling is recommended for evaluating incipient motion and sediment
transport for existing and proposed conditions.
Bedform and Habitat Diversity
Final targets for bedform diversity need to be developed further, but a preliminary target
of 40-50% pool should be considered based on observed fish densities in Reach 1.
Results from hydraulic modeling should be compared to habitat suitability for Brown Trout
(Raleigh et al. 1986; Louhi et al. 2008; Ayllon et al. 2010), Rainbow Trout (Raleigh et al.
1984), and Mottled Sculpin (Persinger 2003) to investigate the quantity and quality of fish
habitat for existing and proposed conditions. Examples of habitat modeling approaches for
brown trout are available in Richer et al. (2017) and Richer et al. (2019). The creation of
suitable habitat for all trout life stages, including fry, juvenile, adult, and spawning, should
be targeted and evaluated during design development. 2D hydraulic modeling is
recommended to evaluate changes in habitat conditions for target species.
Habitat recommendations should also be used to develop target conditions in secondary
channels to support fry and juvenile life stages for trout (see Appendix D).
Riparian Vegetation
Channel dimensions should be designed to ensure that riparian floodplains are inundated
with a return interval of 1.5-2.0 years. Riparian areas that meet the criteria for frequency
of inundation should be targeted for vegetation treatments.
Native riparian species should be identified and used to develop a revegetation plan for the
project.
Large Woody Material
The Large Wood Design Tool (Rafferty 2013), or equivalent, should be used to evaluate
the stability of large wood structures. Acceptable targets for stability will need to be
developed during the next design phase, but some wood structures should be expected to
mobilize during large floods.
The availability of suitable large woody material on site should be evaluated during the
next design phases. Additional sources of large woody material will likely need to be
identified.
Habitat Boulders
Incipient motion analysis should be performed to evaluate the flow at which habitat
boulders will be mobilized, particularly if boulders will be placed upstream of the Breeze
Bridge.
30
�Diversion Structure
2D hydraulic modeling is recommended for evaluating water surface elevations and
sediment transport near the diversion structure. Hydraulic modeling should be conducted
for a target range of flows to ensure that the full decreed water right will be delivered to
the ditch during the irrigation season.
Water depths and velocities over the diversion structure should be compared to fish passage
criteria for target species to ensure the new structure does not create a migration barrier.
The potential for sediment deposition in the vicinity near the diversion structure should
also be evaluated during the next design phases.
5. Project Schedule
The Kemp-Breeze SWA habitat project will entail a three-phase approach, starting with strategy
and planning, followed by design and permitting, and ending with implementation and monitoring
(Table 13). Support for the project will come from various sections at CPW, including the Aquatic
Section (AS), Aquatic Research Section (ARS), Capital Development Section (CAPD), and
Northwest Region (NW). This project will be managed by CPW in collaboration with the greater
Habitat Project Stream Team, which includes members from Denver Water, the Subdistrict, CPW,
Grand County, and other parties including but not limited to private landowners. The proposed
restoration process and preliminary timeline for the Kemp-Breeze SWA habitat project is
presented in Table 13, including responsibilities within CPW.
6. Project Budget
The total budget for Kemp-Breeze Habitat Project is $1,200,000 including the cost of design,
which shall not exceed $200,000. CPW is providing in-kind contributions to support assessment,
conceptual design, and monitoring for the project. Note that the in-kind contributions from CPW
are separate from the total budget of $1,200,000 for design and construction.
31
�Table 13. Proposed restoration process, responsibilities, and timeline for the Kemp-Breeze SWA
habitat project. CPW sections: AS = Aquatic Section; ARS = Aquatic Research Section; and
CAPD = Capital Development Section (Engineering).
Step
1. Planning
2. Prioritize actions
Step
3. Design
4. Permitting
Step
5. Implementation
6. Monitoring
7. Adaptive
management
Phase I: Strategy and Planning
Tasks
Responsibility
Identify goals and objectives
AS and ARS
Evaluate goals and limiting factors AS and ARS
Site selection
AS, ARS, and CAPD
Phase II: Design and Permitting
Tasks
Responsibility
Survey and analysis
ARS and AS
ARS, AS, and
Evaluate alternatives
Consultant
Conceptual design
ARS, AS, and CAPD
Consultant, CAPD,
Preliminary design
ARS, and AS
Consultant, CAPD,
Final design
ARS, and AS
Consultant, CAPD,
404 permit
and AS
Consultant, CAPD,
Floodplain permit*
ARS, and AS
Consultant, CAPD,
Other permits (e.g., 1041)
and AS
Landowner agreements
CAPD, AS, and NW
Phase III. Implementation and Monitoring
Tasks
Responsibility
Contract documents
CAPD
Contractor, CAPD,
Construction
AS, and NW
Baseline
AS and ARS
Implementation
AS and ARS
Effectiveness
AS and ARS
Contractor, CAPD,
Maintenance
ARS, and AS
Information dissemination
AS and ARS
32
Timeline
2017-2018
2017-2018
2018-2019
Timeline
2018-2019
2018-2019
2018-2019
2019-2020
2019-2020
2020
2020
2020
2020
Timeline
2020-2021
2020-2022
1980-2020
2021-2023
2023-2028
2023-2028
2023-2028
�7. References
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Transactions of the American Fisheries Society 136: 1736-1741.
Ayllón, D., A. Almodóvar, G. G. Nicola, and B. Elvira. 2010. Ontogenetic and spatial variations
in brown trout habitat selection. Ecology of Freshwater Fish 19: 420–432.
Baxter, C. V., K. D. Fausch, and W.C. Saunders. 2005. Tangled webs: reciprocal flows of
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Effective discharge calculation: a practical guide. U.S. Army Corps of Engineers, Engineer
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Conejos of southern Colorado. Great Basin Naturalist 55:1-18.
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�Erickson, R. C. 1983. Benthic field studies for the Windy Gap study reach, Colorado River,
Colorado, fall, 1980 to fall, 1981. Prepared for The Northern Colorado Water Conservancy
District, Municipal Sub-District.
Fore, L. S., J. R. Karr, and R. W. Wisseman. 1996. Assessing invertebrate responses to human
activities: Evaluating alternative approaches. Journal of the North American Benthological
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Streambanks: a Manual of Bioengineering Treatments for Colorado Streams. Colorado Water
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Julien, P. Y. 1998. Erosion and sedimentation. Cambridge University Press, New York.
Kowalski, D. A. 2014. Colorado River aquatic resources investigations. Federal Aid Project F237-R21. Federal Aid in Fish and Wildlife Restoration, Job Progress Report. Colorado Parks
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Louhi, P., A. Mäki‐Petäys, and J. Erkinaro. 2008. Spawning habitat of Atlantic salmon and brown
trout: General criteria and intragravel factors. River Research and Applications 24: 330–339.
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Montgomery, D. R., and J. M. Buffington. 1997. Channel-reach morphology in mountain drainage
basins. GSA Bulletin 109: 596-611. U.S. Army Corps of Engineers, Engineer Research and
Development Center, Washington, DC.
Municipal Subdistrict. 2011a. Windy Gap Firming Project Fish and Wildlife Enhancement Plan.
Prepared by the Northern Colorado Water Conservancy District.
Municipal Subdistrict. 2011b. Windy Gap Firming Project Fish and Wildlife Mitigation Plan.
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Nehring, R. B. 1987. Stream fisheries investigations. Federal Aid Project F-51-R. Federal Aid in
Fish and Wildlife Restoration, Job Progress Report. Colorado Division of Wildlife, Fish
Research Section. Fort Collins, Colorado.
Nehring, R. B., and R. M. Andersen. 1993. Determination of population-limiting critical salmonid
habitats in Colorado stream using the Physical Habitat Simulation System. Rivers 4: 1-19.
Nehring, R. B., B. Heinold, and J. Pomeranz. 2011. Colorado River Aquatic Resources
Investigations, Federal Aid Project F-237R-10. Aquatic Research Section, Colorado Division
of Wildlife.
Persinger, J. W. 2003. Developing habitat suitability criteria for individual species and habitat
guilds in the Shenandoah River Basin. Virginia Polytechnic Institute and State University,
Blacksburg, VA.
34
�Raleigh, R. F., T. Hickman, R. C. Solomon, and P. C. Nelson. 1984. Habitat suitability
information: Rainbow trout. U.S. Fish and Wildlife Service. FWS/OBS-82/10.60. 64 pp.
Raleigh, R. F., L. D. Zuckerman, and P. C. Nelson. 1986. Habitat suitability index models and
instream flow suitability curves: Brown trout, revised. U.S. Fish and Wildlife Service. Servo
Biol. Rep. 82(10.124). 65 pp. [First printed as: FWS/OBS-82/10.71, September 1984].
Rafferty, M. 2013. Development of a computational design tool for evaluating the stability of large
wood structures proposed for stream enhancement. Department of Civil Engineering, Colorado
State University, Fort Collins.
Richards, D. C., M. G. Rolston, and F. V. Dunkle. 2000. A comparison of salmonfly density
upstream and downstream of Ennis Reservoir. Intermountain Journal of Sciences 6(1):1-9.
Richer, E. E., E. A. Gates, A. T. Herdrich, and M. C. Kondratieff. 2017. Upper Arkansas River
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Richer, E. E., E. A. Gates, M. C. Kondratieff, and A. T. Herdrich. 2019. Modelling changes in
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35
�Vinson, M. R. 2001. Long-term dynamics of an invertebrate assemblage downstream from a large
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36
�Appendix A
COLORADO PARKS AND WILDLIFE
Kemp-Breeze SWA Habitat Project, Colorado River
Site Assessment
Prepared by:
Colorado Parks and Wildlife
Aquatic Research Section
317 W. Prospect Road
Fort Collins, CO 80526
SHEET
DESCRIPTION
1
Site Assessment Overview
2-9
Longitudinal Profile and Assessment
10-19
Photo Points
20-27
Historical Aerial Images
June 1, 2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
�Appendix A
810
0
82
0
83 0
00
840
0
850
0
8600
7600
7700
7500
650
0
660
0
67
00
6800
690
0
7000
7100
6100
6200
6300
6000
0
530
00
48
00
46
0
4400
430
3900
400
0
3400
0
320
00
21
8000
(
!
7900
7800
(
!
0
740
7300
00
(
!!
(
72
(
!
6400
0
590
5800
5700
00
56
0
550
0
(
!
REACH 1
540
(
!!
(
5200
00
51
5000
4900
(
41 !
4700
00
00
(
!
45
(
!
00
3800
42
(
!
0
370
3600
3500
0
0
330
300
REACH 2
0
140
0
130
0
120
00
11 0
100
900
800
700
0
00
1
15 600
(
00 !
(
!
(
!
3100
17
2600
2500
0
240 0
0
23 0
220
H4
00
20 0
0
19 00
18
AC
RE
2700
2800
290
0
REACH 3
400
0
7,465
7,465
Elevation (ft)
0
50
(
!!
(
60
100
2300
00
(
!
7,460
7,460
Longitudinal
Profile
Longitudinal
Profile
Water Surface
Water Surface
Streambed
Streambed
7,455
7,455
7,450
7,450
7,445
7,445
7,440
7,440
00
500
500
1,000
1,000
1,500
1,500
2,000
2,000
2,500
2,500
3,000
3,000
3,500
3,500
4,000
4,000
4,500
4,500
5,000
5,000
5,500
5,500
6,000
6,000
6,500
6,500
7,000
7,000
7,500
7,500
8,000
8,000
8,500
8,500
Station
Station (ft)
(ft)
(
!
Project Reaches
Riffle
Glide
Photo Points
Run
Island
Thalweg
Pool
0 140 280
560
840
1,120
Feet
Pebble Count
A-1
º
SITE ASSESSMENT
DRAWN: TLAMBERT
5/10/2019
CHECKED: ERICHER
5/10/2019
APPROVED:
SHEET: 1 OF 9
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix A
0
810
7700
00
840
0
83
200
300
Side Channel
00
82
100
0
7600
7500
0
00
7100
7900
40
7800
0
7300
72
7000
PC1-1
PC1-2
740
PC1-3
8000
PC14
7,469
7,468
Elevation (ft)
7,467
850
0
Island formation may be indicative
of sediment deposition associated
with decreased transport capacity;
Split flow condition enhances
habitat complexity
Wide and shallow area
8600
Existing side channel is
connected on downstream
end during low flows
Power lines
Parshall Hole
Longitudinal Profile
Water Surface
Streambed
7,466
7,465
7,464
7,463
7,462
7,461
7,000
7,100
7,200
7,300
(
!
7,400
7,500
7,600
Photo Points
Riffle
Glide
Thalweg
Run
Island
Pebble Count
Pool
7,700
0 25 50
7,800
7,900
Station (ft)
100
150
200
Feet
Contour (1 ft)
A-2
8,000
º
8,100
8,200
8,300
SITE ASSESSMENT
DRAWN: TLAMBERT
5/10/2019
CHECKED: ERICHER
5/10/2019
APPROVED:
SHEET: 2 OF 9
8,400
8,500
8,600
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix A
Handicap fishing pier and
access trail to parking lot
Pool adjacent to the handicap
fishing pier provides good holding
water for adult trout and should
be maintained if possible
Duck blind
PC1-8
Wide and shallow area
0
PC1-6
PC1
-5
(PP-4
!
7000
( PP-1
!
( PP-3
!
690
6800
( PP-2
!
0
67
00
0
650
660
500
0
400
Side Channel
100
5500
540
300
00
600
56
5700
6200
6100
PC1-7
6400
0
PC1-A
0
590
5800
PC1-10
6000
PC1-9
6300
Monitoring location for benthic
macroinvertebrates, trout fry,
and sediment transport
(PP-5
!
Island formation may be indicative of sediment deposition
associated with decreased transport capacity; Channel
on river left provides excellent fry habitat for trout and
creation of similar habitat is desireable
Colorado River near
Parshall stream gage
Wide and shallow area
7,465
7,464
Elevation (ft)
7,463
Longitudinal Profile
Water Surface
Streambed
7,462
7,461
7,460
7,459
7,458
7,457
7,456
5,400
5,500
5,600
(
!
5,700
5,800
5,900
6,000
Photo Points
Riffle
Glide
Thalweg
Run
Island
Pebble Count
Pool
6,100
0 25 50
6,200
Station (ft)
100
150
6,300
200
Feet
Contour (1 ft)
A-3
6,400
º
6,500
6,600
6,700
SITE ASSESSMENT
DRAWN: TLAMBERT
5/10/2019
CHECKED: ERICHER
5/10/2019
APPROVED:
SHEET: 3 OF 9
6,800
6,900
7,000
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix A
Williams Ditch head gate:
Culvert diameter = 2.5 ft
Upstream invert = 7457.34 ft
Downstream invert = 7457.35
Barb structure
Barb structure
Push-up diversion structure:
Max elevation = 7459.84 ft
Min elevation = 7457.91
Length = 370 ft; Slope = 0.52%
Fine sediment deposition upstream
of the diversion structure
Williams Ditch
0
48
00
46
4400
00
0
3900
0
00
5000
Barb structure
4900
( PP-8
!
( PP-9
!
! PP-6
(
PP-7
51
4700
00
00
00
42
41
540
45
0
400
PC2-1
5200
370
3800
0
PC2-2
530
PC2-3
430
PC2-4
Breeze Bridge
Downstream facing "barb" structure,
backwater areas downstream of
barbs are poor fish habitat where
deposition of fine sediment is common
Wetland area
7,460
7,459
Elevation (ft)
7,458
Longitudinal Profile
Water Surface
Streambed
7,457
7,456
7,455
7,454
7,453
7,452
3,700
3,800
3,900
4,000
(
!
4,100
4,200
4,300
Photo Points
Riffle
Glide
Thalweg
Run
Island
Pebble Count
Pool
4,400
0 25 50
4,500
4,600
Station (ft)
100
150
200
Feet
Contour (1 ft)
A-4
4,700
º
4,800
4,900
5,000
SITE ASSESSMENT
DRAWN: TLAMBERT
5/10/2019
CHECKED: ERICHER
5/10/2019
APPROVED:
SHEET: 4 OF 9
5,100
5,200
5,300
5,400
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix A
Williams Ditch
High width/depth ratio
likely causing aggradation
Long compound pool
that lacks cover
Williams Ditch
2800
PC2-1
0
Barb structure
PC2-9
Barb structure
0
PC2-8
0
290
240
2500
2600
2700
Wetland area
PC2-7
3400
0
00
370
320
21
PC2-4
3600
3100
0
Steep riffle (slope = 1.8%) with
large contraction in channel
width (170 ft to 92 ft)
-2
PC
PC225-A
3500
0
220
-1
Wide and shallow area with
evidence of deposition
(PP-12
!
(PP-11
!
Barb structure
Historical side channel in cottonwood gallery
with high potential for enhanced habitat
diversity and incorporation of large wood
Barb structure
(PP-15
!
(
!
7,456
7,455
7,454
Elevation (ft)
3
PC
330
00
(PP-13
!
3
PC
0
23
0
300
PC2-6
7,453
Longitudinal Profile
Water Surface
Streambed
7,452
7,451
7,450
7,449
7,448
7,447
7,446
2,100
2,200
2,300
(
!
2,400
2,500
2,600
Photo Points
Riffle
Glide
Thalweg
Run
Island
Pebble Count
Pool
2,700
2,800
0 25 50
2,900
Station (ft)
100
150
3,000
200
Feet
Contour (1 ft)
A-5
3,100
º
3,200
3,300
3,400
SITE ASSESSMENT
DRAWN: TLAMBERT
5/10/2019
CHECKED: ERICHER
5/10/2019
APPROVED:
SHEET: 5 OF 9
3,500
3,600
3,700
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
( PP-9
!
�Appendix A
Williams Ditch
Williams Ditch
Wide and shallow area with evidence
of deposition, note alternating pattern
with upstream deposition area
PC3-8
PC3-9
16
00
( PP-15
!
( PP-14
!
00
1000
15
1400
1300
1200
900
0
1100
600
50
800
00
00
PC3-7
PC3-10
700
2000
21
0
3-5
PCP3C-A
PC3-6
190
PC3-4
PC3-1
17
Riparian bench with
lower bank heights
PC3-3
1800
Thalweg should be located on
the outside of the bend, which
may indicate that channel is in
the process of evoluation
PC3-2
( PP-16
!
Wide and shallow area with
evidence of deposition
( PP-17
!
( PP-18
!
Long featureless riffle with high width/depth ratio
and plane bed morphology that lacks fish habitat;
May function as migration barrier during extreme
low flows due to inadequate depth
( PP-20
!
( PP-19
!
7,451
7,450
Elevation (ft)
7,449
Longitudinal Profile
Water Surface
Streambed
7,448
7,447
7,446
7,445
7,444
7,443
7,442
500
600
700
800
(
!
900
1,000
1,100
Photo Points
Riffle
Glide
Thalweg
Run
Island
Pebble Counts
Pool
1,200
0 25 50
1,300
Station (ft)
100
150
1,400
200
Feet
Contour (1 ft)
A-6
º
1,500
1,600
1,700
1,800
SITE ASSESSMENT
DRAWN: TLAMBERT
5/10/2019
CHECKED: ERICHER
5/10/2019
APPROVED:
SHEET: 6 OF 9
1,900
2,000
2,100
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix A
100
0
Williams Ditch
Thalweg should be located on
the outside of the bend, which
may indicate that channel is in
the process of evoluation
Riparian bench with
lower bank heights
15
300
20
0
Channel is confined by
high terrace on river left
00
800
1000
700
0
40
1400
Compound pool provides
good fish habitat
1300
1200
900
0
1100
600
50
Compound pool provides
good fish habitat
( PP-18
!
( PP-20
!
( PP-19
!
Long featureless riffle
7,448
Longitudinal Profile
Water Surface
Streambed
7,447
Elevation (ft)
7,446
7,445
7,444
7,443
7,442
7,441
0
50
100
150
200
(
!
250
300
350
400
450
500
Photo Points
Riffle
Glide
Thalweg
Run
Island
Pebble Counts
Pool
550
600
0 25 50
650 700 750
Station (ft)
100
150
200
Feet
Contour (1 ft)
A-7
800
º
850
900
950 1,000 1,050 1,100 1,150 1,200 1,250 1,300 1,350 1,400
SITE ASSESSMENT
DRAWN: TLAMBERT
5/10/2019
CHECKED: ERICHER
5/10/2019
APPROVED:
SHEET: 7 OF 9
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix A
PC1-1
PC14
PC1-2
PC1-3
7600
40
7800
7500
0
7700
740
7300
7000
0
Existing side channel is
connected on downstream
end during low flows
SIDE CHANNEL 1 PROFILE
Longitudinal Profile
Water Surface
Streambed
7,466
Elevation (ft)
300
200
100
0
00
7100
72
Island formation may be indicative
of sediment deposition associated
with decreased transport capacity;
Split flow condition enhances
habitat complexity
Side Channel
7,465
7,464
7,463
0
20
40
60
(
!
80
100
120
140
160
Photo Points
Contour (1 ft)
Pool
Pebble Counts
Riffle
Glide
Thalweg
Run
Island
Side Channel 1
180
0
15 30
200
220
Station (ft)
60
90
240
120
260
º
Feet
A-8
280
300
320
340
SITE ASSESSMENT
DRAWN: TLAMBERT
5/10/2019
CHECKED: ERICHER
5/10/2019
APPROVED:
SHEET: 8 OF 9
360
380
400
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix A
Pool adjacent to the handicap fishing pier provides good holding
water for adult trout and should be maintained if possible
Handicap fishing pier and
access trail to parking lot
PC1-8
56
5700
600
00
300
200
0
( PP-2
!
500
400
100
540
5500
Side Channel
0
( PP-3
!
(PP-4
!
Island formation may be indicative of sediment deposition
associated with decreased transport capacity; Channel
on river left provides excellent fry habitat for trout and
creation of similar habitat is desireable
(PP-5
!
SIDE CHANNEL 2 PROFILE
Longitudinal Profile
Water Surface
Streambed
7,461
Elevation (ft)
6300
0
5800
PC1-A
6200
PC1-10
6100
590
Monitoring location for benthic
macroinvertebrates, trout fry,
and sediment transport
6000
PC1-9
7,460
7,459
7,458
0
50
100
(
!
150
200
250
Photo Points
Contour (1 ft)
Pool
Thalweg
Riffle
Glide
Side Channel 2
Run
Island
300
0 15 30
350
Station (ft)
60
Pebble Count
90
400
120
º
Feet
A-9
450
500
550
SITE ASSESSMENT
DRAWN: TLAMBERT
5/10/2019
CHECKED: ERICHER
5/10/2019
APPROVED:
SHEET: 9 OF 9
600
650
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix A
Photo Point – 1
Photo Point – 2
A - 10
�Appendix A
Photo Point – 3
Photo Point – 4
A - 11
�Appendix A
Photo Point – 5
Photo Point – 6
A - 12
�Appendix A
Photo Point – 7
Photo Point – 8
A - 13
�Appendix A
Photo Point – 9
Photo Point – 10
A - 14
�Appendix A
Photo Point – 11
Photo Point – 12
A - 15
�Appendix A
Photo Point – 13
Photo Point – 14
A - 16
�Appendix A
Photo Point – 15
Photo Point – 16
A - 17
�Appendix A
Photo Point – 17
Photo Point – 18
A - 18
�Appendix A
Photo Point – 19
Photo Point – 20
A - 19
�Colorado River, Kemp-Breeze SWA, 10/24/1938
Breeze Bridge
A - 20
Appendix A
�Colorado River, Kemp-Breeze SWA, 9/14/1946
Breeze Bridge
A - 21
Appendix A
�Colorado River, Kemp-Breeze SWA, 9/1994
Breeze Bridge
A - 22
Appendix A
�Colorado River, Kemp-Breeze SWA, 9/1999
Breeze Bridge
A - 23
Appendix A
�Colorado River, Kemp-Breeze SWA, 10/2005
Breeze Bridge
A - 24
Appendix A
�Colorado River, Kemp-Breeze SWA, 10/2011
Breeze Bridge
A - 25
Appendix A
�Colorado River, Kemp-Breeze SWA, 10/2013
Breeze Bridge
A - 26
Appendix A
�Colorado River, Kemp-Breeze SWA, 9/2016
Breeze Bridge
A - 27
Appendix A
�Appendix B
IHA Parametric Scorecard
Colorado River at Parshall 1996 to 2018 Parametric
Period of Analysis: 1996-2018 ( 23 years)
NormalizationFactor
1
Mean annual flow
449.1
Non-Normalized Mean Flow
449.1
Annual C. V.
1.41
Flow predictability
0.67
Constancy/predictability
0.69
% of floods in 60d period
0.77
Flood-free season
170
Parameter Group #1
October
November
December
January
February
March
April
May
June
July
August
September
Means
Coeff. of Var.
268.6
222.4
178.2
167
165.5
215
428.8
956.1
1446
653.9
381.3
301.2
0.2888
0.1954
0.1695
0.1639
0.1944
0.3546
0.5742
0.7466
0.8745
0.9181
0.408
0.3375
Parameter Group #2
1-day minimum
3-day minimum
7-day minimum
30-day minimum
90-day minimum
1-day maximum
3-day maximum
7-day maximum
30-day maximum
90-day maximum
Number of zero days
Base flow index
127
133
139.6
155.6
165.4
2389
2301
2100
1578
1070
0
0.3684
0.2471
0.235
0.2024
0.1716
0.1674
0.6547
0.6757
0.725
0.7942
0.7606
0
0.3558
Parameter Group #3
Date of minimum
Date of maximum
316.3
171.4
0.2695
0.0486
Parameter Group #4
Low pulse count
Low pulse duration
High pulse count
High pulse duration
Low Pulse Threshold
High Pulse Threshold
6.043
15.13
1.913
17.78
174
1083
0.5764
0.7764
0.862
1.041
Parameter Group #5
Rise rate
Fall rate
Number of reversals
38.87
-35.73
141
0.4704
-0.4649
0.1474
EFC Low Flows
October Low Flow
November Low Flow
December Low Flow
January Low Flow
February Low Flow
March
Low Flow
April
Low Flow
May
Low Flow
June
Low Flow
July
Low Flow
August Low Flow
September Low Flow
EFC Parameters
Extreme low peak
Extreme low duration
Extreme low timing
Extreme low freq.
High flow peak
High flow duration
High flow timing
High flow frequency
High flow rise rate
High flow fall rate
Small Flood peak
Small Flood duration
Small Flood timing
Small Flood freq.
Small Flood riserate
Small Flood fallrate
Large flood peak
Large flood duration
Large flood timing
Large flood freq.
Large flood riserate
Large flood fallrate
Means
Coeff. of Var.
241.3
224
183.9
173
174.8
201.8
253.1
232.7
239.8
317.4
296.5
250.7
0.1426
0.1767
0.137
0.1356
0.161
0.1686
0.2363
0.2743
0.1863
0.1223
0.1676
0.2144
133.6
8.422
54.02
4.696
475.8
12.24
183.5
4.783
65.12
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2764
89.57
167.6
0.6087
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5384
145.5
168.5
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78.12
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0.9512
0.1461
0.8332
0.1711
0.5385
0.4558
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0.3916
0.3904
0.03449
0.8198
0.7282
-0.5243
0.08787
0.2187
0.03671
3.313
0.2339
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EFC low flow threshold:
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EFC extreme low flow threshold:
243
391
146
EFC small flood minimum peak flow:
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�Appendix B
M O FFAT
C O L L E C T I O N
S Y S T E M
P R O J E C T
F I N A L E N V I R O N M E N TA L I M PA C T S TAT E M E N T
Appendix H:
Hydrologic Data and PACSM Output
Photo provided courtesy of
Denver Water.
B-9
�Appendix B
Appendix H
Hydrologic Data and PACSM Output
Appendix H
Hydrologic Data and PACSM Output
H-1
Comparison of Current Conditions, Full Use of the Existing System,
and EIS Alternatives with RFFAs
H-2
Reservoir Storage Changes
H-3
PACSM Output – Changes in Streamflows, Diversions, and
Reservoir Outflows
H-4
PACSM Output – Average Daily Hydrographs
H-5
PACSM Output – Flow Duration Curves
H-6
Analysis of Daily Flow Changes
H-7
EIS Locations of Interest Comparisons
H-8
Average Annual Net Evaporation Comparisons
H-9
Flow Duration and Effective Discharge Curves
H-10
Sediment Supply and Bedload Capacity Curves
H-11
Groundwater Comment Letter and Corps’ Response
H-12
Native Flows
H-13
Grand County and Summit County Water Shortages
H-14
Peak Flows
H-15
Dry Year Frequency and Duration
H-16
Basin Maps
H-17
Aerial Photo Results
H-18
Historic Photo Comparisons
H-19
Stream Discharge Measurement Data
H-20
Flood Flow Frequency Data
H-21
Phase 2 Sediment Transport Graphs
H-22
Operations of the Environmental Pool (for Mitigation Purposes) at
Gross Reservoir as Evaluated by the Corps
Note: Alternative 1a (Alt 1a) occurrences throughout this appendix refer to the Proposed
Action (without the Environmental Pool) for the Moffat Collection System
Project. Appendix M contains the hydrologic results for the Proposed Action with
the Environmental Pool.
H-i
B - 10
�Appendix B
Appendix H-1
Comparison of Current Conditions, Full Use of the Existing System,
and EIS Alternatives with RFFAs
Table H-1.59. Colorado River below Confluence with Williams Fork River (cfs)
Flow Change and % Change are based on comparisons to Current Conditions
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
45 Year Average
Current Conditions
258.5
228.4
182.7
185.5
168.2
206.4
421.5
605.8
Full Use
Flow
268.8
233.2
186.0
189.8
175.5
207.2
375.8
485.2
No Act
Flow
269.9
231.2
186.1
192.3
174.2
212.3
375.6
477.7
Alt 1a
Flow
268.3
229.2
184.5
190.5
172.5
211.7
374.1
470.3
Alt 1c
Flow
268.4
229.2
184.8
190.6
172.5
211.7
374.1
470.2
Alt 8a
Flow
268.1
229.6
184.4
190.3
172.5
211.7
374.9
471.2
Alt 10a
Flow
268.2
229.6
184.4
190.3
172.5
211.7
374.9
471.2
Alt 13a
Flow
268.1
229.1
184.4
190.2
172.5
211.4
374.5
465.9
Flow change from Current Conditions
Full Use
Flow Change
10.2
4.8
3.4
4.2
7.3
0.8
-45.7
-120.6
No Act
Flow Change
11.4
2.7
3.4
6.7
6.0
6.0
-45.9
-128.2
Alt 1a
Flow Change
9.8
0.7
1.8
4.9
4.4
5.3
-47.4
-135.5
Alt 1c
Flow Change
9.8
0.8
2.1
5.0
4.4
5.4
-47.4
-135.6
Alt 8a
Flow Change
9.6
1.2
1.7
4.7
4.4
5.4
-46.6
-134.6
Alt 10a
Flow Change
9.6
1.2
1.7
4.7
4.4
5.4
-46.6
-134.7
Alt 13a
Flow Change
9.6
0.7
1.7
4.7
4.4
5.1
-47.0
-139.9
Percent change in flow from Current Conditions
Full Use
% Change
4%
2%
2%
2%
4%
0%
-11%
-20%
No Act
% Change
4%
1%
2%
4%
4%
3%
-11%
-21%
Alt 1a
% Change
4%
0%
1%
3%
3%
3%
-11%
-22%
Alt 1c
% Change
4%
0%
1%
3%
3%
3%
-11%
-22%
Alt 8a
% Change
4%
1%
1%
3%
3%
3%
-11%
-22%
Alt 10a
% Change
4%
1%
1%
3%
3%
3%
-11%
-22%
Alt 13a
% Change
4%
0%
1%
3%
3%
2%
-11%
-23%
Dry Year Average (1954, 1955, 1963, 1977, 1981)
Current Conditions
235.8
202.3
Full Use
Flow
238.2
203.2
No Act
Flow
238.3
203.2
Alt 1a
Flow
238.3
203.2
Alt 1c
Flow
238.2
203.2
Alt 8a
Flow
238.3
203.2
Alt 10a
Flow
238.3
203.2
Alt 13a
Flow
238.3
203.2
Full Use
No Act
Alt 1a
Alt 1c
Alt 8a
Alt 10a
Alt 13a
Flow Change
Flow Change
Flow Change
Flow Change
Flow Change
Flow Change
Flow Change
2.5
2.5
2.5
2.5
2.5
2.5
2.5
0.9
1.0
1.0
1.0
1.0
1.0
1.0
Full Use
No Act
Alt 1a
Alt 1c
Alt 8a
Alt 10a
Alt 13a
% Change
% Change
% Change
% Change
% Change
% Change
% Change
1%
1%
1%
1%
1%
1%
1%
0%
0%
0%
0%
0%
0%
0%
Wet Year Average (1952, 1962, 1983, 1984, 1986)
Current Conditions
304.5
255.0
Full Use
Flow
318.5
264.6
No Act
Flow
327.8
265.9
Alt 1a
Flow
327.9
261.3
Alt 1c
Flow
327.9
261.4
Alt 8a
Flow
327.9
261.0
Alt 10a
Flow
327.9
261.1
Alt 13a
Flow
327.9
261.0
Full Use
No Act
Alt 1a
Alt 1c
Alt 8a
Alt 10a
Alt 13a
Flow Change
Flow Change
Flow Change
Flow Change
Flow Change
Flow Change
Flow Change
14.0
23.3
23.4
23.4
23.4
23.4
23.4
9.6
10.9
6.3
6.4
6.0
6.1
6.0
Full Use
No Act
Alt 1a
Alt 1c
Alt 8a
Alt 10a
Alt 13a
% Change
% Change
% Change
% Change
% Change
% Change
% Change
5%
8%
8%
8%
8%
8%
8%
4%
4%
2%
3%
2%
2%
2%
151.0
154.3
154.3
154.3
154.3
154.3
154.3
154.3
139.5
142.6
155.8
274.9
171.8
140.4
144.2
157.7
274.3
174.6
140.4
144.2
157.7
274.3
174.6
140.4
144.2
157.7
274.3
174.6
140.4
144.2
157.7
274.3
174.6
140.4
144.2
157.7
274.3
174.6
140.4
144.2
157.7
274.3
174.6
140.4
144.2
157.7
274.3
174.6
Flow change from Current Conditions
3.3
1.0
1.6
1.9
-0.6
2.8
3.3
1.0
1.6
1.9
-0.6
2.8
3.3
1.0
1.6
1.9
-0.6
2.8
3.3
1.0
1.6
1.9
-0.6
2.8
3.3
1.0
1.6
1.9
-0.6
2.8
3.3
1.0
1.6
1.9
-0.6
2.8
3.3
1.0
1.6
1.9
-0.6
2.8
Percent change in flow from Current Conditions
2%
1%
1%
1%
0%
2%
2%
1%
1%
1%
0%
2%
2%
1%
1%
1%
0%
2%
2%
1%
1%
1%
0%
2%
2%
1%
1%
1%
0%
2%
2%
1%
1%
1%
0%
2%
2%
1%
1%
1%
0%
2%
223.0
231.5
232.0
224.6
226.7
223.7
223.7
223.7
202.1
191.2
273.3
764.8 1,721.7
216.3
202.7
295.7
612.6 1,307.6
217.2
200.8
296.8
612.6 1,299.5
211.7
197.8
296.3
612.0 1,260.3
212.5
197.9
296.3
612.0 1,260.6
211.8
197.8
296.3
612.0 1,260.5
211.8
197.8
296.3
612.0 1,260.4
211.8
197.8
296.3
612.0 1,260.4
Flow change from Current Conditions
8.5
14.2
11.6
22.3
-152.2
-414.1
9.0
15.1
9.6
23.5
-152.2
-422.2
1.6
9.6
6.7
23.0
-152.7
-461.4
3.8
10.4
6.7
23.0
-152.8
-461.1
0.7
9.7
6.7
22.9
-152.7
-461.2
0.7
9.7
6.7
22.9
-152.7
-461.3
0.7
9.7
6.7
22.9
-152.8
-461.3
Percent change in flow from Current Conditions
4%
7%
6%
8%
-20%
-24%
4%
7%
5%
9%
-20%
-25%
1%
5%
3%
8%
-20%
-27%
2%
5%
4%
8%
-20%
-27%
0%
5%
3%
8%
-20%
-27%
0%
5%
3%
8%
-20%
-27%
0%
5%
3%
8%
-20%
-27%
B - 11
Jun
Jul
Aug
Sep Average
860.8
831.8
802.2
729.1
730.9
735.1
734.9
734.4
598.6
588.5
583.1
553.9
553.9
561.6
561.9
558.3
380.4
354.0
354.8
351.5
351.5
354.3
354.4
353.9
288.1
286.7
289.6
286.6
286.9
287.1
287.1
287.0
366.1
348.5
345.8
335.2
335.4
336.7
336.8
335.8
-29.1
-58.6
-131.8
-130.0
-125.7
-125.9
-126.5
-10.1
-15.4
-44.6
-44.7
-37.0
-36.7
-40.3
-26.4
-25.6
-29.0
-29.0
-26.2
-26.1
-26.5
-1.5
1.5
-1.5
-1.2
-1.0
-1.0
-1.2
-16.9
-19.7
-30.2
-30.0
-28.7
-28.7
-29.6
-3%
-7%
-15%
-15%
-15%
-15%
-15%
-2%
-3%
-7%
-7%
-6%
-6%
-7%
-7%
-7%
-8%
-8%
-7%
-7%
-7%
-1%
1%
-1%
0%
0%
0%
0%
-5%
-5%
-8%
-8%
-8%
-8%
-8%
151.2
173.4
173.4
173.4
173.4
173.4
173.4
173.4
190.4
280.7
280.7
279.1
279.9
279.1
279.1
279.1
333.4
340.2
341.4
340.9
340.9
340.9
340.9
340.9
305.8
318.0
318.0
318.0
318.0
318.0
318.0
318.0
204.7
216.6
216.7
216.5
216.6
216.5
216.5
216.5
22.2
22.2
22.2
22.2
22.2
22.2
22.2
90.3
90.3
88.7
89.5
88.7
88.7
88.7
6.8
8.0
7.5
7.5
7.5
7.5
7.5
12.1
12.1
12.1
12.1
12.2
12.2
12.1
12.1
12.2
12.0
12.1
12.0
12.0
12.0
15%
15%
15%
15%
15%
15%
15%
47%
47%
47%
47%
47%
47%
47%
2%
2%
2%
2%
2%
2%
2%
4%
4%
4%
4%
4%
4%
4%
6%
6%
6%
6%
6%
6%
6%
2,997.6
3,002.5
2,922.9
2,800.4
2,804.0
2,819.8
2,818.9
2,814.7
1,816.1
1,974.4
1,959.5
1,940.7
1,941.6
1,954.6
1,955.0
1,948.2
609.5
574.5
564.5
567.4
569.1
567.5
567.5
567.3
330.6
311.1
309.4
309.8
309.3
309.6
309.6
309.6
809.4
776.0
767.4
750.9
751.6
753.5
753.5
752.6
4.8
-74.7
-197.2
-193.6
-177.8
-178.7
-182.9
158.3
143.3
124.6
125.5
138.4
138.9
132.1
-35.0
-45.0
-42.1
-40.4
-42.0
-42.0
-42.2
-19.5
-21.2
-20.8
-21.3
-21.0
-21.0
-21.0
-31.5
-40.0
-56.6
-55.8
-53.9
-53.9
-54.9
0%
-2%
-7%
-6%
-6%
-6%
-6%
9%
8%
7%
7%
8%
8%
7%
-6%
-7%
-7%
-7%
-7%
-7%
-7%
-6%
-6%
-6%
-6%
-6%
-6%
-6%
-4%
-5%
-7%
-7%
-7%
-7%
-7%
H1-59
�Appendix B
Appendix H-3
PACSM Output – Changes in Streamflows, Diversions, and Reservoir Outflows
Table H-3.32. Colorado River below Confluence with Williams Fork River (cfs)
Flow Change and % Change are based on comparisons to Full Use Existing System
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
45 Year Average
Full Use Existing System
268.8
233.2
186.0
189.8
175.5
207.2
375.8
485.2
No Act
Flow
269.9
231.2
186.1
192.3
174.2
212.3
375.6
477.7
Alt 1a
Flow
268.3
229.2
184.5
190.5
172.5
211.7
374.1
470.3
Alt 1c
Flow
268.4
229.2
184.8
190.6
172.5
211.7
374.1
470.2
Alt 8a
Flow
268.1
229.6
184.4
190.3
172.5
211.7
374.9
471.2
Alt 10a
Flow
268.2
229.6
184.4
190.3
172.5
211.7
374.9
471.2
Alt 13a
Flow
268.1
229.1
184.4
190.2
172.5
211.4
374.5
465.9
Flow change from Full Use Existing System
No Act
Flow Change
1.1
-2.1
0.1
2.5
-1.3
5.1
-0.2
-7.6
Alt 1a
Flow Change
-0.5
-4.1
-1.6
0.7
-2.9
4.5
-1.6
-14.9
Alt 1c
Flow Change
-0.4
-4.0
-1.3
0.8
-2.9
4.5
-1.7
-15.0
Alt 8a
Flow Change
-0.6
-3.6
-1.7
0.5
-2.9
4.6
-0.9
-14.0
Alt 10a
Flow Change
-0.6
-3.6
-1.7
0.5
-2.9
4.6
-0.9
-14.0
Alt 13a
Flow Change
-0.6
-4.1
-1.7
0.5
-2.9
4.2
-1.3
-19.3
Percent change in flow from Full Use Existing System
No Act
% Change
0%
-1%
0%
1%
-1%
2%
0%
-2%
Alt 1a
% Change
0%
-2%
-1%
0%
-2%
2%
0%
-3%
Alt 1c
% Change
0%
-2%
-1%
0%
-2%
2%
0%
-3%
Alt 8a
% Change
0%
-2%
-1%
0%
-2%
2%
0%
-3%
Alt 10a
% Change
0%
-2%
-1%
0%
-2%
2%
0%
-3%
Alt 13a
% Change
0%
-2%
-1%
0%
-2%
2%
0%
-4%
Dry Year Average (1954, 1955, 1963, 1977, 1981)
Full Use Existing System
238.2
203.2
No Act
Flow
238.3
203.2
Alt 1a
Flow
238.3
203.2
Alt 1c
Flow
238.2
203.2
Alt 8a
Flow
238.3
203.2
Alt 10a
Flow
238.3
203.2
Alt 13a
Flow
238.3
203.2
No Act
Alt 1a
Alt 1c
Alt 8a
Alt 10a
Alt 13a
Flow Change
Flow Change
Flow Change
Flow Change
Flow Change
Flow Change
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
No Act
Alt 1a
Alt 1c
Alt 8a
Alt 10a
Alt 13a
% Change
% Change
% Change
% Change
% Change
% Change
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Wet Year Average (1952, 1962, 1983, 1984, 1986)
Full Use Existing System
318.5
264.6
No Act
Flow
327.8
265.9
Alt 1a
Flow
327.9
261.3
Alt 1c
Flow
327.9
261.4
Alt 8a
Flow
327.9
261.0
Alt 10a
Flow
327.9
261.1
Alt 13a
Flow
327.9
261.0
No Act
Alt 1a
Alt 1c
Alt 8a
Alt 10a
Alt 13a
Flow Change
Flow Change
Flow Change
Flow Change
Flow Change
Flow Change
9.3
9.4
9.4
9.4
9.4
9.4
1.4
-3.3
-3.2
-3.6
-3.5
-3.6
No Act
Alt 1a
Alt 1c
Alt 8a
Alt 10a
Alt 13a
% Change
% Change
% Change
% Change
% Change
% Change
3%
3%
3%
3%
3%
3%
1%
-1%
-1%
-1%
-1%
-1%
H3-32
Jun
Jul
Aug
Sep Average
831.8
802.2
729.1
730.9
735.1
734.9
734.4
588.5
583.1
553.9
553.9
561.6
561.9
558.3
354.0
354.8
351.5
351.5
354.3
354.4
353.9
286.7
289.6
286.6
286.9
287.1
287.1
287.0
348.5
345.8
335.2
335.4
336.7
336.8
335.8
-29.5
-102.7
-100.9
-96.7
-96.8
-97.4
-5.4
-34.6
-34.6
-26.9
-26.6
-30.2
0.8
-2.6
-2.5
0.3
0.4
-0.1
2.9
0.0
0.2
0.5
0.4
0.3
-2.8
-13.4
-13.1
-11.8
-11.8
-12.7
-4%
-12%
-12%
-12%
-12%
-12%
-1%
-6%
-6%
-5%
-5%
-5%
0%
-1%
-1%
0%
0%
0%
1%
0%
0%
0%
0%
0%
-1%
-4%
-4%
-3%
-3%
-4%
154.3
140.4
144.2
157.7
274.3
174.6
154.3
140.4
144.2
157.7
274.3
174.6
154.3
140.4
144.2
157.7
274.3
174.6
154.3
140.4
144.2
157.7
274.3
174.6
154.3
140.4
144.2
157.7
274.3
174.6
154.3
140.4
144.2
157.7
274.3
174.6
154.3
140.4
144.2
157.7
274.3
174.6
Flow change from Full Use Existing System
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Percent change in flow from Full Use Existing System
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
173.4
173.4
173.4
173.4
173.4
173.4
173.4
280.7
280.7
279.1
279.9
279.1
279.1
279.1
340.2
341.4
340.9
340.9
340.9
340.9
340.9
318.0
318.0
318.0
318.0
318.0
318.0
318.0
216.6
216.7
216.5
216.6
216.5
216.5
216.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-1.6
-0.8
-1.6
-1.6
-1.6
1.2
0.7
0.8
0.7
0.7
0.7
0.0
0.0
0.0
0.0
0.0
0.0
0.1
-0.1
0.0
-0.1
-0.1
-0.1
0%
0%
0%
0%
0%
0%
0%
-1%
0%
-1%
-1%
-1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
231.5
216.3
202.7
295.7
612.6 1,307.6
232.0
217.2
200.8
296.8
612.6 1,299.5
224.6
211.7
197.8
296.3
612.0 1,260.3
226.7
212.5
197.9
296.3
612.0 1,260.6
223.7
211.8
197.8
296.3
612.0 1,260.5
223.7
211.8
197.8
296.3
612.0 1,260.4
223.7
211.8
197.8
296.3
612.0 1,260.4
Flow change from Full Use Existing System
0.5
0.9
-1.9
1.1
0.0
-8.0
-6.9
-4.6
-4.9
0.7
-0.6
-47.3
-4.8
-3.8
-4.8
0.7
-0.6
-47.0
-7.8
-4.5
-4.9
0.6
-0.6
-47.1
-7.8
-4.5
-4.9
0.6
-0.6
-47.2
-7.8
-4.5
-4.9
0.6
-0.6
-47.2
Percent change in flow from Full Use Existing System
0%
0%
-1%
0%
0%
-1%
-3%
-2%
-2%
0%
0%
-4%
-2%
-2%
-2%
0%
0%
-4%
-3%
-2%
-2%
0%
0%
-4%
-3%
-2%
-2%
0%
0%
-4%
-3%
-2%
-2%
0%
0%
-4%
3,002.5
2,922.9
2,800.4
2,804.0
2,819.8
2,818.9
2,814.7
1,974.4
1,959.5
1,940.7
1,941.6
1,954.6
1,955.0
1,948.2
574.5
564.5
567.4
569.1
567.5
567.5
567.3
311.1
309.4
309.8
309.3
309.6
309.6
309.6
776.0
767.4
750.9
751.6
753.5
753.5
752.6
-79.5
-202.0
-198.5
-182.7
-183.5
-187.8
-14.9
-33.7
-32.8
-19.8
-19.4
-26.2
-10.0
-7.2
-5.4
-7.1
-7.1
-7.2
-1.7
-1.4
-1.8
-1.5
-1.6
-1.6
-8.6
-25.1
-24.4
-22.5
-22.5
-23.4
-3%
-7%
-7%
-6%
-6%
-6%
-1%
-2%
-2%
-1%
-1%
-1%
-2%
-1%
-1%
-1%
-1%
-1%
-1%
0%
-1%
0%
-1%
-1%
-1%
-3%
-3%
-3%
-3%
-3%
B - 12
�Appendix B
Appendix H-4 – PACSM Output – Average Daily Hydrographs
Figure H-4.94. Colorado River below Confluence with Williams Fork River – Average Daily Flow (cfs)
1,000
900
Current Conditions
Full Use Existing System
No Action
800
Alternative 1a
Alternative 1c
Alternative 8a
700
Alternative 10a
Alternative 13 a
cfs
600
500
400
300
200
100
0
Mar
Apr
May
Jun
Jul
Day
H4-94
B - 13
Aug
Sep
�Appendix B
Appendix H-4 – PACSM Output – Average Daily Hydrographs
Figure H-4.95. Colorado River below Confluence with Williams Fork River – Wet Year Average Daily Flow (cfs)
4,000
Current Conditions
3,500
Full Use Existing System
No Action
Alternative 1a
3,000
Alternative 1c
Alternative 8a
Alternative 10a
Alternative 13 a
cfs
2,500
2,000
1,500
1,000
500
0
Mar
Apr
May
Jun
Jul
Aug
Sep
Day
H4-95
B - 14
�Appendix B
Appendix H-4 – PACSM Output – Average Daily Hydrographs
Figure H-4.96. Colorado River below Confluence with Williams Fork River – Dry Year Average Daily Flow (cfs)
700
Current Conditions
600
Full Use Existing System
No Action
Alternative 1a
Alternative 1c
500
Alternative 8a
Alternative 10a
Alternative 13 a
cfs
400
300
200
100
0
Mar
Apr
May
Jun
Jul
Day
H4-96
B - 15
Aug
Sep
�Appendix B
Appendix H-5 – PACSM Output – Flow Duration Curves
Figure H-5.16. Flow Duration Curve – Colorado River below the Confluence with Williams Fork River
8000
7000
6000
Flow (cfs)
5000
4000
3000
2000
1000
0
0
10
20
30
40
50
60
70
Alt. 1a
Alt 1c
80
90
100
Percent Exceedence
Current Conditions
Full Use Existing System
No Action
H5-16
B - 16
Alt 8a
Alt 10a
Alt 13a
�Appendix B
Appendix H-6
Analysis of Daily Flow Changes
Table H-6.3. Daily Flow Changes in the Colorado River Basin Compared to Current
Conditions
Colorado River below Windy Gap (Node 1350)
Range and % Occurrence of Daily Flow Changes Compared to Current Conditions, May through July
Percentage of Days in May through July Flow Changes Occur
Daily Flow Change
Full Use
Alt. 1a
Alt. 1c
Alt. 8a
Alt. 10a
Alt. 13a
Increase > 100 cfs
3.6%
2.3%
2.3%
2.4%
2.4%
2.4%
Increase of 1 to 99 cfs
15.6%
16.0%
16.0%
16.4%
16.4%
16.2%
Change of -1 to 1 cfs
17.1%
16.5%
16.6%
16.5%
16.5%
16.5%
Decrease of 1 to 99 cfs
36.6%
34.6%
34.4%
34.2%
34.2%
34.3%
Decrease of 100 to 199 cfs
7.9%
8.2%
8.2%
8.1%
8.1%
8.2%
Decrease of 200 to 299 cfs
4.3%
4.9%
5.1%
5.0%
5.0%
5.0%
Decrease of 300 to 399 cfs
3.6%
4.1%
4.3%
4.2%
4.2%
4.1%
Decrease of 400 to 499 cfs
2.4%
2.3%
2.1%
2.2%
2.2%
2.3%
Decrease of 500 to 999 cfs
8.6%
9.0%
9.1%
9.1%
9.1%
9.0%
Decrease of 1000 to 1999 cfs
0.3%
2.0%
2.0%
1.9%
1.9%
2.0%
Decrease > 2000 cfs
0.0%
0.1%
0.1%
0.1%
0.1%
0.1%
No Action
3.2%
15.7%
16.7%
36.2%
8.0%
4.6%
3.8%
2.6%
8.8%
0.4%
0.0%
Colorado River below the Confluence with the Williams Fork River (Node 1430)
Range and % Occurrence of Daily Flow Changes Compared to Current Conditions, May through July
Percentage of Days in May through July Flow Changes Occur
Daily Flow Change
Full Use
Alt. 1a
Alt. 1c
Alt. 8a
Alt. 10a
Alt. 13a
Increase > 100 cfs
11.6%
8.8%
9.1%
9.0%
9.0%
8.8%
Increase of 1 to 99 cfs
25.5%
25.0%
24.6%
25.1%
25.2%
25.1%
Change of -1 to 1 cfs
12.8%
13.2%
13.3%
13.3%
13.2%
13.3%
Decrease of 1 to 99 cfs
26.3%
24.0%
23.8%
24.0%
24.0%
24.2%
Decrease of 100 to 199 cfs
5.7%
7.4%
7.4%
7.3%
7.3%
6.6%
Decrease of 200 to 299 cfs
3.4%
3.9%
4.0%
3.8%
3.8%
3.9%
Decrease of 300 to 399 cfs
4.3%
4.0%
4.0%
3.9%
3.9%
4.6%
Decrease of 400 to 499 cfs
2.8%
2.9%
2.9%
3.0%
3.0%
2.9%
Decrease of 500 to 999 cfs
7.5%
8.9%
8.9%
8.7%
8.7%
8.6%
Decrease of 1000 to 1999 cfs
0.2%
1.9%
2.0%
1.8%
1.8%
1.9%
Decrease > 2000 cfs
0.0%
0.1%
0.1%
0.1%
0.1%
0.1%
No Action
10.4%
25.5%
13.1%
25.4%
6.1%
3.8%
4.3%
2.9%
8.1%
0.4%
0.0%
Colorado River near Kremmling (Node 5020)
Range and % Occurrence of Daily Flow Changes Compared to Current Conditions, May through July
Percentage of Days in May through July Flow Changes Occur
Daily Flow Change
Full Use
Alt. 1a
Alt. 1c
Alt. 8a
Alt. 10a
Alt. 13a
Increase > 100 cfs
7.6%
5.0%
5.2%
5.2%
5.1%
5.0%
Increase of 1 to 99 cfs
22.1%
20.3%
20.0%
20.5%
20.5%
20.5%
Change of -1 to 1 cfs
2.1%
2.1%
2.0%
2.1%
2.1%
2.0%
Decrease of 1 to 99 cfs
32.7%
29.7%
29.8%
29.7%
29.7%
29.8%
Decrease of 100 to 199 cfs
7.5%
9.1%
9.1%
9.0%
9.0%
8.7%
Decrease of 200 to 299 cfs
5.4%
6.3%
6.4%
6.4%
6.4%
6.2%
Decrease of 300 to 399 cfs
4.9%
5.1%
5.3%
5.3%
5.3%
6.0%
Decrease of 400 to 499 cfs
3.5%
4.5%
4.3%
4.3%
4.4%
4.4%
Decrease of 500 to 999 cfs
8.0%
9.7%
9.6%
9.4%
9.4%
9.4%
Decrease of 1000 to 1999 cfs
4.3%
5.2%
5.1%
5.0%
5.0%
5.0%
Decrease of 2000 to 2999 cfs
1.7%
2.5%
2.6%
2.5%
2.5%
2.5%
Decrease > 3000 cfs
0.2%
0.5%
0.5%
0.5%
0.5%
0.5%
No Action
5.5%
20.6%
2.1%
31.3%
7.7%
6.2%
5.5%
4.2%
9.3%
4.6%
2.5%
0.5%
H6-6
B - 17
�Appendix B
Appendix H-6
Analysis of Daily Flow Changes
Table H-6.19. Summary of Maximum Daily Flow Reductions Compared to Current
Conditions
Location
Denver Water's Fraser River
Diversion
Denver Water's Jim Ck Diversion
Denver Water's St. Louis Ck
Tributary Diversions
St. Louis Ck near Fraser Gage
Denver Water's Little Vasquez
Ck Diversion
Vasqeuz Ck Gage
Denver Water's Englewood
Ranch Gravity System
Denver Water's Main Ranch Ck
Diversion
Fraser River near Winter Park
Gage
Fraser River below St. Louis
Creek
Fraser River at Granby Gage
Demver Water's Steelman Ck
Diversion
Williams Fork River below
Steelman Ck
Williams Fork Reservoir Outflow
Muddy Creek below Wolford
Mountain Reservoir
Colorado River below Windy
Gap
Colorado River below Confluence
with Williams Fork River
Current Conditions
Date
Flow (cfs)
Alt. 1a
Flow (cfs)
Flow
Reduction
% Flow
Reduction
Current Conditions
Date
Flow (cfs)
No Action
Flow (cfs)
Flow
Reduction
% Flow
Reduction
4-Jul
235
5
230
98%
9-Jun
194
1
193
100%
1-Jun
71
1
70
98%
13-Jun
71
2
69
98%
22-Jun
123
0
123
100%
16-Jun
117
0
117
100%
16-Jun
274
73
201
73%
16-Jun
274
73
201
73%
19-May
71
1
70
98%
19-May
71
1
70
98%
19-Jun
368
39
330
89%
28-May
225
7
217
97%
25-May
48
8
40
83%
20-May
41
6
36
86%
Multiple
34.0 - 58.6
4.0 - 28.6
30
51% - 88%
Multiple
34.0 - 58.6
4.0 - 28.6
30
51% - 88%
10-Jun
388
62
326
84%
9-Jun
290
31
259
89%
5-Jul
968
283
686
71%
16-Jun
715
90
625
87%
1-Jun
1346
612
734
55%
16-Jun
1071
417
654
61%
5-Jul
60
0
60
100%
5-Jul
60
0
60
100%
5-Jul
212
12
200
94%
5-Jul
212
12
200
94%
27-Jul
991
351
640
65%
14-Jul
852
244
608
71%
25-Apr
1286
20
1266
98%
25-Apr
1286
20
1266
98%
22-Jun
4384
1456
2928
67%
1-Jul
2959
663
2295
78%
22-Jun
4453
1515
2938
66%
2-Jul
2790
641
2150
77%
Colorado River near Kremmling
7-Jun
8293
4509
3784
46%
8-Jun
8695
4869
3826
44%
Dillon Reservoir Outflow
Green Mountain Reservoir
Outflow
South Boulder Creek at
Pinecliffe Gage
15-Jun
2276
50
2226
98%
15-Jun
2276
50
2226
98%
7-Jun
3783
60
3723
98%
7-Jun
3783
60
3723
98%
23-Jun
623
377
247
40%
30-May
956
432
525
55%
Gross Reservoir Outflow
South Boulder Creek near
Eldorado Springs Gage
North Fork South Platte River
below Geneva Creek Gage
North Fork South Platte River
above Pine
23-May
655
139
516
79%
23-May
655
139
516
79%
23-May
594
68
526
89%
23-May
594
68
526
89%
9-Aug
663
109
554
84%
9-Aug
663
110
553
83%
10-Aug
665
181
484
73%
10-Aug
665
179
486
73%
Antero Reservoir Outflow
Eleven Mile Canyon Reservoir
Outflow
13-Jul
604
35
569
94%
2-Jan
728
68
660
91%
25-Jul
852
53
798
94%
2-Aug
962
52
909
95%
Cheesman Reservoir Outflow
South Platte River at Waterton
Gage
South Platte River at Denver
Gage
South Platte River at Henderson
Gage
28-Mar
1142
35
1107
97%
28-Mar
1142
49
1093
96%
18-Jul
900
100
801
89%
15-Jun
1858
951
906
49%
22-Jun
3415
1604
1811
53%
22-Jun
3415
1606
1809
53%
10-May
1648
384
1264
77%
22-Jun
3615
2361
1254
35%
Note:
Maximum daily flow reductions for other action alternatives are similar to Alternative 1a.
B - 18
H6-27
�Appendix B
Appendix H-7
EIS Locations of Interest Comparisons
Table H-7.1. Comparison of Average Annual Flows, Reservoir Outflows, and Diversions versus Current Conditions (AF)
Current
Conditions
Location
Colorado River Mainstem
Colorado River below Windy Gap
diversion
Colorado River blw Confluence
with Williams Fork River
Colorado River near Kremmling
gage
Muddy Creek Basin
Wolford Mountain Reservoir
outflow
Blue River Basin
West Portal Roberts Tunnel
diversion
Dillon Reservoir outflow
Blue River below Boulder Creek
Node
Avg. Annual
Flow
Full Use Existing System
Avg. Annual
Flow
Diff.
Alternative 1a
Percent Diff
Avg.
Annual
Flow
Diff.
Alternative 1c
Percent
Diff
Avg.
Annual
Flow
Diff.
Alternative 8a
Percent
Diff
Avg. Annual
Flow
Diff.
Alternative 10a
Percent
Diff
Avg.
Annual
Flow
Diff.
Alternative 13a
Percent
Diff
Avg.
Annual
Flow
Diff.
No Action
Percent
Diff
Avg. Annual
Flow
Diff.
Percent
Diff
1350
155,653
134,685
-20,968
-13%
126,767
-28,886
-19%
126,868
-28,785
-18%
127,628
-28,025
-18%
127,618
-28,035
-18%
127,123
-28,530
-18%
132,912
-22,741
-15%
1430
265,063
252,699
-12,364
-5%
243,081
-21,982
-8%
243,228
-21,835
-8%
244,215
-20,848
-8%
244,228
-20,835
-8%
243,540
-21,523
-8%
250,717
-14,346
-5%
5020
698,958
650,723
-48,235
-7%
636,349
-62,609
-9%
636,113
-62,845
-9%
637,978
-60,980
-9%
637,944
-61,015
-9%
637,118
-61,840
-9%
638,639
-60,319
-9%
1600
63,540
63,824
284
0%
63,878
338
1%
63,878
337
1%
63,879
338
1%
63,881
341
1%
63,880
340
1%
63,930
390
1%
4240
69,676
96,939
27,263
39%
101,775
32,099
46%
102,191
32,515
47%
101,281
31,605
45%
101,321
31,645
45%
101,461
31,785
46%
107,254
37,578
54%
4250
4500
124,392
184,296
96,668
156,130
-27,724
-28,166
-22%
-15%
91,881
151,343
-32,511
-32,953
-26%
-18%
91,485
150,947
-32,907
-33,349
-26%
-18%
92,374
151,836
-32,019
-32,460
-26%
-18%
92,329
151,791
-32,063
-32,505
-26%
-18%
92,186
151,648
-32,206
-32,648
-26%
-18%
86,485
145,947
-37,907
-38,349
-30%
-21%
Green Mountain Reservoir outflow
4650
284,276
256,192
-28,085
-10%
251,382
-32,894
-12%
251,000
-33,276
-12%
251,873
-32,403
-11%
251,825
-32,451
-11%
251,689
-32,588
-11%
245,982
-38,294
-13%
Blue River at mouth
South Boulder Creek Basin
South Boulder Creek at Pinecliffe
gage
Gross Reservoir inflow
Gross Reservoir outflow
South Boulder Creek near
Eldorado Springs gage
North Fork South Platte River
Basin
North Fork South Platte below
Geneva Creek gage
North Fork South Platte above
Pine
South Platte River Mainstem
Antero Reservoir outflow
Eleven Mile Reservoir outflow
Cheesman Reservoir outflow
South Platte River at Waterton
gage
South Platte below Chatfield
Resevoir
4800
306,163
278,089
-28,074
-9%
273,279
-32,884
-11%
272,898
-33,265
-11%
273,775
-32,388
-11%
273,724
-32,439
-11%
273,588
-32,575
-11%
267,882
-38,281
-13%
57120
106,043
108,752
2,709
3%
119,036
12,993
12%
118,878
12,835
12%
117,913
11,870
11%
117,907
11,863
11%
118,567
12,524
12%
111,056
5,013
5%
57140
57140
112,902
111,454
115,652
114,079
2,750
2,625
2%
2%
126,090
123,757
13,188
12,303
12%
11%
125,930
123,815
13,028
12,361
12%
11%
124,950
122,776
12,048
11,322
11%
10%
124,943
122,773
12,041
11,319
11%
10%
125,614
123,363
12,712
11,909
11%
11%
117,991
116,378
5,089
4,924
5%
4%
57180
46,680
46,330
-351
-1%
45,345
-1,335
-3%
45,310
-1,371
-3%
45,330
-1,351
-3%
45,332
-1,349
-3%
45,337
-1,343
-3%
46,091
-590
-1%
50700
117,494
143,778
26,284
22%
148,480
30,986
26%
148,878
31,384
27%
148,005
30,510
26%
148,043
30,549
26%
148,180
30,686
26%
153,685
36,190
31%
50750
141,915
168,195
26,280
19%
172,897
30,982
22%
173,295
31,380
22%
172,421
30,506
21%
172,460
30,545
22%
172,596
30,681
22%
178,102
36,186
25%
50150
50300
50450
21,674
104,564
180,255
21,723
105,228
180,900
49
665
646
0%
1%
0%
21,734
105,247
180,903
60
684
648
0%
1%
0%
21,735
105,268
180,925
61
705
670
0%
1%
0%
21,734
105,264
180,918
59
700
664
0%
1%
0%
21,733
105,233
180,888
59
669
633
0%
1%
0%
21,732
105,161
180,816
58
597
561
0%
1%
0%
21,787
105,583
181,227
113
1,020
973
1%
1%
1%
51200
112,256
100,722
-11,534
-10%
98,042
-14,214
-13%
97,889
-14,367
-13%
98,030
-14,226
-13%
98,027
-14,229
-13%
97,941
-14,315
-13%
96,918
-15,338
-14%
51290
122,191
109,221
-12,970
-11%
106,854
-15,337
-13%
106,705
-15,486
-13%
106,803
-15,388
-13%
106,802
-15,388
-13%
106,712
-15,479
-13%
105,046
-17,145
-14%
South Platte River at Denver gage
51540
236,313
229,265
-7,048
-3%
228,420
-7,893
-3%
228,284
-8,030
-3%
228,351
-7,962
-3%
228,358
-7,956
-3%
228,270
-8,044
-3%
226,008
-10,305
-4%
South Platte River at Henderson
gage
58440
285,978
279,342
-6,636
-2%
283,614
-2,364
-1%
283,537
-2,441
-1%
282,036
-3,942
-1%
282,662
-3,316
-1%
285,029
-949
0%
281,256
-4,722
-2%
Note: A positive difference denotes an increase in flow, whereas a negative difference denotes a decrease in flow.
H7-2
B - 19
�Appendix B
Appendix H-7
EIS Locations of Interest Comparisons
Table H-7.2. Comparison of Average Annual Dry Year Flows, Reservoir Outflows, and Diversions versus Current Conditions (AF)
Current
Conditions
Full Use Existing System
Alternative 1a
Node
Avg. Annual
Flow
Williams Fork near Leal gage
3750
37,448
36,166
-1,282
-3%
Avg.
Annual
Flow
36,166
Williams Fork Reservoir outflow
3950
70,389
79,520
9,131
13%
79,469
Location
Colorado River Mainstem
Colorado River below Windy Gap
diversion
Colorado River blw Confluence
with Williams Fork River
Colorado River near Kremmling
gage
Muddy Creek Basin
Wolford Mountain Reservoir
outflow
Avg. Annual
Flow
Diff.
Percent Diff
Alternative 1c
-1,282
-3%
Avg.
Annual
Flow
36,166
9,080
13%
79,519
Percent
Diff
Diff.
Alternative 8a
-1,282
-3%
Avg.
Annual
Flow
36,166
9,130
13%
79,469
Percent
Diff
Diff.
Alternative 10a
-1,282
-3%
Avg.
Annual
Flow
36,166
9,080
13%
79,469
Percent
Diff
Diff.
Alternative 13a
-1,282
-3%
Avg.
Annual
Flow
36,166
9,080
13%
79,469
Percent
Diff
Diff.
No Action
-1,282
-3%
Avg.
Annual
Flow
36,166
9,080
13%
79,593
Percent
Diff
Diff.
Diff.
Percent Diff
-1,282
-3%
9,204
13%
0%
1350
69,285
69,313
28
0%
69,313
28
0%
69,313
28
0%
69,313
28
0%
69,313
28
0%
69,313
28
0%
69,313
28
1430
148,222
157,041
8,819
6%
156,997
8,775
6%
157,042
8,820
6%
156,997
8,775
6%
156,997
8,775
6%
156,997
8,775
6%
157,121
8,899
6%
5020
428,773
423,977
-4,796
-1%
423,855
-4,918
-1%
423,788
-4,985
-1%
423,973
-4,800
-1%
423,983
-4,790
-1%
423,891
-4,882
-1%
423,901
-4,872
-1%
1600
43,941
46,842
2,901
7%
46,843
2,902
7%
46,842
2,901
7%
46,842
2,901
7%
46,842
2,901
7%
46,843
2,902
7%
46,842
2,901
7%
Blue River Basin
West Portal Roberts Tunnel
diversion
Dillon Reservoir outflow
Blue River below Boulder Creek
Green Mountain Reservoir outflow
4240
125,491
149,236
23,745
19%
148,599
23,108
18%
148,278
22,787
18%
148,625
23,134
18%
148,512
23,021
18%
148,500
23,009
18%
154,173
28,682
23%
4250
4500
4650
50,138
89,901
190,714
41,082
80,405
181,160
-9,056
-9,496
-9,554
-18%
-11%
-5%
41,161
80,484
181,083
-8,977
-9,417
-9,631
-18%
-10%
-5%
41,111
80,434
180,968
-9,027
-9,467
-9,746
-18%
-11%
-5%
41,161
80,484
181,201
-8,977
-9,417
-9,513
-18%
-10%
-5%
41,161
80,484
181,210
-8,977
-9,417
-9,504
-18%
-10%
-5%
41,161
80,484
181,119
-8,977
-9,417
-9,595
-18%
-10%
-5%
41,036
80,359
181,005
-9,102
-9,542
-9,709
-18%
-11%
-5%
Blue River at mouth
4800
203,588
194,059
-9,529
-5%
193,980
-9,608
-5%
193,866
-9,722
-5%
194,098
-9,490
-5%
194,107
-9,481
-5%
194,016
-9,572
-5%
193,901
-9,687
-5%
2%
South Boulder Creek Basin
South Boulder Creek at Pinecliffe
gage
Gross Reservoir inflow
Gross Reservoir outflow
South Boulder Creek near
Eldorado Springs gage
North Fork South Platte River
Basin
North Fork South Platte below
Geneva Creek gage
North Fork South Platte above
Pine
South Platte River Mainstem
57120
77,075
78,486
1,411
2%
78,549
1,474
2%
78,549
1,474
2%
78,549
1,474
2%
78,549
1,474
2%
78,549
1,474
2%
78,549
1,474
57140
57140
81,946
82,512
566
82,513
567
1%
82,513
567
1%
82,513
567
1%
82,513
567
1%
82,513
567
1%
82,513
567
1%
83,607
87,100
3,493
1%
4%
101,089
17,482
21%
100,635
17,028
20%
99,469
15,862
19%
99,486
15,879
19%
99,634
16,027
19%
88,529
4,922
6%
57180
29,077
29,122
45
0%
29,268
191
1%
29,263
186
1%
29,253
176
1%
29,254
177
1%
29,255
178
1%
29,137
60
0%
50700
151,435
184,592
33,157
22%
187,368
35,933
24%
187,097
35,662
24%
187,411
35,976
24%
187,306
35,871
24%
187,377
35,942
24%
190,225
38,790
26%
50750
161,354
194,676
33,322
21%
197,493
36,139
22%
197,224
35,870
22%
197,535
36,181
22%
197,431
36,077
22%
197,506
36,152
22%
200,350
38,996
24%
50150
8,835
9,175
340
4%
9,443
608
7%
9,431
596
7%
9,396
561
6%
9,396
561
6%
9,396
561
6%
9,132
297
3%
Eleven Mile Reservoir outflow
50300
1%
1,624
2%
1,682
91,768
92,821
1,053
93,392
93,450
Cheesman Reservoir outflow
50450
5%
9,335
7%
9,572
140,946
147,709
6,763
150,281
150,518
South Platte River at Waterton
51200
-5%
-1,035
-3%
-1,044
31,508
29,821
-1,687
30,473
30,464
gage
South Platte below Chatfield
51290
-10%
-1,563
-7%
-1,568
22,413
20,128
-2,285
20,850
20,845
Resevoir
South Platte River at Denver gage
51540
6%
7,304
8%
7,323
90,565
95,825
5,260
97,869
97,888
South Platte River at Henderson
58440
2%
6,639
5%
6,705
129,727
132,651
2,924
136,366
136,432
gage
Note: A positive difference denotes an increase in flow, whereas a negative difference denotes a decrease in flow.
Average annual dry year flows for locations on the West Slope are based on an average of the five driest years, which include 1954, 1955, 1963, 1977, and 1981.
Average annual dry year flows for locations on the East Slope are based on an average of the five driest years, which include 1950, 1954, 1963, 1977, and 1981.
2%
7%
93,351
150,329
1,583
9,383
2%
7%
93,233
150,403
1,465
9,457
2%
7%
93,198
150,281
1,430
9,335
2%
7%
94,873
157,750
3,105
16,804
3%
12%
-3%
30,491
-1,017
-3%
30,471
-1,037
-3%
30,497
-1,011
-3%
29,502
-2,006
-6%
-7%
20,828
-1,585
-7%
20,789
-1,624
-7%
20,848
-1,565
-7%
18,713
-3,700
-17%
8%
97,807
7,242
8%
97,788
7,223
8%
97,857
7,292
8%
95,466
4,901
5%
5%
134,486
4,759
4%
135,333
5,606
4%
137,369
7,642
6%
135,718
5,991
5%
Antero Reservoir outflow
H7-4
B - 20
�Appendix B
Appendix H-7
EIS Locations of Interest Comparisons
Table H-7.3. Comparison of Average Annual Wet Year Flows, Reservoir Outflows, and Diversions versus Current Conditions (AF)
Current
Conditions
Full Use Existing System
Alternative 1a
Alternative 1c
Alternative 8a
Alternative 10a
Alternative 13a
No Action
Williams Fork near Leal gage
3750
103,482
Avg.
Annual
Flow
102,706
-776
-1%
101,283
-2,199
-2%
101,314
-2,168
-2%
101,260
-2,222
-2%
101,265
-2,217
-2%
101,291
-2,191
-2%
102,295
-1,187
-1%
Williams Fork Reservoir outflow
3950
133,027
151,134
18,107
14%
148,279
15,252
11%
148,298
15,271
11%
148,259
15,232
11%
148,266
15,239
11%
148,287
15,260
11%
150,074
17,047
13%
1350
415,269
374,520
-40,749
-10%
359,266
-56,003
-13%
359,799
-55,470
-13%
361,227
-54,042
-13%
361,194
-54,075
-13%
360,483
-54,786
-13%
369,418
-45,851
-11%
1430
586,021
563,057
-22,964
-4%
544,947
-41,074
-7%
545,499
-40,522
-7%
546,889
-39,132
-7%
546,863
-39,158
-7%
546,173
-39,848
-7%
556,895
-29,126
-5%
5020
1,282,699
1,220,678
-62,021
-5%
1,194,763
-87,936
-7%
1,194,457
-88,242
-7%
1,198,737
-83,962
-7%
1,198,623
-84,076
-7%
1,197,099
-85,600
-7%
1,198,608
-84,091
-7%
1600
101,025
100,591
-434
0%
100,596
-429
0%
100,597
-428
0%
100,593
-432
0%
100,594
-431
0%
100,595
-430
0%
100,587
-438
0%
Location
Colorado River Mainstem
Colorado River below Windy
Gap diversion
Colorado River blw Confluence
with Williams Fork River
Colorado River near Kremmling
gage
Muddy Creek Basin
Wolford Mountain Reservoir
outflow
Blue River Basin
West Portal Roberts Tunnel
diversion
Dillon Reservoir outflow
Blue River below Boulder Creek
Green Mountain Reservoir
outflow
Blue River at mouth
Node
Avg. Annual
Flow
Avg. Annual
Percent Diff
Flow
Diff.
Diff.
Percent
Diff
Avg. Annual
Flow
Diff.
Percent
Diff
Avg. Annual
Flow
Diff.
Percent
Diff
Avg. Annual
Flow
Percent Avg. Annual
Diff
Flow
Diff.
Percent
Diff
Diff.
Avg. Annual
Flow
Percent
Diff
Diff.
4240
35,336
58,781
23,445
66%
60,638
25,302
72%
61,384
26,048
74%
60,315
24,979
71%
60,465
25,129
71%
60,604
25,268
72%
68,242
32,906
93%
4250
237,024
213,691
-23,333
-10%
205,778
-31,246
-13%
204,908
-32,116
-14%
207,805
-29,219
-12%
207,715
-29,309
-12%
206,884
-30,140
-13%
197,753
-39,271
-17%
4500
323,250
299,460
-23,790
-7%
291,548
-31,702
-10%
290,678
-32,572
-10%
293,574
-29,676
-9%
293,484
-29,766
-9%
292,654
-30,596
-9%
283,524
-39,726
-12%
4650
459,181
429,039
-30,142
-7%
421,229
-37,952
-8%
420,371
-38,810
-8%
423,263
-35,918
-8%
423,176
-36,005
-8%
422,341
-36,840
-8%
413,135
-46,046
-10%
4800
493,468
463,321
-30,147
-6%
455,511
-37,957
-8%
454,654
-38,814
-8%
457,546
-35,922
-7%
457,458
-36,010
-7%
457,623
-35,845
-7%
447,416
-46,052
-9%
South Boulder Creek Basin
South Boulder Creek at
Pinecliffe gage
Gross Reservoir inflow
57120
106,663
110,216
3,553
3%
124,595
17,932
17%
124,279
17,615
17%
124,306
17,643
17%
124,348
17,685
17%
124,532
17,869
17%
115,028
8,365
8%
57140
113,810
128,991
15,181
13%
141,044
27,234
24%
140,378
26,568
23%
140,710
26,900
24%
140,751
26,941
24%
140,807
26,997
24%
132,157
18,347
16%
Gross Reservoir outflow
57140
108,704
112,084
3,380
3%
127,312
18,608
17%
127,195
18,491
17%
127,500
18,796
17%
127,525
18,821
17%
127,482
18,778
17%
116,252
7,548
7%
57180
58,300
56,503
-1,797
-3%
53,485
-4,815
-8%
53,419
-4,881
-8%
53,495
-4,805
-8%
53,483
-4,817
-8%
53,492
-4,808
-8%
55,812
-2,488
-4%
South Boulder Creek near
Eldorado Springs gage
North Fork South Platte River
Basin
North Fork South Platte below
Geneva Creek gage
North Fork South Platte above
Pine
South Platte River Mainstem
50700
98,125
117,629
19,504
20%
114,926
16,801
17%
115,306
17,181
18%
114,749
16,624
17%
114,846
16,721
17%
114,818
16,693
17%
125,352
27,227
28%
50750
148,964
168,481
19,517
13%
165,800
16,836
11%
166,177
17,213
12%
165,608
16,644
11%
165,706
16,742
11%
165,674
16,710
11%
176,211
27,247
18%
Antero Reservoir outflow
50150
33,710
33,708
-2
0%
33,707
-3
0%
33,708
-2
0%
33,708
-2
0%
33,707
-3
0%
33,707
-3
0%
33,708
-2
0%
Eleven Mile Reservoir outflow
50300
143,716
143,904
188
0%
143,159
-557
0%
143,145
-571
0%
143,245
-471
0%
143,169
-547
0%
143,161
-555
0%
144,101
385
0%
Cheesman Reservoir outflow
50450
301,717
303,206
1,489
0%
302,258
541
0%
302,253
536
0%
302,349
632
0%
302,271
554
0%
302,210
493
0%
303,178
1,461
0%
-6%
287,775
-19,093
-6%
287,830
-19,038
-6%
287,642
-19,226
-6%
285,959
-20,909
-7%
South Platte River at Waterton
51200
-5%
-6%
306,868
291,091
-15,777
287,635 -19,233
287,364 -19,504
gage
South Platte below Chatfield
51290
-5%
-6%
362,022
344,965
-17,057
341,365 -20,657
341,003 -21,019
Resevoir
South Platte River at Denver
51540
-2%
-2%
556,160
545,161
-10,999
543,270 -12,890
542,918 -13,242
gage
South Platte River at Henderson
58440
-2%
-7,967
-1%
-7,965
653,510
638,918
-14,592
645,543
645,545
gage
Note: A positive difference denotes an increase in flow, whereas a negative difference denotes a decrease in flow.
Average annual wet year flows for locations on the West Slope are based on an average of the five wettest years, which include 1952, 1962, 1983, 1984, and 1986.
Average annual wet year flows for locations on the East Slope are based on an average of the five wettest years, which include 1949, 1970, 1973, 1983, and 1984.
H7-6
B - 21
-6%
341,456
-20,566
-6%
341,499
-20,523
-6%
341,189
-20,833
-6%
339,998
-22,024
-6%
-2%
543,382
-12,778
-2%
543,403
-12,757
-2%
543,099
-13,061
-2%
541,582
-14,578
-3%
-1%
643,692
-9,818
-2%
644,442
-9,068
-1%
648,211
-5,299
-1%
643,714
-9,796
-1%
�Appendix B
Appendix H-9
Flow Duration and Effective Discharge Curves
Figure H-9.11
CR-2: Colorado River at Kemp Breeze State Wildlife Area
Flow Duration Curve- CR-2
120.00
100.00
~ Cu rrent
--a- Fu ll Use
- -No Action
80.00
--6-Aiternative l A
;:-
"'
>"'
';;;-
- -Alternative 8A
>
e."'
<::
0
60.00
·~
=
0
~
u::
40.00
20.00
l
0.00
~
u
0.00
1000.00
2000.00
3000.00
4000.00
5000.00
6000.00
7000.00
Flow {ds}
H9-11
B - 22
�Appendix B
Appendix H-9
Flow Duration and Effective Discharge Curves
Effective Discharge Results
Site
Abbv
Average
X-sec
Q.n(cfs)
Current
Full Use
Alt.lA
Alt8A
No Action
5,612
5,612
1,627
1,627
3,620
5 ,189
6,070
1,627
1,627
3,628
5,612
5,612
1,244
2,784
3,813
5,612
5,612
1,244
2,784
3, 813
5,612
6,070
1,627
1,627
3,734
2,277
2,277
1,827
1,827
2,052
2,277
2,125
2,319
2,319
2,260
2,277
2,277
2,319
2,319
2,298
2,277
2,277
2,319
2,319
2, 298
2,277
2,277
2,319
2,319
2,298
Parker
Wilcock & Crowe
574
574
574
574
574
574
574
574
574
574
MPM
Yang
338
338
456
411
501
515
610
610
592
610
610
592
610
610
592
815
606
388
388
549
606
606
482
482
544
606
606
598
598
602
606
606
598
598
602
606
606
598
598
602
990
942
93
941
742
942
942
93
941
730
942
942
941
941
942
942
942
941
941
942
990
942
500
941
843
Colorado at Kemp Breeze SWA
CR-2
XC-6
Parker
Wilcock & Crowe
MPM
Yang
Average
Blue River below Boulder Creek
BR-1
XC -8
Parker
Wilcock & Crowe
MPM
Yang
Average
North Fork of South Platte near Shawnee
NF-1
XC-6
Average
North Fork of South Platte near Pine
NF-2
XC-4
Parker
Wilcock & Crowe
MPM
Yang
Average
South Boulder Creek above Rollinsville
SBC-1
Conditions
XC-7
Parker
Wilcock & Crowe
MPM
Yang
Average
D.eff- Effective Discharge (cfs)
Page 3 of4
H9-19
B - 23
�Appendix B
Appendix H-9
Flow Duration and Effective Discharge Curves
Figure H-9.67
Current Conditions
CR-2: Colorado River at Kemp Breeze State Wildlife Area
Effective Discharge - Current Conditions - CR-2
1,200
T"""------------------------------------------~ Yang Annual Transport
-+-P90 Annual Transport
-+- W-C Annual Transport
"'
OJ
~
<:
800
0
.:::.
.~
....
"'
"'
Q,
u
t
600
0
~
<:
...
E
-;;;
"
<:
<:
..:
400
200 +-~---------------------------------~\--------
0
1,000
2,000
3,000
4,000
5 ,000
6,000
7,000
8,000
Flow {cfs)
H9-71
B - 24
�Appendix B
Appendix H-9
Flow Duration and Effective Discharge Curves
Figure H-9.69
No Action
CR-2: Colorado River at Kemp Breeze State Wildlife Area
Effective Discharge - No Action - CR-2
800
r-------------------------------------------------r=====================,~ Yang Annual Transport
~ P90 Annual Transport
- - - W-C Annual Transport
"'
OJ
~
500
<:
0
.:::.
.~
....
"'0. 400
"'
u
t
0
~
<:
...
E
-;;; 300
"
<:
<:
..:
200
100
0
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
Flow (cfs)
H9-73
B - 25
�Appendix B
Appendix H-9
Flow Duration and Effective Discharge Curves
Figure H-9.70
Alternative 1A
CR-2: Colorado River at Kemp Breeze State Wildlife Area
Effective Discharge - Alternative lA - CR-2
800 ~--------------------------------------------------~====================~-
700
+-------------------------------------------------------_,
Yang Annual Transport
~ P90 Annual Transport
~ W-C Annual Transport
600
..:-
"'>w
~
1:
g
500
·€
at:"' 400
0.
0
~
1:
~
,....
iii
300
"
1:
1:
<(
200
100
0
0
1,000
2,000
3,000
4,000
Flow (cfs)
H9-74
B - 26
5,000
6,000
7,000
8,000
�Appendix B
Appendix H-10
Sediment Supply and Bedload Capacity Curves
Figure H-10.11
Bedload Capacity Comparison
CR-2: Colorado River at Kemp Breeze State Wildlife Area
Bedload Capacity Comparison - CR-2
1,000
900 + - - - - -+------1 ~ Parker (1990)
Wilcock and Crowe (2003)
...,._ MPM
800 +----~----~
~ Yang
- - - Sediment Supply
700
>
"C
"'
',;;-
600
c
0
.!:;:.
~
·;:;
a.
u
"'
"'
"C
"'0
'6
500
400
"'"'
300
200
100
0
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
Flow {cfs)
H10-11
B - 27
�Appendix B
Appendix H-14
Peak Flows
Table H-14.4
Changes in the Peak Flow in an Average Year Compared to Current
Conditions1
Current Conditions
Timing
Peak (cfs)
(Date)
Node Number Node Name
St. Louis - Vasquez Section
2180
St. Louis Ck and Tributaries Diversion
2170
St. Louis Ck Diversion
2300
Elk Ck and Tributaries Diversion
2220
King Ck Diversion
2280
Vasquz Creek Diversion
Alternative 1a
Timing
Peak (cfs)
(Date)
Alt 1a - Current Conditions
Change in
Change in
Peak (cfs) Timing (days)2
39.6
54.1
10.6
1.8
72.0
21-Jun
21-Jun
21-Jun
21-Jun
21-Jun
24.3
41.5
7.1
1.1
46.3
27-Jun
21-Jun
21-Jun
24-Jun
18-Jun
-15.3
-12.5
-3.5
-0.7
-25.7
6
0
0
3
-3
Fraser - Jim Creek Section
2120
Fraser River Diversion
2160
Jim Ck Diversion
2700
Fraser River below St. Louis Ck
2810
Fraser River below Crooked Ck
58.0
15.1
302.0
551.0
10-Jun
12-Jun
21-Jun
16-Jun
41.1
7.9
202.0
436.0
18-Jun
22-Jun
21-Jun
21-Jun
-17.0
-7.2
-100.0
-115.0
8
10
0
5
Ranch Creek Section
2490
North Fork Ranch and Dribble Ck Diversion
2500
Main Ranch Ck Diversion
2520
Middle and South Fork Ranch Ck Diversion
19.3
25.4
34.3
19-Jun
21-Jun
21-Jun
16.5
21.2
24.0
21-Jun
21-Jun
21-Jun
-2.8
-4.2
-10.3
2
0
0
Williams Fork River
3150
Bobtail Ck Diversion
3600
Williams Fork River abv Darling Ck Gage
50.0
203.5
21-Jun
21-Jun
41.6
186.2
21-Jun
21-Jun
-8.4
-17.3
0
0
Colorado River
1350
Colorado River below Windy Gap
1430
Colorado River below Williams Fork River Confluence
5020
Colorado River near Kremmling Gage
801.8
976.2
2,640.9
22-Jun
22-Jun
27-Jun
625.7
814.4
2,072.9
25-Jun
21-Jun
23-Jun
-176.1
-161.8
-568.0
3
-1
-4
Muddy Creek
1600
Wolford Mountain Reservoir Outflow
559.9
31-May
529.2
31-May
-30.7
0
Blue River
4250
4650
900.4
1,337.8
17-Jun
27-Jun
625.7
900.7
27-Jun
23-Jun
-274.7
-437.1
10
-4
South Boulder Creek
57120
South Boulder Creek at Pinecliffe Gage
57140
Gross Reservoir Outflow
57180
South Boulder Creek near Eldorado Springs Gage
710.6
456.9
317.4
8-Jun
23-Jun
9-Jun
838.7
428.6
293.3
8-Jun
26-Jun
9-Jun
128.1
-28.3
-24.1
0
3
0
North Fork South Platte River
50700
North Fork South Platte below Geneva Ck Gage
332.8
24-Jun
434.5
26-Jun
101.7
2
South Platte River
51200
South Platte River at Waterton Gage
58440
South Platte River at Henderson Gage
656.7
1,227.7
14-Jun
17-Jun
614.5
1,190.2
14-Jun
17-Jun
-42.2
-37.5
0
0
Dillon Reservoir Outflow
Green Mtn Reservoir Outflow
1
An average year is defined as the average of the 45-year study period.
A negative value indicates the peak occurs earlier by the number of days shown, whereas a positive value indicates the peak occurs
..later by the number of days shown.
2
H14-5
B - 28
�Appendix B
Appendix H-14
Peak Flows
Table H-14.5
Changes in the Peak Flow in a Wet Year Compared to Current
Conditions1
Node Number Node Name
St. Louis - Vasquez Section
2180
St. Louis Ck and Tributaries Diversion
2170
St. Louis Ck Diversion
2300
Elk Ck and Tributaries Diversion
2220
King Ck Diversion
2280
Vasquz Creek Diversion
Current Conditions
Timing
Peak (cfs)
(Date)
Alternative 1a
Timing
Peak (cfs)
(Date)
Alt 1a - Current Conditions
Change in
Change in
Peak (cfs) Timing (days)2
88.9
106.1
21.8
1.8
177.4
26-Jun
1-Jul
22-Jun
21-Jun
25-Jun
88.7
104.1
22.6
3.9
172.5
27-Jun
27-Jun
21-Jun
22-Jun
21-Jun
-0.2
-2.0
0.8
2.2
-4.9
1
-4
-1
1
-4
Fraser - Jim Creek Section
2120
Fraser River Diversion
2160
Jim Ck Diversion
2700
Fraser River below St. Louis Ck
2810
Fraser River below Crooked Ck
183.3
43.8
703.0
1,269.0
21-Jun
20-Jun
14-Jun
13-Jun
177.2
45.4
675.0
1,152.0
21-Jun
22-Jun
21-Jun
13-Jun
-6.1
1.6
-28.0
-117.0
0
2
7
0
Ranch Creek Section
2490
North Fork Ranch and Dribble Ck Diversion
2500
Main Ranch Ck Diversion
2520
Middle and South Fork Ranch Ck Diversion
40.1
51.1
74.6
20-Jun
20-Jun
20-Jun
40.1
51.1
74.6
20-Jun
20-Jun
20-Jun
0.0
0.0
0.0
0
0
0
Williams Fork River
3150
Bobtail Ck Diversion
3600
Williams Fork River abv Darling Ck Gage
101.2
361.9
21-Jun
21-Jun
101.2
361.8
21-Jun
21-Jun
0.0
-0.1
0
0
Colorado River
1350
Colorado River below Windy Gap
1430
Colorado River below Williams Fork River Confluence
5020
Colorado River near Kremmling Gage
2,929.9
3,569.7
6,872.1
1-Jul
1-Jul
27-Jun
2,925.1
3,667.8
6,831.6
1-Jul
1-Jul
27-Jun
-4.8
98.1
-40.5
0
0
0
Muddy Creek
1600
Wolford Mountain Reservoir Outflow
869.4
29-May
878.3
29-May
8.9
0
Blue River
4250
4650
1,446.1
2,707.4
28-Jun
30-Jun
1,654.0
2,819.4
20-Jun
25-Jun
207.9
112.0
-8
-5
South Boulder Creek
57120
South Boulder Creek at Pinecliffe Gage
57140
Gross Reservoir Outflow
57180
South Boulder Creek near Eldorado Springs Gage
641.1
450.8
383.9
27-May
27-Jun
11-Jun
884.5
519.4
358.7
9-Jun
27-Jun
11-Jun
243.4
68.6
-25.2
13
0
0
North Fork South Platte River
50700
North Fork South Platte below Geneva Ck Gage
415.1
19-Jun
418.5
19-Jun
3.4
0
South Platte River
51200
South Platte River at Waterton Gage
58440
South Platte River at Henderson Gage
2,420.1
4,048.6
13-Jun
14-Jun
2,304.6
3,972.4
13-Jun
6-May
-115.5
-76.2
0
-393
Dillon Reservoir Outflow
Green Mtn Reservoir Outflow
1
An average wet year is defined as the average of the 5 wettest years of the study period on the East and West Slopes, respectively.
A negative value indicates the peak occurs earlier by the number of days shown, whereas a positive value indicates the peak occurs
..later by the number of days shown.
2
3
A second peak of 3,886 cfs occurs on June 14 under Alternative 1a, which is 163 cfs less than the peak on June 14th under Current Conditions.
H14-6
B - 29
�Appendix B
Appendix H-16
Basin Maps
Figure 3: Colorado River Watershed Map with Assessment Locations
19
(C"·' >Represen tative Reach
Gage Locat1on
~
Aenal
· Photo Reach
->
...,..._
Channel V'.ldth Locat1on
1 mch = 14.000 feet
USGS Streams
c·.I Drainage Basin Boundary
B - 30
H16-3
�Appendix B
Appendix H-17
Aerial Photo Results
Table H-17.2. Sinuosity below DW Diversions where Flows have been Decreased
CRl: Colorado River above Parshall
Date
Valley CL Length (ft)
Water CL Length (ft)
Water Length I Valley Length
1962
18424
20729
1.13
2009
18424
20643
1.12
CR2: Colorado River at Kemp Breeze State Wildlife Area
Date
Valley CL Length (ft)
Water CL Length (ft)
Water Length I Valley Length
1983
9186
13804
1.50
2009
9186
13820
1.50
FRl: Fraser River near Winter Park Gage (north segment)
Date
Valley CL Length (ft)
Water CL Length (ft)
Water Length I Valley Length
1962
8668
10318
1.19
2009
8668
10233
1.18
FRl: Fraser River near Winter Park Gage (south segment)
Date
Valley CL Length (ft)
Water CL Length (ft)
Water Length/ Valley Length
1962
7725
9064
1.17
2009
7725
9022
1.17
FR2: Fraser River Tabernash
Date
Valley CL Length (ft)
Water CL Length (ft)
Water Length I Valley Length
1962
19367
26512
1.37
2009
19367
25986
1.34
FR3: St. Louis Creek
Date
Valley CL Length (ft)
Water CL Length (ft)
Water Length I Valley Length
1962
12595
15485
1.23
2009
12595
15646
1.24
FR4: Ranch Creek
Date
Valley CL Length (ft)
Water CL Length (ft)
Water Length I Valley Length
1962
10274
13473
1.31
2009
10274
13025
1.27
FRS: Fraser River Downstream of Denver Water's Diversion (north segment)
Date
Valley CL Length (ft)
Water CL Length (ft)
Water Length I Valley Length
1985
6112
7497
1.23
2009
6112
7804
1.28
FR7: Vasquez Creek (north segment)
Date
Valley CL Length (ft)
1988
2009
Water Length I Valley Length
Water CL Length (ft)
4235
4235
7067
7116
1.67
1.68
WFl: Williams Fork near Sugarloaf Campground
Date
Valley CL Length (ft)
Water Length I Valley Length
Water CL Length (ft)
1983
19257
27056
1.41
2009
19257
27167
1.41
WF2: Williams Fork below Steelman Creek
Date
Valley CL Length (ft)
Water Length I Valley Length
Water CL Length (ft)
1985
5159
6051
1.17
2009
5159
5994
1.16
BRl: Blue River below Boulder Creek
Date
Valley CL Length (ft)
Water CL Length (ft)
Water Length I Valley Length
1983
32886
36937
1.12
2009
32886
36856
1.12
H17-2
B - 31
�Appendix B
Appendix H-17
Aerial Photo Results
Table H-17.5.
Changes in Channel Width below DW Diversions where Flows have been
Decreased
CRl: Colorado River above Parshall
Segment ID
1962
2009
Channel Width (ft)
Channel Width (ft)
1
3
97
101
104
4
77
5
44
44
38
2
6
7
Average
Change in Width (ft)
97
104
90
105
57
55
66
82
72
0
3
-14
28
13
11
28
10
CR2: Colorado River at Kemp Breeze State Wildlife Area
1983
Segment ID
2009
Channel Width (ft)
1
2
3
4
5
6
7
8
9
10
Average
Channel Width (ft)
Change in Width (ft)
120
128
163
75
141
131
138
159
85
134
11
10
-4
92
103
69
120
66
108
110
78
109
18
-3
9
-11
77
10
112
4
100
11
-8
FRl: Fraser River near Winter Park Gage (north segment)
1962
Segment ID
2009
Channel Width (ft)
1
2
3
4
5
6
7
8
9
10
Average
Channel Width (ft)
14
27
15
22
24
13
18
11
15
10
17
B - 32
Change in Width (ft)
16
26
25
28
31
18
19
14
20
14
21
2
-2
10
6
8
5
1
3
5
4
4
H17-5
�Appendix B
Appendix H-20
Flood Flow Frequency Data
Figure H-20.11
CR-2: Colorado River at Kemp Breeze State Wildlife Area
B - 33
H20-11
�Appendix B
Appendix H-21
Phase 2 Sediment Transport Graphs
Figure H-21.21
CR-2, Colorado River at Kemp Breeze State Wildlife Area, Parker 1990
H21-23
B - 34
�Appendix B
Appendix H-21
Phase 2 Sediment Transport Graphs
Figure H-21.22
CR-2, Colorado River at Kemp Breeze State Wildlife Area, Wilcock and Crowe 2003
H21-24
B - 35
�Appendix C
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Colorado River # 8
CP30
CP40
CP50
Kemp Breeze SWA
OPUS!(ADCP
r k C ol
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a
Fo
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ad
r
olo
STATE OF COLORADO C
W
SWA Boundary
Streams
(
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KempBreeze_SurveyControl_2018
0 155 310
620
930
1,240
Feet
KempBreeze_Survey_2018
C-1
º
SURVEY LAYOUT
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 1 OF 6
5/9/2019
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP BREEZE SWA
PLAN VIEW
1 r#
ve
Ri
#
ms
(
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9
�Appendix C
807974
57 .99
.74
8.06
781
7047.89
7144.81
7226.72
7334.84
7439.68
759
8.9
0
6850.45
6723.16
6509.
8
6573 6
.14
6367.
85
.29
9
6208
6049.1
5873.69
5910.06
5737.84
5597.70
5417.60
5026.85
4165.07
4225.47
4282.11
4329.34
3980.46
3787.63
1
3227.79
3317.62
3452.84 3402.19
3557.02 3512.54
3614.2
5
3673.07
3115.4
3197.63
2678.11
570.23
397.22
12
.60
711.00
27
262.59
76
7.86
5130.32
º
4911.95
2
4812.0
4756.73
2828.29
2585.59
2462.48
.16
2257
9 .53
5.0
0
208 193
9
.1
90 02
.
1,160
17
16
7
.88
38.8
4610
46
4580.09
4513.76
4456.53
4398.86
H4
REACH 1
REACH 2
4137.79
R
C
EA
2975.24
REACH 3
15
26
2
.0
13
74
.45
.52
66
10
1
2.4
91
River
Banks
Ineffective Flow
Manning's n
0.039
0.065
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0.03
0.075
Flowpaths
0.035
0.095
0 145 290
580
870
Feet
XSCutLines
C-2
HEC-RAS: EXISITING CONDITIONS
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 2 OF 6
5/7/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix C
0
8.9
4.99
.74
797
57
80
781
8.06
759
7439.68
7334.84
7226.72
7144.81
7047.89
6850.45
6723.16
3.14
657
6509.
86
6208
.29
6049.19
5910.06
5737.84
5873.69
5130.32
5417.60
5597.70
6367.85
REACH 1
Contour (1 ft)
XSCutLines
0.039
River
Ineffective Flow
0.065
Banks
Manning's n
Bridges
0.03
Flowpaths
0.035
0.075
0 50 100
200
300
400
Feet
0.095
C-3
º
HEC-RAS: EXISITING CONDITIONS
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 3 OF 6
5/7/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix C
REACH 3
REACH 2
0.065
Manning's n
Bridges
0.03
Flowpaths
0.035
0.075
5417.60
5026.85
4329.34
4282.11
4225.47
3980.46
Ineffective Flow
4911.95
River
4812.02
0.039
Banks
4638.87
4165.07
4610.88
4580.09
4456.53
XSCutLines
5130.32
4756.73
4513.76
4398.86
4137.79
Contour (1 ft)
REACH 1
0
30 60
120
180
240
Feet
0.095
C-4
º
HEC-RAS: EXISITING CONDITIONS
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 4 OF 6
5/7/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix C
REACH 3
R
C
EA
4329.34
4137.79
4225.47
3980.46
4165.07
3673.07
3614.25
3557.02
3402.19
.79
3227
3197.63
3115.41
2462.48
2975.24
2828.29
2585.59
2678.11
3512.54
3317.62
4282.11
3452.84
4398.86
3787.63
REACH 2
H4
Contour (1 ft)
XSCutLines
0.039
River
Ineffective Flow
0.065
Banks
Manning's n
Bridges
0.03
Flowpaths
0.035
0.075
0 30 60
120
180
240
Feet
0.095
C-5
º
HEC-RAS: EXISITING CONDITIONS
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 5 OF 6
5/7/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix C
3
0.2
8.1
Bridges
0.03
Flowpaths
0.035
0.075
0.095
º
C-6
53
1930.
Manning's n
Feet
5.4
311
H2
.19
Banks
400
1790
0.065
300
AC
.02
Ineffective Flow
200
1676
River
0 50 100
.02
0.039
1526
XSCutLines
1374.45
1066.52
912.41
Contour (1 ft)
RE
1
297
5.24
282
8.29
267
2585
.48
2462
2085.09
1227.60
2257.16
.59
711.0
0
1
57
.22
397
26
2.5
9
7.8
6
REACH 3
HEC-RAS: EXISITING CONDITIONS
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 6 OF 6
5/7/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Colorado River Kemp-Breeze SWA
7475
Legend
EG 25 Year
WS 25 Year
EG 5 Year
Crit 25 Year
7470
WS 5 Year
Crit 5 Year
EG 1.5 Year
WS 1.5 Year
Crit 1.5 Year
EG Baseflow
7465
WS Baseflow
Crit Baseflow
Ground
Right Levee
Elevation (ft)
7460
7455
7450
7445
7440
0
1000
2000
3000
4000
5000
Main Channel Distance (ft)
C-7
6000
7000
8000
9000
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 8057.74 Note: n values for first profile.
.035
7485
.075
.061
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 7975.00 Note: n values for first profile.
.075
.035
7485
Legend
.075
.061
.075
.095
Legend
EG 25 Year
7480
WS 25 Year
7475
WS 5 Year
EG 5 Year
WS 5 Year
EG 1.5 Year
7475
WS 1.5 Year
EG Baseflow
EG 5 Year
Elevation (ft)
Elevation (ft)
7480
EG 1.5 Year
WS 1.5 Year
7470
EG Baseflow
Crit Baseflow
7470
7465
EG 25 Year
WS 25 Year
WS Baseflow
0
100
200
300
400
WS Baseflow
7465
Ground
Ground
Bank Sta
Bank Sta
7460
500
0
100
200
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 7818.06 Note: n values for first profile.
.035
7485
.075
.061
.075
.095
WS 1.5 Year
EG Baseflow
400
500
EG 5 Year
WS 5 Year
EG 1.5 Year
7475
WS 1.5 Year
EG Baseflow
7470
WS Baseflow
Ground
Ground
Bank Sta
Bank Sta
7465
600
0
100
200
.035
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.075
.035
5/7/2019
.075
.061
KB_HECRAS_2018
7476
7480
EG 25 Year
7478
7474
WS 5 Year
7472
EG 1.5 Year
WS 1.5 Year
7470
EG Baseflow
.075
.061
.075 .095
Legend
EG 25 Year
WS 25 Year
7466
7464
500
Station (ft)
WS 1.5 Year
7470
7466
Bank Sta
EG 5 Year
EG 1.5 Year
Ground
400
.035
7472
7468
300
5/7/2019
WS 5 Year
WS Baseflow
200
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
7474
7468
100
500
7476
EG 5 Year
Elevation (ft)
Elevation (ft)
Legend
WS 25 Year
0
400
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 7334.84 Note: n values for first profile.
.
0
7
5
7478
7464
300
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 7439.67 Note: n values for first profile.
7480
.095
Legend
Station (ft)
KB_HECRAS_2018
.075
7480
WS Baseflow
7465
.061
EG 25 Year
EG 1.5 Year
7470
.075
WS 25 Year
WS 5 Year
300
5/7/2019
EG 25 Year
Elevation (ft)
Elevation (ft)
7475
200
500
WS 25 Year
EG 5 Year
100
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
7485
Legend
0
400
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 7598.90 Note: n values for first profile.
7480
7460
300
Station (ft)
EG Baseflow
WS Baseflow
Ground
Bank Sta
0
100
200
300
Station (ft)
C-8
400
500
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 7226.72 Note: n values for first profile.
.035
7478
.075
.061
.
0
7
5
7476
.035
.075
.061
EG 1.5 Year
7470
WS 1.5 Year
EG Baseflow
7468
Legend
EG 25 Year
7480
WS 25 Year
7475
WS 5 Year
EG 5 Year
WS Baseflow
7466
Bank Sta
100
200
300
400
WS 1.5 Year
7470
EG Baseflow
WS Baseflow
7465
Ground
0
EG 1.5 Year
7460
500
Ground
Bank Sta
0
100
200
300
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
7478
.075
5/7/2019
KB_HECRAS_2018
500
600
.061
.075
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 6850.45 Note: n values for first profile.
.095
EG 25 Year
7472
EG 1.5 Year
7470
WS 1.5 Year
EG Baseflow
7468
Elevation (ft)
EG 5 Year
WS 5 Year
.075
.061
7472
WS 25 Year
7474
.035
7474
Legend
7476
Elevation (ft)
400
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 7047.89 Note: n values for first profile.
.
0
7
5
.061
.075
.035
Legend
EG 25 Year
WS 25 Year
EG 5 Year
7470
WS 5 Year
7468
EG 1.5 Year
7466
EG Baseflow
WS 1.5 Year
WS Baseflow
7466
WS Baseflow
7464
Ground
Bank Sta
0
100
200
300
400
7462
500
Ground
Bank Sta
0
100
200
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
7474
.095
5/7/2019
KB_HECRAS_2018
.061
.075
.035
Legend
7476
EG 25 Year
7474
WS 25 Year
7468
EG 1.5 Year
7466
EG Baseflow
WS 1.5 Year
7464
Elevation (ft)
WS 5 Year
300
400
500
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
.035
.095
.061
.075
.035
Legend
EG 25 Year
WS 25 Year
WS 5 Year
7468
EG 1.5 Year
Ground
7462
7460
Station (ft)
WS 1.5 Year
7466
7464
600
EG 5 Year
7470
WS Baseflow
Bank Sta
200
500
7472
EG 5 Year
7470
100
400
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 6573.14 Note: n values for first profile.
7472
0
300
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 6723.16 Note: n values for first profile.
Elevation (ft)
.035
EG 5 Year
WS 5 Year
7472
7462
.075
EG 25 Year
Elevation (ft)
Elevation (ft)
.035
7485
Legend
7474
7464
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 7144.81 Note: n values for first profile.
WS 25 Year
7464
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
EG Baseflow
WS Baseflow
Ground
Bank Sta
0
100
200
300
Station (ft)
C-9
400
500
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 6509.86 Note: n values for first profile.
.035
7480
.095
.061
.075
.035
.
0
9
5
EG 25 Year
WS 1.5 Year
EG Baseflow
7465
Elevation (ft)
Elevation (ft)
EG 5 Year
EG 1.5 Year
.095
.061
.095
EG 25 Year
WS 25 Year
EG 5 Year
7480
WS 5 Year
7475
EG 1.5 Year
7470
EG Baseflow
WS 1.5 Year
WS Baseflow
7465
Bank Sta
0
100
200
KB_HECRAS_2018
300
400
7460
500
Ground
Bank Sta
0
100
200
.035
7485
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.095
5/7/2019
KB_HECRAS_2018
.061
.075
.035
Legend
7478
WS 25 Year
7474
EG 5 Year
7475
WS 5 Year
7472
EG 1.5 Year
WS 1.5 Year
7470
EG Baseflow
Elevation (ft)
EG 25 Year
7480
WS Baseflow
7465
Ground
200
300
400
500
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
.095
.061
.035
.061
EG 1.5 Year
7468
WS 1.5 Year
7466
EG Baseflow
7464
WS Baseflow
Ground
Bank Sta
0
100
200
KB_HECRAS_2018
300
400
500
.075
.035
.095
.061
.075
.035
Legend
EG 25 Year
WS 25 Year
7475
Elevation (ft)
WS 1.5 Year
EG Baseflow
7465
.035
7480
EG 25 Year
EG 1.5 Year
7470
WS Baseflow
400
5/7/2019
WS 25 Year
WS 5 Year
300
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 5873.69 Note: n values for first profile.
EG 5 Year
200
EG 25 Year
EG 5 Year
5/7/2019
7475
100
Legend
7470
7460
600
Legend
0
.
0
3
5
Station (ft)
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.095
.075
WS 5 Year
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 5910.06 Note: n values for first profile.
7480
5/7/2019
WS 25 Year
Station (ft)
KB_HECRAS_2018
500
7462
Bank Sta
100
400
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 6049.19 Note: n values for first profile.
7476
0
300
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 6208.29 Note: n values for first profile.
Elevation (ft)
.035
Legend
Station (ft)
Elevation (ft)
.095
WS Baseflow
Ground
7460
.075
7485
WS 25 Year
7470
.035
7490
Legend
WS 5 Year
7460
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 6367.85 Note: n values for first profile.
7475
7460
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
EG 5 Year
WS 5 Year
EG 1.5 Year
7470
WS 1.5 Year
EG Baseflow
7465
WS Baseflow
Ground
Ground
Bank Sta
Bank Sta
500
Station (ft)
7460
0
100
200
300
Station (ft)
C - 10
400
500
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 5737.84 Note: n values for first profile.
.095
.061
.075
7474
Elevation (ft)
7472
EG 25 Year
7472
WS 25 Year
EG 5 Year
7470
EG 5 Year
7468
WS 5 Year
7466
EG 1.5 Year
WS 1.5 Year
7464
WS Baseflow
7462
Ground
400
Legend
WS 1.5 Year
7464
EG Baseflow
7462
WS Baseflow
7460
Ground
7458
Bank Sta
300
7456
500
Bank Sta
0
100
200
Station (ft)
KB_HECRAS_2018
.035
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.095
.061
.075
5/7/2019
.061
.075
KB_HECRAS_2018
400
500
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 5130.32 Note: n values for first profile.
.
0
3
5
7468
EG 25 Year
EG 5 Year
WS 5 Year
7464
EG 1.5 Year
7462
EG Baseflow
WS 1.5 Year
.061
.075
Legend
EG 25 Year
7468
WS 25 Year
7466
.035
7470
Legend
Elevation (ft)
Elevation (ft)
300
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 5417.60 Note: n values for first profile.
7470
.035
EG 25 Year
EG Baseflow
200
.075
WS 25 Year
EG 1.5 Year
100
.061
7474
7468
0
.095
7476
WS 5 Year
7466
.035
Legend
7470
7460
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 5597.70 Note: n values for first profile.
Elevation (ft)
.035
7476
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
WS 25 Year
EG 5 Year
7466
WS 5 Year
7464
EG 1.5 Year
7462
EG Baseflow
WS 1.5 Year
WS Baseflow
7460
7458
WS Baseflow
7460
Ground
Bank Sta
0
100
200
300
400
7458
500
Ground
Bank Sta
0
100
200
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 5026.85 Note: n values for first profile.
.035
7470
300
400
500
600
Station (ft)
.061
.075
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
.061
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4911.95 Note: n values for first profile.
.095
7470
Legend
EG 25 Year
7468
.075
Legend
EG 25 Year
7468
WS 25 Year
7466
WS 5 Year
WS 25 Year
WS 5 Year
7464
EG 1.5 Year
7462
WS 1.5 Year
EG Baseflow
7460
WS Baseflow
7458
7456
EG 5 Year
EG 5 Year
Elevation (ft)
Elevation (ft)
7466
Ground
Bank Sta
0
100
200
300
400
500
600
Station (ft)
Crit 25 Year
EG 1.5 Year
7464
WS 1.5 Year
Crit 5 Year
7462
Crit 1.5 Year
EG Baseflow
7460
WS Baseflow
Crit Baseflow
Ground
7458
7456
Ineff
Bank Sta
0
100
200
300
Station (ft)
C - 11
400
500
600
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4812.02 Note: n values for first profile.
.035
7472
.061
.075
.035
WS 25 Year
Crit 25 Year
7464
WS 1.5 Year
Crit 5 Year
7462
EG Baseflow
7460
WS Baseflow
7458
Crit Baseflow
Bank Sta
300
400
500
600
EG 5 Year
WS 5 Year
Crit 25 Year
7466
EG 1.5 Year
WS 1.5 Year
7464
Crit 5 Year
7462
EG Baseflow
WS Baseflow
Crit 1.5 Year
Crit Baseflow
Ground
7456
Ineff
200
WS 25 Year
7458
Ground
100
Legend
EG 25 Year
7460
Crit 1.5 Year
7456
7454
700
Ineff
Bank Sta
0
100
200
300
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
400
500
600
700
Station (ft)
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4781.11 BR Breeze Bridge Note: n values for first profile.
7475
.035
7468
Elevation (ft)
Elevation (ft)
WS 5 Year
EG 1.5 Year
.075
7470
EG 5 Year
7466
.061
7472
EG 25 Year
7468
.035
7474
Legend
0
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4781.11 BR Breeze Bridge Note: n values for first profile.
7470
7454
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.061
.075
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4756.73 Note: n values for first profile.
.035
.035
7475
Legend
.061
.075
.035
Legend
EG 25 Year
EG 25 Year
WS 25 Year
7470
WS 25 Year
7470
EG 5 Year
EG 5 Year
Crit 25 Year
7465
EG 1.5 Year
WS 1.5 Year
Crit 5 Year
7460
EG Baseflow
WS Baseflow
WS 5 Year
Elevation (ft)
Elevation (ft)
WS 5 Year
Crit 25 Year
7465
EG 1.5 Year
WS 1.5 Year
Crit 5 Year
7460
EG Baseflow
WS Baseflow
Crit 1.5 Year
7450
Crit 1.5 Year
Crit Baseflow
7455
Ground
0
100
200
300
400
500
600
Crit Baseflow
7455
Ground
Ineff
Ineff
Bank Sta
Bank Sta
7450
700
0
100
200
300
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4638.87 Note: n values for first profile.
.
0
7
5
Elevation (ft)
7472
.061
.075
.035
Legend
7472
EG 25 Year
7470
7470
WS 25 Year
7468
EG 5 Year
WS 5 Year
7466
EG 1.5 Year
WS Baseflow
7460
Ground
7458
7458
Bank Sta
400
500
.035
.075
.061
.075
.035
Legend
EG 25 Year
WS 25 Year
600
Station (ft)
EG 5 Year
EG 1.5 Year
7460
300
5/7/2019
7464
WS 1.5 Year
200
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
WS 5 Year
EG Baseflow
100
700
7466
7462
0
600
7468
7464
7456
500
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4610.88 Note: n values for first profile.
Elevation (ft)
.035
7474
400
Station (ft)
WS 1.5 Year
7462
7456
EG Baseflow
WS Baseflow
Ground
Bank Sta
0
100
200
300
Station (ft)
C - 12
400
500
600
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4580.09 Note: n values for first profile.
.035
7472
.075
.061
.075
.035
.035
7475
Legend
.
0
7
5
EG 25 Year
WS 25 Year
7468
7464
EG 1.5 Year
WS 1.5 Year
7462
EG Baseflow
Elevation (ft)
WS 5 Year
.061
.035
Legend
EG 25 Year
WS 25 Year
EG 5 Year
WS 5 Year
EG 1.5 Year
7465
WS 1.5 Year
EG Baseflow
7460
WS Baseflow
7458
Ground
Ground
Bank Sta
Bank Sta
0
100
200
300
400
500
600
7460
7455
700
WS Baseflow
0
100
200
300
400
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
.
0
7
5
7472
.061
.075
.035
7470
7468
7466
Legend
EG 5 Year
WS 5 Year
7464
EG 1.5 Year
7462
WS 1.5 Year
7460
EG Baseflow
7458
WS Baseflow
Ground
7456
Bank Sta
7454
700
Bank Sta
0
100
200
300
Station (ft)
KB_HECRAS_2018
.035
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.075
400
500
600
700
Station (ft)
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4329.34 Note: n values for first profile.
.061
.075
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4282.11 Note: n values for first profile.
.035
.035
.075
.061
.075
.035
Legend
7472
7470
EG 25 Year
7470
EG 25 Year
7468
WS 25 Year
7468
WS 25 Year
EG 5 Year
7466
7466
WS 5 Year
7464
EG 1.5 Year
7462
WS 1.5 Year
7460
EG Baseflow
7458
WS Baseflow
Ground
7456
7454
Elevation (ft)
7472
.035
EG 5 Year
Ground
600
.075
EG 25 Year
WS Baseflow
500
.061
WS 25 Year
7460
400
.075
7468
WS 1.5 Year
7458
.035
EG 25 Year
EG Baseflow
300
5/7/2019
WS 25 Year
7462
200
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
7470
7464
100
800
7472
EG 1.5 Year
0
700
Legend
WS 5 Year
7466
7456
600
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4398.86 Note: n values for first profile.
Elevation (ft)
.035
7474
500
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4456.53 Note: n values for first profile.
Elevation (ft)
.075
7470
EG 5 Year
7466
7456
Elevation (ft)
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4513.76 Note: n values for first profile.
7470
Elevation (ft)
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
Bank Sta
0
100
200
300
400
500
600
700
Station (ft)
Legend
EG 5 Year
WS 5 Year
7464
EG 1.5 Year
7462
WS 1.5 Year
7460
EG Baseflow
7458
WS Baseflow
Ground
7456
7454
Bank Sta
0
100
200
300
400
Station (ft)
C - 13
500
600
700
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4225.47 Note: n values for first profile.
.075
.061
.
0
7
5
7470
.
0
4
5
.075
.035
Elevation (ft)
7468
7466
Legend
7472
EG 5 Year
7462
EG 1.5 Year
WS 1.5 Year
7460
EG Baseflow
WS Baseflow
7456
Ground
7454
Bank Sta
7452
700
Bank Sta
0
100
200
300
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
.
0
7
5
5/7/2019
.061
.
0
7
5
.035
7480
Legend
EG 25 Year
600
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
.075
5/7/2019
WS 5 Year
EG 1.5 Year
WS 1.5 Year
EG Baseflow
.061
. .
00
73
5
.035
Legend
EG 25 Year
WS 25 Year
EG 5 Year
WS 5 Year
Elevation (ft)
7465
7460
KB_HECRAS_2018
7475
WS 25 Year
EG 5 Year
Elevation (ft)
500
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3980.46 Note: n values for first profile.
7470
7470
Crit 25 Year
EG 1.5 Year
WS 1.5 Year
7465
Crit 5 Year
Crit 1.5 Year
EG Baseflow
7460
WS Baseflow
WS Baseflow
7455
7450
400
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4137.79 Note: n values for first profile.
7475
EG 25 Year
WS 25 Year
7458
Ground
600
Legend
WS 5 Year
WS Baseflow
500
.035
7464
7458
400
.075
7466
WS 1.5 Year
300
.
0
4
5
EG 5 Year
EG Baseflow
200
.075
7468
7460
100
.061
EG 25 Year
EG 1.5 Year
0
.075
WS 25 Year
7462
7456
.035
7470
WS 5 Year
7464
7454
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 4165.07 Note: n values for first profile.
Elevation (ft)
.035
7472
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
Crit Baseflow
7455
Ground
Levee
Bank Sta
0
200
400
600
800
1000
Ground
7450
1200
Bank Sta
0
200
400
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
.
0
7
5
.035
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3787.63 Note: n values for first profile.
.035
7475
.061
600
800
Station (ft)
. .
0 0
7 3
5
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
7475
Legend
.075
.061
EG 25 Year
WS 25 Year
7470
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3673.07 Note: n values for first profile.
. .
0 0
7 3
5
.035
Legend
EG 25 Year
WS 25 Year
7470
EG 5 Year
EG 5 Year
Crit 25 Year
7465
EG 1.5 Year
Crit 5 Year
WS 1.5 Year
7460
Crit 1.5 Year
EG Baseflow
WS 5 Year
Elevation (ft)
Elevation (ft)
WS 5 Year
Crit 25 Year
7465
EG 1.5 Year
Crit 5 Year
WS 1.5 Year
7460
Crit 1.5 Year
EG Baseflow
WS Baseflow
Crit Baseflow
7455
7450
Ground
0
100
200
300
400
500
600
WS Baseflow
Crit Baseflow
7455
Ground
Levee
Levee
Bank Sta
Bank Sta
700
Station (ft)
7450
0
100
200
300
400
Station (ft)
C - 14
500
600
700
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3614.25 Note: n values for first profile.
.035
7475
.
0
7
5
.061
. .
0 0
7 3
5
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
.035
7475
Legend
.075
.061
.075 .
0
3
EG 25 Year
WS 25 Year
7470
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3557.02 Note: n values for first profile.
.035
Legend
EG 25 Year
WS 25 Year
7470
EG 5 Year
EG 5 Year
Crit 25 Year
7465
EG 1.5 Year
WS 1.5 Year
Crit 5 Year
7460
Crit 1.5 Year
EG Baseflow
WS 5 Year
Elevation (ft)
Elevation (ft)
WS 5 Year
Crit 25 Year
7465
EG 1.5 Year
WS 1.5 Year
Crit 5 Year
7460
Crit 1.5 Year
EG Baseflow
WS Baseflow
Crit Baseflow
7455
7450
WS Baseflow
0
100
200
300
400
500
600
Crit Baseflow
7455
Ground
Ground
Levee
Levee
Bank Sta
Bank Sta
7450
700
0
100
200
300
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3512.54 Note: n values for first profile.
.035
7475
.
0
7
5
.061
400
500
600
700
Station (ft)
.075 .
0
3
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3452.84 Note: n values for first profile.
.035
.035
7475
Legend
.
0
7
5
EG 25 Year
WS 25 Year
7470
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.061
.075 .
0
3
.035
Legend
EG 25 Year
WS 25 Year
7470
EG 5 Year
EG 5 Year
Crit 25 Year
7465
EG 1.5 Year
WS 1.5 Year
Crit 5 Year
7460
Crit 1.5 Year
EG Baseflow
WS 5 Year
Elevation (ft)
Elevation (ft)
WS 5 Year
Crit 25 Year
7465
EG 1.5 Year
WS 1.5 Year
Crit 5 Year
7460
Crit 1.5 Year
EG Baseflow
WS Baseflow
Crit Baseflow
7455
7450
WS Baseflow
0
100
200
300
400
500
600
Crit Baseflow
7455
Ground
Ground
Levee
Levee
Bank Sta
Bank Sta
7450
700
0
100
200
300
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3402.19 Note: n values for first profile.
.035
7472
.075
.061
.075
7470
.
0
3
500
600
700
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3317.62 Note: n values for first profile.
.035
.035
7475
Legend
.
0
7
5
EG 25 Year
WS 25 Year
7468
.061
.075
. .
0 0
3 7
5
.035
Legend
EG 25 Year
WS 25 Year
7470
EG 5 Year
EG 5 Year
Crit 25 Year
7464
EG 1.5 Year
WS 1.5 Year
7462
Crit 5 Year
7460
Crit 1.5 Year
EG Baseflow
7458
Crit 25 Year
Elevation (ft)
WS 5 Year
7466
Elevation (ft)
400
Station (ft)
WS 5 Year
7465
Crit 5 Year
EG 1.5 Year
WS 1.5 Year
7460
Crit 1.5 Year
EG Baseflow
WS Baseflow
WS Baseflow
7456
Crit Baseflow
7454
Levee
Levee
Bank Sta
Bank Sta
7452
Ground
0
100
200
300
400
500
600
700
Station (ft)
Crit Baseflow
7455
7450
Ground
0
100
200
300
400
Station (ft)
C - 15
500
600
700
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3227.79 Note: n values for first profile.
.035
7475
.
0
7
5
.061
.075
. .
00
37
5
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
.035
7475
Legend
.075
.061
.075
..
00
37
5
EG 25 Year
WS 25 Year
7470
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3197.63 Note: n values for first profile.
.035
Legend
EG 25 Year
WS 25 Year
7470
EG 5 Year
EG 5 Year
Crit 25 Year
7465
EG 1.5 Year
WS 1.5 Year
Crit 5 Year
7460
Crit 1.5 Year
EG Baseflow
Crit 25 Year
Elevation (ft)
Elevation (ft)
WS 5 Year
WS 5 Year
7465
EG 1.5 Year
Crit 5 Year
WS 1.5 Year
7460
Crit 1.5 Year
EG Baseflow
WS Baseflow
7450
WS Baseflow
Crit Baseflow
7455
Ground
0
200
400
600
Crit Baseflow
7455
Ground
Levee
Levee
Bank Sta
Bank Sta
7450
800
0
200
400
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 3115.41 Note: n values for first profile.
.035
7475
.
0
7
5
.061
600
800
Station (ft)
.075
.
0
3
.035
.
0
7
5
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
.035
7475
Legend
.
0
7
5
EG 25 Year
WS 25 Year
7470
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 2975.24 Note: n values for first profile.
.061
.075
. .
00
37
5
.035
7470
EG 5 Year
WS 1.5 Year
Crit 5 Year
7460
Crit 1.5 Year
EG Baseflow
Crit 25 Year
Elevation (ft)
Elevation (ft)
Crit 25 Year
EG 1.5 Year
WS 5 Year
7465
EG 1.5 Year
WS 1.5 Year
Crit 5 Year
7460
Crit 1.5 Year
EG Baseflow
WS Baseflow
7450
WS Baseflow
Crit Baseflow
7455
200
400
600
800
Crit Baseflow
7455
Ground
0
Ground
Levee
Levee
Bank Sta
Bank Sta
7450
1000
0
200
400
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
.075
.061
600
800
5/7/2019
.075
. .
00
37
5
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 2678.11 Note: n values for first profile.
.035
.035
7475
Legend
.095
.061
.075
EG 25 Year
WS 25 Year
7470
7470
EG 5 Year
. .
00
37
5
.035
Legend
EG 25 Year
WS 25 Year
EG 5 Year
WS 5 Year
7465
Crit 5 Year
EG 1.5 Year
Crit 1.5 Year
7460
WS 1.5 Year
EG Baseflow
Crit 25 Year
Elevation (ft)
Elevation (ft)
Crit 25 Year
WS Baseflow
7465
WS 5 Year
Crit 5 Year
EG 1.5 Year
7460
WS 1.5 Year
Crit 1.5 Year
EG Baseflow
7455
WS Baseflow
Crit Baseflow
7455
7450
Ground
0
200
400
600
1000
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 2828.29 Note: n values for first profile.
7475
WS 25 Year
EG 5 Year
WS 5 Year
7465
Legend
EG 25 Year
800
1000
Crit Baseflow
7450
Ground
Levee
Levee
Bank Sta
Bank Sta
1200
Station (ft)
7445
0
200
400
600
Station (ft)
C - 16
800
1000
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 2585.59 Note: n values for first profile.
.035
7475
.095
.075
.061
.075
. .
00
37
5
7470
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 2462.48 Note: n values for first profile.
.035
.035
7475
Legend
.095
.075
.061
.075
EG 25 Year
WS 25 Year
7470
EG 5 Year
WS 1.5 Year
7460
Crit 5 Year
EG Baseflow
WS Baseflow
7455
Crit 1.5 Year
7465
7445
Crit 25 Year
WS 1.5 Year
7460
Crit 5 Year
EG Baseflow
WS Baseflow
7455
Crit 1.5 Year
Crit Baseflow
7450
Ground
0
200
400
600
800
Ground
Levee
Levee
Bank Sta
Bank Sta
7445
1000
0
200
400
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
600
800
1000
Station (ft)
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 2257.16 Note: n values for first profile.
7470
. .035
0
9
5
.095
.061
.075
7465
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 2085.09 Note: n values for first profile.
..
00
37
5
.035
.035
7470
Legend
.
0
9
5
EG 25 Year
WS 25 Year
.061
.075 . . .
00 0
37 9
5 5
.035
Legend
EG 25 Year
WS 25 Year
7465
EG 5 Year
EG 5 Year
Crit 25 Year
7460
EG 1.5 Year
WS 1.5 Year
Crit 5 Year
7455
EG Baseflow
WS Baseflow
Crit 25 Year
Elevation (ft)
Elevation (ft)
WS 5 Year
WS 5 Year
7460
EG 1.5 Year
Crit 5 Year
WS 1.5 Year
7455
Crit 1.5 Year
EG Baseflow
Crit 1.5 Year
WS Baseflow
Crit Baseflow
7450
7445
200
400
600
800
Crit Baseflow
7450
Ground
0
Ground
Levee
Levee
Bank Sta
Bank Sta
7445
1000
0
200
400
Station (ft)
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.035
600
800
1000
5/7/2019
.095
.061
. . .
0 00
9 39
5 5
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 1790.19 Note: n values for first profile.
.035
.035
7470
Legend
.
0
7
5
EG 25 Year
WS 25 Year
7465
.061
. . . .035
0 0 0
9 3 9
5 5
7465
EG 5 Year
Crit 5 Year
EG 1.5 Year
WS 1.5 Year
7455
Crit 1.5 Year
EG Baseflow
WS 5 Year
7460
Crit 5 Year
EG 1.5 Year
WS 1.5 Year
7455
Crit 1.5 Year
EG Baseflow
WS Baseflow
Crit Baseflow
7450
Ground
0
200
400
600
800
1000
WS 25 Year
Crit 25 Year
Elevation (ft)
Elevation (ft)
WS 5 Year
7460
Legend
EG 25 Year
EG 5 Year
Crit 25 Year
7445
1200
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 1930.53 Note: n values for first profile.
7470
WS 25 Year
EG 1.5 Year
Crit Baseflow
7450
Legend
EG 25 Year
WS 5 Year
Elevation (ft)
Elevation (ft)
Crit 25 Year
EG 1.5 Year
.035
EG 5 Year
WS 5 Year
7465
. .
00
37
5
WS Baseflow
Crit Baseflow
7450
Ground
Levee
Levee
Bank Sta
Bank Sta
1200
Station (ft)
7445
0
200
400
600
Station (ft)
C - 17
800
1000
1200
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
.035
.061
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 1676.02 Note: n values for first profile.
7464
.
0
7
5
7462
. . .035
00
93
5
EG 25 Year
7456
EG 1.5 Year
WS 1.5 Year
7454
Crit 1.5 Year
EG Baseflow
7452
Elevation (ft)
Elevation (ft)
Crit 5 Year
WS Baseflow
7450
Ground
Bank Sta
400
600
800
1000
EG 5 Year
7458
Crit 25 Year
EG 1.5 Year
7456
Crit 5 Year
WS 1.5 Year
7454
Crit 1.5 Year
EG Baseflow
7452
WS Baseflow
Crit Baseflow
Ground
7446
1200
Levee
Bank Sta
0
200
400
600
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
.
0
7
5
.061
.095 .
0
3
5
Elevation (ft)
7458
7456
Legend
7464
7454
EG 1.5 Year
WS 1.5 Year
7452
EG Baseflow
7450
WS Baseflow
7448
Ground
7446
7444
1400
Bank Sta
0
200
400
600
800
1000
1200
1400
Station (ft)
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 1066.52 Note: n values for first profile.
.035
.
0
7
5
7458
.061
.
0
9
5
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 912.41 Note: n values for first profile.
.035
Legend
7458
EG 25 Year
7456
.035
.
0
7
5
.061
.095
.
0
3
5
.095
.
0
3
5
Legend
EG 25 Year
WS 25 Year
7456
WS 25 Year
7454
EG 5 Year
7454
WS 5 Year
7452
EG 1.5 Year
WS 1.5 Year
7450
EG Baseflow
7448
WS Baseflow
7446
Ground
Elevation (ft)
Elevation (ft)
EG 25 Year
WS 25 Year
Station (ft)
7444
Legend
7454
Bank Sta
7460
.
0
3
5
EG 5 Year
Ground
KB_HECRAS_2018
.095
WS 5 Year
WS Baseflow
1200
.061
7456
7448
1000
.
0
7
5
7458
WS 1.5 Year
7446
.035
EG 5 Year
EG Baseflow
800
5/7/2019
7460
7450
600
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
EG 25 Year
EG 1.5 Year
400
1400
WS 25 Year
7452
200
1200
7462
WS 5 Year
0
1000
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 1227.60 Note: n values for first profile.
Elevation (ft)
.035
7460
7444
800
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 1374.45 Note: n values for first profile.
7462
WS 25 Year
WS 5 Year
Station (ft)
KB_HECRAS_2018
Legend
EG 25 Year
7448
Levee
200
. . .035
00
93
5
7450
Crit Baseflow
7448
.061
7460
Crit 25 Year
WS 5 Year
.075
7462
WS 25 Year
7458
.035
7464
Legend
EG 5 Year
0
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 1526.02 Note: n values for first profile.
7460
7446
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
Bank Sta
0
200
400
600
800
1000
1200
1400
Station (ft)
EG 5 Year
WS 5 Year
7452
EG 1.5 Year
7450
WS 1.5 Year
EG Baseflow
7448
WS Baseflow
7446
7444
Ground
Bank Sta
0
200
400
600
Station (ft)
C - 18
800
1000
1200
�Appendix C
KB_HECRAS_2018
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
KB_HECRAS_2018
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 711.00 Note: n values for first profile.
.035
.075
.061
.095
.035
EG 25 Year
7456
WS 25 Year
.035
7465
Legend
7458
.075
.061
.095
WS 5 Year
7452
EG 1.5 Year
7450
WS 1.5 Year
7448
EG Baseflow
7446
WS Baseflow
Legend
EG 25 Year
7460
WS 25 Year
7455
WS 5 Year
EG 5 Year
Bank Sta
0
100
200
300
400
500
600
EG 1.5 Year
WS 1.5 Year
7450
EG Baseflow
WS Baseflow
7445
Ground
7444
7440
700
Ground
Bank Sta
0
100
200
300
Station (ft)
KB_HECRAS_2018
. .075
7465 0
3
5
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
.061
5/7/2019
KB_HECRAS_2018
.095
.035
.
7460 0
3
5
Legend
EG 25 Year
WS 25 Year
WS 5 Year
EG 1.5 Year
WS 1.5 Year
7450
EG Baseflow
Elevation (ft)
Elevation (ft)
7455
WS Baseflow
7445
100
150
200
250
300
350
.075
.061
400
.095
Legend
WS 25 Year
EG 5 Year
Elevation (ft)
7454
Crit 25 Year
7452
WS 5 Year
7450
EG 1.5 Year
Crit 5 Year
WS 1.5 Year
7448
Crit 1.5 Year
EG Baseflow
7446
WS Baseflow
Crit Baseflow
7444
Ground
Bank Sta
50
100
.095
150
200
.035
Legend
EG 25 Year
WS 25 Year
EG 5 Year
WS 5 Year
EG 1.5 Year
7450
WS 1.5 Year
EG Baseflow
7445
WS Baseflow
Ground
EG 25 Year
0
.061
Bank Sta
5/7/2019
7456
7442
.075
7440
0
50
100
150
200
Station (ft)
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
5/7/2019
Bank Sta
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 7.86 Note: n values for first profile.
7458
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
Ground
Station (ft)
KB_HECRAS_2018
600
7455
EG 5 Year
50
500
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 262.59 Note: n values for first profile.
7460
0
400
Station (ft)
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 397.22 Note: n values for first profile.
7440
.035
EG 5 Year
7454
7442
5/7/2019
Geom: KB_HECRAS_Geometry_2018
River = Colorado River Reach = Kemp-Breeze SWA
RS = 570.23 Note: n values for first profile.
Elevation (ft)
Elevation (ft)
7460
Plan: KB_HECRAS_Plan_Analysis_Existing_2018
250
Station (ft)
C - 19
250
300
350
400
�Appendix C
Note:
HEC-RAS results for existing
conditions in the Colorado River
within the Kemp-Breeze SWA for all
cross-sections and flow profiles.
C - 20
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA
Reach
River Sta
Profile
Q Total
Min Ch El
(cfs)
(ft)
Kemp-Breeze SWA
8057.74
Baseflow
170.00
7467.32
250.00
480.00
7467.32
7467.32
W.S. Elev
(ft)
7468.32
Crit W.S.
(ft)
7468.32
E.G. Elev
(ft)
7468.61
E.G. Slope
(ft/ft)
0.067158
Frctn Slope
(ft/ft)
0.002085
Vel Chnl
(ft/s)
4.34
Flow Area
(sq ft)
39.15
Top Width
(ft)
68.40
7468.72
7469.49
7468.92
7469.64
0.027541
0.009381
0.002407
0.002655
3.56
3.06
70.17
157.07
87.66
123.73
Froude # Chl
1.01
Hydr Radius C
(ft)
0.57
Power Chan
(lb/ft s)
10.39
Shear Chan
(lb/sq ft)
2.39
0.70
0.48
0.80
1.26
4.88
2.26
1.37
0.74
Kemp-Breeze SWA
Kemp-Breeze SWA
8057.74
8057.74
LOC Spawn
RBT Spawn
Kemp-Breeze SWA
8057.74
May Avg
950.00
7467.32
7470.28
7470.49
0.005281
0.002659
3.69
262.25
150.95
0.46
1.96
2.39
0.65
Kemp-Breeze SWA
Kemp-Breeze SWA
8057.74
8057.74
1.5 Year
2 Year
1300.00
1950.00
7467.32
7467.32
7470.55
7471.35
7470.85
7471.69
0.004697
0.003517
0.002639
0.002575
4.43
4.78
303.98
451.64
161.78
200.49
0.52
0.49
2.21
2.98
2.87
3.13
0.65
0.66
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
8057.74
8057.74
8057.74
5 Year
10 Year
25 Year
3150.00
4750.00
6000.00
7467.32
7467.32
7467.32
7472.47
7473.58
7474.37
7472.90
7474.13
7475.00
0.002728
0.002413
0.002317
0.002487
0.002436
0.002431
5.40
6.25
6.73
689.55
948.38
1156.00
224.50
249.69
273.96
0.47
0.48
0.48
4.10
5.19
5.98
3.77
4.89
5.82
0.70
0.78
0.86
Kemp-Breeze SWA
8057.74
50 Year
7500.00
7467.32
7475.20
7475.92
0.002239
0.002405
7.22
1395.59
299.60
0.49
6.81
6.87
0.95
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7975.00
7975.00
7975.00
7975.00
7975.00
7975.00
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
7463.52
7463.52
7463.52
7463.52
7463.52
7463.52
7468.29
7468.64
7469.34
7470.11
7470.39
7471.15
7468.30
7468.67
7469.39
7470.24
7470.60
7471.47
0.000627
0.000829
0.001232
0.001597
0.001688
0.001966
0.000503
0.000670
0.001013
0.001332
0.001411
0.001685
1.02
1.29
1.90
2.94
3.72
4.60
166.53
194.39
252.58
324.40
352.57
441.16
75.94
80.33
87.96
97.69
105.85
130.87
0.12
0.15
0.20
0.28
0.34
0.39
2.17
2.39
2.83
3.41
3.66
4.36
0.09
0.16
0.41
1.00
1.43
2.46
0.08
0.12
0.22
0.34
0.39
0.54
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7975.00
7975.00
7975.00
7975.00
5 Year
10 Year
25 Year
50 Year
3150.00
4750.00
6000.00
7500.00
7463.52
7463.52
7463.52
7463.52
7472.16
7473.16
7473.90
7474.70
7472.68
7473.91
7474.78
7475.69
0.002277
0.002460
0.002553
0.002591
0.001994
0.002192
0.002295
0.002367
5.89
7.22
7.91
8.55
625.94
855.95
1047.75
1273.82
212.31
246.86
269.67
294.26
0.45
0.50
0.52
0.53
5.36
6.34
7.07
7.86
4.49
7.03
8.92
10.87
0.76
0.97
1.13
1.27
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7818.06
7818.06
7818.06
Baseflow
LOC Spawn
RBT Spawn
170.00
250.00
480.00
7464.54
7464.54
7464.54
7468.21
7468.54
7469.19
7468.22
7468.56
7469.23
0.000413
0.000553
0.000848
0.000679
0.000833
0.001140
0.84
1.07
1.61
203.54
234.69
298.33
92.37
95.62
101.30
0.10
0.12
0.17
2.19
2.44
2.92
0.05
0.09
0.25
0.06
0.08
0.15
Kemp-Breeze SWA
Kemp-Breeze SWA
7818.06
7818.06
May Avg
1.5 Year
950.00
1300.00
7464.54
7464.54
7469.93
7470.20
7470.03
7470.37
0.001128
0.001197
0.001406
0.001461
2.54
3.22
375.34
406.10
108.21
112.53
0.24
0.29
3.55
3.82
0.63
0.92
0.25
0.29
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7818.06
7818.06
7818.06
7818.06
7818.06
2 Year
5 Year
10 Year
25 Year
50 Year
1950.00
3150.00
4750.00
6000.00
7500.00
7464.54
7464.54
7464.54
7464.54
7464.54
7470.93
7471.92
7472.90
7473.64
7474.42
7471.19
7472.34
7473.53
7474.38
7475.28
0.001460
0.001760
0.001965
0.002074
0.002171
0.001681
0.001941
0.002126
0.002241
0.002335
4.05
5.25
6.52
7.19
7.87
496.65
679.84
904.18
1087.46
1288.74
148.40
206.90
247.06
253.41
267.75
0.33
0.39
0.45
0.47
0.49
4.50
5.47
6.44
7.17
7.94
1.66
3.16
5.15
6.67
8.47
0.41
0.60
0.79
0.93
1.08
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7598.90
7598.90
7598.90
7598.90
7598.90
7598.90
7598.90
7598.90
7598.90
7598.90
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7466.12
7466.12
7466.12
7466.12
7466.12
7466.12
7466.12
7466.12
7466.12
7466.12
7468.06
7468.35
7468.93
7469.60
7469.87
7470.56
7471.51
7472.45
7473.14
7473.89
7468.07
7468.38
7468.98
7469.72
7470.04
7470.82
7471.91
7473.06
7473.88
7474.77
0.001318
0.001395
0.001614
0.001803
0.001822
0.001956
0.002151
0.002308
0.002429
0.002518
0.001634
0.001615
0.001775
0.001906
0.001919
0.002031
0.002203
0.002338
0.002448
0.002506
1.06
1.27
1.79
2.69
3.35
4.06
5.15
6.36
7.05
7.74
160.08
196.28
267.54
353.57
389.11
494.78
654.08
830.59
981.71
1180.36
121.25
122.61
125.16
128.46
140.67
162.37
174.56
201.03
240.64
292.22
0.16
0.18
0.22
0.29
0.34
0.37
0.42
0.47
0.50
0.52
1.32
1.59
2.12
2.73
2.96
3.64
4.57
5.50
6.19
6.92
0.11
0.18
0.38
0.82
1.13
1.80
3.16
5.04
6.62
8.42
0.11
0.14
0.21
0.31
0.34
0.44
0.61
0.79
0.94
1.09
Kemp-Breeze SWA
Kemp-Breeze SWA
7439.67
7439.67
Baseflow
LOC Spawn
170.00
250.00
7465.18
7465.18
7467.79
7468.09
7467.81
7468.12
0.002080
0.001893
0.002949
0.002937
1.16
1.33
146.19
187.27
136.05
137.08
0.20
0.20
1.07
1.36
0.16
0.21
0.14
0.16
C - 21
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
7439.67
RBT Spawn
480.00
7465.18
7468.64
Crit W.S.
(ft)
E.G. Elev
(ft)
7468.69
E.G. Slope
(ft/ft)
0.001962
Frctn Slope
(ft/ft)
0.002914
Vel Chnl
(ft/s)
1.82
Flow Area
(sq ft)
263.08
Top Width
(ft)
138.94
0.23
Hydr Radius C
(ft)
1.88
Kemp-Breeze SWA
Kemp-Breeze SWA
7439.67
7439.67
May Avg
1.5 Year
950.00
1300.00
7465.18
7465.18
7469.30
7469.57
7469.41
7469.74
0.002019
0.002024
0.002843
0.002818
2.67
3.30
355.60
393.57
142.04
145.76
0.30
0.35
2.48
2.68
0.84
1.12
0.31
0.34
Kemp-Breeze SWA
7439.67
2 Year
1950.00
7465.18
7470.25
7470.49
0.002112
0.002858
3.95
493.83
150.47
0.38
3.29
1.71
0.43
Kemp-Breeze SWA
Kemp-Breeze SWA
7439.67
7439.67
5 Year
10 Year
3150.00
4750.00
7465.18
7465.18
7471.17
7472.10
7471.55
7472.68
0.002256
0.002368
0.002946
0.002989
4.99
6.14
640.50
801.10
167.26
178.36
0.43
0.48
4.20
5.12
2.95
4.65
0.59
0.76
Kemp-Breeze SWA
Kemp-Breeze SWA
7439.67
7439.67
25 Year
50 Year
6000.00
7500.00
7465.18
7465.18
7472.78
7473.53
7473.49
7474.35
0.002468
0.002495
0.002995
0.002919
6.80
7.41
934.91
1114.09
216.80
261.57
0.50
0.51
5.79
6.54
6.07
7.55
0.89
1.02
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7334.84
7334.84
7334.84
7334.84
7334.84
7334.84
7334.84
7334.84
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
7465.63
7465.63
7465.63
7465.63
7465.63
7465.63
7465.63
7465.63
7467.45
7467.75
7468.29
7468.92
7469.15
7469.79
7470.66
7471.54
7467.50
7467.81
7468.39
7469.11
7469.43
7470.17
7471.23
7472.34
0.004502
0.005160
0.004774
0.004299
0.004190
0.004083
0.004008
0.003889
0.003366
0.003657
0.003802
0.004021
0.004069
0.004159
0.004183
0.004152
1.74
1.96
2.49
3.45
4.26
4.96
6.09
7.28
97.77
127.33
192.90
275.14
305.27
393.94
542.17
715.65
88.93
111.18
125.16
132.53
134.02
151.04
181.97
209.70
0.29
0.32
0.35
0.42
0.50
0.52
0.56
0.60
1.10
1.14
1.54
2.07
2.27
2.82
3.68
4.56
0.54
0.72
1.14
1.92
2.53
3.57
5.61
8.06
0.31
0.37
0.46
0.56
0.59
0.72
0.92
1.11
Kemp-Breeze SWA
Kemp-Breeze SWA
7334.84
7334.84
25 Year
50 Year
6000.00
7500.00
7465.63
7465.63
7472.24
7473.03
7473.15
7474.03
0.003710
0.003461
0.004060
0.003912
7.82
8.29
869.41
1057.99
228.27
249.14
0.60
0.59
5.26
6.05
9.52
10.83
1.22
1.31
Kemp-Breeze SWA
Kemp-Breeze SWA
7226.72
7226.72
Baseflow
LOC Spawn
170.00
250.00
7465.21
7465.21
7467.10
7467.37
7467.13
7467.41
0.002612
0.002726
0.002167
0.002419
1.38
1.65
123.48
151.78
105.64
106.34
0.22
0.24
1.16
1.42
0.26
0.40
0.19
0.24
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7226.72
7226.72
7226.72
RBT Spawn
May Avg
1.5 Year
480.00
950.00
1300.00
7465.21
7465.21
7465.21
7467.89
7468.49
7468.70
7467.97
7468.67
7468.99
0.003098
0.003769
0.003953
0.002908
0.003452
0.003584
2.31
3.44
4.30
207.46
276.52
304.00
107.75
124.01
131.40
0.29
0.40
0.49
1.91
2.28
2.41
0.85
1.84
2.56
0.37
0.54
0.59
Kemp-Breeze SWA
Kemp-Breeze SWA
7226.72
7226.72
2 Year
5 Year
1950.00
3150.00
7465.21
7465.21
7469.32
7470.16
7469.72
7470.77
0.004236
0.004369
0.003877
0.004114
5.09
6.32
390.74
525.61
149.88
169.32
0.53
0.58
2.86
3.65
3.85
6.29
0.76
1.00
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7226.72
7226.72
7226.72
10 Year
25 Year
50 Year
4750.00
6000.00
7500.00
7465.21
7465.21
7465.21
7470.99
7471.63
7472.34
7471.89
7472.70
7473.58
0.004443
0.004463
0.004459
0.004227
0.004257
0.004254
7.68
8.41
9.15
669.84
787.56
923.10
177.93
187.75
197.79
0.64
0.65
0.67
4.47
5.11
5.80
9.52
11.97
14.78
1.24
1.42
1.61
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7144.81
7144.81
7144.81
7144.81
7144.81
7144.81
7144.81
7144.81
7144.81
7144.81
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7464.93
7464.93
7464.93
7464.93
7464.93
7464.93
7464.93
7464.93
7464.93
7464.93
7466.93
7467.17
7467.66
7468.22
7468.44
7469.03
7469.86
7470.69
7471.33
7472.05
7466.95
7467.21
7467.73
7468.38
7468.68
7469.39
7470.42
7471.52
7472.33
7473.21
0.001826
0.002161
0.002734
0.003174
0.003264
0.003562
0.003881
0.004026
0.004065
0.004064
0.002293
0.002557
0.003059
0.003415
0.003451
0.003703
0.003871
0.003896
0.003874
0.003837
1.22
1.49
2.13
3.21
4.02
4.84
6.08
7.44
8.16
8.88
139.81
168.24
227.64
302.99
332.84
420.27
552.87
704.06
830.06
974.20
112.00
118.12
127.04
138.44
141.39
152.84
170.55
190.08
198.51
206.41
0.19
0.22
0.28
0.37
0.45
0.49
0.55
0.61
0.63
0.64
1.27
1.46
1.85
2.33
2.51
3.01
3.76
4.59
5.23
5.94
0.18
0.29
0.67
1.48
2.05
3.24
5.54
8.58
10.83
13.37
0.14
0.20
0.32
0.46
0.51
0.67
0.91
1.15
1.33
1.51
Kemp-Breeze SWA
Kemp-Breeze SWA
7047.89
7047.89
Baseflow
LOC Spawn
170.00
250.00
7464.78
7464.78
7466.70
7466.92
7466.73
7466.96
0.002965
0.003073
0.005144
0.005164
1.29
1.54
131.65
162.06
136.54
137.26
0.23
0.25
0.96
1.17
0.23
0.35
0.18
0.23
Kemp-Breeze SWA
Kemp-Breeze SWA
7047.89
7047.89
RBT Spawn
May Avg
480.00
950.00
7464.78
7464.78
7467.36
7467.89
7467.43
7468.05
0.003446
0.003685
0.004975
0.004606
2.16
3.20
222.24
296.96
139.08
142.30
0.30
0.39
1.59
2.07
0.74
1.52
0.34
0.48
C - 22
Froude # Chl
Power Chan
(lb/ft s)
0.42
Shear Chan
(lb/sq ft)
0.23
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
7047.89
1.5 Year
1300.00
7464.78
7468.10
Crit W.S.
(ft)
E.G. Elev
(ft)
7468.35
E.G. Slope
(ft/ft)
0.003655
Frctn Slope
(ft/ft)
0.004477
Vel Chnl
(ft/s)
3.97
Flow Area
(sq ft)
327.38
Top Width
(ft)
143.47
0.46
Hydr Radius C
(ft)
2.26
Kemp-Breeze SWA
Kemp-Breeze SWA
7047.89
7047.89
2 Year
5 Year
1950.00
3150.00
7464.78
7464.78
7468.68
7469.50
7469.03
7470.03
0.003852
0.003861
0.004251
0.003989
4.73
5.85
414.44
563.19
169.18
188.86
0.50
0.54
2.75
3.57
3.13
5.02
0.66
0.86
Kemp-Breeze SWA
7047.89
10 Year
4750.00
7464.78
7470.37
7471.12
0.003773
0.003747
7.02
729.33
196.27
0.59
4.42
7.31
1.04
Kemp-Breeze SWA
Kemp-Breeze SWA
7047.89
7047.89
25 Year
50 Year
6000.00
7500.00
7464.78
7464.78
7471.04
7471.77
7471.92
7472.79
0.003696
0.003629
0.003608
0.003491
7.63
8.27
862.75
1012.09
200.91
206.37
0.59
0.60
5.09
5.81
8.96
10.89
1.17
1.32
Kemp-Breeze SWA
Kemp-Breeze SWA
6850.45
6850.45
Baseflow
LOC Spawn
170.00
250.00
7463.84
7463.84
7465.63
7465.85
7465.71
7465.94
0.011028
0.010429
0.006269
0.005693
2.32
2.44
73.36
102.26
121.15
139.53
0.52
0.50
0.60
0.73
0.96
1.16
0.42
0.48
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
6850.45
6850.45
6850.45
6850.45
6850.45
6850.45
6850.45
6850.45
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7463.84
7463.84
7463.84
7463.84
7463.84
7463.84
7463.84
7463.84
7466.32
7466.93
7467.14
7467.81
7468.72
7469.66
7470.38
7471.16
7466.45
7467.14
7467.46
7468.19
7469.24
7470.36
7471.18
7472.07
0.007804
0.005920
0.005611
0.004714
0.004124
0.003721
0.003522
0.003360
0.004870
0.004363
0.004253
0.003957
0.003723
0.003586
0.003511
0.003448
2.84
3.70
4.50
4.98
5.80
6.75
7.23
7.74
169.14
257.02
289.53
393.58
554.72
739.88
885.65
1048.94
143.03
147.98
150.62
164.26
193.38
199.57
205.54
212.49
0.46
0.49
0.57
0.56
0.56
0.58
0.57
0.57
1.17
1.73
1.92
2.40
3.25
4.17
4.88
5.65
1.62
2.36
3.02
3.52
4.85
6.54
7.76
9.17
0.57
0.64
0.67
0.71
0.84
0.97
1.07
1.19
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
6723.16
6723.16
6723.16
6723.16
Baseflow
LOC Spawn
RBT Spawn
May Avg
170.00
250.00
480.00
950.00
7462.83
7462.83
7462.83
7462.83
7464.86
7465.16
7465.73
7466.40
7464.90
7465.20
7465.81
7466.57
0.004038
0.003580
0.003326
0.003349
0.001922
0.002008
0.002255
0.002519
1.54
1.75
2.30
3.28
110.26
143.03
208.92
289.49
110.57
112.78
116.16
124.42
0.27
0.27
0.30
0.38
0.99
1.26
1.79
2.31
0.39
0.49
0.85
1.59
0.25
0.28
0.37
0.48
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
6723.16
6723.16
6723.16
1.5 Year
2 Year
5 Year
1300.00
1950.00
3150.00
7462.83
7462.83
7462.83
7466.64
7467.32
7468.23
7466.90
7467.68
7468.77
0.003335
0.003368
0.003378
0.002559
0.002770
0.002913
4.07
4.77
5.89
319.75
413.07
568.72
126.44
151.53
180.01
0.45
0.48
0.52
2.51
3.08
3.98
2.13
3.09
4.94
0.52
0.65
0.84
Kemp-Breeze SWA
Kemp-Breeze SWA
6723.16
6723.16
10 Year
25 Year
4750.00
6000.00
7462.83
7462.83
7469.12
7469.80
7469.90
7470.72
0.003457
0.003500
0.003013
0.003074
7.16
7.86
734.04
867.75
193.23
202.48
0.57
0.59
4.86
5.53
7.52
9.50
1.05
1.21
Kemp-Breeze SWA
6723.16
50 Year
7500.00
7462.83
7470.52
7471.61
0.003538
0.003110
8.58
1019.10
212.47
0.60
6.26
11.85
1.38
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
6573.14
6573.14
6573.14
6573.14
6573.14
6573.14
6573.14
6573.14
6573.14
6573.14
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7461.43
7461.43
7461.43
7461.43
7461.43
7461.43
7461.43
7461.43
7461.43
7461.43
7464.59
7464.87
7465.42
7466.06
7466.31
7466.97
7467.87
7468.77
7469.45
7470.20
7464.61
7464.90
7465.47
7466.18
7466.49
7467.24
7468.30
7469.40
7470.21
7471.09
0.001120
0.001283
0.001629
0.001963
0.002026
0.002318
0.002538
0.002650
0.002721
0.002755
0.001403
1.03
165.79
116.80
0.001581
0.001954
0.002306
0.002378
0.002688
0.002931
0.003018
0.003054
0.003059
1.26
1.81
2.75
3.44
4.18
5.24
6.42
7.08
7.72
199.00
264.56
344.98
377.63
469.68
632.94
809.58
950.43
1111.68
118.94
122.26
128.79
131.46
163.06
190.17
202.19
211.07
221.08
0.15
0.17
0.22
0.30
0.36
0.40
0.45
0.50
0.52
0.53
1.41
1.66
2.14
2.65
2.84
3.34
4.15
5.04
5.71
6.45
0.10
0.17
0.40
0.90
1.24
2.02
3.45
5.36
6.87
8.57
0.10
0.13
0.22
0.33
0.36
0.48
0.66
0.83
0.97
1.11
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
6509.86
6509.86
6509.86
6509.86
Baseflow
LOC Spawn
RBT Spawn
May Avg
170.00
250.00
480.00
950.00
7462.23
7462.23
7462.23
7462.23
7464.50
7464.76
7465.28
7465.88
7464.52
7464.80
7465.34
7466.03
0.001810
0.001994
0.002387
0.002746
0.003288
0.003399
0.003550
0.003626
1.19
1.44
2.04
3.06
142.27
173.54
235.47
310.59
114.66
118.10
122.20
127.84
0.19
0.21
0.26
0.35
1.24
1.47
1.92
2.41
0.17
0.26
0.58
1.27
0.14
0.18
0.29
0.41
Kemp-Breeze SWA
Kemp-Breeze SWA
6509.86
6509.86
1.5 Year
2 Year
1300.00
1950.00
7462.23
7462.23
7466.11
7466.73
7466.34
7467.06
0.002830
0.003155
0.003623
0.003662
3.82
4.60
340.32
423.59
130.69
137.24
0.42
0.46
2.59
3.06
1.75
2.78
0.46
0.60
C - 23
Froude # Chl
Power Chan
(lb/ft s)
2.05
Shear Chan
(lb/sq ft)
0.52
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
6509.86
5 Year
3150.00
7462.23
7467.59
Crit W.S.
(ft)
E.G. Elev
(ft)
7468.10
E.G. Slope
(ft/ft)
0.003424
Frctn Slope
(ft/ft)
0.003663
Vel Chnl
(ft/s)
5.75
Flow Area
(sq ft)
570.00
Top Width
(ft)
188.61
0.52
Hydr Radius C
(ft)
3.80
Kemp-Breeze SWA
Kemp-Breeze SWA
6509.86
6509.86
10 Year
25 Year
4750.00
6000.00
7462.23
7462.23
7468.46
7469.13
7469.20
7470.00
0.003469
0.003452
0.003561
0.003484
6.98
7.61
741.89
886.08
207.39
219.98
0.57
0.58
4.66
5.33
7.04
8.74
1.01
1.15
Kemp-Breeze SWA
6509.86
50 Year
7500.00
7462.23
7469.87
7470.88
0.003416
0.003415
8.25
1053.57
233.75
0.59
6.06
10.67
1.29
Kemp-Breeze SWA
6367.85
Baseflow
170.00
7462.40
7463.99
7464.04
0.007736
0.005086
1.86
91.18
112.02
0.36
0.81
0.73
0.39
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
6367.85
6367.85
6367.85
LOC Spawn
RBT Spawn
May Avg
250.00
480.00
950.00
7462.40
7462.40
7462.40
7464.25
7464.74
7465.32
7464.31
7464.84
7465.51
0.007049
0.005831
0.005006
0.004888
0.004526
0.004234
2.03
2.54
3.48
123.00
189.33
273.28
128.72
138.55
145.80
0.37
0.38
0.45
0.95
1.36
1.86
0.85
1.26
2.03
0.42
0.50
0.58
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
6367.85
6367.85
6367.85
6367.85
6367.85
6367.85
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7462.40
7462.40
7462.40
7462.40
7462.40
7462.40
7465.54
7466.17
7467.05
7467.96
7468.66
7469.41
7465.82
7466.54
7467.58
7468.69
7469.50
7470.38
0.004803
0.004301
0.003929
0.003657
0.003516
0.003413
0.004197
0.004084
0.003877
0.003694
0.003581
0.003465
4.27
4.88
5.86
6.93
7.49
8.08
304.63
402.32
567.98
750.84
895.46
1057.13
147.45
169.91
197.83
204.61
210.14
217.91
0.52
0.53
0.55
0.58
0.58
0.59
2.05
2.65
3.53
4.43
5.13
5.88
2.63
3.48
5.08
7.02
8.43
10.12
0.62
0.71
0.87
1.01
1.13
1.25
Kemp-Breeze SWA
6208.29
Baseflow
170.00
7461.27
7463.20
7463.23
0.003597
0.002686
1.51
112.80
105.93
0.26
1.05
0.35
0.24
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
6208.29
6208.29
6208.29
6208.29
6208.29
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
250.00
480.00
950.00
1300.00
1950.00
7461.27
7461.27
7461.27
7461.27
7461.27
7463.47
7464.02
7464.65
7464.87
7465.50
7463.52
7464.11
7464.83
7465.14
7465.89
0.003587
0.003615
0.003628
0.003698
0.003884
0.002849
0.003096
0.003259
0.003307
0.003447
1.75
2.32
3.36
4.19
4.97
142.92
206.82
283.12
310.29
402.75
111.13
118.84
123.17
127.34
163.99
0.27
0.31
0.39
0.47
0.51
1.26
1.71
2.25
2.43
2.94
0.49
0.89
1.71
2.35
3.54
0.28
0.39
0.51
0.56
0.71
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
6208.29
6208.29
6208.29
5 Year
10 Year
25 Year
3150.00
4750.00
6000.00
7461.27
7461.27
7461.27
7466.40
7467.31
7468.01
7466.96
7468.09
7468.92
0.003827
0.003731
0.003648
0.003484
0.003467
0.003434
6.05
7.24
7.85
568.57
756.55
914.86
194.24
218.60
232.56
0.54
0.58
0.59
3.78
4.67
5.36
5.46
7.87
9.58
0.90
1.09
1.22
Kemp-Breeze SWA
6208.29
50 Year
7500.00
7461.27
7468.79
7469.82
0.003517
0.003357
8.43
1100.20
242.51
0.59
6.12
11.33
1.34
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
6049.19
6049.19
6049.19
6049.19
6049.19
6049.19
6049.19
6049.19
6049.19
6049.19
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7460.95
7460.95
7460.95
7460.95
7460.95
7460.95
7460.95
7460.95
7460.95
7460.95
7462.78
7463.03
7463.54
7464.15
7464.37
7464.99
7465.88
7466.79
7467.50
7468.28
7462.80
7463.06
7463.61
7464.30
7464.60
7465.32
7466.39
7467.52
7468.36
7469.28
0.002082
0.002317
0.002682
0.002943
0.002974
0.003079
0.003185
0.003230
0.003238
0.003208
0.002469
0.002648
0.002920
0.003059
0.003045
0.003101
0.003161
0.003178
0.003178
0.003161
1.24
1.50
2.09
3.09
3.86
4.62
5.76
6.98
7.63
8.28
137.44
167.03
229.34
308.32
340.58
439.41
594.14
765.87
905.71
1067.52
116.06
119.25
124.16
144.24
149.32
164.98
183.22
194.67
202.85
211.01
0.20
0.22
0.27
0.36
0.43
0.46
0.50
0.55
0.56
0.57
1.17
1.39
1.83
2.33
2.53
3.14
4.02
4.92
5.62
6.39
0.19
0.30
0.64
1.32
1.81
2.79
4.60
6.93
8.67
10.60
0.15
0.20
0.31
0.43
0.47
0.60
0.80
0.99
1.14
1.28
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
5910.06
5910.06
5910.06
5910.06
5910.06
5910.06
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
7460.77
7460.77
7460.77
7460.77
7460.77
7460.77
7462.43
7462.66
7463.13
7463.73
7463.96
7464.57
7462.46
7462.70
7463.20
7463.87
7464.18
7464.88
0.002976
0.003054
0.003192
0.003181
0.003118
0.003123
0.003515
0.003698
0.003721
0.003616
0.003535
0.003439
1.30
1.54
2.11
3.04
3.77
4.48
131.00
162.21
227.62
311.99
344.97
439.14
135.40
137.16
139.48
144.26
146.31
159.02
0.23
0.25
0.29
0.37
0.43
0.46
0.97
1.18
1.62
2.15
2.36
2.97
0.23
0.35
0.68
1.30
1.73
2.60
0.18
0.22
0.32
0.43
0.46
0.58
Kemp-Breeze SWA
Kemp-Breeze SWA
5910.06
5910.06
5 Year
10 Year
3150.00
4750.00
7460.77
7460.77
7465.46
7466.38
7465.94
7467.07
0.003137
0.003127
0.003350
0.003269
5.55
6.72
587.59
749.25
172.80
179.98
0.50
0.54
3.85
4.76
4.19
6.25
0.75
0.93
C - 24
Froude # Chl
Power Chan
(lb/ft s)
4.67
Shear Chan
(lb/sq ft)
0.81
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
5910.06
25 Year
6000.00
7460.77
7467.08
Crit W.S.
(ft)
E.G. Elev
(ft)
7467.90
E.G. Slope
(ft/ft)
0.003119
Frctn Slope
(ft/ft)
0.003216
Vel Chnl
(ft/s)
7.35
Flow Area
(sq ft)
877.30
Top Width
(ft)
183.74
0.003167
8.02
1022.41
195.61
Froude # Chl
0.55
Hydr Radius C
(ft)
5.46
Power Chan
(lb/ft s)
7.82
Shear Chan
(lb/sq ft)
1.06
0.56
6.23
9.72
1.21
Kemp-Breeze SWA
5910.06
50 Year
7500.00
7460.77
7467.86
7468.83
0.003115
Kemp-Breeze SWA
5873.69
Baseflow
170.00
7460.66
7462.30
7462.33
0.004215
0.005550
1.49
113.90
123.72
0.27
0.92
0.36
0.24
Kemp-Breeze SWA
Kemp-Breeze SWA
5873.69
5873.69
LOC Spawn
RBT Spawn
250.00
480.00
7460.66
7460.66
7462.52
7462.98
7462.56
7463.07
0.004568
0.004393
0.005110
0.004458
1.75
2.34
142.45
205.41
133.88
136.98
0.30
0.34
1.06
1.49
0.53
0.95
0.30
0.41
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
5873.69
5873.69
5873.69
May Avg
1.5 Year
2 Year
950.00
1300.00
1950.00
7460.66
7460.66
7460.66
7463.57
7463.79
7464.41
7463.74
7464.05
7464.76
0.004148
0.004041
0.003806
0.004152
0.004075
0.003849
3.29
4.05
4.72
288.79
320.73
416.80
145.03
147.01
162.04
0.41
0.48
0.50
1.98
2.16
2.77
1.68
2.21
3.10
0.51
0.55
0.66
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
5873.69
5873.69
5873.69
5873.69
5 Year
10 Year
25 Year
50 Year
3150.00
4750.00
6000.00
7500.00
7460.66
7460.66
7460.66
7460.66
7465.31
7466.23
7466.95
7467.74
7465.82
7466.95
7467.79
7468.71
0.003584
0.003421
0.003317
0.003220
0.003594
0.003419
0.003298
0.003203
5.73
6.84
7.42
8.02
571.72
741.83
880.11
1038.23
179.28
188.62
195.88
205.91
0.53
0.56
0.57
0.57
3.66
4.57
5.29
6.07
4.69
6.68
8.12
9.79
0.82
0.98
1.09
1.22
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
5737.84
5737.84
5737.84
Baseflow
LOC Spawn
RBT Spawn
170.00
250.00
480.00
7460.28
7460.28
7460.28
7461.52
7461.81
7462.37
7461.57
7461.87
7462.46
0.007639
0.005754
0.004524
0.002412
0.002301
0.002435
1.82
1.95
2.42
93.63
128.13
198.44
118.25
121.91
128.00
0.36
0.34
0.34
0.79
1.04
1.53
0.68
0.73
1.05
0.38
0.37
0.43
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
5737.84
5737.84
5737.84
5737.84
5737.84
May Avg
1.5 Year
2 Year
5 Year
10 Year
950.00
1300.00
1950.00
3150.00
4750.00
7460.28
7460.28
7460.28
7460.28
7460.28
7463.00
7463.22
7463.87
7464.80
7465.75
7463.18
7463.49
7464.23
7465.33
7466.48
0.004157
0.004110
0.003892
0.003604
0.003418
0.002636
0.002655
0.002780
0.002870
0.002927
3.38
4.18
4.85
5.84
6.95
280.68
310.81
408.53
572.09
756.89
134.76
137.09
162.48
185.35
201.55
0.41
0.49
0.51
0.53
0.56
2.06
2.24
2.83
3.75
4.69
1.81
2.40
3.33
4.93
6.96
0.53
0.57
0.69
0.84
1.00
Kemp-Breeze SWA
Kemp-Breeze SWA
5737.84
5737.84
25 Year
50 Year
6000.00
7500.00
7460.28
7460.28
7466.50
7467.30
7467.34
7468.28
0.003280
0.003187
0.002929
0.002906
7.51
8.11
910.50
1087.00
211.44
231.31
0.56
0.57
5.43
6.22
8.34
10.04
1.11
1.24
Kemp-Breeze SWA
Kemp-Breeze SWA
5597.70
5597.70
Baseflow
LOC Spawn
170.00
250.00
7457.88
7457.88
7461.21
7461.51
7461.22
7461.53
0.001166
0.001230
0.001801
0.001987
1.01
1.21
167.93
205.95
124.24
125.38
0.15
0.17
1.34
1.63
0.10
0.15
0.10
0.13
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
5597.70
5597.70
5597.70
5597.70
5597.70
5597.70
5597.70
5597.70
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7457.88
7457.88
7457.88
7457.88
7457.88
7457.88
7457.88
7457.88
7462.06
7462.67
7462.92
7463.55
7464.47
7465.39
7466.12
7466.92
7462.11
7462.79
7463.09
7463.81
7464.90
7466.05
7466.92
7467.86
0.001519
0.001819
0.001856
0.002084
0.002339
0.002535
0.002631
0.002661
0.002432
0.002747
0.002756
0.002897
0.002957
0.003005
0.003011
0.002982
1.74
2.67
3.35
4.13
5.28
6.56
7.26
7.93
275.67
358.22
392.23
484.77
628.00
789.22
936.87
1129.03
128.47
139.39
143.03
148.54
163.98
186.66
222.67
256.06
0.21
0.29
0.34
0.38
0.44
0.50
0.52
0.53
2.12
2.68
2.92
3.55
4.46
5.37
6.09
6.88
0.35
0.81
1.14
1.91
3.44
5.58
7.26
9.06
0.20
0.30
0.34
0.46
0.65
0.85
1.00
1.14
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
5417.60
5417.60
5417.60
5417.60
5417.60
5417.60
5417.60
5417.60
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
7458.47
7458.47
7458.47
7458.47
7458.47
7458.47
7458.47
7458.47
7460.86
7461.13
7461.57
7462.10
7462.32
7462.95
7463.90
7464.87
7460.90
7461.17
7461.67
7462.28
7462.58
7463.28
7464.36
7465.50
0.003143
0.003737
0.004509
0.004623
0.004512
0.004297
0.003858
0.003618
0.005316
0.005356
0.005039
0.004586
0.004451
0.004036
0.003574
0.003254
1.51
1.79
2.43
3.39
4.12
4.65
5.44
6.40
112.24
139.81
197.25
280.23
315.48
419.27
582.82
754.27
98.94
114.53
143.44
162.46
163.45
168.14
174.64
178.93
0.25
0.29
0.37
0.46
0.52
0.52
0.52
0.54
1.13
1.21
1.36
1.70
1.91
2.48
3.41
4.37
0.33
0.51
0.93
1.67
2.21
3.10
4.47
6.31
0.22
0.28
0.38
0.49
0.54
0.67
0.82
0.99
Kemp-Breeze SWA
Kemp-Breeze SWA
5417.60
5417.60
25 Year
50 Year
6000.00
7500.00
7458.47
7458.47
7465.62
7466.45
7466.36
7467.30
0.003479
0.003364
0.003093
0.003000
6.90
7.42
890.59
1047.23
184.41
208.08
0.53
0.53
5.11
5.92
7.65
9.24
1.11
1.24
C - 25
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Crit W.S.
(ft)
E.G. Elev
(ft)
E.G. Slope
(ft/ft)
Frctn Slope
(ft/ft)
Vel Chnl
(ft/s)
Flow Area
(sq ft)
Top Width
(ft)
Froude # Chl
Hydr Radius C
(ft)
Power Chan
(lb/ft s)
Shear Chan
(lb/sq ft)
Kemp-Breeze SWA
Kemp-Breeze SWA
5130.32
5130.32
Baseflow
LOC Spawn
170.00
250.00
7458.22
7458.22
7459.30
7459.56
7459.36
7459.63
0.010869
0.008311
0.004545
0.004176
2.03
2.18
83.71
114.67
116.91
122.28
0.42
0.40
0.72
0.94
0.99
1.06
0.49
0.49
Kemp-Breeze SWA
5130.32
RBT Spawn
480.00
7458.22
7460.11
7460.22
0.005669
0.003694
2.61
183.85
126.01
0.38
1.45
1.34
0.51
Kemp-Breeze SWA
Kemp-Breeze SWA
5130.32
5130.32
May Avg
1.5 Year
950.00
1300.00
7458.22
7458.22
7460.77
7461.02
7460.97
7461.31
0.004550
0.004390
0.003511
0.003518
3.54
4.33
268.18
300.14
129.26
132.60
0.43
0.51
2.06
2.25
2.07
2.67
0.59
0.62
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
5130.32
5130.32
5130.32
2 Year
5 Year
10 Year
1950.00
3150.00
4750.00
7458.22
7458.22
7458.22
7461.75
7462.82
7463.89
7462.12
7463.33
7464.56
0.003798
0.003320
0.002943
0.003454
0.003462
0.003353
4.90
5.74
6.69
398.76
565.74
766.02
137.24
185.02
190.43
0.50
0.51
0.53
2.93
3.89
4.95
3.40
4.63
6.07
0.69
0.81
0.91
Kemp-Breeze SWA
Kemp-Breeze SWA
5130.32
5130.32
25 Year
50 Year
6000.00
7500.00
7458.22
7458.22
7464.69
7465.54
7465.46
7466.43
0.002769
0.002692
0.003297
0.003272
7.17
7.74
921.31
1092.05
194.37
212.02
0.52
0.53
5.75
6.59
7.12
8.57
0.99
1.11
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
5026.85
5026.85
5026.85
5026.85
5026.85
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
170.00
250.00
480.00
950.00
1300.00
7457.28
7457.28
7457.28
7457.28
7457.28
7458.85
7459.15
7459.75
7460.43
7460.67
7458.88
7459.19
7459.83
7460.60
7460.94
0.002482
0.002505
0.002596
0.002792
0.002883
0.002009
0.002125
0.002306
0.002565
0.002656
1.38
1.63
2.21
3.29
4.14
123.43
153.78
216.72
288.36
314.36
101.80
103.34
105.25
106.41
107.40
0.22
0.23
0.27
0.35
0.43
1.21
1.48
2.04
2.67
2.87
0.26
0.38
0.73
1.53
2.14
0.19
0.23
0.33
0.46
0.52
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
5026.85
5026.85
5026.85
5026.85
5026.85
2 Year
5 Year
10 Year
25 Year
50 Year
1950.00
3150.00
4750.00
6000.00
7500.00
7457.28
7457.28
7457.28
7457.28
7457.28
7461.38
7462.35
7463.26
7463.95
7464.71
7461.76
7462.96
7464.19
7465.09
7466.05
0.003155
0.003613
0.003854
0.003992
0.004060
0.002972
0.003385
0.003594
0.003704
0.003772
4.99
6.27
7.76
8.59
9.40
391.03
502.78
628.53
740.74
875.27
110.94
126.16
152.53
175.09
180.89
0.47
0.54
0.60
0.63
0.64
3.45
4.16
5.06
5.73
6.47
3.39
5.89
9.44
12.27
15.41
0.68
0.94
1.22
1.43
1.64
Kemp-Breeze SWA
Kemp-Breeze SWA
4911.95
4911.95
Baseflow
LOC Spawn
170.00
250.00
7456.83
7456.83
7458.63
7458.91
7457.55
7457.73
7458.65
7458.94
0.001659
0.001825
0.000767
0.000963
1.20
1.45
141.82
172.51
106.60
108.80
0.18
0.20
1.33
1.58
0.16
0.26
0.14
0.18
Kemp-Breeze SWA
Kemp-Breeze SWA
4911.95
4911.95
RBT Spawn
May Avg
480.00
950.00
7456.83
7456.83
7459.49
7460.15
7458.09
7458.66
7459.56
7460.30
0.002063
0.002365
0.001304
0.001657
2.03
3.07
236.73
309.92
110.80
113.21
0.24
0.33
2.12
2.71
0.55
1.23
0.27
0.40
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4911.95
4911.95
4911.95
4911.95
4911.95
4911.95
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7456.83
7456.83
7456.83
7456.83
7456.83
7456.83
7460.39
7461.06
7462.01
7462.92
7463.63
7464.39
7458.99
7459.49
7460.31
7461.29
7461.95
7462.68
7460.62
7461.41
7462.55
7463.75
7464.62
7465.56
0.002455
0.002804
0.003177
0.003359
0.003446
0.003514
0.001748
0.002113
0.002501
0.002714
0.002839
0.002950
3.85
4.69
5.93
7.30
8.05
8.82
337.37
415.92
534.42
679.19
797.95
933.09
114.35
119.21
143.99
165.36
172.48
182.82
0.40
0.44
0.51
0.57
0.58
0.60
2.92
3.44
4.21
5.11
5.81
6.56
1.72
2.82
4.95
7.83
10.05
12.68
0.45
0.60
0.84
1.07
1.25
1.44
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4812.02
4812.02
4812.02
4812.02
4812.02
4812.02
4812.02
4812.02
4812.02
4812.02
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7455.87
7455.87
7455.87
7455.87
7455.87
7455.87
7455.87
7455.87
7455.87
7455.87
7458.56
7458.83
7459.38
7460.02
7460.27
7460.93
7461.86
7462.79
7463.50
7464.26
7456.86
7457.02
7457.39
7457.92
7458.25
7458.76
7459.55
7460.50
7461.14
7461.86
7458.57
7458.84
7459.42
7460.11
7460.42
7461.16
7462.26
7463.41
7464.26
7465.20
0.000440
0.000594
0.000898
0.001226
0.001307
0.001649
0.002019
0.002239
0.002380
0.002511
0.79
1.01
1.54
2.45
3.10
3.89
5.06
6.32
7.05
7.81
216.53
246.94
311.73
388.10
418.80
500.81
627.69
769.08
877.32
994.39
112.91
114.48
117.95
121.36
122.46
127.59
150.85
179.51
193.60
203.72
0.10
0.12
0.17
0.24
0.30
0.35
0.41
0.47
0.49
0.52
1.91
2.14
2.62
3.17
3.38
3.88
4.66
5.58
6.28
7.03
0.04
0.08
0.23
0.59
0.86
1.55
2.97
4.93
6.58
8.61
0.05
0.08
0.15
0.24
0.28
0.40
0.59
0.78
0.93
1.10
Kemp-Breeze SWA
4781.11
Bridge
C - 26
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Crit W.S.
(ft)
E.G. Elev
(ft)
E.G. Slope
(ft/ft)
Frctn Slope
(ft/ft)
Vel Chnl
(ft/s)
Flow Area
(sq ft)
Top Width
(ft)
Froude # Chl
Hydr Radius C
(ft)
Power Chan
(lb/ft s)
Shear Chan
(lb/sq ft)
Kemp-Breeze SWA
Kemp-Breeze SWA
4756.73
4756.73
Baseflow
LOC Spawn
170.00
250.00
7454.30
7454.30
7458.56
7458.83
7455.65
7455.99
7458.56
7458.84
0.000199
0.000300
0.000486
0.000660
0.64
0.86
264.11
291.71
102.34
103.77
0.07
0.09
2.56
2.79
0.02
0.04
0.03
0.05
Kemp-Breeze SWA
4756.73
RBT Spawn
480.00
7454.30
7459.38
7456.51
7459.41
0.000531
0.000987
1.37
350.31
108.24
0.13
3.26
0.15
0.11
Kemp-Breeze SWA
Kemp-Breeze SWA
4756.73
4756.73
May Avg
1.5 Year
950.00
1300.00
7454.30
7454.30
7460.02
7460.27
7457.19
7457.59
7460.10
7460.40
0.000830
0.000930
0.001340
0.001437
2.27
2.91
420.79
450.08
114.15
125.73
0.20
0.26
3.78
3.97
0.44
0.67
0.20
0.23
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4756.73
4756.73
4756.73
2 Year
5 Year
10 Year
1950.00
3150.00
4750.00
7454.30
7454.30
7454.30
7460.92
7461.84
7462.76
7458.19
7459.11
7460.11
7461.14
7462.22
7463.37
0.001248
0.001602
0.001916
0.001738
0.002015
0.002231
3.74
4.97
6.34
535.63
666.94
803.30
143.44
155.73
167.20
0.31
0.37
0.44
4.49
5.40
6.31
1.31
2.68
4.79
0.35
0.54
0.75
Kemp-Breeze SWA
Kemp-Breeze SWA
4756.73
4756.73
25 Year
50 Year
6000.00
7500.00
7454.30
7454.30
7463.46
7464.21
7460.77
7461.60
7464.23
7465.16
0.002124
0.002324
0.002374
0.002493
7.16
8.00
908.54
1022.28
174.55
185.22
0.47
0.50
6.99
7.73
6.64
8.97
0.93
1.12
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4638.87
4638.87
4638.87
4638.87
4638.87
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
170.00
250.00
480.00
950.00
1300.00
7456.69
7456.69
7456.69
7456.69
7456.69
7458.48
7458.73
7459.24
7459.82
7460.04
7458.51
7458.76
7459.29
7459.94
7460.23
0.002526
0.002478
0.002433
0.002519
0.002507
0.002934
0.002794
0.002646
0.002678
0.002650
1.19
1.40
1.88
2.77
3.45
142.28
178.20
254.71
342.58
376.83
147.16
148.31
150.72
152.81
153.51
0.21
0.23
0.26
0.33
0.39
0.96
1.20
1.68
2.22
2.43
0.18
0.26
0.48
0.97
1.31
0.15
0.19
0.26
0.35
0.38
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4638.87
4638.87
4638.87
4638.87
4638.87
2 Year
5 Year
10 Year
25 Year
50 Year
1950.00
3150.00
4750.00
6000.00
7500.00
7456.69
7456.69
7456.69
7456.69
7456.69
7460.66
7461.57
7462.51
7463.21
7463.98
7460.93
7461.98
7463.11
7463.94
7464.84
0.002583
0.002612
0.002632
0.002671
0.002682
0.002684
0.002666
0.002655
0.002680
0.002687
4.12
5.12
6.23
6.87
7.50
472.88
620.03
779.94
905.89
1065.45
155.63
166.51
176.23
183.53
234.05
0.42
0.45
0.50
0.51
0.52
3.02
3.92
4.84
5.53
6.30
2.01
3.28
4.96
6.34
7.91
0.49
0.64
0.80
0.92
1.05
Kemp-Breeze SWA
Kemp-Breeze SWA
4610.88
4610.88
Baseflow
LOC Spawn
170.00
250.00
7456.56
7456.56
7458.40
7458.64
7458.42
7458.68
0.003449
0.003175
0.003737
0.003464
1.32
1.51
129.08
165.44
145.83
148.55
0.25
0.25
0.88
1.11
0.25
0.33
0.19
0.22
Kemp-Breeze SWA
Kemp-Breeze SWA
4610.88
4610.88
RBT Spawn
May Avg
480.00
950.00
7456.56
7456.56
7459.16
7459.73
7459.22
7459.86
0.002889
0.002851
0.003065
0.003045
1.97
2.86
243.38
332.51
153.46
156.21
0.28
0.35
1.58
2.12
0.56
1.08
0.29
0.38
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4610.88
4610.88
4610.88
4610.88
4610.88
4610.88
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7456.56
7456.56
7456.56
7456.56
7456.56
7456.56
7459.96
7460.58
7461.50
7462.44
7463.14
7463.91
7460.15
7460.85
7461.91
7463.03
7463.86
7464.76
0.002806
0.002792
0.002721
0.002679
0.002689
0.002692
0.003017
0.003006
0.002932
0.002899
0.002916
0.002921
3.54
4.18
5.14
6.21
6.82
7.45
367.26
466.21
616.86
779.82
907.90
1065.32
157.29
160.36
168.40
178.50
185.81
239.44
0.41
0.43
0.46
0.50
0.51
0.52
2.32
2.91
3.82
4.75
5.45
6.22
1.44
2.12
3.34
4.94
6.25
7.79
0.41
0.51
0.65
0.80
0.92
1.05
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4580.09
4580.09
4580.09
4580.09
4580.09
4580.09
4580.09
4580.09
4580.09
4580.09
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7456.71
7456.71
7456.71
7456.71
7456.71
7456.71
7456.71
7456.71
7456.71
7456.71
7458.28
7458.53
7459.06
7459.62
7459.83
7460.44
7461.34
7462.25
7462.94
7463.69
7458.31
7458.57
7459.12
7459.77
7460.06
7460.75
7461.81
7462.94
7463.76
7464.66
0.004062
0.003794
0.003258
0.003259
0.003253
0.003245
0.003169
0.003147
0.003173
0.003181
0.003537
0.003373
0.003086
0.003158
0.003135
0.003154
0.003091
0.003059
0.003081
0.003087
1.43
1.62
2.09
3.04
3.78
4.47
5.49
6.65
7.31
7.99
118.97
154.00
229.86
312.93
344.37
436.98
582.66
736.30
855.82
991.55
134.44
141.82
145.30
148.06
149.36
156.96
165.41
172.47
177.96
183.99
0.27
0.27
0.29
0.37
0.44
0.46
0.50
0.54
0.56
0.57
0.88
1.08
1.57
2.10
2.29
2.87
3.77
4.67
5.35
6.09
0.32
0.42
0.67
1.30
1.76
2.60
4.09
6.10
7.74
9.66
0.22
0.26
0.32
0.43
0.46
0.58
0.74
0.92
1.06
1.21
Kemp-Breeze SWA
4513.76
Baseflow
170.00
7456.16
7458.04
7458.07
0.003107
0.003996
1.34
126.75
128.53
0.24
0.98
0.26
0.19
C - 27
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
4513.76
LOC Spawn
250.00
7456.16
7458.31
Crit W.S.
(ft)
E.G. Elev
(ft)
7458.34
E.G. Slope
(ft/ft)
0.003018
Frctn Slope
(ft/ft)
0.003876
Vel Chnl
(ft/s)
1.55
Flow Area
(sq ft)
161.79
Top Width
(ft)
134.72
0.25
Hydr Radius C
(ft)
1.19
Kemp-Breeze SWA
Kemp-Breeze SWA
4513.76
4513.76
RBT Spawn
May Avg
480.00
950.00
7456.16
7456.16
7458.85
7459.42
7458.92
7459.55
0.002928
0.003061
0.003723
0.003639
2.01
2.94
238.38
323.14
145.85
151.49
0.28
0.35
1.61
2.10
0.59
1.18
0.30
0.40
Kemp-Breeze SWA
4513.76
1.5 Year
1300.00
7456.16
7459.64
7459.84
0.003024
0.003540
3.65
356.02
151.91
0.42
2.30
1.59
0.43
Kemp-Breeze SWA
Kemp-Breeze SWA
4513.76
4513.76
2 Year
5 Year
1950.00
3150.00
7456.16
7456.16
7460.25
7461.16
7460.54
7461.60
0.003067
0.003016
0.003410
0.003208
4.34
5.32
449.91
597.54
155.57
166.98
0.45
0.48
2.86
3.72
2.38
3.72
0.55
0.70
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4513.76
4513.76
4513.76
10 Year
25 Year
50 Year
4750.00
6000.00
7500.00
7456.16
7456.16
7456.16
7462.08
7462.77
7463.52
7462.72
7463.54
7464.44
0.002975
0.002994
0.002997
0.003110
0.003105
0.003084
6.43
7.06
7.71
755.98
878.64
1017.70
175.85
181.00
186.70
0.52
0.54
0.55
4.62
5.30
6.04
5.52
6.99
8.71
0.86
0.99
1.13
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4456.53
4456.53
4456.53
4456.53
4456.53
4456.53
4456.53
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
7456.18
7456.18
7456.18
7456.18
7456.18
7456.18
7456.18
7457.79
7458.06
7458.62
7459.18
7459.39
7460.01
7460.94
7457.84
7458.12
7458.70
7459.34
7459.64
7460.34
7461.41
0.005330
0.005159
0.004893
0.004398
0.004200
0.003814
0.003418
0.004140
0.004211
0.004479
0.004219
0.004021
0.003660
0.003317
1.69
1.91
2.34
3.25
3.99
4.59
5.50
100.54
130.92
205.42
292.71
325.79
424.63
576.17
108.16
119.02
148.98
156.93
157.42
158.89
167.75
0.31
0.32
0.35
0.42
0.49
0.50
0.51
0.93
1.10
1.37
1.85
2.05
2.65
3.57
0.52
0.67
0.98
1.65
2.15
2.90
4.19
0.31
0.35
0.42
0.51
0.54
0.63
0.76
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4456.53
4456.53
4456.53
10 Year
25 Year
50 Year
4750.00
6000.00
7500.00
7456.18
7456.18
7456.18
7461.87
7462.56
7463.32
7462.54
7463.36
7464.26
0.003256
0.003222
0.003175
0.003136
0.003094
0.003038
6.58
7.20
7.82
734.61
857.01
996.48
175.08
180.42
186.26
0.55
0.56
0.56
4.48
5.16
5.91
5.99
7.47
9.17
0.91
1.04
1.17
Kemp-Breeze SWA
4398.86
Baseflow
170.00
7455.84
7457.56
7457.60
0.003308
0.004978
1.48
115.14
105.68
0.25
1.08
0.33
0.22
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4398.86
4398.86
4398.86
LOC Spawn
RBT Spawn
May Avg
250.00
480.00
950.00
7455.84
7455.84
7455.84
7457.83
7458.36
7458.94
7457.87
7458.44
7459.10
0.003503
0.004115
0.004050
0.005279
0.005420
0.004591
1.74
2.27
3.19
143.49
211.68
298.07
111.29
140.13
153.56
0.27
0.33
0.40
1.28
1.50
1.92
0.49
0.87
1.55
0.28
0.38
0.49
Kemp-Breeze SWA
Kemp-Breeze SWA
4398.86
4398.86
1.5 Year
2 Year
1300.00
1950.00
7455.84
7455.84
7459.16
7459.81
7459.40
7460.13
0.003853
0.003515
0.004298
0.003722
3.91
4.49
332.70
434.27
154.80
158.56
0.47
0.48
2.12
2.72
2.00
2.68
0.51
0.60
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4398.86
4398.86
4398.86
4398.86
5 Year
10 Year
25 Year
50 Year
3150.00
4750.00
6000.00
7500.00
7455.84
7455.84
7455.84
7455.84
7460.77
7461.72
7462.42
7463.19
7461.22
7462.35
7463.16
7464.06
0.003220
0.003023
0.002973
0.002910
0.003328
0.003159
0.003134
0.003088
5.37
6.40
6.97
7.55
591.96
768.94
904.28
1057.32
180.45
190.71
195.42
199.72
0.50
0.53
0.53
0.54
3.60
4.54
5.23
5.99
3.89
5.47
6.76
8.22
0.72
0.86
0.97
1.09
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4329.34
4329.34
4329.34
4329.34
4329.34
4329.34
4329.34
4329.34
4329.34
4329.34
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7455.45
7455.45
7455.45
7455.45
7455.45
7455.45
7455.45
7455.45
7455.45
7455.45
7457.18
7457.43
7457.95
7458.59
7458.82
7459.52
7460.50
7461.43
7462.11
7462.87
7457.25
7457.51
7458.06
7458.78
7459.10
7459.86
7460.98
7462.12
7462.94
7463.84
0.008325
0.008847
0.007461
0.005248
0.004825
0.003948
0.003441
0.003304
0.003309
0.003282
0.009421
0.008008
0.006193
0.004848
0.004525
0.003865
0.003361
0.003245
0.003265
0.003242
2.03
2.29
2.68
3.48
4.22
4.72
5.59
6.70
7.34
7.99
83.62
109.03
179.03
272.75
307.82
415.30
575.55
738.53
863.34
1007.57
95.22
112.70
144.48
149.22
150.44
158.59
169.01
180.17
187.09
194.78
0.38
0.41
0.42
0.45
0.52
0.50
0.51
0.55
0.56
0.57
0.87
0.96
1.23
1.81
2.02
2.69
3.63
4.55
5.21
5.95
0.92
1.22
1.54
2.06
2.56
3.13
4.37
6.28
7.91
9.75
0.45
0.53
0.57
0.59
0.61
0.66
0.78
0.94
1.08
1.22
Kemp-Breeze SWA
4282.11
Baseflow
170.00
7454.90
7456.73
7456.80
0.010748
0.004218
2.12
80.15
103.90
0.43
0.77
1.10
0.52
Kemp-Breeze SWA
Kemp-Breeze SWA
4282.11
4282.11
LOC Spawn
RBT Spawn
250.00
480.00
7454.90
7454.90
7457.05
7457.66
7457.12
7457.77
0.007283
0.005223
0.003749
0.003431
2.19
2.61
114.32
183.79
109.89
118.46
0.38
0.37
1.04
1.55
1.03
1.32
0.47
0.50
C - 28
Froude # Chl
Power Chan
(lb/ft s)
0.35
Shear Chan
(lb/sq ft)
0.22
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
4282.11
May Avg
950.00
7454.90
7458.36
Crit W.S.
(ft)
E.G. Elev
(ft)
7458.55
E.G. Slope
(ft/ft)
0.004493
Frctn Slope
(ft/ft)
0.003278
Vel Chnl
(ft/s)
3.45
Flow Area
(sq ft)
275.15
Top Width
(ft)
136.56
0.43
Hydr Radius C
(ft)
2.00
Kemp-Breeze SWA
Kemp-Breeze SWA
4282.11
4282.11
1.5 Year
2 Year
1300.00
1950.00
7454.90
7454.90
7458.61
7459.34
7458.88
7459.68
0.004253
0.003784
0.003197
0.003086
4.20
4.70
309.59
416.27
139.82
156.33
0.50
0.50
2.20
2.76
2.45
3.06
0.58
0.65
Kemp-Breeze SWA
4282.11
5 Year
3150.00
7454.90
7460.34
7460.82
0.003284
0.002945
5.56
578.42
167.36
0.50
3.73
4.25
0.77
Kemp-Breeze SWA
Kemp-Breeze SWA
4282.11
4282.11
10 Year
25 Year
4750.00
6000.00
7454.90
7454.90
7461.28
7461.95
7461.97
7462.78
0.003188
0.003221
0.002985
0.003077
6.68
7.34
741.65
866.77
181.39
188.77
0.54
0.56
4.65
5.32
6.19
7.85
0.93
1.07
Kemp-Breeze SWA
4282.11
50 Year
7500.00
7454.90
7462.71
7463.68
0.003203
0.003100
7.99
1012.56
195.98
0.57
6.07
9.69
1.21
Kemp-Breeze SWA
4225.47
Baseflow
170.00
7454.58
7456.52
7456.55
0.002235
0.001045
1.38
123.40
94.17
0.21
1.31
0.25
0.18
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4225.47
4225.47
4225.47
4225.47
4225.47
4225.47
4225.47
4225.47
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7454.58
7454.58
7454.58
7454.58
7454.58
7454.58
7454.58
7454.58
7456.86
7457.49
7458.20
7458.46
7459.19
7460.19
7461.14
7461.82
7456.90
7457.56
7458.35
7458.69
7459.50
7460.65
7461.78
7462.59
0.002279
0.002425
0.002496
0.002490
0.002565
0.002657
0.002801
0.002942
0.001221
0.001555
0.001872
0.001956
0.002142
0.002360
0.002599
0.002795
1.59
2.15
3.07
3.79
4.45
5.43
6.46
7.07
156.77
223.66
309.42
343.29
441.64
592.49
760.16
886.21
101.30
111.37
127.88
130.86
140.75
164.39
182.56
188.58
0.23
0.27
0.35
0.41
0.43
0.49
0.54
0.55
1.54
2.00
2.40
2.62
3.24
3.78
4.43
5.09
0.35
0.65
1.15
1.54
2.31
3.40
5.00
6.61
0.22
0.30
0.37
0.41
0.52
0.63
0.77
0.93
Kemp-Breeze SWA
4225.47
50 Year
7500.00
7454.58
7462.59
7463.48
0.003002
0.002910
7.65
1034.03
195.36
0.55
5.84
8.38
1.09
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4165.07
4165.07
4165.07
Baseflow
LOC Spawn
RBT Spawn
170.00
250.00
480.00
7453.27
7453.27
7453.27
7456.47
7456.80
7457.41
7456.48
7456.82
7457.46
0.000603
0.000760
0.001082
0.000619
0.000818
0.001135
0.94
1.18
1.74
179.95
211.85
275.16
92.66
99.16
106.75
0.12
0.14
0.19
1.93
2.12
2.55
0.07
0.12
0.30
0.07
0.10
0.17
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4165.07
4165.07
4165.07
May Avg
1.5 Year
2 Year
950.00
1300.00
1950.00
7453.27
7453.27
7453.27
7458.11
7458.38
7459.09
7458.23
7458.56
7459.35
0.001456
0.001577
0.001815
0.001439
0.001514
0.001702
2.69
3.38
4.12
353.00
384.48
474.72
117.01
120.32
134.62
0.27
0.33
0.38
2.97
3.14
3.56
0.73
1.05
1.66
0.27
0.31
0.40
Kemp-Breeze SWA
Kemp-Breeze SWA
4165.07
4165.07
5 Year
10 Year
3150.00
4750.00
7453.27
7453.27
7460.08
7461.01
7460.49
7461.62
0.002110
0.002418
0.001862
0.002058
5.13
6.25
621.66
781.44
162.84
177.67
0.45
0.50
3.98
4.74
2.69
4.47
0.52
0.72
Kemp-Breeze SWA
Kemp-Breeze SWA
4165.07
4165.07
25 Year
50 Year
6000.00
7500.00
7453.27
7453.27
7461.67
7462.43
7462.41
7463.30
0.002658
0.002822
0.002153
0.002070
6.93
7.58
901.41
1045.26
185.92
195.80
0.52
0.53
5.39
6.12
6.19
8.17
0.89
1.08
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
4137.79
4137.79
4137.79
4137.79
4137.79
4137.79
4137.79
4137.79
4137.79
4137.79
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7453.19
7453.19
7453.19
7453.19
7453.19
7453.19
7453.19
7453.19
7453.19
7453.19
7456.45
7456.78
7457.39
7458.09
7458.37
7459.09
7460.11
7461.06
7461.77
7462.62
7456.47
7456.80
7457.43
7458.18
7458.50
7459.29
7460.41
7461.51
7462.28
7463.14
0.000635
0.000884
0.001192
0.001423
0.001455
0.001599
0.001655
0.001772
0.001779
0.001583
0.001068
0.001300
0.001609
0.001829
0.001863
0.002032
0.002147
0.002120
0.002180
0.002034
0.91
1.12
1.59
2.37
2.94
3.51
4.37
5.40
5.87
6.04
187.31
224.14
302.35
401.24
442.45
558.28
733.16
917.86
1156.65
1508.25
103.67
121.13
134.81
146.84
151.33
167.36
177.16
239.81
386.81
468.79
0.12
0.14
0.19
0.25
0.30
0.33
0.36
0.41
0.42
0.40
1.80
1.84
2.22
2.69
2.87
3.40
4.35
5.25
5.93
6.76
0.06
0.11
0.26
0.57
0.77
1.19
1.97
3.13
3.87
4.03
0.07
0.10
0.17
0.24
0.26
0.34
0.45
0.58
0.66
0.67
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3980.46
3980.46
3980.46
Baseflow
LOC Spawn
RBT Spawn
170.00
250.00
480.00
7454.55
7454.55
7454.55
7456.27
7456.56
7457.11
7455.42
7455.62
7455.92
7456.30
7456.59
7457.17
0.002157
0.002099
0.002290
0.002541
0.002530
0.002638
1.23
1.44
1.97
138.76
174.07
243.43
122.50
123.07
127.93
0.20
0.21
0.25
1.13
1.40
1.88
0.19
0.26
0.53
0.15
0.18
0.27
Kemp-Breeze SWA
Kemp-Breeze SWA
3980.46
3980.46
May Avg
1.5 Year
950.00
1300.00
7454.55
7454.55
7457.75
7458.00
7456.37
7456.66
7457.89
7458.20
0.002438
0.002471
0.002774
0.002810
2.91
3.62
326.49
358.66
131.49
133.60
0.33
0.39
2.45
2.65
1.08
1.48
0.37
0.41
C - 29
Froude # Chl
Power Chan
(lb/ft s)
1.94
Shear Chan
(lb/sq ft)
0.56
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
3980.46
2 Year
1950.00
7454.55
7458.66
Crit W.S.
(ft)
7457.13
E.G. Elev
(ft)
7458.96
E.G. Slope
(ft/ft)
0.002668
Frctn Slope
(ft/ft)
0.002937
Vel Chnl
(ft/s)
4.34
Flow Area
(sq ft)
449.50
Top Width
(ft)
139.40
584.04
792.90
148.11
186.64
Froude # Chl
0.43
Hydr Radius C
(ft)
3.18
Power Chan
(lb/ft s)
2.30
Shear Chan
(lb/sq ft)
0.53
0.48
0.49
3.92
4.89
3.82
4.89
0.71
0.79
Kemp-Breeze SWA
Kemp-Breeze SWA
3980.46
3980.46
5 Year
10 Year
3150.00
4750.00
7454.55
7454.55
7459.60
7460.58
7457.91
7458.78
7460.05
7461.17
0.002898
0.002581
0.003097
0.002935
5.39
6.21
Kemp-Breeze SWA
3980.46
25 Year
6000.00
7454.55
7461.21
7459.36
7461.92
0.002735
0.002899
6.92
910.35
191.22
0.52
5.50
6.50
0.94
Kemp-Breeze SWA
3980.46
50 Year
7500.00
7454.55
7461.96
7459.98
7462.79
0.002709
0.002848
7.49
1102.38
315.02
0.52
6.24
7.91
1.06
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3787.63
3787.63
3787.63
Baseflow
LOC Spawn
RBT Spawn
170.00
250.00
480.00
7454.18
7454.18
7454.18
7455.77
7456.06
7456.59
7455.02
7455.16
7455.50
7455.80
7456.10
7456.66
0.003037
0.003108
0.003071
0.003917
0.003930
0.003721
1.40
1.60
2.14
121.34
156.02
224.35
113.08
125.54
130.27
0.24
0.25
0.29
1.07
1.23
1.71
0.28
0.38
0.70
0.20
0.24
0.33
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3787.63
3787.63
3787.63
3787.63
3787.63
3787.63
3787.63
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7454.18
7454.18
7454.18
7454.18
7454.18
7454.18
7454.18
7457.20
7457.42
7458.06
7458.95
7459.84
7460.57
7461.33
7456.03
7456.27
7456.78
7457.54
7458.36
7458.93
7459.54
7457.35
7457.66
7458.39
7459.45
7460.58
7461.36
7462.23
0.003186
0.003224
0.003249
0.003317
0.003366
0.003078
0.002999
0.003488
0.003436
0.003304
0.003284
0.003289
0.002984
0.002882
3.12
3.88
4.59
5.70
6.94
7.29
7.85
304.39
335.95
428.46
565.80
713.58
900.40
1074.43
136.27
142.95
147.52
162.72
167.15
212.38
252.09
0.37
0.44
0.47
0.51
0.56
0.55
0.55
2.23
2.40
2.98
3.84
4.73
5.45
6.20
1.38
1.87
2.78
4.53
6.90
7.63
9.11
0.44
0.48
0.61
0.80
0.99
1.05
1.16
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3673.07
3673.07
3673.07
3673.07
3673.07
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
170.00
250.00
480.00
950.00
1300.00
7453.69
7453.69
7453.69
7453.69
7453.69
7455.30
7455.59
7456.15
7456.79
7457.02
7454.64
7454.82
7455.22
7455.78
7456.07
7455.35
7455.65
7456.24
7456.95
7457.26
0.005243
0.005129
0.004602
0.003836
0.003670
0.002314
0.002465
0.002553
0.002537
0.002516
1.71
1.90
2.35
3.21
3.94
99.35
131.30
204.56
295.85
330.18
103.88
119.58
141.04
145.92
147.66
0.31
0.32
0.34
0.40
0.46
0.96
1.10
1.45
2.02
2.23
0.54
0.67
0.98
1.55
2.01
0.31
0.35
0.42
0.48
0.51
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3673.07
3673.07
3673.07
2 Year
5 Year
10 Year
1950.00
3150.00
4750.00
7453.69
7453.69
7453.69
7457.69
7458.59
7459.50
7456.52
7457.23
7458.00
7458.01
7459.07
7460.19
0.003361
0.003251
0.003215
0.002609
0.002700
0.002774
4.54
5.56
6.73
431.20
578.67
734.12
157.73
167.27
174.67
0.47
0.50
0.55
2.87
3.76
4.67
2.73
4.25
6.30
0.60
0.76
0.94
Kemp-Breeze SWA
Kemp-Breeze SWA
3673.07
3673.07
25 Year
50 Year
6000.00
7500.00
7453.69
7453.69
7460.26
7461.05
7458.55
7459.14
7461.00
7461.88
0.002894
0.002772
0.002560
0.002469
7.05
7.55
920.04
1110.27
225.58
262.38
0.53
0.53
5.43
6.21
6.91
8.12
0.98
1.07
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3614.25
3614.25
3614.25
3614.25
3614.25
3614.25
3614.25
3614.25
3614.25
3614.25
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7453.29
7453.29
7453.29
7453.29
7453.29
7453.29
7453.29
7453.29
7453.29
7453.29
7455.19
7455.47
7456.03
7456.68
7456.93
7457.59
7458.49
7459.41
7460.17
7460.97
7454.09
7454.24
7454.55
7455.10
7455.40
7455.86
7456.58
7457.42
7457.99
7458.62
7455.20
7455.49
7456.08
7456.78
7457.09
7457.83
7458.88
7460.00
7460.83
7461.71
0.001297
0.001443
0.001621
0.001802
0.001831
0.002084
0.002279
0.002418
0.002281
0.002213
0.001627
0.001724
0.001863
0.002013
0.002025
0.002195
0.002365
0.002489
0.002451
0.002273
1.04
1.25
1.74
2.61
3.26
3.96
5.02
6.20
6.61
7.08
163.66
200.29
275.41
363.92
398.74
493.11
635.61
791.85
982.18
1206.22
126.52
132.35
135.06
138.24
139.80
150.41
163.26
175.11
248.33
318.29
0.16
0.18
0.22
0.28
0.34
0.38
0.43
0.48
0.48
0.48
1.29
1.51
2.03
2.61
2.83
3.33
4.22
5.12
5.88
6.68
0.11
0.17
0.36
0.77
1.05
1.72
3.01
4.80
5.53
6.53
0.10
0.14
0.21
0.29
0.32
0.43
0.60
0.77
0.84
0.92
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3557.02
3557.02
3557.02
3557.02
3557.02
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
170.00
250.00
480.00
950.00
1300.00
7453.40
7453.40
7453.40
7453.40
7453.40
7455.09
7455.36
7455.91
7456.55
7456.80
7454.31
7454.45
7454.73
7455.19
7455.47
7455.11
7455.39
7455.97
7456.67
7456.97
0.002102
0.002096
0.002163
0.002264
0.002250
0.002291
0.002425
0.002457
0.002483
0.002456
1.18
1.39
1.88
2.74
3.39
143.66
180.32
255.93
346.80
383.04
131.40
134.87
139.95
145.94
149.10
0.20
0.21
0.24
0.31
0.37
1.09
1.33
1.82
2.36
2.57
0.17
0.24
0.46
0.92
1.23
0.14
0.17
0.25
0.33
0.36
Kemp-Breeze SWA
Kemp-Breeze SWA
3557.02
3557.02
2 Year
5 Year
1950.00
3150.00
7453.40
7453.40
7457.45
7458.34
7455.90
7456.59
7457.70
7458.75
0.002315
0.002457
0.002501
0.002608
4.06
5.11
483.45
629.77
158.31
167.97
0.40
0.44
3.20
4.09
1.87
3.20
0.46
0.63
C - 30
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
3557.02
10 Year
4750.00
7453.40
7459.25
Crit W.S.
(ft)
7457.42
E.G. Elev
(ft)
7459.86
E.G. Slope
(ft/ft)
0.002563
Frctn Slope
(ft/ft)
0.002692
Vel Chnl
(ft/s)
6.28
Flow Area
(sq ft)
785.55
Top Width
(ft)
175.08
0.49
Hydr Radius C
(ft)
4.99
Kemp-Breeze SWA
Kemp-Breeze SWA
3557.02
3557.02
25 Year
50 Year
6000.00
7500.00
7453.40
7453.40
7459.94
7460.82
7457.95
7458.51
7460.68
7461.58
0.002641
0.002336
0.002759
0.002611
6.94
7.18
907.86
1175.39
180.47
323.38
0.51
0.49
5.67
6.55
6.50
6.86
0.94
0.96
Kemp-Breeze SWA
Kemp-Breeze SWA
3512.54
3512.54
Baseflow
LOC Spawn
170.00
250.00
7452.79
7452.79
7454.98
7455.25
7454.05
7454.21
7455.01
7455.28
0.002506
0.002839
0.001538
0.001761
1.31
1.54
129.36
162.22
115.17
129.81
0.22
0.24
1.12
1.24
0.23
0.34
0.18
0.22
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3512.54
3512.54
3512.54
RBT Spawn
May Avg
1.5 Year
480.00
950.00
1300.00
7452.79
7452.79
7452.79
7455.79
7456.43
7456.67
7454.59
7455.17
7455.50
7455.86
7456.55
7456.86
0.002815
0.002735
0.002691
0.001950
0.002067
0.002072
2.01
2.88
3.55
238.36
329.80
366.04
142.61
148.19
151.10
0.27
0.34
0.40
1.66
2.21
2.41
0.59
1.09
1.44
0.29
0.38
0.40
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3512.54
3512.54
3512.54
3512.54
3512.54
2 Year
5 Year
10 Year
25 Year
50 Year
1950.00
3150.00
4750.00
6000.00
7500.00
7452.79
7452.79
7452.79
7452.79
7452.79
7457.32
7458.20
7459.10
7459.78
7460.52
7455.94
7456.64
7457.37
7457.94
7458.53
7457.59
7458.63
7459.73
7460.55
7461.44
0.002709
0.002772
0.002831
0.002884
0.002936
0.002220
0.002381
0.002472
0.002544
0.002606
4.19
5.22
6.38
7.04
7.73
465.54
606.29
754.43
870.63
1000.32
155.35
161.85
168.10
172.84
184.36
0.43
0.47
0.51
0.53
0.55
2.98
3.85
4.75
5.42
6.16
2.11
3.48
5.35
6.87
8.72
0.50
0.67
0.84
0.98
1.13
Kemp-Breeze SWA
Kemp-Breeze SWA
3452.84
3452.84
Baseflow
LOC Spawn
170.00
250.00
7453.30
7453.30
7454.90
7455.15
7453.89
7454.00
7454.91
7455.17
0.001039
0.001198
0.001657
0.001768
0.94
1.15
180.95
216.72
138.03
140.51
0.14
0.16
1.31
1.54
0.08
0.13
0.08
0.12
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3452.84
3452.84
3452.84
3452.84
3452.84
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
480.00
950.00
1300.00
1950.00
3150.00
7453.30
7453.30
7453.30
7453.30
7453.30
7455.69
7456.33
7456.58
7457.23
7458.12
7454.28
7454.73
7454.98
7455.46
7456.14
7455.74
7456.42
7456.72
7457.44
7458.46
0.001430
0.001616
0.001644
0.001852
0.002066
0.001895
0.001994
0.001986
0.002159
0.002294
1.63
2.45
3.06
3.71
4.72
293.89
387.01
424.89
525.51
671.35
145.08
149.23
151.77
159.17
168.66
0.20
0.27
0.32
0.36
0.41
2.02
2.58
2.79
3.31
4.13
0.29
0.64
0.88
1.42
2.51
0.18
0.26
0.29
0.38
0.53
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3452.84
3452.84
3452.84
10 Year
25 Year
50 Year
4750.00
6000.00
7500.00
7453.30
7453.30
7453.30
7459.03
7459.72
7460.47
7456.94
7457.49
7458.05
7459.55
7460.36
7461.24
0.002178
0.002261
0.002329
0.002340
0.002379
0.002413
5.82
6.45
7.11
829.35
953.69
1098.10
177.35
183.87
226.48
0.46
0.47
0.49
5.03
5.72
6.46
3.98
5.21
6.68
0.68
0.81
0.94
Kemp-Breeze SWA
3402.19
Baseflow
170.00
7453.35
7454.80
7454.15
7454.83
0.003048
0.003600
1.27
133.82
145.38
0.23
0.92
0.22
0.17
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3402.19
3402.19
3402.19
3402.19
3402.19
3402.19
3402.19
3402.19
3402.19
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7453.35
7453.35
7453.35
7453.35
7453.35
7453.35
7453.35
7453.35
7453.35
7455.05
7455.58
7456.20
7456.44
7457.08
7457.96
7458.88
7459.58
7460.34
7454.28
7454.58
7455.00
7455.26
7455.68
7456.35
7457.12
7457.61
7458.18
7455.08
7455.64
7456.32
7456.62
7457.33
7458.34
7459.43
7460.24
7461.12
0.002867
0.002632
0.002522
0.002448
0.002547
0.002561
0.002521
0.002506
0.002502
0.003413
0.003245
0.003149
0.003105
0.003242
0.003178
0.003009
0.002909
0.002823
1.47
1.92
2.74
3.38
3.99
4.94
5.97
6.53
7.12
170.34
250.17
346.29
384.77
488.39
644.16
821.14
960.43
1116.41
147.88
153.14
157.61
159.49
167.09
185.45
196.50
200.25
222.66
0.24
0.26
0.33
0.38
0.41
0.45
0.48
0.49
0.51
1.15
1.63
2.19
2.40
2.91
3.77
4.68
5.38
6.14
0.30
0.51
0.94
1.24
1.84
2.98
4.40
5.50
6.83
0.21
0.27
0.34
0.37
0.46
0.60
0.74
0.84
0.96
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3317.62
3317.62
3317.62
3317.62
3317.62
3317.62
3317.62
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
7452.80
7452.80
7452.80
7452.80
7452.80
7452.80
7452.80
7454.48
7454.74
7455.28
7455.88
7456.09
7456.70
7457.57
7453.81
7453.98
7454.33
7454.85
7455.16
7455.62
7456.41
7454.52
7454.79
7455.36
7456.05
7456.35
7457.04
7458.06
0.004317
0.004133
0.004100
0.004042
0.004065
0.004264
0.004049
0.002388
0.002516
0.002828
0.003102
0.003055
0.003190
0.003152
1.56
1.80
2.33
3.30
4.07
4.70
5.63
109.08
138.82
205.99
288.21
319.12
414.49
559.51
113.42
116.88
131.52
141.93
146.18
163.16
170.92
0.28
0.29
0.33
0.41
0.49
0.52
0.55
0.96
1.19
1.56
2.02
2.17
2.53
3.25
0.40
0.55
0.93
1.68
2.25
3.16
4.63
0.26
0.31
0.40
0.51
0.55
0.67
0.82
Kemp-Breeze SWA
Kemp-Breeze SWA
3317.62
3317.62
10 Year
25 Year
4750.00
6000.00
7452.80
7452.80
7458.48
7459.20
7457.18
7457.69
7459.16
7459.98
0.003654
0.003417
0.002975
0.002870
6.62
7.11
725.32
866.65
192.18
203.22
0.57
0.57
4.14
4.85
6.25
7.35
0.94
1.03
C - 31
Froude # Chl
Power Chan
(lb/ft s)
5.01
Shear Chan
(lb/sq ft)
0.80
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
3317.62
50 Year
7500.00
7452.80
7459.98
Crit W.S.
(ft)
7458.23
E.G. Elev
(ft)
7460.87
E.G. Slope
(ft/ft)
0.003211
Frctn Slope
(ft/ft)
0.002776
Vel Chnl
(ft/s)
7.61
Flow Area
(sq ft)
1029.05
Top Width
(ft)
211.68
Froude # Chl
0.56
Hydr Radius C
(ft)
5.63
Power Chan
(lb/ft s)
8.58
Shear Chan
(lb/sq ft)
1.13
Kemp-Breeze SWA
3227.79
Baseflow
170.00
7452.24
7454.28
7453.34
7454.30
0.001513
0.002070
1.07
158.57
131.47
0.17
1.20
0.12
0.11
Kemp-Breeze SWA
3227.79
LOC Spawn
250.00
7452.24
7454.53
7453.47
7454.56
0.001692
0.002221
1.30
191.90
134.20
0.19
1.43
0.20
0.15
Kemp-Breeze SWA
Kemp-Breeze SWA
3227.79
3227.79
RBT Spawn
May Avg
480.00
950.00
7452.24
7452.24
7455.04
7455.64
7453.78
7454.27
7455.10
7455.75
0.002068
0.002455
0.002566
0.002908
1.83
2.70
262.41
352.32
144.10
161.34
0.24
0.32
1.81
2.17
0.43
0.90
0.23
0.33
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3227.79
3227.79
3227.79
1.5 Year
2 Year
5 Year
1300.00
1950.00
3150.00
7452.24
7452.24
7452.24
7455.88
7456.48
7457.36
7454.55
7455.02
7455.69
7456.05
7456.73
7457.74
0.002380
0.002476
0.002524
0.002877
0.003076
0.003285
3.32
3.97
4.94
391.27
490.99
642.44
162.88
167.20
177.14
0.38
0.41
0.44
2.39
2.95
3.81
1.18
1.81
2.96
0.36
0.46
0.60
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3227.79
3227.79
3227.79
10 Year
25 Year
50 Year
4750.00
6000.00
7500.00
7452.24
7452.24
7452.24
7458.31
7459.03
7459.81
7456.49
7456.97
7457.55
7458.86
7459.68
7460.58
0.002468
0.002445
0.002423
0.003397
0.003439
0.003460
5.95
6.51
7.08
815.26
955.08
1114.99
189.24
198.50
208.57
0.48
0.49
0.50
4.74
5.46
6.24
4.35
5.43
6.69
0.73
0.83
0.94
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3197.63
3197.63
3197.63
3197.63
Baseflow
LOC Spawn
RBT Spawn
May Avg
170.00
250.00
480.00
950.00
7452.34
7452.34
7452.34
7452.34
7454.21
7454.45
7454.94
7455.49
7453.41
7453.58
7453.93
7454.43
7454.24
7454.49
7455.02
7455.66
0.003002
0.003045
0.003269
0.003499
0.002359
0.002406
0.002613
0.002862
1.35
1.59
2.19
3.25
126.39
156.95
219.67
292.56
124.64
126.11
130.09
135.23
0.24
0.25
0.30
0.38
1.01
1.24
1.68
2.21
0.26
0.38
0.75
1.57
0.19
0.24
0.34
0.48
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3197.63
3197.63
3197.63
3197.63
3197.63
1.5 Year
2 Year
5 Year
10 Year
25 Year
1300.00
1950.00
3150.00
4750.00
6000.00
7452.34
7452.34
7452.34
7452.34
7452.34
7455.69
7456.23
7456.98
7457.71
7458.30
7454.71
7455.19
7455.90
7456.73
7457.34
7455.95
7456.62
7457.62
7458.71
7459.52
0.003547
0.003923
0.004453
0.004967
0.005188
0.002883
0.003229
0.003610
0.003849
0.003913
4.08
5.00
6.42
8.05
8.94
320.17
395.23
503.92
615.30
713.82
137.20
142.17
148.72
156.80
178.41
0.46
0.51
0.59
0.67
0.70
2.41
2.95
3.69
4.42
5.00
2.18
3.61
6.59
11.03
14.48
0.53
0.72
1.03
1.37
1.62
Kemp-Breeze SWA
3197.63
50 Year
7500.00
7452.34
7458.94
7457.99
7460.41
0.005340
0.003944
9.83
834.12
191.40
0.73
5.64
18.49
1.88
Kemp-Breeze SWA
3115.41
Baseflow
170.00
7452.25
7454.02
7453.27
7454.04
0.001902
0.001807
1.08
156.71
151.58
0.19
1.03
0.13
0.12
Kemp-Breeze SWA
Kemp-Breeze SWA
3115.41
3115.41
LOC Spawn
RBT Spawn
250.00
480.00
7452.25
7452.25
7454.26
7454.74
7453.39
7453.65
7454.29
7454.79
0.001949
0.002137
0.001913
0.002203
1.29
1.79
193.72
267.68
152.77
155.12
0.20
0.24
1.26
1.72
0.20
0.41
0.15
0.23
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
3115.41
3115.41
3115.41
3115.41
3115.41
3115.41
3115.41
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7452.25
7452.25
7452.25
7452.25
7452.25
7452.25
7452.25
7455.29
7455.52
7456.06
7456.84
7457.66
7458.32
7459.04
7454.07
7454.32
7454.73
7455.36
7456.09
7456.62
7457.23
7455.41
7455.69
7456.31
7457.25
7458.28
7459.05
7459.90
0.002384
0.002389
0.002705
0.002985
0.003070
0.003056
0.003031
0.002520
0.002509
0.002945
0.003272
0.003347
0.003279
0.003228
2.68
3.33
4.07
5.16
6.32
6.91
7.52
354.26
390.40
479.14
612.19
771.59
905.16
1055.79
159.97
162.41
166.53
179.33
200.50
205.92
211.81
0.32
0.38
0.42
0.48
0.53
0.54
0.55
2.20
2.39
2.86
3.59
4.40
5.06
5.77
0.88
1.19
1.96
3.45
5.33
6.67
8.21
0.33
0.36
0.48
0.67
0.84
0.96
1.09
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
2975.24
2975.24
2975.24
2975.24
2975.24
2975.24
2975.24
2975.24
2975.24
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7452.12
7452.12
7452.12
7452.12
7452.12
7452.12
7452.12
7452.12
7452.12
7453.77
7454.00
7454.43
7454.93
7455.15
7455.61
7456.32
7457.11
7457.78
7452.94
7453.06
7453.35
7453.78
7454.04
7454.46
7455.11
7455.84
7456.38
7453.79
7454.02
7454.49
7455.05
7455.34
7455.90
7456.79
7457.80
7458.59
0.001718
0.001878
0.002272
0.002668
0.002638
0.003220
0.003602
0.003663
0.003527
0.005130
0.005585
0.006109
0.006071
0.005689
0.005504
0.004802
0.004032
0.003596
1.05
1.28
1.82
2.77
3.43
4.30
5.50
6.70
7.25
161.26
195.95
263.60
342.77
378.47
454.09
583.14
737.90
874.03
150.96
153.06
156.56
160.57
162.19
168.18
192.36
200.13
205.10
0.18
0.20
0.25
0.33
0.40
0.46
0.52
0.57
0.58
1.07
1.28
1.68
2.13
2.33
2.72
3.42
4.21
4.88
0.12
0.19
0.43
0.98
1.32
2.35
4.23
6.45
7.79
0.11
0.15
0.24
0.35
0.38
0.55
0.77
0.96
1.07
Kemp-Breeze SWA
2975.24
50 Year
7500.00
7452.12
7458.50
7456.92
7459.44
0.003444
0.003322
7.86
1028.04
246.50
0.58
5.60
9.46
1.20
C - 32
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
2828.29
Baseflow
170.00
7452.02
7452.83
250.00
480.00
7452.02
7452.02
7452.92
7453.23
Crit W.S.
(ft)
7452.83
E.G. Elev
(ft)
7453.02
E.G. Slope
(ft/ft)
0.069314
Frctn Slope
(ft/ft)
0.008085
Vel Chnl
(ft/s)
3.45
Flow Area
(sq ft)
49.32
Top Width
(ft)
125.14
7452.92
7453.23
7453.18
7453.56
0.073527
0.047045
0.008677
0.008892
4.08
4.59
61.24
104.67
130.99
151.29
Froude # Chl
0.97
Hydr Radius C
(ft)
0.39
Power Chan
(lb/ft s)
5.88
Shear Chan
(lb/sq ft)
1.71
1.05
0.97
0.47
0.69
8.76
9.32
2.15
2.03
Kemp-Breeze SWA
Kemp-Breeze SWA
2828.29
2828.29
LOC Spawn
RBT Spawn
Kemp-Breeze SWA
2828.29
May Avg
950.00
7452.02
7453.70
7453.64
7454.13
0.025139
0.007889
5.28
179.96
172.88
0.91
1.04
8.62
1.63
Kemp-Breeze SWA
Kemp-Breeze SWA
2828.29
2828.29
1.5 Year
2 Year
1300.00
1950.00
7452.02
7452.02
7453.88
7454.48
7453.88
7454.25
7454.46
7455.06
0.020131
0.011479
0.007296
0.005787
6.12
6.11
212.45
321.33
177.09
186.40
0.98
0.81
1.20
1.78
9.27
7.79
1.51
1.27
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
2828.29
2828.29
2828.29
5 Year
10 Year
25 Year
3150.00
4750.00
6000.00
7452.02
7452.02
7452.02
7455.45
7456.51
7457.30
7454.86
7455.55
7456.01
7456.07
7457.21
7458.04
0.006719
0.004461
0.003667
0.004694
0.004037
0.003747
6.33
6.76
6.97
509.94
736.14
927.84
204.23
223.65
253.30
0.68
0.62
0.58
2.65
3.68
4.47
7.04
6.93
7.13
1.11
1.02
1.02
Kemp-Breeze SWA
2828.29
50 Year
7500.00
7452.02
7458.11
7456.52
7458.91
0.003206
0.003546
7.29
1145.52
313.49
0.56
5.28
7.70
1.06
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
2678.11
2678.11
2678.11
2678.11
2678.11
2678.11
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
7448.49
7448.49
7448.49
7448.49
7448.49
7448.49
7450.80
7451.16
7451.87
7452.67
7452.95
7453.73
7449.81
7450.01
7450.47
7451.25
7451.68
7452.40
7450.85
7451.22
7451.98
7452.88
7453.25
7454.14
0.002939
0.003162
0.003629
0.003805
0.003733
0.003478
0.001207
0.001449
0.001873
0.002231
0.002308
0.002540
1.71
2.02
2.64
3.62
4.45
5.13
99.28
124.06
181.93
262.55
291.96
381.76
66.81
71.77
87.55
107.06
109.39
119.53
0.25
0.27
0.32
0.41
0.48
0.49
1.48
1.72
2.06
2.43
2.65
3.35
0.46
0.68
1.23
2.09
2.75
3.74
0.27
0.34
0.47
0.58
0.62
0.73
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
2678.11
2678.11
2678.11
2678.11
5 Year
10 Year
25 Year
50 Year
3150.00
4750.00
6000.00
7500.00
7448.49
7448.49
7448.49
7448.49
7454.74
7455.66
7456.33
7457.03
7453.27
7454.24
7454.95
7455.71
7455.36
7456.58
7457.44
7458.33
0.003464
0.003670
0.003829
0.003943
0.002818
0.003196
0.003452
0.003675
6.33
7.78
8.60
9.40
528.46
695.59
845.39
1036.92
167.76
201.89
258.22
274.90
0.53
0.60
0.62
0.64
4.36
5.26
5.93
6.63
5.97
9.39
12.19
15.34
0.94
1.21
1.42
1.63
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
2585.59
2585.59
2585.59
Baseflow
LOC Spawn
RBT Spawn
170.00
250.00
480.00
7447.42
7447.42
7447.42
7450.71
7451.05
7451.74
7448.88
7449.09
7449.53
7450.72
7451.08
7451.79
0.000653
0.000828
0.001141
0.000650
0.000833
0.001183
1.00
1.25
1.84
170.72
200.06
260.41
83.69
86.52
89.62
0.12
0.14
0.19
2.02
2.29
2.87
0.08
0.15
0.38
0.08
0.12
0.20
Kemp-Breeze SWA
Kemp-Breeze SWA
2585.59
2585.59
May Avg
1.5 Year
950.00
1300.00
7447.42
7447.42
7452.52
7452.80
7450.23
7450.64
7452.65
7453.01
0.001464
0.001567
0.001514
0.001633
2.86
3.63
331.88
358.62
93.25
94.62
0.27
0.33
3.50
3.73
0.92
1.32
0.32
0.36
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
2585.59
2585.59
2585.59
2585.59
2585.59
2 Year
5 Year
10 Year
25 Year
50 Year
1950.00
3150.00
4750.00
6000.00
7500.00
7447.42
7447.42
7447.42
7447.42
7447.42
7453.56
7454.54
7455.41
7456.04
7456.70
7451.28
7452.25
7453.34
7454.22
7455.04
7453.88
7455.07
7456.26
7457.10
7457.99
0.001936
0.002337
0.002809
0.003129
0.003433
0.002017
0.002429
0.002776
0.003018
0.003230
4.51
5.88
7.50
8.45
9.41
435.28
576.75
728.09
880.92
1053.17
115.56
158.18
215.67
254.03
276.74
0.38
0.45
0.53
0.57
0.61
4.29
5.24
6.09
6.71
7.36
2.34
4.49
8.01
11.07
14.84
0.52
0.76
1.07
1.31
1.58
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
2462.48
2462.48
2462.48
2462.48
2462.48
2462.48
2462.48
2462.48
2462.48
2462.48
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7447.64
7447.64
7447.64
7447.64
7447.64
7447.64
7447.64
7447.64
7447.64
7447.64
7450.63
7450.95
7451.59
7452.34
7452.61
7453.33
7454.29
7455.18
7455.82
7456.51
7448.70
7448.90
7449.44
7450.14
7450.54
7451.18
7452.13
7453.28
7453.96
7454.80
7450.64
7450.97
7451.64
7452.46
7452.80
7453.62
7454.76
7455.88
7456.67
7457.51
0.000647
0.000839
0.001228
0.001567
0.001704
0.002104
0.002527
0.002744
0.002914
0.003046
0.000462
0.000629
0.000982
0.001339
0.001452
0.001792
0.002168
0.002450
0.002670
0.002778
0.98
1.23
1.83
2.82
3.56
4.36
5.53
6.83
7.59
8.33
173.92
202.45
262.50
337.08
368.19
462.63
629.34
833.18
1003.10
1213.69
87.32
90.31
97.18
108.78
118.20
146.80
216.87
245.37
282.84
333.92
0.12
0.15
0.20
0.27
0.34
0.39
0.46
0.52
0.54
0.56
1.98
2.23
2.68
3.25
3.40
3.83
4.51
5.39
6.02
6.70
0.08
0.14
0.38
0.90
1.29
2.19
3.94
6.30
8.31
10.61
0.08
0.12
0.21
0.32
0.36
0.50
0.71
0.92
1.10
1.27
Kemp-Breeze SWA
Kemp-Breeze SWA
2257.16
2257.16
Baseflow
LOC Spawn
170.00
250.00
7446.37
7446.37
7450.54
7450.83
7448.16
7448.40
7450.55
7450.84
0.000346
0.000490
0.000729
0.000957
0.77
1.01
219.60
247.86
96.91
98.92
0.09
0.11
2.23
2.46
0.04
0.08
0.05
0.08
C - 33
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
2257.16
RBT Spawn
480.00
7446.37
7451.40
Crit W.S.
(ft)
7448.91
E.G. Elev
(ft)
7451.44
E.G. Slope
(ft/ft)
0.000803
Frctn Slope
(ft/ft)
0.001394
Vel Chnl
(ft/s)
1.57
Flow Area
(sq ft)
305.32
Top Width
(ft)
101.61
0.16
Hydr Radius C
(ft)
2.94
Kemp-Breeze SWA
Kemp-Breeze SWA
2257.16
2257.16
May Avg
1.5 Year
950.00
1300.00
7446.37
7446.37
7452.08
7452.34
7449.67
7450.02
7452.18
7452.50
0.001158
0.001252
0.001850
0.001961
2.52
3.20
380.67
413.36
119.86
134.46
0.24
0.29
3.45
3.66
0.63
0.92
0.25
0.29
Kemp-Breeze SWA
2257.16
2 Year
1950.00
7446.37
7452.99
7450.61
7453.24
0.001545
0.002295
4.02
509.03
154.67
0.34
4.26
1.65
0.41
Kemp-Breeze SWA
Kemp-Breeze SWA
2257.16
2257.16
5 Year
10 Year
3150.00
4750.00
7446.37
7446.37
7453.89
7454.73
7451.51
7452.69
7454.29
7455.35
0.001881
0.002201
0.002604
0.002755
5.21
6.54
665.87
850.27
201.22
227.67
0.40
0.47
5.14
5.96
3.14
5.35
0.60
0.82
Kemp-Breeze SWA
Kemp-Breeze SWA
2257.16
2257.16
25 Year
50 Year
6000.00
7500.00
7446.37
7446.37
7455.34
7456.03
7453.35
7454.06
7456.10
7456.90
0.002455
0.002545
0.002839
0.002802
7.36
8.00
997.70
1202.18
262.80
311.97
0.50
0.52
6.54
7.22
7.38
9.17
1.00
1.15
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
2085.09
2085.09
2085.09
2085.09
2085.09
2085.09
2085.09
2085.09
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
7448.54
7448.54
7448.54
7448.54
7448.54
7448.54
7448.54
7448.54
7450.39
7450.64
7451.12
7451.69
7451.89
7452.47
7453.30
7454.17
7449.53
7449.73
7450.06
7450.56
7450.84
7451.30
7452.12
7453.05
7450.42
7450.68
7451.19
7451.85
7452.15
7452.83
7453.83
7454.87
0.002424
0.002638
0.002995
0.003415
0.003504
0.003761
0.003840
0.003548
0.002890
0.003016
0.003377
0.003764
0.003840
0.004087
0.004214
0.004038
1.29
1.55
2.17
3.23
4.05
4.88
5.97
6.95
132.24
161.80
221.48
293.88
321.55
410.27
571.32
784.81
118.97
122.30
124.44
132.10
138.91
165.64
235.09
248.51
0.21
0.24
0.29
0.38
0.46
0.50
0.55
0.57
1.11
1.32
1.77
2.23
2.41
2.93
3.69
4.56
0.22
0.34
0.72
1.54
2.13
3.35
5.28
7.02
0.17
0.22
0.33
0.47
0.53
0.69
0.88
1.01
Kemp-Breeze SWA
Kemp-Breeze SWA
2085.09
2085.09
25 Year
50 Year
6000.00
7500.00
7448.54
7448.54
7454.85
7455.59
7453.71
7454.25
7455.62
7456.42
0.003322
0.003101
0.003853
0.003650
7.37
7.78
955.25
1163.57
258.91
305.07
0.57
0.56
5.23
5.96
8.00
8.98
1.08
1.15
Kemp-Breeze SWA
Kemp-Breeze SWA
1930.53
1930.53
Baseflow
LOC Spawn
170.00
250.00
7448.00
7448.00
7449.94
7450.17
7449.21
7449.38
7449.97
7450.21
0.003505
0.003480
0.004655
0.004657
1.36
1.60
124.73
156.46
135.48
138.40
0.25
0.26
0.92
1.13
0.27
0.39
0.20
0.25
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
1930.53
1930.53
1930.53
RBT Spawn
May Avg
1.5 Year
480.00
950.00
1300.00
7448.00
7448.00
7448.00
7450.59
7451.10
7451.29
7449.75
7450.17
7450.44
7450.67
7451.27
7451.55
0.003838
0.004169
0.004226
0.004880
0.004930
0.004919
2.23
3.30
4.13
215.61
287.61
315.04
140.14
144.46
145.69
0.32
0.41
0.49
1.53
1.98
2.15
0.82
1.70
2.34
0.37
0.52
0.57
Kemp-Breeze SWA
Kemp-Breeze SWA
1930.53
1930.53
2 Year
5 Year
1950.00
3150.00
7448.00
7448.00
7451.82
7452.58
7450.90
7451.60
7452.20
7453.18
0.004457
0.004646
0.004877
0.004818
4.97
6.23
392.47
525.92
150.26
197.53
0.54
0.59
2.65
3.41
3.67
6.16
0.74
0.99
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
1930.53
1930.53
1930.53
10 Year
25 Year
50 Year
4750.00
6000.00
7500.00
7448.00
7448.00
7448.00
7453.37
7454.00
7454.69
7452.41
7452.95
7453.59
7454.23
7455.00
7455.82
0.004636
0.004521
0.004357
0.004701
0.004558
0.004398
7.52
8.15
8.74
689.56
829.29
993.66
215.18
229.18
244.62
0.65
0.65
0.65
4.20
4.82
5.51
9.14
11.09
13.11
1.22
1.36
1.50
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
1790.19
1790.19
1790.19
1790.19
1790.19
1790.19
1790.19
1790.19
1790.19
1790.19
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7447.64
7447.64
7447.64
7447.64
7447.64
7447.64
7447.64
7447.64
7447.64
7447.64
7449.28
7449.50
7449.89
7450.38
7450.56
7451.11
7451.91
7452.73
7453.37
7454.07
7448.62
7448.83
7449.23
7449.69
7449.96
7450.35
7451.00
7451.76
7452.27
7452.86
7449.32
7449.56
7449.99
7450.58
7450.86
7451.51
7452.50
7453.57
7454.35
7455.21
0.006480
0.006549
0.006412
0.005919
0.005798
0.005359
0.005001
0.004767
0.004595
0.004439
0.006229
0.006136
0.005567
0.005083
0.004969
0.004679
0.004466
0.004343
0.004251
0.004186
1.68
1.88
2.51
3.55
4.39
5.08
6.14
7.36
7.98
8.61
101.19
132.82
191.48
267.46
295.87
384.46
516.36
656.17
771.37
911.24
127.16
147.43
152.98
156.66
157.85
162.20
168.34
175.25
183.12
217.73
0.33
0.35
0.40
0.48
0.57
0.58
0.61
0.65
0.65
0.66
0.79
0.90
1.25
1.70
1.86
2.38
3.16
3.97
4.61
5.31
0.54
0.69
1.25
2.23
2.96
4.05
6.07
8.70
10.55
12.66
0.32
0.37
0.50
0.63
0.67
0.80
0.99
1.18
1.32
1.47
Kemp-Breeze SWA
Kemp-Breeze SWA
1676.02
1676.02
Baseflow
LOC Spawn
170.00
250.00
7447.15
7447.15
7448.56
7448.80
7448.11
7448.24
7448.60
7448.85
0.005992
0.005761
0.003779
0.003803
1.62
1.82
105.06
137.62
131.82
146.49
0.32
0.33
0.79
0.94
0.48
0.61
0.30
0.34
Kemp-Breeze SWA
Kemp-Breeze SWA
1676.02
1676.02
RBT Spawn
May Avg
480.00
950.00
7447.15
7447.15
7449.26
7449.81
7448.49
7448.96
7449.35
7449.98
0.004879
0.004413
0.003701
0.003615
2.34
3.30
205.31
287.86
148.38
150.96
0.35
0.42
1.38
1.90
0.98
1.72
0.42
0.52
C - 34
Froude # Chl
Power Chan
(lb/ft s)
0.23
Shear Chan
(lb/sq ft)
0.15
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
1676.02
1.5 Year
1300.00
7447.15
7450.02
Crit W.S.
(ft)
7449.22
E.G. Elev
(ft)
7450.28
E.G. Slope
(ft/ft)
0.004305
Frctn Slope
(ft/ft)
0.003574
Vel Chnl
(ft/s)
4.08
Flow Area
(sq ft)
318.96
Top Width
(ft)
152.26
0.50
Hydr Radius C
(ft)
2.08
Kemp-Breeze SWA
Kemp-Breeze SWA
1676.02
1676.02
2 Year
5 Year
1950.00
3150.00
7447.15
7447.15
7450.61
7451.44
7449.65
7450.32
7450.96
7451.97
0.004120
0.004012
0.003571
0.003537
4.75
5.83
410.98
548.44
161.32
169.94
0.51
0.55
2.63
3.45
3.21
5.04
0.68
0.86
Kemp-Breeze SWA
1676.02
10 Year
4750.00
7447.15
7452.28
7451.08
7453.05
0.003973
0.003548
7.06
693.59
176.34
0.60
4.28
7.50
1.06
Kemp-Breeze SWA
Kemp-Breeze SWA
1676.02
1676.02
25 Year
50 Year
6000.00
7500.00
7447.15
7447.15
7452.93
7453.62
7451.60
7452.18
7453.85
7454.72
0.003944
0.003955
0.003553
0.003595
7.72
8.44
810.02
941.73
183.39
195.95
0.61
0.63
4.93
5.62
9.37
11.70
1.21
1.39
Kemp-Breeze SWA
Kemp-Breeze SWA
1526.02
1526.02
Baseflow
LOC Spawn
170.00
250.00
7446.52
7446.52
7448.01
7448.25
7447.34
7447.44
7448.03
7448.28
0.002599
0.002696
0.003027
0.003050
1.24
1.47
136.95
169.73
136.88
140.21
0.22
0.24
1.00
1.21
0.20
0.30
0.16
0.20
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
1526.02
1526.02
1526.02
1526.02
1526.02
1526.02
1526.02
1526.02
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7446.52
7446.52
7446.52
7446.52
7446.52
7446.52
7446.52
7446.52
7448.72
7449.30
7449.52
7450.12
7450.97
7451.82
7452.48
7453.18
7447.72
7448.17
7448.44
7448.89
7449.58
7450.30
7450.85
7451.42
7448.78
7449.43
7449.73
7450.41
7451.41
7452.48
7453.28
7454.14
0.002904
0.003015
0.003014
0.003125
0.003142
0.003188
0.003218
0.003281
0.003102
0.003145
0.003163
0.003171
0.003154
0.003186
0.003206
0.003271
2.02
2.95
3.65
4.32
5.36
6.53
7.19
7.90
237.27
322.52
356.63
451.80
592.15
739.72
857.62
989.17
144.69
151.22
154.57
161.92
169.23
176.22
182.25
238.69
0.28
0.36
0.42
0.45
0.49
0.54
0.56
0.57
1.64
2.13
2.30
2.80
3.65
4.50
5.16
5.85
0.60
1.18
1.58
2.36
3.83
5.85
7.45
9.46
0.30
0.40
0.43
0.55
0.72
0.90
1.04
1.20
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
1374.45
1374.45
1374.45
1374.45
Baseflow
LOC Spawn
RBT Spawn
May Avg
170.00
250.00
480.00
950.00
7445.99
7445.99
7445.99
7445.99
7447.55
7447.77
7448.25
7448.82
7447.57
7447.81
7448.31
7448.96
0.003571
0.003477
0.003322
0.003284
0.002825
0.002836
0.002845
0.002897
1.33
1.56
2.08
2.99
127.35
160.59
231.22
317.77
144.82
147.72
149.90
155.15
0.25
0.26
0.29
0.37
0.88
1.09
1.54
2.04
0.26
0.37
0.66
1.25
0.20
0.24
0.32
0.42
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
1374.45
1374.45
1374.45
1.5 Year
2 Year
5 Year
1300.00
1950.00
3150.00
7445.99
7445.99
7445.99
7449.03
7449.64
7450.49
7449.25
7449.93
7450.93
0.003324
0.003217
0.003167
0.002917
0.002902
0.002937
3.69
4.33
5.34
352.19
451.49
598.05
161.33
167.62
176.22
0.44
0.46
0.49
2.18
2.76
3.61
1.67
2.40
3.81
0.45
0.55
0.71
Kemp-Breeze SWA
Kemp-Breeze SWA
1374.45
1374.45
10 Year
25 Year
4750.00
6000.00
7445.99
7445.99
7451.35
7452.01
7452.00
7452.79
0.003184
0.003194
0.003013
0.003058
6.49
7.12
752.25
875.81
184.35
191.55
0.54
0.55
4.46
5.11
5.75
7.26
0.89
1.02
Kemp-Breeze SWA
1374.45
50 Year
7500.00
7445.99
7452.69
7453.63
0.003260
0.003107
7.82
1012.26
234.05
0.57
5.80
9.23
1.18
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
1227.60
1227.60
1227.60
1227.60
1227.60
1227.60
1227.60
1227.60
1227.60
1227.60
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7445.90
7445.90
7445.90
7445.90
7445.90
7445.90
7445.90
7445.90
7445.90
7445.90
7447.13
7447.36
7447.84
7448.41
7448.63
7449.23
7450.09
7450.93
7451.58
7452.28
7447.15
7447.39
7447.90
7448.53
7448.81
7449.49
7450.49
7451.54
7452.33
7453.16
0.002291
0.002357
0.002463
0.002575
0.002581
0.002632
0.002730
0.002856
0.002931
0.002965
0.002938
1.15
148.01
151.00
0.002944
0.002995
0.003068
0.003074
0.003074
0.003042
0.002969
0.002872
0.002793
1.37
1.88
2.76
3.43
4.09
5.12
6.30
6.96
7.60
182.63
255.85
344.10
379.12
478.09
623.72
772.65
890.46
1063.59
151.98
154.05
157.48
159.86
166.76
174.24
178.48
196.16
274.04
0.20
0.22
0.26
0.33
0.39
0.42
0.46
0.51
0.53
0.55
0.98
1.20
1.65
2.17
2.36
2.94
3.79
4.63
5.27
5.97
0.16
0.24
0.48
0.96
1.30
1.97
3.30
5.19
6.72
8.40
0.14
0.18
0.25
0.35
0.38
0.48
0.65
0.82
0.96
1.10
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
1066.52
1066.52
1066.52
1066.52
Baseflow
LOC Spawn
RBT Spawn
May Avg
170.00
250.00
480.00
950.00
7445.34
7445.34
7445.34
7445.34
7446.65
7446.88
7447.34
7447.88
7446.68
7446.92
7447.41
7448.03
0.003906
0.003780
0.003718
0.003717
0.003229
0.003272
0.003388
0.003449
1.39
1.62
2.17
3.14
122.58
154.51
222.12
305.39
140.84
142.85
150.83
157.85
0.26
0.27
0.31
0.39
0.87
1.08
1.51
2.00
0.29
0.41
0.76
1.46
0.21
0.25
0.35
0.46
Kemp-Breeze SWA
Kemp-Breeze SWA
1066.52
1066.52
1.5 Year
2 Year
1300.00
1950.00
7445.34
7445.34
7448.07
7448.67
7448.31
7448.99
0.003724
0.003639
0.003444
0.003391
3.91
4.59
336.78
439.72
160.39
193.17
0.47
0.49
2.18
2.74
1.98
2.86
0.51
0.62
C - 35
Froude # Chl
Power Chan
(lb/ft s)
2.28
Shear Chan
(lb/sq ft)
0.56
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
1066.52
5 Year
3150.00
7445.34
7449.53
Crit W.S.
(ft)
E.G. Elev
(ft)
7450.00
E.G. Slope
(ft/ft)
0.003411
Frctn Slope
(ft/ft)
0.003277
Vel Chnl
(ft/s)
5.54
Flow Area
(sq ft)
624.77
Top Width
(ft)
230.64
0.51
Hydr Radius C
(ft)
3.60
Kemp-Breeze SWA
Kemp-Breeze SWA
1066.52
1066.52
10 Year
25 Year
4750.00
6000.00
7445.34
7445.34
7450.45
7451.18
7451.07
7451.84
0.003088
0.002816
0.003135
0.002982
6.45
6.80
852.65
1047.39
264.53
272.15
0.53
0.52
4.52
5.24
5.62
6.27
0.87
0.92
Kemp-Breeze SWA
1066.52
50 Year
7500.00
7445.34
7451.94
7452.67
0.002636
0.002810
7.20
1257.46
280.60
0.52
6.00
7.11
0.99
Kemp-Breeze SWA
912.41
Baseflow
170.00
7444.96
7446.16
7446.18
0.002714
0.003733
1.23
138.16
144.59
0.22
0.95
0.20
0.16
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
912.41
912.41
912.41
LOC Spawn
RBT Spawn
May Avg
250.00
480.00
950.00
7444.96
7444.96
7444.96
7446.38
7446.82
7447.36
7446.41
7446.89
7447.50
0.002860
0.003100
0.003209
0.003799
0.003773
0.003577
1.47
2.03
3.00
169.91
236.21
317.51
146.98
150.25
155.34
0.24
0.29
0.37
1.15
1.57
2.08
0.30
0.62
1.25
0.21
0.30
0.42
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
912.41
912.41
912.41
912.41
912.41
912.41
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7444.96
7444.96
7444.96
7444.96
7444.96
7444.96
7447.56
7448.16
7449.03
7449.90
7450.57
7451.33
7447.78
7448.46
7449.49
7450.58
7451.37
7452.22
0.003194
0.003168
0.003151
0.003182
0.003163
0.003001
0.003489
0.003336
0.003164
0.003045
0.002906
0.002636
3.73
4.43
5.46
6.64
7.25
7.72
349.37
447.14
601.67
775.37
942.40
1182.09
158.30
168.50
186.34
223.21
278.75
341.62
0.44
0.46
0.50
0.54
0.55
0.55
2.28
2.88
3.75
4.62
5.29
6.05
1.70
2.53
4.03
6.10
7.57
8.75
0.46
0.57
0.74
0.92
1.04
1.13
Kemp-Breeze SWA
711.00
Baseflow
170.00
7443.95
7445.39
7445.43
0.005455
0.006039
1.51
112.54
146.17
0.30
0.77
0.40
0.26
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
711.00
711.00
711.00
711.00
711.00
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
250.00
480.00
950.00
1300.00
1950.00
7443.95
7443.95
7443.95
7443.95
7443.95
7445.60
7446.05
7446.62
7446.84
7447.49
7445.64
7446.13
7446.78
7447.07
7447.79
0.005290
0.004693
0.004011
0.003827
0.003517
0.005340
0.004344
0.003769
0.003644
0.003451
1.75
2.27
3.14
3.86
4.40
142.54
211.63
302.29
337.10
442.84
150.32
155.94
159.25
160.48
166.82
0.32
0.34
0.40
0.47
0.48
0.95
1.36
1.89
2.09
2.64
0.55
0.90
1.49
1.93
2.55
0.31
0.40
0.47
0.50
0.58
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
711.00
711.00
711.00
5 Year
10 Year
25 Year
3150.00
4750.00
6000.00
7443.95
7443.95
7443.95
7448.42
7449.35
7450.09
7448.84
7449.94
7450.74
0.003178
0.002916
0.002679
0.003276
0.003114
0.002955
5.24
6.18
6.56
608.03
810.57
1013.81
191.23
245.81
311.84
0.49
0.52
0.51
3.50
4.43
5.16
3.64
4.98
5.67
0.69
0.81
0.86
Kemp-Breeze SWA
711.00
50 Year
7500.00
7443.95
7450.95
7451.62
0.002333
0.002710
6.78
1325.34
427.53
0.49
6.02
5.95
0.88
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
570.23
570.23
570.23
570.23
570.23
570.23
570.23
570.23
570.23
570.23
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
5 Year
10 Year
25 Year
50 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
3150.00
4750.00
6000.00
7500.00
7443.21
7443.21
7443.21
7443.21
7443.21
7443.21
7443.21
7443.21
7443.21
7443.21
7444.53
7444.83
7445.43
7446.08
7446.31
7446.96
7447.86
7448.76
7449.46
7450.24
7444.58
7444.89
7445.52
7446.24
7446.56
7447.30
7448.37
7449.48
7450.30
7451.21
0.006722
0.005390
0.004032
0.003548
0.003473
0.003387
0.003379
0.003333
0.003276
0.003185
0.001674
0.001801
0.001982
0.002220
0.002294
0.002509
0.002782
0.003001
0.003146
0.003271
1.80
1.92
2.32
3.23
4.00
4.69
5.77
6.93
7.53
8.11
94.55
129.98
206.85
295.42
328.02
424.81
584.07
767.81
919.34
1102.12
110.56
120.98
131.28
143.88
145.14
157.92
197.98
211.27
222.52
247.76
0.34
0.33
0.33
0.39
0.46
0.48
0.52
0.56
0.57
0.57
0.85
1.07
1.57
2.16
2.38
2.99
3.86
4.75
5.45
6.23
0.64
0.69
0.92
1.55
2.07
2.96
4.70
6.86
8.39
10.05
0.36
0.36
0.40
0.48
0.52
0.63
0.81
0.99
1.11
1.24
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
397.22
397.22
397.22
397.22
397.22
397.22
Baseflow
LOC Spawn
RBT Spawn
May Avg
1.5 Year
2 Year
170.00
250.00
480.00
950.00
1300.00
1950.00
7441.96
7441.96
7441.96
7441.96
7441.96
7441.96
7444.26
7444.55
7445.12
7445.74
7445.97
7446.59
7444.28
7444.57
7445.16
7445.84
7446.13
7446.84
0.000743
0.000891
0.001175
0.001519
0.001628
0.001933
0.000663
0.000814
0.001108
0.001448
0.001548
0.001865
0.90
1.11
1.63
2.55
3.23
4.03
189.78
224.25
294.32
373.03
402.78
486.29
119.91
121.43
124.53
128.72
130.59
139.97
0.13
0.14
0.19
0.26
0.32
0.37
1.57
1.83
2.33
2.86
3.04
3.62
0.07
0.11
0.28
0.69
1.00
1.76
0.07
0.10
0.17
0.27
0.31
0.44
Kemp-Breeze SWA
Kemp-Breeze SWA
397.22
397.22
5 Year
10 Year
3150.00
4750.00
7441.96
7441.96
7447.44
7448.26
7447.87
7448.96
0.002330
0.002715
0.002284
0.002683
5.27
6.70
608.64
733.58
148.07
154.38
0.44
0.51
4.46
5.27
3.42
5.99
0.65
0.89
C - 36
Froude # Chl
Power Chan
(lb/ft s)
4.25
Shear Chan
(lb/sq ft)
0.77
�Appendix C
HEC-RAS Plan: Existing River: Colorado River Reach: Kemp-Breeze SWA (Continued)
Reach
River Sta
Profile
Q Total
Min Ch El
W.S. Elev
(cfs)
(ft)
(ft)
Kemp-Breeze SWA
397.22
25 Year
6000.00
7441.96
7448.86
7500.00
7441.96
Crit W.S.
(ft)
E.G. Elev
(ft)
7449.75
E.G. Slope
(ft/ft)
0.003024
Frctn Slope
(ft/ft)
0.003000
Vel Chnl
(ft/s)
7.59
Flow Area
(sq ft)
827.66
Top Width
(ft)
162.01
7449.49
7450.62
0.003361
0.003337
8.56
945.50
210.70
Froude # Chl
0.55
Hydr Radius C
(ft)
5.87
Power Chan
(lb/ft s)
8.41
Shear Chan
(lb/sq ft)
1.11
0.59
6.49
11.66
1.36
Kemp-Breeze SWA
397.22
50 Year
Kemp-Breeze SWA
262.59
Baseflow
170.00
7440.63
7444.18
7444.19
0.000595
0.001287
0.81
208.97
129.71
0.11
1.60
0.05
0.06
Kemp-Breeze SWA
Kemp-Breeze SWA
262.59
262.59
LOC Spawn
RBT Spawn
250.00
480.00
7440.63
7440.63
7444.44
7444.97
7444.46
7445.01
0.000747
0.001047
0.001519
0.001920
1.03
1.53
243.76
314.71
131.78
135.75
0.13
0.18
1.84
2.30
0.09
0.23
0.09
0.15
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
262.59
262.59
262.59
May Avg
1.5 Year
2 Year
950.00
1300.00
1950.00
7440.63
7440.63
7440.63
7445.55
7445.77
7446.35
7445.64
7445.92
7446.58
0.001382
0.001473
0.001801
0.002306
0.002404
0.002727
2.41
3.06
3.85
394.63
425.32
506.81
138.65
139.46
143.71
0.25
0.31
0.36
2.82
3.02
3.57
0.59
0.85
1.55
0.24
0.28
0.40
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
262.59
262.59
262.59
262.59
5 Year
10 Year
25 Year
50 Year
3150.00
4750.00
6000.00
7500.00
7440.63
7440.63
7440.63
7440.63
7447.15
7447.93
7448.49
7449.09
7447.55
7448.58
7449.33
7450.16
0.002238
0.002651
0.002976
0.003314
0.003107
0.003429
0.003657
0.003879
5.09
6.50
7.38
8.32
625.32
753.03
852.03
963.00
156.49
170.52
179.65
197.19
0.43
0.50
0.54
0.58
4.36
5.13
5.69
6.28
3.10
5.52
7.81
10.82
0.61
0.85
1.06
1.30
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7.86
7.86
7.86
Baseflow
LOC Spawn
RBT Spawn
170.00
250.00
480.00
7442.65
7442.65
7442.65
7443.83
7444.03
7444.45
7443.35
7443.46
7443.70
7443.86
7444.07
7444.52
0.004600
0.004605
0.004602
1.41
1.65
2.14
120.66
151.95
224.05
153.02
158.82
177.06
0.28
0.30
0.34
0.79
0.96
1.26
0.32
0.45
0.78
0.23
0.27
0.36
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
Kemp-Breeze SWA
7.86
7.86
7.86
7.86
7.86
May Avg
1.5 Year
2 Year
5 Year
10 Year
950.00
1300.00
1950.00
3150.00
4750.00
7442.65
7442.65
7442.65
7442.65
7442.65
7444.90
7445.07
7445.55
7446.25
7446.97
7444.11
7444.36
7444.73
7445.32
7445.98
7445.05
7445.30
7445.88
7446.75
7447.70
0.004601
0.004602
0.004606
0.004601
0.004605
3.10
3.87
4.58
5.67
6.89
306.25
336.14
425.66
559.71
704.52
182.38
183.06
185.15
197.82
207.57
0.42
0.50
0.53
0.58
0.63
1.67
1.83
2.29
2.99
3.70
1.49
2.03
3.02
4.86
7.32
0.48
0.53
0.66
0.86
1.06
Kemp-Breeze SWA
Kemp-Breeze SWA
7.86
7.86
25 Year
50 Year
6000.00
7500.00
7442.65
7442.65
7447.52
7448.12
7446.45
7446.95
7448.40
7449.16
0.004602
0.004602
7.55
8.24
822.02
951.27
214.61
216.51
0.64
0.66
4.25
4.84
9.21
11.47
1.22
1.39
C - 37
�Appendix D
Colorado River at Parshall
Fishery management report
Jon Ewert, Aquatic Biologist, Colorado Parks and Wildlife
March 2019
Introduction
300
Located approximately 10 miles east of Kremmling,
CO on US highway 40, this section of the Colorado River
offers approximately 4 miles of public access on the
Kemp-Breeze, Lone Buck, and Paul Gilbert State Wildlife
Areas (SWA), managed by Colorado Parks and Wildlife
(CPW), and the Bureau of Land Management’s (BLM)
Sunset property unit. This is one of the most well-known
and heavily fished trout rivers in the state. Despite heavy
angling pressure, trout populations here are generally excellent and this is a designated Gold Medal fishery.
Rainbow trout
Pounds per surface acre
250
Brown trout
200
4
264
100
187
158
131
50
Regulations
0
This section is under special regulations, restricted to
fishing with flies and lures only, and all trout must be returned to the water immediately.
11
3
150
1
6
111
108
5
117
9
10
126
122
12
15
134
134
154
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Figure 1. Brown and rainbow trout biomass estimates, ParshallSunset, 2007-2018.
35
8000
Stocking
7000
# fish >6" per mile
Whirling disease-resistant strains of rainbow trout
were stocked at various sizes through 2015 with the goal
of reestablishing a wild, self-sustaining rainbow trout population. Results of these efforts are discussed in more detail on pages 5-6.
Fishery surveys
Rainbow trout
6000
Brown trout
5000
4000
65
71
3410
3557 3833
306
152
4691
3936
3561
1000
0
114
153
3973
3976
205
127
103
3000
2000
The information in this report reflects trout population
data collected on the two-mile reach of river beginning
just upstream of the “Parshall Hole” and extending downstream through the Kemp-Breeze SWA to the irrigation
diversion on the BLM Sunset property. This survey is
conducted in the third or fourth week of September annually. Population estimates are obtained by raft electrofishing using standard mark-recapture methodology .
Figure 1 displays estimates for trout biomass in pounds
per surface acre over the 2-mile reach. From 2007-2011,
this estimate declined annually, and from 2011-2018 the
estimate has steadily increased. In all years this estimate
has generously exceeded the minimum Gold Medal criteria of at least 60 lbs./acre. During this period brown trout
have contributed an average of 95% of this estimate while
rainbows have contributed 5%.
Figure 2 displays trout population estimates in fish per
mile 6” or larger. The high brown trout estimate in 2007 is
the result of multiple large year classes of young brown
trout recruiting during the relatively low-water years leading up to that year (see Figure 5). It is common to see high
recruitment of juvenile brown trout during drought periods, simultaneous with declining numbers of large fish.
The increase in rainbow trout estimates beginning in 2012
reflects the introduction of Whirling Disease resistant
rainbows to this section of river (see discussion on page 56). During this time, brown trout have contributed an average of 97% of these estimates and rainbows have contributed 3%.
39
31
7708
4093
3917
2908
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Figure 2. Estimates of brown and rainbow trout fish per mile
larger than 6”, Parshall-Sunset, 2007-2018.
60
# fish > 14" per surface acre
2
Rainbow trout
Brown trout
1
5
40
3
4
6
1
52
44
20
4
19
0
3
2007
24
28
2009
3
39
31
26
17
2008
33
2010
2011
2012
15
13
2013
2014
2015
2016
2017
2018
Figure 3. Density estimates of quality-sized (>14”) brown and
rainbow trout per surface acre, Parshall-Sunset, 2007-2018.
Figure 3 displays density estimates of trout greater than
14” per surface acre, which is the second biological criteria for Gold Medal designation, requiring a minimum of
12 trout per acre 14” or larger. In years such as 2013 and
2017, these estimates have come close to slipping below
that standard.
Historic density estimates of quality trout from the
years 1981-2004, collected by Colorado Division of Wild1
�Appendix D
120
160
20
70
9
3
5
62
40
26
35
20
85
81
47 45
56
66 60
3
107
100
58
55
32
2003
2001
2002
1999
2000
1997
1998
1995
1996
1993
1994
1991
1992
1989
1990
1987
1988
1985
1986
1983
120
80
40
0
160
21 20
10 4 14 13
1984
1981
15
21
48
2004
75
10
Number of fish captured
80
0
10
7
1982
# fish > 35 cm per surface acre
7
Brown trout
60
2007
10
Rainbow trout
100
2008
120
Figure 4. Density estimates of brown and rainbow trout >35 CM
per surface acre, Parshall-Sunset, 1981-2004.
80
life research biologist Barry Nehring and colleagues, are
displayed in Figure 4. The parasite which causes whirling
disease was first introduced to the Colorado River during
this time, and its effects are evident in the decline of the
rainbow fishery and subsequent expansion of brown trout
densities. Regardless, in 15 of the 18 sampling occasions
during this period, quality trout estimates exceeded 50 fish
per acre, while this has occurred only once in the most
recent decade (Figure 3). This information suggests that
this fishery has undergone a long-term decline. All the
reasons for this are not known, but two of the most likely
culprits are a long-term degradation in the quality of invertebrate forage, long-term degradation in the quality of
physical habitat (particularly overwinter habitat), some
combination of those two factors, or an issue not yet
known.
Figures 5 and 6 (following page) display the size distributions for all brown trout captured in the Parshall-Sunset
reach in September from 2007-2018. The vertical axis on
all graphs is the same, enabling comparisons among years.
The vertical bars represent the number of fish that were
captured in each size class by centimeter (15 cm = 6”).
Viewing the data in this way reveals a wealth of useful
information including rough estimates of annual growth
and survival rates. Fish less than 15 cm are not effectively
captured during these surveys, so it is difficult to assess
the abundance of the age-0 year class (fish that were born
the year of the survey) from this data. However, the age-1
year class (born the year prior to the sample), in the 12-20
cm range, is represented more accurately.
When studying this survey data, a question sometimes
arises regarding movement of trout. The question is
whether or not the data represents the “true” resident population of fish, or whether the fish move so much that it is
more of a single snapshot in time of the trout that happen
to be occupying the reach on that day. There are a few
aspects of this data which at least partially answer that
question. First, the survey is conducted as close to the
same date as possible every year. If the results are heavily
influenced by fish movements, those movements should at
least be similar among years as long as the dates of the
survey are consistent. Anecdotally, many fish are collected each year that have small scars in the tail where they
were marked in previous years’ surveys, proving that
those fish occupy the same reach across multiple years.
40
0
Number of fish captured
160
2009
120
80
40
0
160
Age-1
(born 2009)
2010
Age-2
(born 2008)
120
80
Adult population
(born 2007 and before)
Age-0
(born 2010)
40
0
160
2011
120
80
40
0
Number of fish captured
160
2012
120
80
40
0
0
4
8
12
16
20 24 28 32 36
Length of fish in cm
40
44
48
52
Figure 5. Brown trout size distribution, 2007-2012.
2
56
�Number of fish captured
160
Appendix D
Also, the analysis below demonstrates that year class
strength is a strong predictor of the future adult population. If the population was heavily influenced by emigration or immigration, this would not necessarily be the
case. There are examples of other reaches of the Colorado
(such as the Radium survey reach) where the number of
juvenile fish has never explained the high density of adult
fish present, meaning that the reach “gains” fish from
elsewhere.
The strength of the age-1 year class in any given year
is of great interest because of its ability to predict trends in
the adult population in future years. Due to high mortality
rates in small fish, strong age-1 year classes are necessary
in order to maintain the adult population. We have seen an
oscillation in the abundance of age-1 fish that appears to
occur over 2– or 3-year cycles (Figure 7).
The result of weak age-1 recruitment in 2008 and 2009
can be seen in the weakening adult population in 2011 and
2012. That weakening of the adult population is evident
on page 2 in the biomass and quality trout estimates for
those years.
In 2012 the age-2 fish were poised to bolster the adult
population, which took place in 2013 and 2014. This also
appears in Figure 1 in the improving biomass estimates in
those years and the increase in quality trout in 2014.
2013 revealed another strong age-2 year class; however the age-1 group was weak in both 2013 and 2014.
The adult population in 2014 reflects the benefit of the
strong age-1 groups of 2011 and 2012. This is also evident
in the increased number of quality trout that we observed
in 2014. However, the weak recruitment years of 2013
and 2014 resulted in moderate decreases in the adult population in 2015 and 2016, which was ultimately manifested
in the lower quality fish estimate in 2016. Age-1 recruitment in 2015 and 2016 returned to strong levels, which
again bolstered the adult population in 2017 and 2018.
Age-0 capture in 2016 was low, resembling that of 2012
and 2013, which predicted a weak Age-1 year class in
2017.
Quality trout density estimates in 2017 were among the
lowest ever (Figure 3). However, the 2017 sample revealed a large, overlapping group of Age-2 and 3 fish
(peaking at 28 cm) resulting from the strong age-1 groups
in 2015 and 2016. These fish advanced in size in 2018,
which resulted in an improved quality trout estimate in
2018 and we anticipate this to continue with another increase in 2019. 2018 saw another weak age-1 group, and
Age-0 capture in 2018 was exceptionally weak. If this
manifests as a weak Age-1 group in 2019, this will be the
first time since 2007 that we have observed three consecutive weak Age-1 groups, which predicts poor estimates of
quality fish (>14”) in 2020, 2021, and 2022.
We have observed an oscillation in both the strength
of Age-1 year classes and density of quality trout (Figure
7). We do not have a strong understanding of factors that
produce strong or weak year classes in any given year on
this reach of the Colorado. In some rivers, above-average
runoff results in high mortality of brown trout, thus forming poor year classes, while drought years see high survival of age-0 fish due to the lack of intense flows. However,
we have seen counterexamples of that dynamic in the Col-
2013
120
80
40
0
160
2014
120
80
40
0
Number of fish captured
160
2015
120
80
40
0
160
2016
120
80
40
0
160
2017
120
80
40
0
Number of fish captured
160
2018
120
80
40
0
0
4
8
12
16
20 24 28 32 36
Length of fish in cm
40
44
48
52
56
Figure 6. Brown trout size distribution, 2013-2018.
3
�Appendix D
orado River in recent years. 2011 produced a peak runoff
period that was far above average, yet a strong year class
survived. Conversely, 2012 was a drought year that produced a weak age-1 group the following year. Intensity of
runoff probably plays a role in some years, but does not
appear to be the chief factor determining year class
strength on this reach.
Spawning habitat quality could act as a limiting factor
in the formation of year classes. However, if there was a
general lack of spawning habitat, there would be no reason for the variability in year class strength that we have
observed. All year classes would be equally poor.
In some winters, anchor ice, frazil ice, and various formations of ice damming are common on this reach of the
Colorado. It is possible that harsh winter conditions exacerbated by low flows lead to high mortality rates of brown
trout eggs that are incubating in the gravel, which would
result in poor year class formation. We do not currently
have a way to quantify those conditions, and the degree to
which they vary among winters. However, in-channel habitat improvements would address this issue by enhancing
the quality of spawning riffles as well as overwintering
habitat, making these areas less vulnerable to the harsh
winter conditions that can take place during periods of
cold weather and low flows.
It is difficult to determine exactly how the two patterns
of oscillation in Figure 7 are related. Under a recruitmentdriven hypothesis, strong juvenile year classes would predict peaks in large fish density by approximately two
years, as described above. However, a predation-driven
dynamic could also be at play, in which a higher density
of large fish actually limits the strength of juvenile yearclasses through predation pressure. The true determination
of these trajectories is most likely driven my a more complex interaction among these two factors as well as others,
such as water year type.
2
Age-1 fish
Departure from average
1.8
Quality trout
1.6
2016
1.2
0.8
0.6
0.4
2012
2010
1.4
1
Figure 8. The largest brown captured in 2014. 21”, 4.6 lbs.
2011
2015
2007
2014
2008
2009
2018
2017
2013
0.2
0
Figure 7. Oscillation in quality trout estimates (dashed line) and
number of juvenile (12-23 cm) brown trout handled annually.
Values for both parameters were standardized to the average for
the period, represented by the flat line.
Figure 9. This 15” brown trout had recently eaten a rodent.
4
�Appendix D
Status of wild rainbow trout
The Colorado River in Grand County historically supported one of the most productive wild rainbow trout fisheries in the world. In 1981, there were estimated to be 75
rainbow trout per acre over 14” (Figure 4). These fish
were all the product of wild reproduction and unsupported
by stocking. Brown trout comprised 25% of the trout population in the river that year. Whirling disease appeared in
the river in 1987 and the proliferation of this parasite ended virtually all successful reproduction of rainbow trout.
In the following years, the brown trout population exploded to fill the habitat that was vacated due to lack of reproduction in the rainbow population. It has always been the
goal of CPW to restore some level of a wild rainbow trout
fishery to this reach of the Colorado. Beginning in 1994,
CPW began stocking fingerling rainbow trout to attempt
to compensate for the lost natural reproduction. Research
has shown that rainbow trout mortality from whirling disease drops dramatically when the fish have reached a
length of 5”. Based on this information, that is the size of
fish that was stocked throughout the 2000’s. Due to the
timing of rainbow spawn in CPW hatcheries, fish of that
size were not available until the fall, usually October.
40,000 5” fish per year were stocked annually in October
in this reach of river.
Figure 10 demonstrates the failure of the stocking strategy described above. Even though 5” fish should be able
to survive in the presence of whirling disease, recruitment
rates from stocking these fingerlings was abysmal, and
rainbow trout continued to constitute a tiny fraction of the
total trout population of this reach.
In more recent years, CPW has developed strains of
rainbow trout that are highly resistant to whirling disease.
We first stocked this fish in this reach in 2008. In 2008
and 2009, the fish were stocked at 5” in October. We did
not observe any evidence that this strain was successful at
recruiting into the population when stocked at that size.
In 2010, we adopted a different stocking strategy based
on the hypothesis that the limitation on recruitment in the
5” plants was timing rather than WD infection. If this was
not the case we should have seen a positive response with
the introduction of the WD-resistant strain in 2008. We
stocked a larger number (60,000) of smaller (1.6 inches
average) fish during the third week of July. We stocked
these small fish out of a raft, only in the most ideal fry
habitat. At this small size the fish are not habituated to
Figure 11. This Parshall Hole rainbow had recently eaten a 10”
brown trout.
306
300
Fish >6" per mile
250
205
200
103
100
35
114
127
71
65
50
153
152
150
31
39
0
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Figure 12. The largest rainbow we captured in 2018, measuring
22”.
Figure 10. Estimates of rainbow trout >6” per mile, ParshallSunset 2007-2018.
5
�Appendix D
30
Number of fish captured
being fed yet, and hopefully develop wild behaviors that
are likely already lost in fish that have been raised to 5” in
a hatchery environment. After encouraging results in
2010, in 2011 and 2012 we continued this stocking strategy and increased the number of fry stocked to 100,000.
Our 2012 survey detected the recruitment of these fish
into the adult rainbow population for the first time (Figure
10). Subsequent surveys have not yielded estimates as
high as 2012, but they have remained above pre-2012 levels. We have documented successful natural reproduction
but it remains to be seen if it will be enough for the percentage of rainbows in the trout population to increase.
Figure 14 displays the size distribution of all the rainbow trout captured over the past six years in this reach. In
2010 we captured rainbow trout smaller than 6” for the
first time. These were the 2” fry that had been stocked two
months previously. By 2013 we observed the development
of a more robust adult population in the 12-16” range as a
result of the fry stocking.
In 2014 we found the most fully developed adult rainbow population to date. The density estimate for rainbows
larger than 14” was 5 fish per acre, which was the highest
estimate in the post-WD era, until 2016 yielded an estimate of 6 per acre. We also did not detect an age-1 year
class in 2014 for the first time since fry stocking began,
for unknown reasons. However, we did collect some age-0
(fry stocked in 2014) fish. 2015 and 2016 saw the return
of moderate age-1 groups.
Due to a disease issue in our hatchery system, 2015
was the last year that we stocked rainbow trout fry. This
was also an opportune time to cease stocking and evaluate
whether or not natural reproduction would sustain and/or
increase rainbow numbers. The 8” age-1 year class seen in
2016, the 12” Age-2 group in 2017, and the 13”-17” adult
group in 2018 represent the last stocked rainbow fry. The
7-9” group in 2017 and 2018 are wild fish, and through
fry monitoring we have observed some successful natural
reproduction. We are hopeful that this trend will continue,
although the numbers of juvenile fish we have observed in
the past two years do not appear to be adequate to sustain
the rainbow fishery. We will consider stocking rainbow
fry again, possibly beginning in 2020.
2013
20
10
0
30
2014
20
10
0
Number of fish captured
30
2015
20
10
0
30
2016
20
10
0
30
2017
20
10
0
Number of fish captured
30
2018
20
10
0
0
2
4
6
8
10
12
14
16
18
20
22
Length of fish in inches
Figure 14. Size distribution of rainbow trout captured on the
Parshall-Sunset reach 2013-2018.
Figure 13. Rainbow trout fry on the raft ready to be stocked.
6
24
�Appendix D
Mountain whitefish invasion
20
2014
In 2013, we collected four juvenile mountain whitefish
on this reach for the first time. This species had never been
captured on this reach of river in a history of biological
survey work that extends back to 1981. There are no
known historical records of mountain whitefish occurring
anywhere in Middle Park upstream of Gore Canyon. This
species is native to the White and Yampa river drainages
but not to the Colorado. There is an established population
in the Colorado downstream of Gore Canyon.
Figure 15 displays the size distribution of whitefish that
we have captured since 2014. That year, we captured two
juvenile whitefish. A year later we captured 22 whitefish
representing three age-classes, which corresponded to the
juveniles we had caught the two previous years. In 2016
our catch increased to 49 mountain whitefish representing
four year-classes and ranging up to 19” in length. We captured fewer in 2017, but still found at least three yearclasses. 2018 saw a large jump in the number that we captured, including the highest number of Age-0 (4-5”) fish
yet found.
In other surveys, we have also captured whitefish as far
upstream as Windy Gap dam. These findings suggest that
we are witnessing the beginning of a significant invasion
of the species into the upper Colorado. The reasons that
this is occurring now are unknown. 2011 saw the highest
flows on the Colorado River since the early 1980’s, and
our current theory is that the prolonged high flows during
that summer allowed adult whitefish to find their way
through Gore Canyon for the first time.
Impacts of mountain whitefish on the trout fishery are
unknown at this time. There are ways in which they might
benefit the fishery (for example, providing an additional
prey source for large, predatory brown trout), but they
may also present new competition with trout for food and
habitat. Catch-and-release regulations on this reach apply
to trout only, so these fish are available for angler harvest.
We will closely monitor this invasion over the coming
years and continually assess whether or not any management changes are warranted.
N=2
10
0
20
2015
N = 22
10
Number of fish captured
0
20
2016
N = 49
10
0
20
2017
N = 33
10
0
20
2018
N = 87
10
0
3
4
5
6
7
8 9 10 11 12 13 14 15 16 17 18 19 20
Length of fish in inches
Figure 15. Size distribution of mountain whitefish captured in
Parshall-Sunset reach, 2014-2018.
Figure 16. Mountain whitefish captured in the Parshall Hole.
7
�Appendix D
Spring 2013 & 2016 surveys of Paul Gilbert—Lone Buck reach
In spring of 2013 & 2016, we conducted a raft electrofishing
Colorado River, Paul Gilbert—Lone Buck
survey of the Colorado River beginning just downstream of the
2013
2016
Byers Canyon bridge and extending to the downstream border of
the Lone Buck State Wildlife Area. This encompassed a river reach
Date of survey
5/6 & 8
4/19 & 21
of approximately 7,000 feet in length. The main reason for this survey was to determine the number of spawning rainbow trout in this
Rainbows: #> 6”/mile
214
182
reach, which contains locations where rainbows regularly spawned
historically. This was the first time since 2013 that we had surveyed
#>14”/surface acre
5
6
this section. These are the only two occasions in recent history that
the reach has been surveyed in the spring.
Biomass (lbs./acre)
13
13
Results of the 2013 and 2016 surveys are contained in the table
1,537
1,178
at right. Rainbow estimates remained essentially the same across Browns: #> 6”/mile
the two occasions, while the number of large brown trout increased
#>14”/acre
11
28
dramatically. This resulted in a greatly increased estimate of brown
trout biomass. The size distribution of both species is shown in the
Biomass (lbs./acre)
74
132
graphs below.
In the 2016 survey, we also captured one mountain whitefish measuring 16”. At that time this was the farthestupstream location that we had captured a whitefish; however, the following month we captured two more whitefish upstream of the town of Hot Sulphur Springs, indicating that they are present in the river up to Windy Gap dam.
A Whirling Disease-resistant rainbow from the Lone Buck reach.
8
�Appendix D
Fry Habitat Recommendations for Maximizing Abundance and Numbers
Eric Fetherman and Brian Avila
As part of a project to determine if habitat covariates collected from 50 ft fry sites could be
useful for estimating fry abundance using a single pass and Bayesian statistics, habitat data were
collected from 20 in the Colorado River scattered throughout the Chimney Rock and Sheriff
ranches. Four of these sites were the historic fry sites at which a three pass removal estimate is
typically used to estimate fry abundance, located at the Sheriff Ranch, in the Red Barn area, and
at the Hitching Post Bridge. Abundance estimates were conducted at these sites in July (pre- and
post-fry stocking), August, September, and October. Additional sites in which only a single pass
was conducted were added at the Sheriff Ranch (four sites), Kinney Creek (four sites), Red Barn
area (five sites), and Hitching Post Bridge (three sites). Habitat covariate data collected included
temperature, depth, width (based on furthest distance from shore a fry was captured during the
estimate), flow, presence of wood, pebble counts (D50), and dissolved oxygen concentration
(August-September only). Additionally, backpack settings (voltage, amperage, and shocking
time) were recorded from each site to determine the effects of conductivity on detection
probability. Month in which sampling occurred was also considered potentially explanatory
because fry length and abundance change over time.
To obtain accurate estimates of fry abundance in the four sites in which a three pass removal was
conducted, abundance was estimated using Program MARK. Pass, fry length, flow, D50,
backpack settings, and whether or not the site had been stocked (Rainbow Trout only) were
included as covariates affecting detection probability. Brown Trout and Rainbow Trout
abundances were estimated separately. Model-averaged abundance estimates from the model
sets containing additive combinations of these covariates were then used to determine which
habitat covariates affected fry abundance in these sites. The number of fish caught on the first
pass from these sites, along with single pass data collected from the other 16 sites was used to
determine habitat effects on fry numbers.
Prior to conducting analyses, SAS Proc Corr was used to determine if any of the variables were
correlated and should not appear in analyses examining the effects of the habitat variables on
abundance or number per site. Width was highly correlated with fry length since fry generally
start to move towards the center of the river as they get larger. Because the remainder of the
habitat variables were collected over the entire width of the site (D50), or an average distance
from shore based on fry site width, it was determined that width was well represented in the
other habitat covariate values collected from each site, and width was removed from the
analyses. Month was highly correlated width and fry length. In addition, month was correlated
with temperature and dissolved oxygen for the sites in which three pass abundance estimates
were conducted, and temperature, dissolved oxygen, whether or not a site had been stocked
(Rainbow Trout only), and flow in the sites in which only a single pass was conducted. Because
the other variables with which month was correlated were thought to be more explanatory
individually than month (which included effects of several variables), month was also removed
from the analyses. Lastly, dissolved oxygen concentration was generally higher than 100%, and
greater than 6 ppm. As such, DO was not included as an explanatory covariate in the analyses
because it never dropped below levels considered optimal for trout.
D-9
�Appendix D
The remaining habitat covariates used in the analysis therefore included D50, presence of wood
(indicator variable; present or not), temperature, depth, flow, and whether or not the site had
been stocked (indicator variable; Rainbow Trout only). For the abundance analysis, presence of
wood was correlated with flow, temperature, and depth. The covariate wood was retained in the
analysis, but never appeared in the same model as the other three covariates. In the fry numbers
analysis, wood was correlated with flow, D50, and whether or not a site had been stocked, and
was similarly removed from models in which the other three covariates were present.
Additionally, flow, depth, and temperature were also correlated, and though retained in the set,
never appeared in the same model. Model sets were constructed using data from a general linear
model analysis conducted using SAS Proc GLM, and Brown Trout and Rainbow Trout model
sets were constructed separately. In addition to containing singular and additive combinations of
D50, presence of wood, temperature, depth, flow, and whether or not the site had been stocked,
within the confines described above from the correlation analysis, a quadratic relationship was
also included for D50, temperature, depth, and flow to determine if there were optimum versus
directional conditions for each of these variables across the fry sites. To minimize parameter
number within the model sets compared to the number of observations contributing to the data
being analyzed, only a single quadratic relationship appeared in any given model in the set (e.g.,
a model never included quadratic relationships for D50 and flow), however, the other variables
were included additively with the quadratic relationships (e.g., quadratic relationship for D50 +
flow).
Note: because the numbers analysis contained data from 20 fry sites on five occasions, it is
discussed as the primary analysis, with supplemental information included from the abundance
analysis, the data for which came from only four fry sites on five occasions.
Brown Trout Fry
A quadratic relationship for D50 appeared in the top four models of the Brown Trout numbers
analysis (w1 = 0.32, w2 = 0.29, w3 = 0.10, and w4 = 0.10) and had the highest cumulative weight
of any other variables included in the model set (cumulative AICc weight = 0.81). Temperature,
which had the next highest cumulative weight (0.35) appeared in the top model, but was not
included again until the seventh model of the set. Depth and flow, included in the third and
fourth model, respectively, appeared to have a lesser effect on Brown Trout fry numbers
(cumulative AICc weights: depth = 0.11, flow = 0.11).
The number of Brown Trout fry per site was maximized at a D50 of 151 mm. Brown Trout fry
number per site is greater than 10 per site (1,056 fry per mile) between a D50 of 96 and 206 mm.
There was a slight negative effect of depth in relation to Brown Trout fry number, and no effect
of flow on fry number. Because there was little measurable effect for these two variables, the fry
sites with a D50 between 96 and 206 mm, and contained greater than 10 Brown Trout fry per site
(n = 13), were examined for average depth and flow. Within sites with a D50 between 96 and
206 mm, numbers were greatest when depth averaged 0.18 (± 0.03) m and flow averaged 0.20 (±
0.09) m/s. Although the model set suggested an effect of temperature on Brown Trout number,
temperature and month were found to be highly correlated, and Brown Trout numbers were
reduced in later sampling months when temperatures were cooler, as is typical with trout fry, so
D - 10
�Appendix D
the effect of temperature is likely a result of the natural reduction in fry numbers between
emergence and the final sampling in October 2018.
30
R² = 0.2062
LOC Number
25
20
15
10
5
0
0
50
100
150
200
250
D50
30
R² = 0.0017
20
15
10
5
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Depth (m)
30
25
R² = 0.0002
LOC Number
LOC Number
25
20
15
10
5
0
0
0.1
0.2
0.3
0.4
Flow (m/s)
D - 11
0.5
0.6
0.7
�Appendix D
In the Brown Trout abundance model set, a quadratic relationship between abundance and D50
also appeared in the top model of the set (w1 = 0.89), as well as the third through sixth models in
the set, and had a cumulative weight of 0.90. The presence of wood in the site was the only
other variable to have an effect, appearing in the first two models of the set, and having a
cumulative weight of 0.99. Overall, the presence of wood, which was only in one site of the
four, reduced abundance. Abundance was highest at the site with a D50 of 120 mm, which falls
within the range of the optimum for Brown Trout fry numbers.
60
y = 0.4813x - 22.448
R² = 0.5483
LOC Abundance
50
40
30
Wood
20
No Wood
Linear (No Wood)
10
0
0
20
40
60
80
100
120
140
D50
Rainbow Trout Fry
Stocking had the largest effect on Rainbow Trout numbers (increased numbers in stocked sites),
appearing in all models with an AICc value less than 5.58 (n = 18), and with a cumulative weight
of 0.95. The top model (AICc weight = 0.16) also contained effects of D50 and temperature,
although the effect of temperature is expected to be a result of the natural reduction in fry
number in later months when temperatures are cooler (similar to Brown Trout). D50 had a
cumulative weight of 0.5. Flow appeared in third model of the set (AICc weight = 0.10), and had
a cumulative weight of 0.20. Because stocking had a large effect on fry number, D50 and flow
were compared between sites where stocking did or did not (natural reproduction) occur.
Because fry stocking is likely to be the primary management strategy for increasing Rainbow
Trout adult numbers in the upper Colorado River for years to come, it is reasonable to draw
conclusions from the sites that had been stocked. Overall, there was no observable relationship
between D50 or flow in sites in which Rainbow Trout were not stocked, likely due to the small
number of fry captured in those sites. Overall, Rainbow Trout fry numbers in stocked sites
increased with an increase in D50. Similarly, an increase in flow resulted in an increase in
Rainbow Trout fry numbers in stocked sites. In the sites containing greater than 5 Rainbow
Trout fry per site (528 fry per mile), D50 averaged 118 (± 71) mm, and flow averaged 0.23 (±
0.13) m/s.
D - 12
�Appendix D
30
NS
25
S
RBT Numbers
R² = 0.0798
Linear (NS)
20
Linear (S)
15
10
5
R² = 0.0843
0
0
50
100
150
200
250
D50
30
NS
RBT Numbers
25
R² = 0.0509
S
Linear (NS)
20
Linear (S)
15
10
5
R² = 0.0996
0
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
Flow (m/s)
Stocking also had the largest effect on Rainbow Trout fry abundance (increased abundance in
stocked sites), appearing in the top three models of the set and having a cumulative weight of
0.62. A quadratic effect of flow also appeared in the top model (AICc weight = 0.09). However,
when broken out by stocked and not stocked sites, a similar positive relationship was observed
between flow and Rainbow Trout fry abundance. Average flow in the sites that were stocked
was 0.24 (± 0.09) m/s. Although depth first appeared in the fourth model of the set (AICc
weight = 0.05), it had the second highest cumulative weight relative to stocking, with a
cumulative weight of 0.35. Depth has a large negative effect on Rainbow Trout fry abundance in
stocked sites. Average depth in stocked fry sites was 0.17 (± 0.03) m. Unlike Rainbow Trout fry
numbers, no effect of D50 was observed for Rainbow Trout fry abundance.
D - 13
�Appendix D
30
NS
25
S
RBT Abundance
R² = 0.2279
Linear (NS)
20
Linear (S)
15
10
5
R² = 0.2298
0
0.00
0.10
0.20
0.30
0.40
0.50
Flow (m/s)
30
NS
RBT Abundance
25
S
R² = 0.1177
Linear (NS)
20
Linear (S)
15
10
5
R² = 0.0257
0
0.00
0.05
0.10
0.15
0.20
0.25
Depth (m)
Habitat Recommendations
To manage for both fry species, it appears that an optimal D50 of 151 mm (range 96 to 206) will
be sufficient for maximizing fry number and abundance for both species as average values for
the sites with the highest numbers fall within this range. Similarly, the averages (± SD) overlap
for flow and depth, with flows ranging from 0.20-0.23 m/s and depths around 0.17-0.18 m.
Given the relationships with depth and flow in the Rainbow Trout fry, there may be an
opportunity to manage for Rainbow Trout fry and exclude Brown Trout fry by incorporating
higher flows (greater than 0.24 m/s) and shallower depths (less than 0.17 m). However, these
values were obtained separately and on an additive basis (i.e., no interaction), so it is unknown
whether a combination of both higher flows and shallower depths would be beneficial for
Rainbow Trout fry compared to Brown Trout fry.
D - 14
�Appendix D
Whirling Disease and Habitat Recommendations
To determine if severity of infection (myxospore count) was correlated with habitat covariates, a
Pearson correlation coefficient was obtained using Proc Corr in SAS. In addition, the correlation
between myxospore count and overall change in fry number within a site from July to October
was run using the same method. Overall, myxospore count and change in fry number (Brown
Trout and Rainbow Trout fry included in the same analysis) were not correlated, suggesting that
myxospore count did not have an effect on the change in fry number over four months.
However, it should be noted that only those individuals more resistant to whirling disease are
expected to be present in October. As such, myxospore counts are expected to be lower and
show a narrower range than would be expected if more susceptible individuals had survived to
October, which could have resulted in the non-significant correlation between the two values.
Myxospore count was not significantly correlated with D50, temperature, depth, or flow. The
highest correlation occurred between myxospore count and D50 (p = 0.22), and the relationship
was negative (Pearson correlation coefficient = -0.21), suggesting that myxospore count
decreased with an increase in D50. Given that triactinomyxon releases from high-density
Tubifex worm colonies likely drives infection severity, this relationship makes sense, since worm
habitat is typically sand/silt with high organic matter. Given that Rainbow Trout numbers were
higher in sites with higher D50, and numbers and abundances were higher in sites with increased
flow, it is possible that these sites had smaller Tubifex colonies due to available worm habitat,
and produced lower numbers of triactinomyxons. As such, including larger D50 and/or higher
flows in fry sites may be beneficial from the standpoint of whirling disease infection, especially
for Rainbow Trout fry.
Habitat variables were measured within fry sites only. However, because triactinomyxons are
buoyant and distributed throughout the water column, it is probably equally important to reduce
sediment accumulation and worm habitat above fry sites to reduce production of and contact
with the infectious waterborne stage of the parasite.
D - 15
�Appendix E
COLORADO PARKS AND WILDLIFE
Kemp-Breeze SWA Habitat Project, Colorado River
Conceptual Design
Prepared by:
Colorado Parks and Wildlife
Aquatic Research Section
317 W. Prospect Road
Fort Collins, CO 80526
June 1, 2019
SHEET
DESCRIPTION
1
Conceptual Design Overview
2
Conceptual Design Reach 1
3
Conceptual Design Reach 2
4
Conceptual Design Reach 3
5
Conceptual Design Reach 4
6
Conceptual Cross-Sections
7
Channel Narrowing Concepts
8
Channel Narrowing Concepts
9
Channel Narrowing Concepts
10
Bank Biostabilization Concepts
11
Constructed Riffle Concepts
12
Toe Wood Sod Mat Detail
13
Log Vane J-Hook Detail
14
Cross-Vane Detail
15
Boulder Cluster Detail
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
�Appendix E
REACH 3
AC
RE
REACH 2
REACH 1
H4
0 145 290
580
870
1,160
Feet
CONCEPT DESIGN
Thalweg
Develop Pool
Regrade Channel
Habitat Boulders
Bank Tops (Existing)
Existing Pool
Develop Side Channel
Large Wood
DRAWN: ERICHER
SWA Boundary
Narrow Channel
Excavate Floodplain
Diversion Structure
CHECKED:
De-armor Riffle
Develop Island
Ditch Realignment
APPROVED:
SHEET: 1 OF 15
6/3/2019
º
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix E
Parking area
REACH 1
8100
Some riffle locations should not receive
de-armoring treatments to act as controls
for monitoring and evaluation
8000
790
0
78
00
77
00
7600
7500
7000
7100
6600
6500
6400
6300
7300
7200
6900
0
680
6700
Habitat conditions in this
side channel should be
used as a design analog
7400
6200
6100
6000
Parking area
5900
5800
5700
5600
5400
0
530
5500
Handicap fishing pier: do not disturb,
existing pool should be maintained
and possibly developed
Parshall Hole should
be maintained
Excavated material to be used for fill, but
material suitability and excavation locations
need to be field verified
0 50 100
200
300
400
Feet
CONCEPT DESIGN
Thalweg
Develop Pool
Regrade Channel
Habitat Boulders
Bank Tops (Existing)
Existing Pool
Develop Side Channel
Large Wood
DRAWN: ERICHER
SWA Boundary
Narrow Channel
Excavate Floodplain
Diversion Structure
CHECKED:
De-armor Riffle
Develop Island
Ditch Realignment
APPROVED:
SHEET: 2 OF 15
6/3/2019
º
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix E
REACH 2
Habitat boulders included in concept,
but effects on stream gage and bridge
warrants further consideration
5400
Remove existing push-up dam
and reuse materials if size is
adequate for intended purpose
5600
Diversion return channel:
consider Sediment Sluice
(not depicted)
5500
Diversion head gate:
consider Fish Screen
(not depicted)
0
530
3900
4900
0
520
5100
5000
4800
4700
4600
4500
4400
4300
4200
4100
4000
Monitoring location for benthic
macroinvertebrates, trout fry,
and sediment transport
Steam gage:
do not disturb
Boulder diversion structure:
consider Constructed Riffle
or Cross-Vane diversion
Breeze Bridge: may not support
transporation of materials; scour
analysis needs to be conducted
Wetland area
0 25 50
100
150
200
Feet
CONCEPT DESIGN
Thalweg
Develop Pool
Regrade Channel
Habitat Boulders
Bank Tops (Existing)
Existing Pool
Develop Side Channel
Large Wood
DRAWN: ERICHER
SWA Boundary
Narrow Channel
Excavate Floodplain
Diversion Structure
CHECKED:
De-armor Riffle
Develop Island
Ditch Realignment
APPROVED:
SHEET: 3 OF 15
6/3/2019
º
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix E
REACH 3
Consider realignment of ditch away from the
stream bank to reduce bank erosion potential
and improve floodplain connectivity
3400
370
0
3500
360
0
3100
3900
3800
4400
4200
4100
4000
Excavated material to be used for fill, but
material suitability and excavation locations
need to be field verified
4300
3200
300
0
3300
29
00
2800
2700
2600
Wetland area
Wetland area
0 30 60
120
180
240
Feet
CONCEPT DESIGN
Thalweg
Develop Pool
Regrade Channel
Habitat Boulders
Bank Tops (Existing)
Existing Pool
Develop Side Channel
Large Wood
DRAWN: ERICHER
Williams Ditch
Narrow Channel
Excavate Floodplain
Diversion Structure
CHECKED:
SWA Boundary
De-armor Riffle
Develop Island
Ditch Realignment
APPROVED:
SHEET: 4 OF 15
6/1/2019
º
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix E
Constructed wetland:
do not disturb
REACH 4
260
0
250
0
2400
2300
2200
2100
28
00
27
00
1400
1300
1200
1000
900
800
700
00
29
Excavated material to be used for fill, but
material suitability and excavation locations
need to be field verified
Wetland area
Cottonwood trees are available onsite
for use as large woody material, but
suitability should be verified
30
00
500
400
1500
1100
600
1600
00
17
30
0
20
0
2000
0
180
1900
10
0
0
Williams Ditch:
do not disturb
Hay meadows with numerous
irrigation ditches
0
50 100
200
300
400
Feet
CONCEPT DESIGN
Thalweg
Develop Pool
Regrade Channel
Habitat Boulders
Bank Tops (Existing)
Existing Pool
Develop Side Channel
Large Wood
DRAWN: ERICHER
Williams Ditch
Narrow Channel
Excavate Floodplain
Diversion Structure
CHECKED:
SWA Boundary
De-armor Riffle
Develop Island
Ditch Realignment
APPROVED:
SHEET: 5 OF 15
6/1/2019
º
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
PLAN VIEW
�Appendix E
RIPARIAN VEGETATION
80'
FLOOD RELIEF CHANNELS
RIFFLE
ELEVATION VIEW (1/16" = 1')
THALWEG DEVELOPMENT
1A
RIPARIAN VEGETATION
CONVEX POINT BAR SLOPE
92'
FLOOD RELIEF CHANNELS
LATERAL SCOUR POOL
ELEVATION VIEW (1/16" = 1')
MAX DEPTH AND SHEAR AT 0.2*W
1B
RIPARIAN VEGETATION
LESS DEFINED POINT BAR
92'
FLOOD RELIEF CHANNELS
CONVERGENCE POOL
ELEVATION VIEW (1/16" = 1')
MORE CENTERED THALWEG
1C
CONCEPTUAL DESIGN ONLY - NOT FOR CONSTRUCTION
NOTES FOR CONCEPTUAL CROSS-SECTIONS:
RIFFLE DIMENSIONS WERE ESTIMATED FROM HYDRAULIC GEOMETRY EQUATIONS IN TORRIZO AND PITLICK (2004) AND POOL
DIMENSIONS WERE ESTIMATED WITH EQUATIONS IN SOAR AND THORNE (2001)
RIFFLE: WIDTH = 80 FT; AVERAGE DEPTH = 2.6 FT; AREA = 202 SQ-FT
LATERAL SCOUR POOL: WIDTH = 92 FT; MAX DEPTH = 5.0 FT; AREA = 208 SQ-FT
CONVERGENCE POOL: WIDTH = 92 FT; MAX DEPTH = 5.0 FT; AREA = 235 SQ-FT
TYPICAL CROSS-SECTION DIMENSIONS NEED TO BE VALIDATED BASED ON SEDIMENT TRANSPORT ANALYSIS
CONCEPTUAL CROSS-SECTIONS
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 6 OF 15
05/31/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS & WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
CONCEPT DESIGN
�Appendix E
COTTONWOOD GALLERY
RIPARIAN VEGETATION
145'
EXISTING CROSS-SECTION
ELEVATION VIEW (1" = 30')
2A
NARROWED SINGLE CHANNEL
ELEVATION VIEW (1" = 30')
2B
NARROWED MULTITHREAD CHANNEL
ELEVATION VIEW (1" = 30')
2C
RIPARIAN SOD MAT WITH WILLOWS
CUT INTO TERRACE
5'
FILL WITH MATERIAL FROM TERRACE AND REVEGETATE
80'
33'
TRANSPLATED SOD MAT WITH WILLOWS
CUT INTO TERRACE
INCORPORATE SIDE CHANNEL TO IMPROVE
FLOOD CONVEYANCE AND HABITAT DIVERSITY
15'
70'
FILL AND REVEGETATE
CONCEPTUAL DESIGN ONLY - NOT FOR CONSTRUCTION
CONCEPTUAL CROSS-SECTION DESIGN FOR HEC-RAS STATION 5910
EXISTING CHANNEL: WIDTH = 145 FT; DEPTH = 2.6 FT
NARROWED SINGLE CHANNEL: WIDTH = 80 FT; DEPTH = 2.6 FT
NARROWED MULTITHREAD CHANNEL - MAIN CHANNEL: WIDTH = 70 FT; DEPTH = 2.4 FT
NARROWED MULTITHREAD CHANNEL - SIDE CHANNEL: WIDTH = 15 FT; DEPTH = 2.2 FT
CHANNEL NARROWING CONCEPTS
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 7 OF 15
05/31/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS & WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
CONCEPT DESIGN
�Appendix E
COTTONWOOD GALLERY
RIPARIAN VEGETATION
145'
EXISTING CROSS-SECTION
ELEVATION VIEW (1" = 30')
2A
NARROWED SINGLE CHANNEL WITH
COTTONWOOD FILL
ELEVATION VIEW (1" = 30')
2D
NARROWED SINGE CHANNEL WITH
TOE WOOD
ELEVATION VIEW (1" = 30')
2E
RIPARIAN SOD MAT WITH WILLOWS
CUT INTO
TERRACE
UTILIZE COTTONWOOD FROM CUT AREA AS FILL
80'
TRANSPLANTED SOD MAT WITH WILLOWS
FILL AND REVEGETATE
CUT INTO
TERRACE
FILL AND REVEGETATE
80'
TRANSPLATED SOD MAT WITH TOE WOOD
CONCEPTUAL DESIGN ONLY - NOT FOR CONSTRUCTION
CONCEPTUAL CROSS-SECTION DESIGN FOR HEC-RAS STATION 5910
EXISTING CHANNEL: WIDTH = 145 FT; DEPTH = 2.6 FT
NARROWED SINGLE CHANNEL: WIDTH = 80 FT; DEPTH = 2.6 FT
CHANNEL NARROWING CONCEPTS
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 8 OF 15
05/31/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS & WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
CONCEPT DESIGN
�Appendix E
DEPOSITIONAL AREA BEHIND "BARB"
WILLIAMS IRRIGATION DITCH
160'
RIPARIAN SOD MAT WITH WILLOWS
OLD "BARB" TREATMENT
RIPARIAN SOD MAT
WITH WILLOW
EXISTING CROSS-SECTION
ELEVATION VIEW (1" = 30')
3A
FILL AND
REVEGETATE
CUT INTO TERRACE
CUT NEW IRRIGATION DITCH
FILL OLD IRRIGATION
DITCH
80'
CUT
FILL WITH MATERIAL FROM
TERRACE AND REVEGETATE
TRANSPANTED SOD MAT WITH WILLOWS
TRANSPLANTED SOD MAT WITH WILLOWS
NARROWED CHANNEL WITH DEFINED THALWEG
NARROWED SINGLE CHANNEL
ELEVATION VIEW (1" = 30')
CONCEPTUAL DESIGN ONLY - NOT FOR CONSTRUCTION
CONCEPTUAL CROSS-SECTION DESIGN FOR HEC-RAS STATION 3402
EXISTING CHANNEL: WIDTH = 160 FT; DEPTH = 2.4 FT
NARROWED SINGLE CHANNEL: WIDTH = 80 FT; DEPTH = 2.6 FT
3B
CHANNEL NARROWING CONCEPTS
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 9 OF 15
05/31/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS & WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
CONCEPT DESIGN
�Appendix E
COBBLE TOE WITH SOD MAT
ELEVATION VIEW (NTS)
4A
COIR LOG WITH SOIL LIFT
ELEVATION VIEW (NTS)
4D
COBBLE TOE WITH SOIL LIFT
ELEVATION VIEW (NTS)
4B
TOE WOOD WITH SOD MAT
ELEVATION VIEW (NTS)
4E
COIR LOG TOE WITH SOD MAT
ELEVATION VIEW (NTS)
4C
TOE WOOD WITH SOIL LIFT
ELEVATION VIEW (NTS)
4F
BANK BIOSTABILIZATION CONCEPTS
CONCEPTUAL DESIGN ONLY - NOT FOR CONSTRUCTION
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 10 OF 15
05/31/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS & WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
CONCEPT DESIGN
�Appendix E
CONSTRUCTED RIFFLE DIVERSION
PLAN VIEW (NTS)
CROSS VANE & CONSTRUCTED RIFFLE
PLAN VIEW (NTS)
5A
CONSTRUCTED RIFFLE EXAMPLES
PHOTOS
5C
CONSTRUCTED RIFFLE CONCEPTS
CONCEPTUAL DESIGN ONLY - NOT FOR CONSTRUCTION
5B
DRAWN: ERICHER
CHECKED:
APPROVED:
SHEET: 11 OF 15
05/31/2019
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS & WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
CONCEPT DESIGN
�Appendix E
A
A
A
A
A
A
12
�Appendix E
LOG VANE J-HOOK COMBO DETAIL
CONCEPT ONLY – NOT FOR CONSTRUCTION
DRAWN:
5/31/2019
CHECKED:
APPROVED:
SHEET: 13 OF 15
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
CONCEPTUAL DESIGN
�Appendix E
*Reprinted from Rosgen (2006)
CROSS-VANE DETAIL
CONCEPT ONLY – NOT FOR CONSTRUCTION
DRAWN:
*Rosgen, D. L. 2006. The cross-vane, w-weir, and j-hook vane structures. Wildland
Hydrology, Fort Collins, CO.
5/11/2019
CHECKED:
APPROVED:
SHEET: 14 OF 15
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
CONCEPTUAL DESIGN
�Appendix E
BOULDER CLUSTER DETAIL
CONCEPT ONLY – NOT FOR CONSTRUCTION
DRAWN:
5/11/2019
CHECKED:
APPROVED:
SHEET: 15 OF 15
STATE OF COLORADO
DEPARTMENT OF NATURAL RESOURCES
COLORADO PARKS AND WILDLIFE
FORT COLLINS, COLORADO
COLORADO RIVER
KEMP-BREEZE SWA
CONCEPTUAL DESIGN
�
https://cpw.cvlcollections.org/files/original/0237f6c6dd39d15f694cd1c6a1ba6c5c.pdf
9c3aa426b891b82d83c400a2cf7b4ded
PDF Text
Text
The Role of Colorado Parks and Wildlife in
Restoring Colorado Rivers
Matt Kondratieff
Aquatic Research Scientist
Colorado Parks and Wildlife
Fort Collins, CO
Co-author: Karen Hertel
Research Librarian
Colorado Parks and Wildlife Fort
Collins, CO
�History of Development in Western US
Borrowed
from LTPBR
Workshop
�Creation of CO State Fish Commissioner (1877)
In 1877, the Colorado General Assembly enacted an entire
chapter dedicated to fish.
• Section 1225 of Chapter 52 of the General Laws of Colorado
created the position of State Fish Commissioner
�Failure to Provide Fish Way (1877)
• G.L. § 1218 created a duty to erect and maintain fish ways:
Any person or persons, or the officers maintaining of and servants of any company or corporation, maintaining
or keeping up any dam, weir or other artificial obstruction, in or upon any stream of water in this state, shall
erect and keep up, and maintain at such dam, weir or other artificial obstruction, a sufficient sluice or fishway
for the free passage of fish up and down any such stream.
• G.L. § 1220 established the penalty for failing to provide a fish way in accordance with G.L. § 1218:
Any person or persons, or the officers or servants of any company or corporation, convicted of violating any of
the provisions of this act, shall be fined in any sum not less than twenty-five dollars, nor more than three
hundred dollars; or shall be imprisoned in the county jail not less than thirty days nor more than six months, or
both fine and imprisonment, in the discretion of the court.
�Failure to Provide Fish Way (1877)
�Birth of Colorado Parks & Wildlife (1897)
• Department of Forestry, Game and Fish, 1897
• Department of Game and Fish, 1899
• Game, Fish and Parks Department, 1963
• Colorado Division of Wildlife, 1968
• Colorado Parks and Wildlife, 2011 to present
�Civilian Conservation Corps (CCC) 1930s
Rim Rock Drive CO Natl Monument
CCC Ditch, San Miguel River
Red Rocks Amphitheater, Morrison
�CCC Check Dams 1930s
Log/Loose rock check dam
Loose rock check dam, Reuters Gully
Log check dam, Trout Creek
�Highways vs Streams
(1960s)
�Tenmile Creek 1975-1976
�Rio Grande River, Coller SWA 1979
�Trout Response to Log Drops
1988-1995
�Vocational Heavy Construction Technology
(VHCT) Program 1990-2015
�Rod Van Velson’s Other Projects…
• 7 additional projects; 2.5 miles
�Response of Pools & Trout Populations to
Large Wood (i.e. toe-wood) 2009-2015
Collaborators: Matt Kondratieff, Dr. Eric Fetherman, Tyler Swarr, and Eric Richer
�Upper Arkansas River Habitat Project
2012-2015
Before
After
�Kemp-Breeze SWA Habitat Project 2022-2024
Before
After
�Colorado River Windy Gap Dam 2022-2024
�CPW’s Role in Restoring CO Rivers
Unique aspects of the CPW Stream Restoration History
• Incorporation of Research Scientists into design and
monitoring/evaluation a common thread across time
• Restoration work completed exclusively on public lands with
access for public angling
• Unique partnership with Department of Corrections to conduct
stream restoration work using inmates for 25 years
�Rodney Charles Van Velson
August 13, 1940 – April 17, 2025
�Questions?
��Colorado River Windy Gap Dam
�Colorado River Windy Gap Dam
�
https://cpw.cvlcollections.org/files/original/a8a63a94a3433d381b091fd0cf843504.pdf
021256b5341c56cc5a7c0036cde3b862
PDF Text
Text
LAKE AND RESERVOIR HYDROACOUSTIC ASSESSMENTS
William M. Pate
Research Associate
Andrew J. Treble
Aquatic Research Data Analyst
Adam G. Hansen, Ph.D.
Aquatic Research Scientist
Annual Report
Colorado Parks & Wildlife
Aquatic Research Section
317 West Prospect Road
Fort Collins, Colorado
April 2021
�STATE OF COLORADO
Jared Polis, Governor
COLORADO DEPARTMENT OF NATURAL RESOURCES
Dan Gibbs, Executive Director
COLORADO PARKS & WILDLIFE
Dan Prenzlow, Director
WILDLIFE COMMISSION
Michelle Zimmerman, Chair
Marvin McDaniel, Vice Chair
James Vigil, Secretary
Taishya Adams
Betsy Blecha
Robert William Bray
Charles Garcia
Marie Haskett
Carrie Besnette Hauser
Luke B. Schafer
Eden Vardy
Ex Officio/Non-Voting Members:
Kate Greenberg, Dan Gibbs, and Dan Prenzlow
AQUATIC RESEARCH STAFF
George J. Schisler, Aquatic Research Leader
Kelly Carlson, Aquatic Research Program Assistant
Peter Cadmus, Aquatic Research Scientist/Toxicologist, Water Pollution Studies
Eric R. Fetherman, Aquatic Research Scientist, Salmonid Disease Studies
Ryan M. Fitzpatrick, Aquatic Research Scientist, Eastern Plains Native Fishes
Adam G. Hansen, Aquatic Research Scientist, Coldwater Lakes and Reservoirs
Matthew C. Kondratieff, Aquatic Research Scientist, Stream Habitat Restoration
Dan A. Kowalski, Aquatic Research Scientist, Stream & River Ecology
Kevin B. Rogers, Aquatic Research Scientist, Cutthroat Trout Studies
Eric E. Richer, Aquatic Research Scientist/Hydrologist, Stream Habitat Restoration
Zachary Hooley-Underwood, Aquatic Research Scientist, West Slope Three-Species Studies
Andrew J. Treble, Aquatic Database Manager/Analyst, Aquatic Data Analysis Studies
Brad Neuschwanger, Hatchery Manager, Fish Research Hatchery
Tracy Davis, Hatchery Technician, Fish Research Hatchery
Andrew Perkins, Hatchery Technician, Fish Research Hatchery
Alexandria Austermann, Librarian
2
�Prepared by:
William M. Pate, Research Associate
Approved by:___________________________________________________________
George J. Schisler, Aquatic Wildlife Research Chief
Date:______________________
The results of the research investigations contained in this report represent work of the
authors and may or may not have been implemented as Parks and Wildlife policy by
the Director or the Wildlife Commission.
3
�INTRODUCTION
Hydroacoustic surveys enable rapid estimation of the depth-distribution, density and
abundance of pelagic fish species such as kokanee (Oncorhynchus nerka; Brandt 1996). Mobile
hydroacoustics is a quantitative method for sampling the water column of a large lake or
reservoir that allows for greater spatial coverage than passive methods such as pelagic gill
netting or active methods such as midwater trawling (Hubert 1996). However, some pelagic
netting is required for target verification and assessment of key species. Hydroacoustic surveys
are generally most effective in this regard when few pelagic species are present. Colorado has
many coldwater reservoirs containing relatively simple pelagic fish assemblages comprised
mostly of salmonid sport fish that lend themselves well to this sampling method. These waters
are often large, deep, and have little structure to interfere with the transducer signal (Beauchamp
et al. 2009).
Colorado Parks and Wildlife began using hydroacoustic sampling techniques in 1994,
primarily as a tool for monitoring key kokanee fisheries and broodstocks that supply eggs to
support statewide stocking efforts (Martinez 1994). Kokanee waters, such as Lake Granby and
Blue Mesa Reservoir, provide upwards of $30 million in economic benefit to the state annually
(Johnson et al. 2009). Hydroacoustic surveys conducted on these and other waters are necessary
for monitoring the health of these valuable fisheries and identifying when additional
management interventions or research might be required (Johnson and Martinez 2000). Here, we
report on results from standard hydroacoustic surveys conducted in 2020.
METHODS
Hydroacoustic surveys were conducted during the week surrounding the new moon in
August and September 2020 on five Colorado Reservoirs. Timing the surveys to coincide with
the new moon is advantageous to hydroacoustic sampling because kokanee naturally disperse on
the thermocline during dark nights (Parkinson et al. 1994; Beauchamp et al. 1997; Hardiman et
al. 2004). This behavior facilitates target tracking and elimination of false targets during postprocessing of raw data. August surveys included Blue Mesa (8/18/2020), Vallecito (8/20/20),
and Williams Fork (8/17/2020) Reservoirs while September surveys included Blue Mesa
(9/16/2020), Granby (9/14/2020), and Wolford Mountain (9/15/2020) Reservoirs. Blue Mesa
Reservoir was surveyed on two occasions to quantify the difference in abundance of kokanee
4
�before and hypothetically after most mature individuals staging to spawn in Sapinero or Cebolla
basins exited the reservoir and were migrating upstream. By conducting surveys during these two
periods, it may be possible to better predict run size and egg take at the Roaring Judy Hatchery.
Nocturnal hydroacoustic surveys were completed using a Hydroacoustics Technology,
Inc. (HTI; Seattle, Washington) model 241 digital split-beam echosounder operating at 200 kHz.
This unit was linked to a laptop computer running HTI’s Digital Echo Processing software
(DEP) and corresponding real-time target tracking algorithm. A global positioning sensor
(Lowrance HDS5, Tulsa, Oklahoma) was also attached to the laptop computer to provide highresolution boat and transect locations. The HTI transducer was attached to an HTI model 624
tow fin and deployed on the starboard side of the boat approximately 0.5-1.0 m below the
surface. A constant boat speed of 5 km/h, ping rate of 5 pings/sec and a pulse length of 0.4 ms
was used during data acquisition. Proper system calibration was confirmed prior to every survey
using a tungsten-carbide sphere.
After completion of each survey, transect data were scrutinized in Echoscape (HTI,
Seattle, Washington) and erroneous targets were removed. Bottom tracks were also edited if
necessary. Fish targets were considered false if moving erratically (multiple echoes and
directional changes in the track) or if different parts of the same track were simultaneously
recorded at different depths. Other targets were scrutinized if there were large fluctuations in
target strength (≥10 dB) across the track. Once data were considered clean, the file was exported
from Echoscape to an Access database. Two files were extracted from Access, which included
the fish target (.FISH) and bottom (.BOT) files and both were saved as tab delimited text files for
import into separate analysis software. This process was repeated for each transect.
The remainder of post-processing occurred in LabView 2011 (National Instruments,
Austin, Texas) modules developed by Kevin Rogers in the HydroAcoustics Kit (HAcK; Rogers
in preparation). The first step was to run the InterpretFish_2020.vi module. This module
prompted the user for the previously mentioned fish target and bottom files for the desired
transect. The output included transect- and depth-specific (every 5 m depth strata) prey and
predator density estimates and corresponding length frequency distributions (5 cm bins) of fish
targets observed across all depths in the water column. The length cutoff for parsing predators
from prey was 42.5 cm. Target strengths of tracked fish were converted to lengths using the
equation developed by Love (1971). Martinez (1995) showed that fish ≥42.5 cm total length or ≥
5
�-33dB were piscivorous and primarily Lake Trout in key kokanee waters. Next, mean lake-wide
density estimates were calculated using the SummarizeLake_4.0.vi module. Lake-wide lengthfrequency estimates were calculated using the PlotLake_2000.vi module. Both modules report
estimates from depths ≥2 m. Unlike other waters, analyses for Blue Mesa Reservoir incorporated
the RETRO SUMMARY 2020.vi module to ensure output format was consistent with historical
survey results. This module has been used in conjunction with kokanee egg take from the
following year in an effort to better predict future egg take trends at the Roaring Judy Hatchery.
Results from the retro-summary are not used to estimate predator and prey densities. See Rogers
(in preparation) for a complete description and underpinnings to each of these modules.
RESULTS and DISCUSSION
Blue Mesa Reservoir
Eleven standard transects (total length = 18,241 m) were surveyed on August 18, 2020,
including six in Sapinero and five in the Cebolla basins. Water surface elevation during the
survey was 7,482.3 ft and conditions were calm. The average lake-wide population estimate for
all fish from these transects was 308,093 (Table 1). Appendix A shows detailed results from each
transect. The corresponding estimated number of prey/acre (mean ± 95% CI) was 35.649 ±
13.462 and predators/acre was 1.042 ± 0.513. We observed a slight increase in 20-40 cm fish
(potential spawning adult kokanee) targets from 2019 (80,000) to 2020 (107,456; Figure 1).
Conversely, the estimated number of 10-20 cm fish (immature) targets was largely similar
between 2019 (97,894) and 2020 (97,106; Figure 2). The retro-summary provided an estimate of
262,484 prey targets and 6,519 predator targets after applying the same 425 mm cutoff and after
only considering fish inhabiting depths ≥10 m (Figure 3). After parsing the average lake-wide
population estimate into different 5 cm size-bins, frequency was highest in the 5-10 cm sizerange at 77,109 ± 38,888 fish and second highest within 10-15 cm at 56,359 ± 27,363 fish
(Figure 4). Lastly, fish were most concentrated within 20-30 m depths when integrated across
transects (Figure 5).
The same eleven transects (total length = 19,816 m) were surveyed on September 16,
2020. The surface elevation during the survey was 7,474.2 ft. Appendix B shows details of each
transect. The estimated number of prey/acre (mean ± 95% CI) for September was 24.146 ± 5.209
and predators/acre was 0.746 ± 0.406. The lake-wide estimate of all fish targets was 208,784
6
�(Table 1). The retro-summary demonstrated a decrease in the lake-wide abundance of prey fish
from 262,484 individuals in August to 198,461 in September (difference of 64,023 fish).
Similarly, the estimated abundance of predators decreased by 1,456 individuals to a total of
5,063 fish in September. Length-frequency was again highest in the 5-10 cm size-range at 52,408
± 11,823 followed by 10-15 cm with 44,185 ± 11,020 (Figure 7). Similar to the August survey,
fish were most concentrated within 20-30 m depths across transects and basins (Figure 8).
August-September comparisons with regard to predicting kokanee run size and egg take are
ongoing.
Table 1. Lake-wide predator and prey density estimates with total abundance for all fish for
Hydroacoustic surveys completed in 2020. Surface elevation was at the time of sampling and
surface acres represents the total when at full pool.
Sampling Surface
Surface
Prey/ Predators/ Lake-wide
Water Name
Date
Acres Elevation (ft) Acre
Acre
Abundance
Blue Mesa Reservoir 8/18/2020
9,180
7,482.3
35.649
1.042
308,093
Blue Mesa Reservoir 9/16/2020
9,180
7,474.2
24.146
0.746
208,784
Lake Granby
9/14/2020
7,260
8,271.3
13.139
0.960
98,948
Vallecito Reservoir 8/20/2020
2,720
7,640.8
7.576
0.556
19,827
Williams Fork
Reservoir
8/17/2020
1,860
7,805.8
15.208
0.903
27,371
Wolford Mountain
Reservoir
9/15/2020
1,550
7,484.2
55.675
2.516
91,696
7
�320,000
280,000
Population Estimate
240,000
200,000
160,000
120,000
80,000
40,000
0
Year
Figure 1. Estimated population size of 20-40 cm fish targets (sum over 25-40 cm size-bins and
depths from HAcK output) from eleven transects acquired on August 18, 2020 in the Sapinero
and Cebolla basins compared to estimates from previous years. Target strengths in decibels were
converted to fish length using the equation developed by Love (1971).
320,000
280,000
Population Estimate
240,000
200,000
160,000
120,000
80,000
40,000
0
Year
Figure 2. Estimated population size of 10-20 cm targets (sum over 15-20 cm size-bins and depths
from HAcK output) from eleven transects acquired on August 18, 2020 in the Sapinero and
Cebolla basins compared to estimates from previous years. Target strengths in decibels were
converted to fish length using the equation developed by Love (1971).
8
�Figure 3. Estimated predator (fish targets ≥425 mm total length) and prey (fish <425 mm)
abundance in Cebolla and Sapinero basins of Blue Mesa Reservoir surveyed on August 18, 2020.
Results were determined using a proprietary module in LabView (HydroAcoustic Kit Retro
Summary 2020.vi) and raw data using a Hydroacoustic Technology Inc. Model 241 Digital SplitBeam Echosounder.
9
�Figure 4. Mean abundance by fish length in Cebolla and Sapinero basins of Blue Mesa Reservoir
surveyed on August 18, 2020. Length bins for the figure at right are in 5 cm increments. Mean
values and corresponding upper 95% CIs are for the first five bins up to and including 25 cm.
Raw data were obtained with a Hydroacoustic Technology Inc. Model 241 Digital Split-Beam
Echosounder and post-processed using a proprietary module in LabView (HydroAcoustic Kit
PlotLakeLF_2000.vi).
10
�Depth (m)
0
‐2
‐5
‐10
‐15
‐20
‐25
‐30
‐35
‐40
‐45
‐50
‐55
‐60
‐65
‐70
Prey
Predator
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
3
Density (individuals/1,000 m )
1.6
1.8
2.0
Figure 5. Estimated density of prey (fish targets <425 mm total length) and predators (fish targets
≥425 mm) by 5 m depth-strata from the hydroacoustic survey completed on August 18, 2020 in
Cebolla and Sapinero basins of Blue Mesa Reservoir. Each depth category represents a 5 m bin
(e.g., the -15 m bin represents the depth strata from ≥ -10 to < -15 m).
11
�Figure 6. Estimated (fish targets ≥425 mm total length) and prey (fish <425 mm) abundance in
Cebolla and Sapinero basins of Blue Mesa Reservoir surveyed on September 16, 2020. Results
were determined using a proprietary module in LabView (HydroAcoustic Kit Retro Summary
2020.vi) and raw data using a Hydroacoustic Technology Inc. Model 241 Digital Split-Beam
Echosounder.
12
�Figure 7. Mean abundance by fish length in Cebolla and Sapinero basins of Blue Mesa Reservoir
surveyed on September 16, 2020. Length bins for the figure at right are in 5 cm increments.
Mean values and corresponding upper 95% CIs are for the first five bins up to and including 25
cm. Raw data were obtained with a Hydroacoustic Technology Inc. Model 241 Digital SplitBeam Echosounder and post-processed using a proprietary module in LabView (HydroAcoustic
Kit PlotLakeLF_2000.vi).
13
�Depth (m)
0
‐2
‐5
‐10
‐15
‐20
‐25
‐30
‐35
‐40
‐45
‐50
‐55
‐60
‐65
‐70
Prey
Predator
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
Density (individuals/1,000 m3)
1.6
1.8
2.0
Figure 8. Estimated density of prey (fish targets <425 mm total length) and predators (fish targets
≥425 mm) by 5 m depth-strata from the hydroacoustic survey completed on September 16, 2020
in Cebolla and Sapinero basins of Blue Mesa Reservoir. Each depth category represents a 5 m
bin (e.g., the -15 m bin represents the depth strata from ≥ -10 to < -15 m).
14
�Lake Granby
There were ten transects (total length = 14,689 m) surveyed on September 14, 2020. The
surface elevation during the survey was 8,271.3 ft. Appendix C shows results from each transect
in detail. Length-frequency (mean ± 95% CI) was highest in the 5-10 cm size class at 22,702 ±
7,302 followed by 15-20 cm at 30,276 ± 4,670 fish (Figure 9). These two categories were
followed closely by 10-15 cm, 25-30 cm, and then 20-25 cm. The highest density of prey was at
35-40 m depths followed by 25-30 m then 30-35 m (Figure 10). The highest predator density was
observed in 25-30 m depths. The average number of prey/acre was 13.139 ± 3.768 fish and
predators/acre was 0.960 ± 0.494. The lake-wide abundance of all fish was estimated at 98,948
(Table 1).
When comparing estimates of fish density in Blue Mesa Reservoir and Lake Granby from
the same month (September), Blue Mesa Reservoir exhibited a greater density (by 11.007/acre)
of prey-sized fish <42.5 cm, but slightly fewer (by 0.214/acre) predator-sized fish >42.5 cm. In
addition, the estimated total prey biomass in Lake Granby (10.189 ± 3.812 MT) was far less than
Blue Mesa Reservoir (18.806 ± 7.277 MT). The depth-distribution of fish in Granby also
differed from Blue Mesa Reservoir. Fish were distributed more evenly across depths in Granby,
including depths >20 m which were likely predominately Lake Trout.
15
�Figure 9. Mean abundance by fish length for Lake Granby surveyed on September 14, 2020.
Length bins for the figure at right are in 5 cm increments. Mean values and corresponding upper
95% CIs are for the first five bins up to and including 25 cm. Raw data were obtained with a
Hydroacoustic Technology Inc. Model 241 Digital Split-Beam Echosounder and post-processed
using a proprietary module in LabView (HydroAcoustic Kit PlotLakeLF_2000.vi).
16
�0
‐2
‐5
‐10
Depth (m)
‐15
‐20
‐25
‐30
‐35
‐40
‐45
Prey
Predator
‐50
‐55
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Density (individuals/1,000 m3)
0.8
0.9
1.0
Figure 10. Estimated density of prey (fish targets <425 mm total length) and predators (fish
targets ≥425 mm) by 5 m depth-strata from the hydroacoustic survey completed on September
14, 2020 in Lake Granby. Each depth category represents a 5 m bin (e.g., the -15 m bin
represents the depth strata from ≥ -10 to < -15 m).
17
�Vallecito Reservoir
There were five transects (total length = 6,877 m) surveyed on August 20, 2020. The
surface elevation during the survey was 7,640.8 ft. Appendix D shows results from each transect
in detail. Length-frequency (mean ± 95% CI) was highest in the 10-15 cm size class at 8,780 ±
8,585 fish followed by 5-10 cm at 5,665 ± 5,225 (Figure 11). There were <1,000 fish per 5 cm
bin at sizes ≥25 cm. The estimate for the 15-20 cm size bin was 1,715 ± 1,188. The highest
density of prey was observed within 10-15 m depths followed by 15-20 m and then 5-10 m
(Figure 12). The highest predator density was observed within 2-5 m depths. The average
number of prey/acre was estimated at 7.576 ± 7.168 and predators/acre was 0.556 ± 0.712. Total
fish abundance was 19,827 (Table 1). Transect 5 was added in an attempt to increase sample size
and survey deeper water. However, no part of the reservoir surveyed was deeper than 20 m.
Figure 11. Mean abundance by fish length for Vallecito Reservoir surveyed on August 20, 2020.
Length bins for the figure at right are in 5 cm increments. Mean values and corresponding upper
95% CIs are for the first five bins up to and including 25 cm. Raw data were obtained with a
Hydroacoustic Technology Inc. Model 241 Digital Split-Beam Echosounder and post-processed
using a proprietary module in LabView (HydroAcoustic Kit PlotLakeLF_2000.vi).
18
�0
‐2
Depth (m)
‐5
‐10
‐15
‐20
Prey
Predator
‐25
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
3
Density (individuals/1,000 m )
1.6
1.8
2.0
Figure 12. Estimated density of prey (fish targets <425 mm total length) and predators (fish
targets ≥425 mm) by 5 m depth-strata from the hydroacoustic survey completed on August 20,
2020 in in Vallecito Reservoir. Each depth category represents a 5 m bin (e.g., the -15 m bin
represents the depth strata from ≥ -10 to < -15 m).
19
�Williams Fork Reservoir
There were only two transects (total length = 6,877 m) surveyed on August 17, 2020 in
Williams Fork Reservoir. The surface elevation during the survey was 7,805.8 ft. Appendix E
shows results from each transect in detail. Length-frequency (mean ± 95% CI) shows a typical
right skewed graph, and abundance was highest for the 5-10 cm size class at 6,592 ± 36,746 fish
followed by 10-15 cm targets at 4,826 ± 27,687 (Figure 13). The highest density of prey was
observed within 15-20 m depths followed by 20-25 m then 10-15 m. The highest predator
density was observed within 25-30 m depths. The average number of prey/acre was 15.208 ±
55.119 and predators/acre was 0.903 ± 0.260. Total fish abundance was estimated at 27,371
(Table 1). It should be noted that these very large confidence intervals are indicative of a large
standard deviation between the two transects in this survey.
Figure 13. Mean abundance by fish length for Williams Fork Reservoir surveyed on August 17,
2020. Length bins for the figure at right are in 5 cm increments. Mean values and corresponding
upper 95% CIs are for the first five bins up to and including 25 cm. Raw data were obtained with
a Hydroacoustic Technology Inc. Model 241 Digital Split-Beam Echosounder and postprocessed using a proprietary module in LabView (HydroAcoustic Kit PlotLakeLF_2000.vi).
20
�0
‐2
‐5
‐10
Depth (m)
‐15
‐20
‐25
‐30
‐35
‐40
Prey
‐45
Predator
‐50
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Density (individuals/1,000 m3)
0.8
0.9
1.0
Figure 14. Estimated density of prey (fish targets <425 mm total length) and predators (fish
targets ≥425 mm) by 5 m depth-strata from the hydroacoustic survey completed on August 17,
2020 in Williams Fork Reservoir. Each depth category represents a 5 m bin (e.g., the -15 m bin
represents the depth strata from ≥ -10 to < -15 m).
21
�Wolford Mountain Reservoir
There were five transects (total length = 6,101 m) surveyed on September 15, 2020. The
surface elevation during the survey was 7,484.2 ft. Appendix F shows results from each transect
in detail. Length-frequency (mean ± 95% CI) was highest in the 5-10 cm size class with 23,086 ±
22,335 fish followed by 30-35 cm fish at 11,923 ± 7,102, 20-25 cm fish at 11,817 ± 10,210, and
25-30 cm fish at 11,760 ± 4,330 (Figure 15). All other groupings contained an estimate of
<10,000 fish. The highest density of prey was within 10-15 m depths followed by 5-10 m then 25 m (Figure 16). The highest predator density was observed within 10-15 m depths. The average
number of prey/acre was estimated at 55.675 ± 34.289 fish and predators/acre was 2.516 ± 2.881.
Total fish abundance was 91,696 (Table 1). Even though confidence intervals were large,
Wolford Mountain Reservoir had the greatest estimated abundance of prey/acre.
Figure 15. Mean abundance by fish length for Wolford Mountain Reservoir surveyed on
September 15, 2020. Length bins for the figure at right are in 5 cm increments. Mean values and
corresponding upper 95% CIs are for the first five bins up to and including 25 cm. Raw data
were obtained with a Hydroacoustic Technology Inc. Model 241 Digital Split-Beam
Echosounder and post-processed using a proprietary module in LabView (HydroAcoustic Kit
PlotLakeLF_2000.vi).
22
�0
‐2
Depth (m)
‐5
‐10
‐15
‐20
Prey
‐25
Predator
‐30
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Density (individuals/1,000 m3)
3.5
4.0
4.5
Figure 16. Estimated density of prey (fish targets <425 mm total length) and predators (fish
targets ≥425 mm) by 5 m depth-strata from the hydroacoustic survey completed on September
15, 2020 in Wolford Mountain Reservoir. Each depth category represents a 5 m bin (e.g., the -15
m bin represents the depth strata from ≥ -10 to < -15 m).
ACKNOWLEDGEMENTS
We would like to thank Kevin Rogers for development and continued training with the
proprietary software package (HydroAcoustics Kit) used in LabView. We would also like to
thank Dan Brauch for assistance while completing surveys on Blue Mesa Reservoir.
23
�LITERATURE CITED
Beauchamp, D. A., C. Luecke, W. A. Wurtsbaugh, H. G. Gross, P. E. Budy, S. Spaulding, R.
Dillenger, and C. P. Gubala. 1997. Hydroacoustic assessment of abundance and diel
distribution of Sockeye Salmon and kokanee in the Sawtooth Valley Lakes, Idaho. North
American Journal of Fisheries Management 17:253-267.
Beauchamp, D. A., D. L. Parrish, and R. A. Whaley. 2009. Coldwater fish in large standing
waters. Pages 97-117 in S. A. Bonar, W. A. Hubert, and D. W. Willis, editors. Standard
methods for sampling North American freshwater fishes. American Fisheries Society,
Bethesda, Maryland.
Brandt, S. B. 1996. Acoustic assessment of fish abundance and distribution. Pages 385-432 in B.
R. Murphy and D. W. Willis, editors. Fisheries techniques, 2nd edition. American
Fisheries Society, Bethesda, Maryland.
Hardiman, J. M., B. M. Johnson, and P. J. Martinez. 2004. Do Predators Influence the
Distribution of Age-0 kokanee in a Colorado Reservoir? Transactions of the American
Fisheries Society 133:1366-1378.
Hubert, W. A. 1996. Passive capture techniques. Pages 157-181 in B. R. Murphy and D. W.
Willis, editors. Fisheries techniques, 2nd edition. American Fisheries Society, Bethesda,
Maryland.
Johnson, B. M., and P. J. Martinez. 2000. Trophic economics of Lake Trout management in
reservoirs of differing productivity. North American Journal of Fisheries Management
20:127–143.
Love, R. H. 1971. Dorsal-aspect target strength of an individual fish. Journal of the Acoustical
Society of America 49:816-823.
Martinez, P. J. 1994. Coldwater reservoir ecology. Colorado Division of Wildlife, Federal Aid in
Sport Fish Restoration, Project F-85, Progress Report, Fort Collins.
Martinez, P. J. 1995. Coldwater reservoir ecology. Colorado Division of Wildlife, Federal Aid in
Sport Fish Restoration, Project F-242R-2, Progress Report, Fort Collins.
Parkinson, E. A., B. E. Rieman, and L. G. Rudstam. 1994. Comparison of acoustic and trawl
methods for estimating density and age composition of kokanee. Transactions of the
American Fisheries Society 123:841-854.
24
�Appendix A
Individual transect output files from the Hydroacoustic Kit (InterpretFish_2020.vi) for Cebolla and Sapinero basins of Blue Mesa
Reservoir surveyed on August 18, 2020.
25
�26
�27
�28
�29
�30
�31
�32
�33
�34
�35
�Appendix B
Individual transect output files from the Hydroacoustic Kit (InterpretFish_2020.vi) for Cebolla and Sapinero basins of Blue Mesa
Reservoir surveyed on September 16, 2020.
36
�37
�38
�39
�40
�41
�42
�43
�44
�45
�46
�Appendix C
Individual transect output files from the HydroAcoustic Kit (InterpretFish_2020.vi) for Lake Granby surveyed on September 14, 2020.
47
�48
�49
�50
�51
�52
�53
�54
�55
�56
�Appendix D
Individual transect output files from the HydroAcoustic Kit (InterpretFish_2020.vi) for Vallecito Reservoir surveyed on August 20,
2020.
57
�58
�59
�60
�61
�Appendix E
Individual transect output files from the HydroAcoustic Kit (InterpretFish_2020.vi) for Williams Fork Reservoir surveyed on August
17, 2020.
62
�63
�Appendix F
Individual transect output files from the HydroAcoustic Kit (InterpretFish_2020.vi) for Wolford Mountain Reservoir surveyed on
September 15, 2020.
64
�65
�66
�67
�68
�
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Text
An innovative program of the
Colorado Department of
Corrections, the Colorado Division
of Wildlife and the Colorado
Contractors Association trains
inmates to restore rivers.
MORE
THAN A
RIVER
By
By
22
Colorado Outdoors
�At left: The South
Platte River, the first
cooperative restoration
project, is appropriately called the “Dream
Stream.” Photos at
right: Inmates receive
heavy equipment
training as well as
other skills that prepare them to re-enter
society. The inmates
perform work that
improves both aquatic
habitat and angler
access, such as new
river channels, reducing riverbank erosion,
reducing silt loads,
flood control and constructing parking lots.
Center photo: Inmates
pose at a groundbreaking ceremony at
Antero Reservoir..
D
DURING 1996, IN A CONFERENCE ROOM BEHIND THE WALLS
of the Buena Vista Correctional Facility, staff from the
Department of Corrections (DOC) and the Division of
Wildlife (DOW) planned a bold new concept that would
provide training opportunities for inmates and improve river
channel and trout habitats in South Park streams.
The focus of the plan was a Vocational Heavy
Construction Technology Program developed by Tom
Bowen, a former prison guard and now a DOC vocational
education instructor who was long disappointed with the
recidivism rate of inmates released from prison. The program provides an opportunity for inmates to receive heavy
equipment experience then employment in the construction
industry.
The Colorado Contractors Association and the Operators
Engineers Union sponsor the program and provide an advisory board from their membership. Inmates are required to
discuss their criminal records and describe their life goals to
the board. The advisory board also approves projects submitted by the DOW and other state, federal, county and city
agencies.
Inmates receive at least 18 months of on-the-job training
in heavy equipment and maintenance. Upon completion of
the program the inmates are presented to the Denver
Community Board for approval and placed in the
Independence Halfway House. Student inmates, once at the
halfway house, interview with Contractors Association
member construction companies and choose their own jobs.
Their average first-year income ranges between $46,000 $51,000. They
now become taxpayers and are
required by law
to pay 20 percent
of their income
for crime restitution. An additional 10 percent
is placed in a
mandatory savings account to
serve as a safety
net. They remain
in the halfway
house until approved by the Community Corrections
Division for the Intensive Supervision Program and wear an
ankle bracelet.
In 1998, the first cooperative restoration project was
completed in a river segment near the upper end of the
“Dream Stream,” appropriately named by anglers. The
Dream Steam is the segment of the South Platte River located between Spinney and Elevenmile reservoirs.
The next construction project reduced Threemile Creek
silt loads entering the Dream Stream. Previous flood events
By Rod Van Velson
September/October 2003
23
�Sweatwater Creek, which adjoins the
Knight-Imler State Wildlife Area,
before (top) and after excavated pool
improvements.
from the Threemile Creek watershed had
deposited huge sediment loads in more
than a mile of the Dream Stream. A new
high-flow channel was constructed to
direct Threemile Creek floodwaters into an
abandoned borrow pit created during the
construction of Spinney Dam. A 500-foot
low-level dam constructed on the Lower
Spinney State Wildlife Area and located
between two low ridges increased the
capacity of the borrow area. A pipe gate
slowly releases impounded floodwaters,
after losing its silt load in the borrow area,
onto a riparian vegetation buffer strip
ensuring waters entering the Dream Stream
contain little if any silt.
Another project was the construction of
a new channel for the South Fork of the
South Platte River immediately downstream from Antero Reservoir. Inmates
excavated a new meandering stream channel and then installed more than 180 pieces
of woody materials and about 370 boulders
in 41 pools and 41 riffles created in the
new stream. Excavated materials were
hauled off site and re-vegetated. The new
stream channel was lined with nearly 1,000
yards of .5-2.5 inch gravel to create trout
spawning habitat. This entire project was
accomplished with minimal damage to the
existing riparian vegetation and new riverbanks. The Denver Water Department, a
third partner in this project, designed and
funded the headgate and diversion structure needed to redirect water into the new
stream channel.
Last year’s drought provided another
river restoration opportunity. When the
stream flow in the South Fork of the South
Platte dried up during the late summer of
2002, it created a unique opportunity to
install river channel and trout habitat treatments that would speed up the recovery
process. The most successful river restoration projects occur where land management and riparian vegetation are improved
prior to habitat restoration.
River channel and trout habitat treatments were installed in the dry riverbed.
Consequently damage to the riverbank
vegetation by heavy equipment was almost
non-existent. This is an important issue
because riparian vegetation is the “glue”
that holds riverbanks together and reduces
riverbank erosion.
During its first four years, DOW and
DOC cooperative projects restored about
2.7 river miles through two different state
wildlife areas and river segments leased for
public fishing in South Park. Other projects
include construction of the .7 mile flood
control channel, the new South Fork channel (.7 mile), construction of angler access
roads and parking lots plus spring development on a state wildlife area.
Over the years, erosion resulted in miles
of over-width river channels and degraded
river habitats across South Park. These
degraded river channels contain shallow
water during low flows. And because pools
have filled with river transported materials,
they lack deep-water pool habitats essential
for over-winter survival of adult trout populations.
In the South Fork the restoration of an
over-width river channel between
Highways 9 and 24 near Hartsel was completed during the spring of 2003. Restoring
natural river functions in this river segment
involved excavation of pool habitats located along outside curves of the river then
using the excavated river-bed materials to
build point bars. Students also hauled tons
of gravel materials and riparian sod blocks
to narrow the river channel and installed
native materials to reduce riverbank erosion and create additional trout habitats.
Inmate students are taught surveying
skills and also annually plant willows and
riparian vegetation for stabilization of
riverbanks. Willow planting techniques are
modified to increase survival and reduce
time required to stabilize riverbank erosion
in South Parks’ harsh, cold and windy climates. Bare root willow plantings have
proven to be very effective along certain
river bank sites. Studies to find better willow species for use in river restoration projects continue.
Terry Kish, Director of Human
Resources Services for the Colorado
Contractors Association, Inc. comments,
“The CCA is in the seventh year of partnership with the Department of Corrections
in this successful program. It has been a
very rewarding and satisfying endeavor.
The number one factor in determining if a
person will return to prison is their placement in a steady, well-paying job.”
DOW Director Russell George attended
a Colorado Contractors Association advisory meeting his first week on the job in
fall 2000, and saw firsthand one of the
completed river restoration projects. He
has been a supporter since then and
encourages expansion of the program so
additional DOW projects can be completed
and additional lives can be restored.
Rivers are constantly in a state of
change. Incarcerated men re-direct their
lives. Recruited inmates go through the
program as river restoration techniques
evolve. Goals and lifestyle changes take
place. And yes, river channel and trout
habitats have been restored in South Park.
Fishing license fees are used to improve
and change trout habitats plus restore hope
to men who are sincere about changing
their lives. ❏
Rod Van Velson is an aquatic research biologist with the Division of Wildlife. Tom
Bowen, a vocational education instructor with
the Department of Corrections, contributed to
this article.
22
The treatments to improve fish habitat to the South Platte River near
Hartsel include importing gravel, logs, boulders and riparian sod blocks.
Colorado Outdoors
�
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17352
Federal Register / Vol. 75, No. 65 / Tuesday, April 6, 2010 / Proposed Rules
sroberts on DSKD5P82C1PROD with PROPOSALS
documentation certifying the type of
service it is providing for each REAG or
MEA within its license service territory
and the type of technology it is utilizing
to provide such service. Further, the
proposed compliance procedures would
require the supporting documentation to
provide the assumptions used to create
the coverage maps, including the
propagation model and the signal
strength necessary to provide service
with the licensee’s technology.
Steps Taken To Minimize Significant
Economic Impact on Small Entities, and
Significant Alternatives Considered
17. The RFA requires an agency to
describe any significant alternatives that
it has considered in reaching its
proposed approach, which may include
the following four alternatives: (1) The
establishment of differing compliance or
reporting requirements or timetables
that take into account the resources
available to small entities; (2) the
clarification, consolidation, or
simplification of compliance or
reporting requirements under the rule
for small entities; (3) the use of
performance, rather than design
standards; and (4) an exemption from
coverage of the rule, or any part thereof,
for small entities.
18. The Public Notice specifically
invites comments on a range of potential
performance requirements and invites
interested parties to suggest alternative
proposals. At this time, the Commission
has not excluded any alternative
proposal concerning performance
requirements from its consideration, but
it would do so in this proceeding if the
record indicates that a particular
proposal would have a significant and
unjustifiable adverse economic impact
on small entities.
19. In the Public Notice, the
Commission discusses possible
reporting requirements to ensure that
spectrum is used intensively in the
public interest. In particular, the
Commission is considering a proposal to
require licensees to provide additional
reports demonstrating the level of
service provided to the public.
However, the Commission will not
consider any alternative that would
have a significant and unjustifiable
adverse economic impact on small
entities.
20. The Commission solicits any
alternative proposals that would not
incur significant and unjustifiable
adverse impact on small entities.
Federal Rules That May Duplicate,
Overlap, or Conflict With the Proposed
Rules
21. None.
VerDate Nov<24>2008
16:32 Apr 05, 2010
Jkt 220001
List of Subjects in 47 CFR Part 27
Communications common carriers,
Radio.
Federal Communications Commission.
Marlene H. Dortch,
Secretary.
[FR Doc. 2010–7761 Filed 4–5–10; 8:45 am]
BILLING CODE 6712–01–P
DEPARTMENT OF THE INTERIOR
Background
Fish and Wildlife Service
50 CFR Part 17
[FWS-R1-ES-2009-0043]
[MO 92210-0-0008 B2]
Endangered and Threatened Wildlife
and Plants; 12–month Finding on a
Petition To List the Mountain Whitefish
in the Big Lost River, Idaho, as
Endangered or Threatened
AGENCY: Fish and Wildlife Service,
Interior.
ACTION: Notice of 12–month petition
finding.
SUMMARY: We, the U.S. Fish and
Wildlife Service (Service), announce a
12–month finding on a petition to list
the mountain whitefish (Prosopium
williamsoni) in the Big Lost River,
Idaho, as endangered or threatened
under the Endangered Species Act of
1973, as amended. After review of all
available scientific and commercial
information, we find that the mountain
whitefish in the Big Lost River does not
constitute a listable entity under the Act
and, therefore, listing is not warranted.
However, we ask the public to continue
to submit to us any new information
that becomes available concerning the
taxonomy, biology, ecology, and status
of the mountain whitefish in the Big
Lost River, and to support cooperative
conservation of mountain whitefish
within its historical range in the Big
Lost River.
DATES: The finding announced in this
document was made on April 6, 2010.
ADDRESSES: This finding is available on
the Internet at http://www.fws.gov/
idaho, and also at http://
www.regulations.gov at Docket No.
FWS-R1-ES-2009-0043. Supporting
documentation we used in preparing
this finding is available for public
inspection, by appointment, during
normal business hours at the U.S. Fish
and Wildlife Service, Idaho Fish and
Wildlife Office, 1387 S. Vinnell Way,
Room 368, Boise, ID 83709. Please
submit any new information, materials,
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comments, or questions concerning this
finding to the Service at this address.
FOR FURTHER INFORMATION CONTACT:
Acting State Supervisor, Idaho Fish and
Wildlife Office (see ADDRESSES); by
telephone at 208-378-5243; and by
facsimile at 208-378-5262. Persons who
use a telecommunications device for the
deaf (TDD) may call the Federal
Information Relay Service (FIRS) at 800877-8339.
SUPPLEMENTARY INFORMATION:
Section 4(b)(3)(B) of the Endangered
Species Act of 1973, as amended (Act)
(16 U.S.C. 1531 et seq.), requires that,
for any petition to revise the Federal
Lists of Endangered and Threatened
Wildlife and Plants that contains
substantial scientific and commercial
information indicating that listing the
species may be warranted, we make a
finding within 12 months of the date of
receipt of the petition. In this 12–month
finding, we may determine that the
petitioned action is either: (1) Not
warranted, (2) warranted, or (3)
warranted, but immediate proposal of a
regulation implementing the petitioned
action is precluded by other pending
proposals to determine whether species
are endangered or threatened , and
expeditious progress is being made to
add or remove qualified species from
the Federal Lists of Endangered and
Threatened Wildlife and Plants. Section
4(b)(3)(C) of the Act requires that we
treat a petition for which the requested
action is found to be warranted but
precluded as though resubmitted on the
date of such finding, that is, requiring a
subsequent finding to be made within
12 months. We must publish these 12–
month findings in the Federal Register.
Previous Federal Actions
On June 15, 2006, we received a
petition from Western Watersheds
Project to emergency list as endangered
or threatened the population of
mountain whitefish in the Big Lost
River, Idaho, as a separate species,
subspecies, or distinct population
segment (DPS) under the Act. The
petitioner also requested that we
designate critical habitat concurrent
with the listing.
In an August 21, 2006, letter to the
petitioner, we acknowledged receipt of
the petition and explained that we
would not be able to address the
petition at that time due to other
priorities relating to court orders and
settlement agreements. We further
indicated we had reviewed the petition
and determined an emergency listing
was not necessary. On October 23, 2007,
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we issued a 90–day finding (72 FR
59983), concluding the petition had
failed to provide substantial information
indicating that listing the Big Lost River
population of mountain whitefish may
be warranted, based on a lack of
information indicating it may be a
listable entity under the Act (a species,
subspecies, or DPS). On January 25,
2008, Western Watersheds Project filed
a complaint challenging the negative
90–day finding. On March 31, 2009, the
United States District Court in Idaho
found that we had considered
information beyond the material in the
petition in issuing the negative finding,
such that we had effectively begun to
conduct a status review (Western
Watersheds Project v. Dirk Kempthorne,
et al., Case No. CV07-409-S-EJL D.
Idaho). The Court directed us to proceed
directly to a status review and, within
1 year, issue a 12–month finding. We
published a notice in the Federal
Register on August 6, 2009 (74 FR
39268) initiating the status review and
requesting new information for
mountain whitefish in the Big Lost
River, Idaho. The 30–day comment and
information period closed on September
8, 2009. This notice constitutes the 12–
month finding on the June 14, 2006,
petition to list the mountain whitefish
in the Big Lost River, Idaho, as
endangered or threatened.
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Species Information
Species Distribution and Habitat
Mountain whitefish are members of
the family Salmonidae (broadly termed
‘‘salmonids’’) and are found in rivers and
lakes throughout mountainous areas of
western North America in Canada and
the United States (Figure 1). In the
United States, they occur in the States
of Washington, Oregon, Idaho,
Wyoming, Montana, Colorado, Utah,
Nevada, and California (NatureServe
2009). Mountain whitefish are relatively
common and widespread in most river
basins in Idaho (AFS 2007, p. 29) and,
in general, occur in mainstem river
reaches that are greater than 15 meters
(m) (49.2 feet (ft)) wide and of low
gradient (Maret et al. 1997, p. 213;
Meyer et al. 2009, p. 763). Results of a
study by Meyer et al. (2009) assessing
the environmental factors related to
distribution, abundance, and life history
characteristics of mountain whitefish in
Idaho show mountain whitefish in
southern Idaho are abundant, longlived, and fast growing (at warmer water
temperatures) until they reach sexual
maturity. The authors also speculate
that mountain whitefish are relatively
secure in the upper Snake River basin,
although little research has been done
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on the mountain whitefish across the
range of the species (Meyer et al. 2009,
pp. 753, 765).
Although the majority of populations
of mountain whitefish occur in riverine
environments, some populations are
restricted to lakes or isolated sink
basins. Mountain whitefish in the Big
Lost River reside in a ‘‘sink’’ drainage,
which was once part of a large
Pleistocene lake system that included
Lake Terreton (Link 2003, in Van Kirk
et al. 2003, p. 6). As Lake Terreton
waters receded, the Big Lost River and
four adjacent drainages lost their surface
connection to the Snake River, resulting
in five isolated sink drainages in Idaho.
It is estimated mountain whitefish
became isolated in the Big Lost River
approximately 10,000 years ago (Behnke
2003, cited in Van Kirk et al. 2003, p.
8). Other populations of mountain
whitefish occur in other sink drainages,
such as tributaries in the Lahontan
Basin in California and Nevada, and the
Bonneville Basin in Utah. Populations
in these basins are similar to the
population in the Big Lost River in that
all are relict populations of mountain
whitefish that formerly resided in large
Pleistocene lake systems that are now
closed basins.
Distribution and Habitat Within the Big
Lost River Basin
Mountain whitefish in the Big Lost
River are physically isolated from other
whitefish populations within the Snake
River basin. The Big Lost River
originates in the Pioneer, Boulder, Lost
River, and White Knob mountain ranges
and flows down the Big Lost River
Valley eastward onto the Snake River
Plain where it terminates at the Big Lost
River Sinks (Figure 2). Major tributaries
include East Fork, Star Hope Creek,
Wildhorse Creek, North Fork, Thousand
Springs Creek, Warm Springs Creek,
Alder Creek, Pass Creek, and Antelope
Creek. Elevations in this area range from
1,459 m (4,787 ft) at the Big Lost River
Sinks to 3,859 m (12,661 ft) at the
summit of Borah Peak. The climate of
the drainage is generally cool and dry.
Annual precipitation along the valley
floor is about 20 centimeters (cm) (7.8
inches (in)), but increases to over 100
cm (39.4 in) at higher elevations.
Vegetation within the basin ranges from
sagebrush steppe at lower elevations, to
coniferous forests at mid elevations, to
alpine at higher elevations. The
drainage is comprised primarily of
Federal land managed by the U.S. Forest
Service (USFS; 42 percent), Bureau of
Land Management (BLM; 26 percent),
and Department of Energy (DOE; 15
percent), with lesser amounts of private
(14 percent) and State (2 percent) lands.
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The drainage is within portions of Butte
and Custer Counties and is sparsely
populated, with agriculture being the
dominant land use on private lands.
Primary uses of Federal land include
cattle grazing and recreation (IDFG
2007, p. 7). Historically, mountain
whitefish occupied approximately 346.1
kilometers (km) (214 miles (mi)) of
habitat in the Big Lost River (Gamett
2009a, p. 5). Recent studies indicate
mountain whitefish currently occupy
134.8 km (86.3 mi) of the Big Lost River,
with an estimated population of 12,639
adult fish (Garren et al. 2009, pp. 5-6).
Although it is lower than suspected
historical numbers, the current
population estimate shows an increase
from surveys conducted between 2002
and 2005, when it was estimated that
approximately 2,539 adult mountain
whitefish occupied 83.3 km (51.8 mi) of
habitat in the Big Lost River (Gamett et
al. 2009, p. 5).
Species Description
Mountain whitefish can reach about
57 cm (22 in) in length at maturity. The
general body shape is slender with a
somewhat round cross section; body
coloration is typically silver on the
sides, dusky olive green or blue on the
back; and the belly is a dull white
(Simpson and Wallace 1982, p. 77).
According to Gamett 2009 (personal
observations and unpublished data, pp.
8-9), mountain whitefish in the Big Lost
River can be distinguished from
mountain whitefish in the nearby
Pahsimeroi River based on color.
Whiteley (2007, pers. comm.) also notes
a color difference, and suggests that
mountain whitefish in the Big Lost
River may also differ in head and body
shape as well. None of these suggested
differences have been quantified or
formally described, however, and
Gamett (2009, p. 9) notes the need for
further research in this regard.
Age of sexual maturity of mountain
whitefish varies, with mountain
whitefish in southern Idaho
documented to reach sexual maturity at
2 to 3 years (Meyer et al. 2009, p. 765),
while fish from the Blacks Fork River in
Utah were reported to reach sexual
maturity at 4 years for males, and 5 to
7 years for females. The species is
relatively long-lived; one fish in Utah
was aged at 12 years (Wydoski 2001, p.
694), while the oldest fish recorded in
the Meyer et al. study in Idaho was
estimated to be 24 years old (2009, p.
761). Mountain whitefish spawn in the
fall, and timing depends on stream
temperatures (Simpson and Wallace
1982, p. 77; Wydoski 2001, p. 694).
Unlike other salmonids, mountain
whitefish are broadcast spawners,
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meaning no nest or redd is created, and
females scatter eggs and the male
fertilizes them (McGinnis 1984, p. 137).
Spawning generally occurs at night,
with fish broadcasting their eggs and
sperm in riffle areas over clean gravel.
Eggs incubate throughout the winter
months, and hatching typically occurs
in March and April. Migrations
associated with spawning behavior
appear to be highly variable across
systems, with some populations
migrating into tributaries to spawn,
while others move very little (Northcote
and Ennis 1994, p. 350). Upon hatching,
fry are thought to occupy lateral habitats
and low velocity areas. Adult habitat is
variable, consisting of shallow riffles,
moderate runs, and deep pools during
the summer, but primarily deeper pools
in the winter (Northcote and Ennis
1994, p. 353).
Mountain whitefish are thought to be
opportunistic bottom feeders,
consuming whatever is in abundance,
including fish eggs during the spawning
season (McGinnis 1984, p. 137). They
are known to actively feed on both
aquatic and terrestrial insects, but may
also eat other small fish on occasion
(NatureServe 2009).
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Taxonomy
The mountain whitefish in the Big
Lost River of Idaho are currently
recognized as members of the single
species Prosopium williamsoni, which
is considered common and widespread
throughout the mountainous western
United States northward into Canada
(Nelson et al. 2004, p. 86; ITIS 2009;
NatureServe 2009). Although the State
of Idaho does not consider the mountain
whitefish occupying the Big Lost River
to be either a significant species or a
species of concern, they have developed
a management plan specific to this
population of mountain whitefish (IDFG
2007, pp. 1-32).
Defining a Species Under the
Endangered Species Act
Our first step in making a 12–month
finding is to establish that the subject
under consideration constitutes a
‘‘species’’ as defined under section 3(16)
of the Act. Section 3(16) defines
‘‘species’’ to include ‘‘any subspecies of
fish or wildlife or plants, and any
distinct population segment of any
species of vertebrate fish or wildlife
which interbreeds when mature’’ (16
U.S.C. 1532(16)). Our implementing
regulations at 50 CFR 424.11 provide
further guidance for determining
whether a species (as defined in the Act
and our regulations at 50 CFR 424.02(k))
is eligible for listing under the Act: ‘‘In
determining whether a particular taxon
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or population is a species for the
purposes of the Act, the Secretary shall
rely on standard taxonomic distinctions
and the biological expertise of the
Department and the scientific
community concerning the relevant
taxonomic group’’ (50 CFR 424.11(a)).
As previously discussed, mountain
whitefish in the Big Lost River are
classified taxonomically as Prosopium
williamsoni, the same as other mountain
whitefish across the range of the
species. Before proceeding further, we
must first determine whether the
mountain whitefish in the Big Lost
River are a separate species, subspecies,
or DPS, and thus constitute a potentially
listable entity under the Act.
Evaluation of Mountain Whitefish in the
Big Lost River as a Species or
Subspecies
The petitioner asked us to list the
population of mountain whitefish in the
Big Lost River, Idaho, as a separate
species, subspecies, or DPS. As
discussed in the ‘‘Taxonomy’’ section
above, mountain whitefish in the Big
Lost River of Idaho are currently
recognized as members of the single
species Prosopium williamsoni, which
is considered common and widespread
throughout the mountainous western
United States northward into Canada
(NatureServe 2009). The American
Fisheries Society and the American
Society of Ichthyologists and
Herpetologists, the scientific authorities
with regard to this taxonomic group, do
not recognize mountain whitefish in the
Big Lost River as a separate species or
subspecies (Nelson et al. 2004, p. 86).
The Integrated Taxonomic Information
System, a database maintained by a
partnership of Federal agencies to
provide scientifically credible
taxonomic information, similarly does
not recognize mountain whitefish in the
Big Lost River as a separate species or
subspecies (ITIS 2009). Thus, per our
implementing regulations at 50 CFR
424.11, standard taxonomic distinctions
and the biological expertise of the
scientific community concerning the
relevant taxonomic group, the mountain
whitefish in the Big Lost River are not
recognized as a separate species or
subspecies of mountain whitefish.
The petitioner, however, maintained
the mountain whitefish in the Big Lost
River should be protected as a separate
species or subspecies of whitefish
‘‘because all genetic analyses
demonstrate that it is genetically
unique—so much so that the genetic
distance observed between Big Lost
River mountain whitefish and
surrounding populations is at least as
large as that seen between other
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subspecies or even species.’’ We
carefully evaluated the petitioner’s
assertion, which relies primarily on the
analysis of molecular genetic data.
Because of the complex and highly
technical nature of molecular analysis,
we consulted with a fisheries genetics
expert within the Service to assess the
potential significance of the genetics
information available to us regarding
mountain whitefish in the Big Lost
River. Dr. Donald E. Campton, Senior
Science Advisor for the U.S. Fish and
Wildlife Service’s Pacific Region
Fisheries Resources Division, and
former President of the Genetics Section
of the American Fisheries Society,
served as our expert on this finding.
No universally accepted definition of
species or subspecies exists. In general
such classifications are based on
multiple lines of evidence that are
consistent with the hypothesis that the
entity in question is a separate species
or subspecies, including factors such as
morphology, physiology, behavior, and
genetic characteristics (Haig et al. 2006,
p. 1586). In reviewing an entity as a
potential species or subspecies, we
consider as many lines of available,
reliable evidence as possible.
Particularly, in the case of an entity that
is being proposed as a new taxonomic
treatment and that has not been
recognized as such by the relevant
scientific community, we bring our
biological expertise to bear and require
multiple lines of persuasive and
credible corroborating evidence to
support any such change, in accordance
with our regulations at 50 CFR
424.11(a).
Information on the genetics of
mountain whitefish in the Big Lost
River of Idaho is available from several
recent publications, including Whiteley
et al. (2006), Campbell and Kozfkay
(2006), and Miller (2006). In Whiteley et
al. (2006), the researchers utilized both
allozymes and microsatellites to
examine the genetic structure of
mountain whitefish populations
throughout the northwestern United
States and British Columbia, plus two
populations from western Alberta.
Allozymes are forms of enzymes coded
for by different alleles at the same
genetic locus, and can be distinguished
by electrophoresis; microsatellites are
repeating sequences of base pairs in the
DNA, and are typically used as highly
variable genetic markers. Whiteley et al.
(2006, p. 2778) found that mountain
whitefish in this region (all
representatives of the species
Prosopium williamsoni), form three
large-scale genetic assemblages based on
allozyme data and five large-scale
genetic assemblages based on
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microsatellite data. The Big Lost River
population was included within the
resulting Upper Snake River assemblage
(Upper Snake) in both scenarios, and is
described as the ‘‘most genetically
divergent’’ site in that assemblage. While
this is an accurate characterization,
examination of the data demonstrates
that the degree of genetic divergence of
mountain whitefish in the Big Lost
River from other populations in the
Upper Snake genetic assemblage largely
reflects the absence of withinpopulation genetic variation in
individuals from the Big Lost River and
is less than the genetic divergence
observed between the Upper Snake and
other major assemblages of mountain
whitefish (Whiteley et al. 2006, Table 1,
pp. 2770-2771). In other words, the
mountain whitefish in the Big Lost
River appear to be divergent largely as
a result of the lack of genetic diversity
exhibited by this population relative to
other populations, not as the result of
any unique genetic characteristics.
Although the most divergent group
within the Upper Snake, Whiteley et al.
(2006, pp. 2775-2776) found the Big
Lost River population still clustered
within that major genetic assemblage.
This result is consistent with that
reported by another researcher in her
study of mitochondrial DNA in
mountain whitefish, detailed further
below. Miller (2006, p. 30) concludes
‘‘the Big Lost River mountain whitefish
still group with other populations from
the upper Snake River Sub-basin.’’
These results do not suggest that
mountain whitefish in the Big Lost
River stand out from among all
populations of mountain whitefish
examined as genetically unique or
differentiated to the point that they
would be considered a separate species
or subspecies. If that were the case, then
one would expect the Big Lost River
mountain whitefish’s level of
divergence to be greater than the level
of divergence observed between the
major genetic groupings, and they
would not cluster within a major genetic
assemblage.
The analysis of Whiteley et al. (2006)
shows mountain whitefish populations
that are geographically isolated are
relatively more distinctive genetically
than populations that may experience
gene flow between them. Although
Whiteley et al. (2006, p. 2780) reported
little evidence of differentiation among
sites within major river basins in
general, they note that the Upper Snake
(which includes the Big Lost River) and
Olympic Peninsula were an exception to
this rule, due to the natural restrictions
on gene flow in these areas. Whiteley et
al. (2006, p. 2780) identified low levels
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of within-population genetic variation
(relatively lower levels of genetic
diversity) in several physically-isolated
populations of mountain whitefish,
including not only the Big Lost River,
but also the Big Wood River, Bull River,
and Thutade Lake. They also noted a
higher degree of genetic differentiation
in several physically-isolated sites in
the region associated with the Upper
Snake River assemblage; in addition to
the Big Lost River, this pattern was
observed at the Henry’s Fork and several
Bonneville Basin sites (Whiteley et al.
2006, p. 2781).
Such results are not unexpected; in
fact, this condition is exactly what
would be predicted by basic
conservation genetics theory for small,
isolated populations (Meffe and Carroll
1994, pp. 156-158). These isolated
populations are relatively genetically
divergent compared to other
populations that experience higher
levels of gene flow (gene flow or genetic
mixing maintains greater levels of
genetic diversity or heterogeneity in the
population). Such a level of
differentiation does not necessarily
suggest a subspecies or species-level
difference; nor does the ability to detect
genetic differences between populations
necessarily equate to meaningful
biological significance (Hedrick 1999,
pp. 316-317). Fish in general, and
particularly freshwater salmonids, tend
to exhibit a high degree of genetic
structuring (Allendorf and Waples 1996,
p. 257; Whiteley et al. 2006, p. 2783),
such that it is not unusual to be able to
easily distinguish between populations
of the same species based on molecular
genetic differences. Yet, if one were to
rely solely on the ability to distinguish
between fish populations based on
genetic differences to identify new
subspecies or species, as Haig et al.
(2006, p. 5, citing Mayden 1999) noted,
‘‘every isolated creek and pond could
have a unique subspecies or species of
fish.’’ This ability to so finely subdivide
species based purely on the ability for
genetic discrimination between them
has led the Service, as described above,
to require a more holistic approach to
species or subspecies analysis that
builds upon multiple lines of evidence,
including, where possible, a full suite of
morphological, physiological,
behavioral, and genetic characteristics,
to support a formerly unrecognized
taxonomic distinction.
The analysis of the genetic
relationships of mountain whitefish by
Whiteley et al. 2006 does not support
the contention that mountain whitefish
of the Big Lost River are distinctive or
unique genetically when compared to
other populations in the Upper Snake
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River assemblage, or when compared to
populations within other assemblages of
the species. Rather, the authors point to
a high degree of genetic differentiation
between many populations of mountain
whitefish in the Upper Snake due to the
topography of the region, and
characterize those populations as ‘‘more
finely subdivided than elsewhere’’
(Whiteley et al. 2006, p. 2781). The
authors also point out that the degree of
genetic differentiation observed in
mountain whitefish among tributaries
within river basins is less than that
observed in populations of other
salmonids, such as bull trout (Salvelinus
confluentus) and westslope cutthroat
trout (Oncorhynchus clarki lewisi) (i.e.,
bull trout and westslope cutthroat trout
show greater levels of genetic
differentiation between populations
within river basins than do mountain
whitefish) (Whiteley et al. 2006, p.
2783). Despite this high degree of
genetic structuring, it has not been
suggested that each individual bull trout
or westslope cutthroat trout population
be considered as a separate species or
subspecies; each genetically
differentiable population of bull trout
and westslope cutthroat trout is still
considered a member of the broader
taxon (species or subspecies,
respectively). If the mountain whitefish
in the Big Lost River were a separate
species or subspecies, based on genetic
characteristics, one would expect
mountain whitefish in the Big Lost
River to exhibit greater genetic
differentiation than populations of
salmonids that are considered members
of the same species or subspecies, not
less.
Campbell and Kofzkay (2006) used
mitochondrial DNA to assess mountain
whitefish populations in Idaho, Utah,
and Montana, and also specifically to
evaluate the origin and divergence of
mountain whitefish in the Big Lost
River. Their results support the three
major genetic assemblages identified by
Whiteley et al. (2006), which Campbell
and Kofzkay (2006, p. 6) describe as the
Upper Snake River drainage (upstream
of Shoshone Falls) and the Bonneville
basin; the Lower Snake River drainage
(downstream of Shoshone Falls)
including the Pahsimeroi and Salmon
Rivers; and the Upper Missouri River.
The authors note the pairwise
divergence estimates between these
major genetic assemblages of mountain
whitefish were very high, ranging from
1.31 to 4.56 percent (Campbell and
Kofzkay 2006, p. 7). For comparison
purposes, they point out that estimates
of mitochondrial DNA sequence
divergence between two salmonid
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subspecies, the westslope cutthroat
trout and Yellowstone cutthroat trout
(Oncorhynchus clarkia bouvieri), range
from 1.5 to 1.9 percent (Gyllensten and
Wilson 1987, IDGF unpublished data,
cited in Campbell and Kofzkay 2006, p.
7). The divergence between the large
major assemblages of mountain
whitefish may thus be similar to the
degree of divergence between
recognized subspecies of cutthroat trout.
However, pairwise divergence
estimates for mountain whitefish in the
Big Lost River are solidly within the
range of normal divergence for
populations of whitefish within the
Upper Snake River assemblage
(Campbell and Kofzkay 2006, Figure 3,
p. 8). The percent sequence divergence
of mountain whitefish from the Big Lost
River compared to other populations
within the Upper Snake River Basin
ranges from 0.33 to 0.49 percent. The
levels of sequence divergence between
subspecies of cutthroat trout (1.4 to 1.9
percent) and between different species
of trout (rainbow trout (O. mykiss) and
cutthroat trout (4.0 to 4.5 percent)
(Campbell and Kozfkay 2006, p. 7) are
far higher than that observed between
mountain whitefish in the Big Lost
River and other populations within the
Upper Snake River assemblage
(Campbell and Kofzkay 2006, p. 8).
According to this study, the genetic
distance between mountain whitefish in
the Big Lost River and surrounding
populations is far less than that
observed between these subspecies or
species of salmonids. Furthermore,
several other populations of mountain
whitefish examined by Campbell and
Kofzkay (2006, Figure 3, p. 8) exhibited
greater levels of divergence from other
populations within their assemblage
than that exhibited by fish from the Big
Lost River (the Boise River populations
in the lower Snake River assemblage, for
example). Thus, the data of Campbell
and Kofzkay (2006) indicate the
mountain whitefish in the Big Lost
River are not particularly distinctive or
unusual in terms of genetic divergence,
when compared to other populations of
mountain whitefish throughout the
range of the species.
Miller (2006) examined the
phylogeography of the genus Prosopium
in western North America, analyzing
mitochondrial DNA using the
cytochrome b (cytb) and NADH
dehyrogenase subunit 2 (ND2)
sequences. This analysis included the
mountain whitefish P. williamsoni, and
three taxa found only in Bear Lake on
the Utah-Idaho border: the Bear Lake
whitefish (P. abyssicola), the Bonneville
whitefish (P. spilonotus), and the
Bonneville cisco (P. gemmifer). Similar
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to the other researchers, Miller reported
a high amount of genetic structure for
mountain whitefish based on drainage
basins or sub-basins. Analyses of
molecular variance demonstrated
between 62.5 and 75.8 percent of the
total genetic variation was found
between drainage basins or subbasins
(Miller 2006, p. 22). Miller’s analysis
found evidence for multiple populations
of mountain whitefish that are
geographically isolated and demonstrate
little to no gene flow, including
populations in the Hoh River, Duchesne
River, Big Wood River, Big Lost River,
and Coeur d’Alene River (Miller 2006,
pp. 22-23).
The nested clade analysis conducted
by Miller resulted in somewhat different
results for the cytb and ND2 sequences.
Analysis based on cytb resulted in the
identification of four major clades of
Prosopium: (1) A Missouri River basin
clade; (2) a Bear Lake Prosopium clade;
(3) a Columbia River subbasin/lower
Snake River subbasin/Lahontan Basin
clade; and (4) a Bonneville basin/upper
Snake River subbasin/Green River
basin/Bear Lake Prosopium clade
(Miller 2006, p. 23). Analysis based on
ND2 resulted in two major clades: (1) A
Columbia River subbasin/lower Snake
River subbasin/Lahontan basin clade,
and (2) a Bonneville Basin/upper Snake
River subbasin/Green River basin/
Missouri River basin/Bear Lake
Prosopium clade (Miller 2006, p. 23),
with the Big Lost River and Missouri
River populations representing two
divergent subgroups within this latter
clade (Miller 2006, Figs. 16a, pp. 130137, and 16c, pp. 146-149). For both
cytb and ND2, she found the haplotypes
for the Big Lost River (upper Snake
River subbasin), the Big Wood River
(lower Snake River subbasin), and the
Hoh River (Columbia River subbasin)
formed isolated clades (included only
haplotypes from their own system, and
did not contain haplotypes from outside
of their clades) (Miller 2006, p. 24).
Miller concluded that these three
populations are genetically distinct from
other populations within their basins
due to their relative isolation. With
regard to the Big Lost River population
in particular, however, she concludes,
‘‘Although distinct from other upper
Snake River populations, the Big Lost
River mountain whitefish still group
with other populations from the upper
Snake River Sub-basin’’ (Miller 2006, p.
30). This result is consistent with that
of Whiteley et al. 2006 (p. 2778); the
mountain whitefish in the Big Lost
River are genetically distinctive within
their major genetic assemblage, but do
not stand out from all other populations
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when considered in the context of the
species across its range.
The petitioner offered additional
information in support of the contention
that mountain whitefish in the Big Lost
River represent a separate species or
subspecies; that additional information
was a reference to an abstract from an
oral presentation made at a meeting of
the Idaho Chapter of the American
Fisheries Society (Van Kirk et al. 2003,
p. 13). This abstract, authored by
Whiteley and Gamett, refers to ‘‘the
fixation of a unique allele in the Big
Lost River population at one of the
microsatellite loci.’’ Data to support this
statement were not available to us. If we
assume that one microsatellite allele has
become fixed in mountain whitefish
occupying the Big Lost River, that
information does not by itself confer any
meaningful genetic significance or
biological or ecological importance (e.g.,
as measured by morphological,
physiological, or behavioral traits)
because microsatellite alleles are
considered selectively neutral, the
frequencies of which largely reflect
random or stochastic processes (e.g.,
genetic drift, population bottlenecks,
founder effects, mutation rates), rather
than selection for traits that confer
increased fitness (Ashley and Dow 1994,
p. 185). Indeed, the total lack of
variability observed in microsatellites
sampled for mountain whitefish in the
Big Lost River (Whiteley et al. 2006, p.
2775) indicates that this population has
likely undergone a past population
bottleneck relative to other populations,
with a subsequent loss of genetic
variability and random fixation (e.g., via
drift of a unique [or nearly unique]
allele) (D. Campton, pers. comm. 2007).
This conclusion is also supported by
the work of Miller, who concludes the
mountain whitefish in the Big Lost
River experienced restricted gene flow
(2006, p. 25). Under such conditions,
genetic distance may increase quickly,
but is not in and of itself indicative of
biological significance (Hedrick 1999,
pp. 315-316). Genetic isolation and a
relatively small population size would
predictably lead to the loss of
haplotypes that might otherwise be
shared with other populations, leading
to the ability to distinguish a population
as ‘‘different.’’ In other words, it is
technically possible to differentiate
between two such populations on the
basis of their genetic characteristics.
However, this purely technical ability
for genetic discrimination between
populations does not necessarily
represent any biological or ecological
importance. We have no information to
indicate that the fixation of any single
microsatellite allele in mountain
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whitefish in the Big Lost River may, in
any way, be biologically important or
significant to the taxon as a whole. Such
fixed allelic differences between
geographically isolated freshwater
populations of salmonid fishes are not
considered uncommon (Allendorf and
Waples 1996, p. 257). Although these
allelic differences may allow for the
detection of statistically significant
differences between populations, and
hence the ability to discriminate
between them on the basis of their
genetic characteristics, as Hedrick
(1999, p. 317) notes, the connection
between biological and statistical
significance may often be weak, and
great care must be taken in interpreting
statistical significance as the equivalent
of biologically meaningful significance.
Mountain whitefish in the Big Lost
River do possess unique mitochondrial
DNA haplotypes, but the same is true of
almost every other mountain whitefish
population sampled by Campbell and
Kofzkay (2006, Table 1, p. 6) and Miller
(2006, Table 3, pp. 51-56, and Table 4,
pp. 57-63). The majority of surveyed
mountain whitefish populations had
unique mitochondrial DNA haplotypes,
as does the population in the Big Lost
River, and some populations had
several. The possession of a populationspecific haplotype is, therefore, not
unique to the mountain whitefish in the
Big Lost River. In addition, the genetic
divergence of mountain whitefish in the
Big Lost River is not necessarily greater
than that observed in other populations.
For example, based on the data of
Campbell and Kofzkay (2006, Figure 3,
p. 8) and Miller (2006, Figure 16, pp.
130-157), the divergence among
haplotypes between fish in the Big Lost
River and other populations in the
Upper Snake River is approximately
three times less than the degree of
divergence observed among individual
mountain whitefish collected from a
single population in the Boise River.
In our review of the best available
information regarding the degree of
genetic divergence of mountain
whitefish in the Big Lost River relative
to other populations of whitefish, we
have determined that many – if not most
– populations of mountain whitefish
sampled by Campbell and Kozfkay
(2006, p. 6) and Miller (2006, pp. 51-63)
can be said to be genetically different
relative to other populations of the
species. Most mitochondrial DNA
haplotypes occur in only one
population and are not shared between
populations, clearly indicating the lack
of gene flow among most populations
(Campbell and Kofzkay 2006, Table 1, p.
6; Miller 2006, Table 3, pp. 51-56, and
Table 4, pp. 57-63). In addition,
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substantially greater mitochondrial DNA
nucleotide diversity exists among
individual fish within some populations
of mountain whitefish, than exists
between mountain whitefish in the Big
Lost River and other populations in the
Upper Snake River (Campbell and
Kofzkay 2006, Figure 3, p. 8; Miller
2006, Figure 16, pp. 130-157). Genetic
analyses by both Whiteley et al. (2006,
pp. 2775-2776) and Miller (2006, p. 30)
determined that mountain whitefish in
the Big Lost River cluster within the
Upper Snake genetic subgroup of
Prosopium williamsoni. Based on the
best available scientific information, we
conclude the evidence is not sufficient
to support recognition of the mountain
whitefish in the Big Lost River as a
separate species or subspecies based on
the genetic characteristics of the
population relative to all other
populations of the species P.
williamsoni.
As we noted earlier, in evaluating
whether an entity may potentially
represent a heretofore unrecognized
species or subspecies, it is important to
consider multiple lines of evidence.
Haig et al. (2006, p. 8) argue that higher
levels of confidence can be obtained in
classifications based on the concurrence
of multiple morphological, molecular,
ecological, behavioral, and
physiological characters. We therefore
considered whether any other
characteristics of mountain whitefish in
the Big Lost River offer any credible
support for the argument that they may
be a separate species or subspecies.
The information available to us
suggests mountain whitefish in the Big
Lost River may exhibit differences in
coloration or morphology. This
suggestion is based on the personal
observations of two researchers, Andrew
Whiteley and Bart Gamett. Dr. Whiteley
suggested that mountain whitefish from
the Big Lost River may differ in color
and form, possibly having shorter heads
and a different body shape, but stated
that these traits have not been
quantified and were based only on his
personal observations (A. Whiteley
2007a, pers. comm.). Mr. Gamett (2009b,
pp. 8-9) also noted that mountain
whitefish from the Big Lost River can be
readily distinguished from specimens of
mountain whitefish found in other
drainages (e.g., Pahsimeroi River) based
on color; however, this has not been
formally described, and is based on
personal opinion. Gamett (2009b, p. 9)
noted that further research is needed to
address this question.
Although mountain whitefish in the
Big Lost River may possibly look
different, we have no evidence before us
to suggest that any differences in color
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or morphology that may exist are
anything other than natural phenotypic
variation that is often observed in
different populations of fish. Natural
variation in characteristics such as body
shape in fish is commonly attributable
to environmental factors, such as water
temperature during development (e.g.,
Barlow 1961, pp. 105-106).
Additionally, many fish exhibit a
considerable degree of intraspecific
(within the species) variation in
morphology, which has been
experimentally demonstrated to be the
result of phenotypic plasticity in
response to the environment, rather
than a heritable response to selection
(e.g., Mittelbach et al. 1999, pp. 111,
126). Head depth is a common plastic
trait in fish related to diet (e.g., Day et
al. 1994, pp. 1723, 1730). We have no
information to suggest that any apparent
differences in morphology or coloration
of the mountain whitefish in the Big
Lost River, which have never been
quantified or formally described, are in
any way biologically meaningful such
that they might represent possible
differentiation to the degree that
subspecies or species recognition might
be warranted—that is, whether they
might possibly be associated with some
fitness advantage or adaptation specific
to this population, as opposed to simple
local variation in phenotypic traits.
It has been suggested that the
mountain whitefish in the Big Lost
River are more genetically divergent
than currently recognized species of
Prosopium endemic to Bear Lake
(Whiteley 2007b, pers. comm.). In her
examination of the three species of
Prosopium endemic to Bear Lake (P.
abyssicola, P. gemmifer, and P.
spilonotus), Miller (2006, pp. 31-32)
found the mitochondrial DNA data
failed to break into discrete clades of
their respective species, possibly
indicative of ongoing adaptive radiation
(i.e., they are still undergoing the
process of speciation), ongoing
hybridization, or other factors. In this
case, although the genetic information
does not provide a clear distinction
between these three groups, other
multiple lines of evidence potentially
support the taxonomic distinction
between these species, including
differences in spawning times, scale
counts, and morphology (Miller 2006
and references therein, pp. 2-3, 34).
Miller notes that although the three Bear
Lake species are not genetically
differentiable, the ‘‘morphological,
ecological, and behavioral differences
are real’’ (Miller 2006, p. 32). However,
she also points out that this lack of
congruence with the genetic information
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does raise some questions regarding the
current classification of these species
(Miller 2006, p. 35), further reinforcing
the point that stronger taxonomic
distinctions can be made based on
multiple lines of consistent supporting
evidence.
By contrast, although mountain
whitefish in the Big Lost River may
show a greater degree of genetic
differentiation from other groups than
that observed in the Bear Lake
Prosopium, we note that any potentially
corroborating morphological, ecological,
behavioral, or physiological
characteristics that might serve as
supporting evidence of meaningful
phenotypic divergence, such as that
used in identifying the three species of
Bear Lake Prosopium, are lacking for
mountain whitefish in the Big Lost
River. Most populations of mountain
whitefish exhibit a high degree of
geographical genetic differentiation
throughout their range (Campbell and
Kofzkay 2006, Figure 3, p. 8; Whiteley
et al. 2006, p. 2781), and several of them
show a greater degree of genetic
differentiation than that exhibited
between the three species of Bear Lake
Prosopium (Miller 2006, Figure 16, pp.
130-157). However, in the absence of
any reliable corresponding evidence
indicative of local adaptation or
phenotypic divergence, we believe there
is insufficient support for the
recognition of any such population as a
new species or subspecies based on this
genetic information. Thus we do not
find the greater genetic divergence
observed in mountain whitefish in the
Big Lost River relative to that observed
between the Bear Lake Prosopium
persuasive evidence that mountain
whitefish in the Big Lost River should
be considered a species or subspecies.
In summary, mountain whitefish
occurring in the Big Lost River are not
currently recognized by the relevant
taxonomic authorities as a species or
subspecies (Nelson et al. 2004, p. 86;
ITIS 2009; NatureServe 2009), and our
evaluation of the best available
scientific and commercial data does not
indicate that mountain whitefish in the
Big Lost River represent a distinct
species or subspecies relative to other
populations of Prosopium williamsoni.
Available evidence indicates there is a
high degree of genetic structuring
between many populations of mountain
whitefish, and particularly those in the
Upper Snake, as is frequently observed
between populations of other freshwater
salmonids (Allendorf and Waples 1996,
p. 257; Miller 2006, p. 25; Whiteley et
al. 2006, pp. 2781, 2783). Modern
molecular techniques allow virtually
every population to be distinguished
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from one another, and almost every
population of mountain whitefish
surveyed had at least one unique
haplotype. Thus every population of
mountain whitefish sampled so far
could be considered genetically
‘‘distinct,’’ including the mountain
whitefish in the Big Lost River. As
explained above, however, the genetic
data before us do not indicate that the
mountain whitefish in the Big Lost
River are biologically unique or unusual
compared to other populations of the
species, so as to warrant consideration
as a separate species or subspecies.
Furthermore, in reviewing all
available information, we found no
substantiated evidence of ecological,
morphological, physiological,
behavioral, or other characteristics that
would indicate any adaptive divergence
or patterns of adaptation have taken
place in mountain whitefish occurring
in the Big Lost River, and that might be
considered additional evidence of a
potentially distinct species or
subspecies. We therefore conclude,
based on all of the best available
scientific and commercial data, that
consideration of mountain whitefish in
the Big Lost River as a separate species
or subspecies is not warranted at this
time.
Evaluation of Mountain Whitefish in the
Big Lost River as a Distinct Population
Segment
To interpret and implement the
distinct vertebrate population segment
(DPS) provisions of the Act and
Congressional guidance, we, in
conjunction with the National Marine
Fisheries Service (now the National
Oceanic and Atmospheric
Administration—Fisheries), published
the Policy Regarding the Recognition of
Distinct Vertebrate Population Segments
(DPS Policy) in the Federal Register on
February 7, 1996 (61 FR 4722). Under
the DPS policy, two basic elements are
considered in the decision regarding the
establishment of a population of a
vertebrate species as a possible DPS. We
must first determine whether the
population qualifies as a DPS; this
requires a finding that the population is
both: (1) Discrete in relation to the
remainder of the species to which it
belongs; and (2) biologically and
ecologically significant to the species to
which it belongs. If the population
meets the first two criteria under the
DPS policy, we then proceed to the
third element in the process, which is
to evaluate the population segment’s
conservation status in relation to the
Act’s standards for listing as an
endangered or threatened species. These
three elements are applied similarly for
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additions to or removals from the
Federal Lists of Endangered and
Threatened Wildlife and Plants.
In accordance with our DPS Policy,
we detail our analysis of whether a
vertebrate population segment under
consideration for listing may qualify as
a DPS. As described above, we first
evaluate the population segment’s
discreteness from the remainder of the
species to which it belongs. Under the
DPS policy, a population segment of a
vertebrate taxon may be considered
discrete if it satisfies either one of the
following conditions:
(1) It is markedly separated from other
populations of the same taxon as a
consequence of physical, physiological,
ecological, or behavioral factors.
Quantitative measures of genetic or
morphological discontinuity may
provide evidence of this separation.
(2) It is delimited by international
governmental boundaries within which
differences in control of exploitation,
management of habitat, conservation
status, or regulatory mechanisms exist
that are significant in light of section
4(a)(1)(D) of the Act.
If we determine that a vertebrate
population segment is discrete under
one or more of the conditions described
in the Service’s DPS policy, we then
consider its biological and ecological
significance to the larger taxon to which
it belongs, in light of Congressional
guidance (see Senate Report 151, 96th
Congress, 1st Session) that the authority
to list DPSes be used ‘‘sparingly’’ while
encouraging the conservation of genetic
diversity. In making this determination,
we consider available scientific
evidence of the discrete population
segment’s importance to the taxon to
which it belongs. Since precise
circumstances are likely to vary
considerably from case to case, the DPS
policy does not describe all the classes
of information that might be used in
determining the biological and
ecological importance of a discrete
population. However, the DPS policy
describes four possible classes of
information that provide evidence of a
population segment’s biological and
ecological importance to the taxon to
which it belongs. As specified in the
DPS policy (61 FR 4722), this
consideration of the population
segment’s significance may include, but
is not limited to, the following:
(1) Persistence of the discrete
population segment in an ecological
setting unusual or unique to the taxon;
(2) Evidence that loss of the discrete
population segment would result in a
significant gap in the range of a taxon;
(3) Evidence that the discrete
population segment represents the only
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surviving natural occurrence of a taxon
that may be more abundant elsewhere as
an introduced population outside its
historic range; or
(4) Evidence that the discrete
population segment differs markedly
from other populations of the species in
its genetic characteristics.
A population segment needs to satisfy
only one of these conditions to be
considered significant. Furthermore,
other information may be used as
appropriate to provide evidence for
significance.
Discreteness
Our DPS policy states that a
population segment of a vertebrate
species may be considered discrete if it
is markedly separated from other
populations of the same taxon as a
consequence of physical, physiological,
ecological, or behavioral factors. We
find that mountain whitefish in the Big
Lost River are discrete, since they occur
in a closed basin lacking a surface
connection to any major river system,
and are therefore physically separated
from the remainder of the populations
in the taxon. We therefore conclude that
mountain whitefish in the Big Lost
River satisfy the discreteness criterion of
the DPS policy.
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Significance
Having determined that mountain
whitefish in the Big Lost River meet the
discreteness criterion, our DPS policy
directs us to next consider available
scientific evidence of the biological and
ecological importance of this discrete
population to the remainder of the
species to which it belongs. In this case,
we evaluate the biological and
ecological significance of the mountain
whitefish in the Big Lost River relative
to mountain whitefish throughout the
remainder of their range in the western
United States and Canada. A discrete
population is considered significant
under the DPS policy if it meets one of
four of the elements identified in the
policy under significance, or can
otherwise be reasonably justified as
being significant. Here we evaluate the
four potential factors suggested by our
DPS policy in evaluating significance.
(1) Persistence of the Discrete
Population Segment in an Ecological
Setting Unusual or Unique to the Taxon
Mountain whitefish in the Big Lost
River are found in a closed surface
drainage basin. However, as noted
earlier, mountain whitefish also occur
in isolated populations in sink
drainages in the Bonneville Basin in
Utah and the Lahontan Basin in
California and Nevada. In addition,
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mountain whitefish also occur in other
geographically isolated settings, such as
above barrier waterfalls (e.g., Big Wood
River, Bull River, Thutade Lake, Henry’s
Fork; Whiteley et al. 2006, pp. 27802781) or above saltwater barriers to
dispersal, as on the Olympic Peninsula
(Whiteley et al. 2006, p. 2781).
Therefore, the mere fact that these
mountain whitefish occupy a physically
isolated drainage is not in and of itself
unique, unusual, or significant to the
species as a whole. Although we
acknowledge that Miller (2006, p. 29)
describes the Big Lost River as the most
unique drainage of the upper Snake
River subbasin due to its geological
history, we note that this reference is
comparing the drainage only within the
context of the subbasin in which it
occurs, and not to the entire range of
mountain whitefish. Miller (2006, p. 2)
points out that members of the genus
Prosopium in western North America
‘‘occupy discrete drainage basins most of
which have complex geological
histories.’’ Residence in a discrete
drainage basin with a complex
geological history therefore appears to
be a general characteristic of the genus.
We have no information indicating
that the geological history of the Big
Lost River drainage, even if considered
unique or unusual, has in any way
contributed to a unique or unusual
ecological setting, such that the
whitefish occurring therein are
biologically or ecologically significant to
the species as a whole. As noted above,
there are other populations of mountain
whitefish in closed ‘‘sink’’ drainages
within the range of the species. We have
no information indicating that the Big
Lost River drainage is ecologically
unusual or unique in any other way (for
example, in terms of unique or unusual
prey species, community composition,
water chemistry, pathogens, or
substrate), apart from its geographic
setting, that may serve as an indicator of
the biological or ecological importance
of the population of mountain whitefish
found there in relation to the species as
a whole. The one exception is a
suggestion that the Big Lost River may
be ecologically unusual because
historically it lacked other large fish
species, such as trout; we discuss this
suggestion below.
Gamett (2009b, p. 8) suggests that the
Big Lost River may be unusual due to
the fact that other than mountain
whitefish, the only other large fish
native to the river are sculpin, and all
other mountain whitefish have evolved
in the presence of other large fish such
as trout and suckers. He states that all
other fish species, including several
species of trout, were not introduced
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into the Big Lost River until the arrival
of the first permanent settlers in the late
1800s (Gamett 2009a, pp. 1, 8). We
carefully considered the potential
ecological or biological significance of
this information. If there were some
evidence that in the absence of trout or
other large fish, mountain whitefish in
the Big Lost River had somehow become
specialized or otherwise adapted to this
particular ecological condition in a way
that set them apart from the remainder
of the species, this may be of potential
biological or ecological importance.
There is no information to suggest that
mountain whitefish in the Big Lost
River became specialized or adapted in
this manner. Several species of trout
were introduced to the Big Lost River
more than 100 years ago, with no
apparent effect—behavioral,
morphological, or otherwise—on the
mountain whitefish population.
Mountain whitefish in the Big Lost
River have shown none of the responses
typical of a native species responding to
an unfamiliar invasive species, such as
niche displacement or competitive
exclusion (Mooney and Cleland 2001,
pp. 5446-5451).
We found no information to suggest
that mountain whitefish in the Big Lost
River had become so specialized
following their isolation from the
remainder of the taxon that they are
now incapable of coexisting with trout.
Studies have shown no evidence of
competition between nonnative fish and
mountain whitefish, and it is considered
unlikely that competition has negatively
affected mountain whitefish in the Big
Lost River, since declines in this
mountain whitefish population were
only reported relatively recently, and
were not observed subsequent to the
introduction of trout over 100 years ago
(IDFG 2007a, p. 22). Therefore, although
the information that mountain whitefish
in the Big Lost River were isolated from
trout and other potentially predatory or
competitive fishes up until
approximately 100 years ago is possibly
of some biological interest, we have no
evidence that it represents any
ecological significance of the setting, or
has resulted in any unique or unusual
adaptations or trait shifts in the
mountain whitefish, such that the
population of mountain whitefish in the
Big Lost River would be considered
biologically or ecologically significant to
the species throughout its range.
On the basis of an evaluation of the
best available scientific information, we
have determined that the Big Lost River
does not represent an ecological setting
that is unusual or unique for mountain
whitefish relative to the taxon’s range in
western North America. Other
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populations of mountain whitefish
occur in closed drainage basins within
the range of the species and other
populations of mountain whitefish
occur in settings that are physically or
geographically isolated (and therefore
reproductively isolated) from the
remainder of the taxon. Although
mountain whitefish may have lived in
the Big Lost River since the estimated
time of their physical isolation some
10,000 years ago in the absence of trout
and other large fish, we have no
evidence that this past ecological
condition is of any biological or
ecological significance. There is no
evidence that the introduction of
multiple species of trout to the Big Lost
River over 100 years ago had any effect
on the mountain whitefish population,
suggesting that their previous absence
had not altered the mountain
whitefish’s behavior or ecology in any
biologically significant ways, or resulted
in any locally adapted traits. None of
the information available to us indicates
that the setting of the Big Lost River is
unique or unusual in any other aspect
of its ecology; we have no information
suggesting the Big Lost River is unusual
or unique in any of its ecological
characteristics such as water chemistry,
temperature, substrate, pathogens, or
prey species utilized. We conclude that
mountain whitefish occurring in the Big
Lost River do not occupy an unusual or
unique ecological setting such as to be
biologically or ecologically significant to
the remainder of the taxon to which
they belong. We therefore conclude that
mountain whitefish in the Big Lost
River do not meet the significance
criterion of the DPS policy based on this
factor.
(2) Evidence That Loss of the Discrete
Population Segment Would Result in a
Significant Gap in the Range of a Taxon
Mountain whitefish are found
throughout mountainous areas of
western North America in the United
States and Canada. They are considered
common and widely distributed
throughout the upper Snake and
Missouri rivers to the east and
northeast, the lower Snake and
Columbia rivers to the west and
northwest, and the Bonneville and
Lahontan basins to the south and
southwest. In southern Idaho alone, the
population of mountain whitefish is
estimated to be 4.7 ± 1.8 million, based
on a study of 119,453 km (74,225 mi) of
stream surveys (Meyer et al. 2009, p.
760). The population of mountain
whitefish in the Big Lost River is
estimated to be 12,639 adults,
occupying 135 km (83 mi) of stream
(Garren et al. 2009, p. 6). The fraction
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of the population and its range
represented by the mountain whitefish
in the Big Lost River is very small when
considered relative to the remainder of
the species’ range in southern Idaho.
When compared to the range of
mountain whitefish throughout western
North America, we find that the gap in
the range that would result from the loss
of the single population of mountain
whitefish in the Big Lost River of Idaho
would not be significant, because it is so
very small. We therefore conclude that
mountain whitefish in the Big Lost
River do not meet the significance
criterion of the DPS policy based on this
factor.
(3) Evidence That the Discrete
Population Segment Represents the
Only Surviving Natural Occurrence of a
Taxon That May Be More Abundant
Elsewhere as an Introduced Population
Outside Its Historical Range
This criterion does not apply to
mountain whitefish in the Big Lost
River because it is not a population
segment representing the only surviving
natural occurrence of the taxon that may
be more abundant elsewhere as an
introduced population outside its
historical range. We therefore conclude
that mountain whitefish in the Big Lost
River do not meet the significance
criterion of the DPS policy based on this
factor.
(4) Evidence That the Discrete
Population Segment Differs Markedly
from Other Populations of the Species
in Its Genetic Characteristics
We evaluated information available to
us regarding the genetic characteristics
of mountain whitefish in the Big Lost
River in our evaluation of this
population as a potentially separate
species or subspecies (see ‘‘Evaluation of
Mountain Whitefish in the Big Lost River
as a Species or Subspecies’’ above). Our
conclusions from this evaluation apply
here as well, and we include the above
discussion under this factor by
reference, although under the DPS
policy we measure the evidence against
a slightly different standard (potential
biological and ecological significance to
the species as a whole, as reflected by
marked differences in its genetic
characteristics). Our evaluation of the
best available scientific information, as
detailed above, does not support the
contention that the genetic
characteristics of mountain whitefish in
the Big Lost River differ markedly from
those of other populations relative to
levels of divergence among other
populations of mountain whitefish. On
the contrary, the information indicates
that the genetic distance observed
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between mountain whitefish in the Big
Lost River and surrounding populations
is less than that observed between other
species or subspecies of salmonids to
which it has been compared (Campbell
and Kozfkay 2006, p. 7), and is also less
than that observed between individual
fish within some populations of
mountain whitefish in other areas
(Miller 2006, Figs. 15 and 16). As
detailed above, the evidence indicates
the degree of genetic differentiation
between mountain whitefish in the Big
Lost River and surrounding populations
is no greater than that observed between
many other populations of mountain
whitefish throughout the range of the
species (Campbell and Kofzkay 2006,
Figure 3, p. 8; Miller 2006, pp. 27-35;
Whiteley et al. 2006, p. 2781). When
measuring this evidence against the DPS
standard, we looked for evidence of
marked differentiation of mountain
whitefish in the Big Lost River when
compared to other populations of
mountain whitefish throughout the
range of the species. We conclude the
degree of genetic divergence observed in
this population does not rise to the level
of significance to the taxon as a whole.
As noted above, the most recent
genetic work (Miller 2006, pp. 27-35;
Whiteley et al. 2006, pp. 2780-2781)
indicates there are several physically
isolated populations of mountain
whitefish that, as expected under a
scenario of reduced gene flow, show
some divergence from their presumed
common populations of origin.
Furthermore, the research demonstrates
that most populations of mountain
whitefish sampled have diverged to the
point of possessing unique haplotypes,
and other populations of mountain
whitefish exhibit a greater degree of
genetic divergence than observed in
mountain whitefish from the Big Lost
River (Campbell and Kozfkay 2006, p.
7). Mountain whitefish, in general,
appear to exhibit a high degree of
genetic structure between populations,
as observed in many species of
freshwater fishes (Gyllensten 1985, p.
691; Allendorf and Waples 1996, p. 257;
Whiteley et al. 2006, p. 2783). More
importantly, however, scientific
information to indicate that the genetic
divergence observed in these
populations confers any fitness
advantage or otherwise contributes to
the biological or ecological importance
of this population, in relation to the
taxon as a whole, is lacking. Particularly
when a population has gone through a
presumed bottleneck, as evidenced by
the lack of microsatellite DNA variation
observed in mountain whitefish in the
Big Lost River, the amount of genetic
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distance is expected to increase very
quickly (Hedrick 1999, p. 315). Such
increased distance does not, however,
automatically confer biological
significance in the absence of any
indication of local adaptive differences.
The Service fully supports conserving
the mountain whitefish as a component
of the native biodiversity of the Big Lost
River. However, whether mountain
whitefish in the Big Lost River are
deserving of conservation in the name of
preserving native biodiversity is not the
same question as whether the mountain
whitefish found in the Big Lost River
may qualify as a listable entity under
the Act. Additionally, under the
‘‘significance’’ prong of the DPS policy,
we are required to apply a different and
specific set of criteria. We find that,
based on the genetic information
available and as detailed in our analysis
in the section ‘‘Evaluation of Mountain
Whitefish in the Big Lost River as a
Species or Subspecies’’ above, mountain
whitefish in the Big Lost River do not
differ markedly from other populations
of the species in their genetic
characteristics such that they are
biologically or ecologically significant to
the species as a whole. Rather, all
available information indicates the level
of genetic differentiation is not unusual
for mountain whitefish, when
considered in the context of the species
across its range. We acknowledge that
mountain whitefish in the Big Lost
River may be genetically distinguished
from other nearby populations, but we
do not consider this degree of
divergence to be a marked level of
differentiation, particularly in light of
the fact that other populations of
mountain whitefish, such as those in the
Boise River (Campbell and Kofzkay
2006, Figure 3. p. 8) and Skokomish
River (Miller 2006, Figure 15c, p. 118),
show greater degrees of difference.
We conclude mountain whitefish, in
general, exhibit a high degree of genetic
structure, and the mountain whitefish in
the Big Lost River are not any more
different or significant to the taxon as a
whole than any of several other
populations of mountain whitefish
throughout the species’ range. The
current genetic characteristics likely
reflect a historical population bottleneck
and the overall isolation of the
population, and we have no supportable
evidence of any corresponding
phenotypic divergence that may be
biologically meaningful or indicative of
local adaptation, such that it should be
considered biologically or ecologically
significant to the taxon as a whole. With
the additional consideration that the
authority to list DPSes be used
‘‘sparingly,’’ we conclude that mountain
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whitefish occurring in the Big Lost River
do not meet the significance criterion of
the DPS policy based on this factor, due
to the number of populations rangewide
that exhibit similar characteristics.
DPS Conclusion
Our DPS policy directs us to evaluate
the significance of a discrete population
in the context of its biological and
ecological significance to the remainder
of the species to which it belongs. Based
on an analysis of the best available
scientific and commercial data, we
conclude that mountain whitefish in the
Big Lost River are discrete due to their
physical separation from the remainder
of the taxon. Mountain whitefish in the
Big Lost River do not, however, meet
any of the four identified elements in
the DPS policy for determining
significance, and we have no
information suggesting the population
could otherwise be reasonably justified
as being significant. Because the
mountain whitefish occupying the Big
Lost River fail to meet our significance
criterion for a DPS under our policy, we
conclude this discrete population is not
significant to the taxon to which it
belongs, and therefore does not qualify
as a DPS under the Act.
Listable Entity Determination
We have determined that mountain
whitefish occurring in the Big Lost River
do not constitute a species or subspecies
separate from the more widespread
Prosopium williamsoni. Although the
population is considered discrete, the
available scientific evidence indicates
this population is not biologically or
ecologically significant to the species as
a whole according to the criteria
outlined in our 1996 DPS policy;
consequently this population cannot be
considered a DPS. We therefore find the
mountain whitefish in the Big Lost
River do not qualify as a listable entity
(species, subspecies, or DPS) under
section 3(16) of the Act. Because we
found that the population segment does
not meet the significance element and
therefore does not qualify as a DPS
under the Service’s DPS policy, we will
not proceed with an evaluation of the
status of the population segment under
the Act.
Significant Portion of the Range
Analysis
The Act defines an endangered
species as one ‘‘in danger of extinction
throughout all or a significant portion of
its range,’’ and a threatened species as
one ‘‘likely to become an endangered
species within the foreseeable future
throughout all or a significant portion of
its range.’’ Having determined that the
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mountain whitefish in the Big Lost
River is not a listable entity (species,
subspecies or DPS) under the Act, we
next consider whether the mountain
whitefish in the Big Lost River
constitutes a significant portion of the
species’ range and, if so, whether it is
in danger of extinction or is likely to
become endangered in the foreseeable
future. We consider a portion of a
species’ range to be significant if it is
part of the current range of the species
and is important to the conservation of
the species because it contributes
meaningfully to the representation,
resiliency, or redundancy of the species.
The contribution must be at a level such
that its loss would result in a decrease
in the ability of the species to persist.
The first step in determining whether
a species is endangered or threatened in
a significant portion of its range is to
identify any portions of the range of the
species that warrant further
consideration. The range of a species
can theoretically be divided into
portions in an infinite number of ways.
However, there is no purpose to
analyzing portions of the range that are
not reasonably likely to be significant
and endangered or threatened. To
identify those portions that warrant
further consideration, we determine
whether there is substantial information
indicating that: (1) The portions may be
significant, and (2) the species may be
in danger of extinction there or likely to
become so within the foreseeable future.
In practice, a key part of this analysis is
whether the threats are geographically
concentrated in some way. If the threats
to the species are essentially uniform
throughout its range, no portion is likely
to warrant further consideration.
Moreover, if any concentration of
threats applies only to portions of the
species’ range that are not significant,
such portions will not warrant further
consideration.
If we identify any portions of a
species’ range that warrant further
consideration, we then determine
whether the species is endangered or
threatened in these portions of its range.
Depending on the biology of the species,
its range, and the threats it faces, it may
be more efficient in some cases for the
Service to address the significance
question first, and in others the status
question first. Thus, if the Service
determines that a portion of the range is
not significant, the Service need not
determine whether the species is
endangered or threatened there;
conversely, if the Service determines
that the species is not endangered or
threatened in a portion of its range, the
Service need not determine if that
portion is significant. However, if the
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Service determines that both a portion
of the range of a species is significant
and the species is endangered or
threatened there, the Service will
specify that portion of the range as
endangered or threatened under section
4(c)(1) of the Act.
The terms ‘‘resiliency,’’ ‘‘redundancy,’’
and ‘‘representation’’ are intended to be
indicators of the conservation value of
portions of the species’ range.
Resiliency of a species allows the
species to recover from periodic
disturbance. A species will likely be
more resilient if large populations exist
in high-quality habitat that is
distributed throughout the range of the
species in such a way as to capture the
environmental variability within the
range of the species. It is likely that the
larger size of a population will help
contribute to the viability of the species.
Thus, a portion of the range of a species
may make a meaningful contribution to
the resiliency of the species if the area
is relatively large and contains
particularly high-quality habitat or if its
location or characteristics make it less
susceptible to certain threats than other
portions of the range. When evaluating
whether or how a portion of the range
contributes to resiliency of the species,
it may help to evaluate the historical
value of the portion and how frequently
the portion is used by the species. In
addition, the portion may contribute to
resiliency for other reasons—for
instance, it may contain an important
concentration of certain types of habitat
that are necessary for the species to
carry out its life-history functions, such
as breeding, feeding, migration,
dispersal, or wintering.
Redundancy of populations may be
needed to provide a margin of safety for
the species to withstand catastrophic
events. This does not mean that any
portion that provides redundancy is a
significant portion of the range of a
species. The idea is to conserve enough
areas of the range such that random
perturbations in the system act on only
a few populations. Therefore, each area
must be examined based on whether
that area provides an increment of
redundancy that is important to the
conservation of the species.
Adequate representation insures that
the species’ adaptive capabilities are
conserved. Specifically, the portion
should be evaluated to see how it
contributes to the genetic diversity of
the species. The loss of genetically
based diversity may substantially
reduce the ability of the species to
respond and adapt to future
environmental changes. A peripheral
population may contribute meaningfully
to representation if there is evidence
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that it provides genetic diversity due to
its location on the margin of the species’
habitat requirements.
Applying the process described
above, we first evaluated whether the
population of mountain whitefish
occurring in the Big Lost River
constitutes a significant portion of the
range of the species. As noted earlier,
mountain whitefish are found
throughout mountainous areas of
western North America in Canada and
the United States. In the United States,
they are known to occur in the States of
Washington, Oregon, Idaho, Wyoming,
Montana, Colorado, Utah, Nevada, and
California (NatureServe 2009).
Mountain whitefish are relatively
common and widespread in most river
basins in Idaho (AFS 2007, p. 29), with
stream size documented to be an
important factor influencing both the
distribution and abundance of mountain
whitefish in the upper Snake River
basin (Meyer et al. 2009, p. 762; Maret
et al. 1997, p. 213). Within the State of
Idaho, mountain whitefish are abundant
where they occur. For example, during
a recent survey of 2,043 study sites in
Idaho across 119,453 km (74,225 mi) of
stream in 21 major river drainages in the
upper Snake River basin (excluding the
Big Lost River), 767 sites in 11 of the 21
river drainages were documented to
support mountain whitefish (Meyer et
al. 2009, p. 760). From this survey the
authors also estimated the abundance of
mountain whitefish to be 4.7 ± 1.8
million in southern Idaho, occurring
mostly in streams wider than 15 m (49
ft) (Meyer et al. 2009, p. 764). The
current population of mountain
whitefish in the Big Lost River is
estimated to be 12,639 adults (Garren et
al. 2009, p. 6) occurring in
approximately 135 km (83 mi) of stream.
The mountain whitefish population
occurring in the Big Lost River thus
represents less than 0.5 percent of the
total estimated numbers of mountain
whitefish in southern Idaho, and
occupies approximately 0.1 percent of
the stream miles of the survey.
Extending this comparison to consider
mountain whitefish in the Big Lost
River relative to the taxon throughout its
range in western North America, the
fraction of the species’ total population
represented by mountain whitefish in
the Big Lost River would be extremely
small.
Although the majority of mountain
whitefish occur in riverine
environments, some populations are
restricted to lakes or isolated sink
basins. The fact that mountain whitefish
in the Big Lost River are found in a
geographically isolated drainage is not
significant to the species as a whole, as
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other populations of mountain whitefish
also occur in physically isolated settings
throughout the range of the species,
such as the Lahontan Basin in California
and Nevada, and the Bonneville Basin
in Utah. As described earlier in our DPS
analysis, we could not find any
information that the Big Lost river
drainage is ecologically unusual,
unique, or otherwise significant to the
species as a whole in any way (for
example, in terms of atypical prey
species, water chemistry, or substrate).
Based on the best available information
we have on mountain whitefish, the
population that occurs in the Big Lost
River does not appear to exist in an
unusual or unique ecological setting, or
contain a large portion of the habitat or
individuals relative to the taxon as a
whole. Rather, the Big Lost River
appears to constitute an extremely small
portion of the species’ overall habitat
and number of individuals when
compared to the Upper Snake River
basin population of mountain whitefish,
and even more so when compared to
mountain whitefish rangewide
throughout western North America. We
thus do not consider mountain
whitefish in the Big Lost River to
provide an important component of
resiliency to the species as a whole.
In terms of representation, mountain
whitefish occurring in the Big Lost River
are not recognized as a species or
subspecies by the relevant taxonomic
authorities, State of Idaho, and others
(Nelson et al. 2004, p. 86; IDFG 2009;
ITIS 2009; NatureServe 2009), and the
best available information indicates that
the genetic distance observed between
mountain whitefish in the Big Lost
River and surrounding populations is
substantially less than that observed
between other species or subspecies of
salmonids (Campbell and Kozfkay 2006,
p. 7). Likewise, as discussed above,
information from the most current
genetic assessments of mountain
whitefish does not indicate this
population is markedly different or
unique in terms of its genetic
characteristics, any more so than many
other populations of mountain whitefish
throughout the range of the species. The
available evidence indicates that there is
a high degree of genetic structuring
between populations of mountain
whitefish, as is frequently observed in
populations of freshwater salmonids
(Allendorf and Waples 1996, p. 257;
Miller 2006, p. 25; Whiteley et al. 2006,
p. 2783). The degree of genetic
differentiation between mountain
whitefish in the Big Lost River and
surrounding populations is no greater
than that observed between other
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populations of mountain whitefish
(Campbell and Kozfkay 2006, Figure 3,
p. 8; Miller 2006, pp. 22, 29-30;
Whiteley et al. 2006, p. 2781). We thus
do not consider mountain whitefish in
the Big Lost River to make a significant
contribution to the representation of the
species as a whole.
Finally, mountain whitefish in the Big
Lost River group with the major genetic
assemblage of the Upper Snake River
and are most genetically similar to that
group. We find it unlikely, however,
that mountain whitefish in the Big Lost
River would provide any meaningful
redundancy to the species if other
populations of mountain whitefish in
the Upper Snake River basin were to be
extirpated by a catastrophic event. The
Big Lost River is geographically
separated from the Snake River and
other streams. It is therefore unlikely
that fish in the Big Lost River would be
a significant source of mountain
whitefish to recolonize streams within
the Upper Snake River.
We have determined the mountain
whitefish in the Big Lost River do not
provide a meaningful contribution to
the species as a whole with regard to
redundancy, resiliency, and
representation of mountain whitefish
throughout their range in western North
America. Based upon this
determination, we find the mountain
whitefish in the Big Lost River do not
represent a significant portion of the
species’ range. Having reached this
conclusion, we will not further evaluate
the status of mountain whitefish in the
Big Lost River as a significant portion of
the range of the species.
constitutes our final response to the
petition.
We strongly support ongoing
conservation efforts to restore habitat for
the mountain whitefish and other native
species residing in the Big Lost River,
and to monitor the status, trends, and
threats to this native population of fish.
We emphasize that our determination
that mountain whitefish in the Big Lost
River do not constitute a listable entity
under the Act should in no way
diminish the value of conserving this
population as an important component
of the natural community. We
encourage all interested parties to assist
with the management and conservation
of mountain whitefish in the Big Lost
River basin and to preserve all elements
of native biodiversity in this ecosystem.
We request that you submit any new
information concerning the status of, or
threats to, the mountain whitefish in the
Big Lost River basin to our Idaho Fish
and Wildlife Office (see ADDRESSES
section) whenever it becomes available.
New information will help us monitor
the mountain whitefish in the Big Lost
River basin and encourage their
conservation.
Finding
The primary authors of this document
are staff members of the Idaho Fish and
Wildlife Office of the U.S. Fish and
Wildlife Service (see ADDRESSES
section).
After a thorough review of the best
scientific and commercial information
available, we find that listing the
mountain whitefish in the Big Lost
River of Idaho is not warranted. We
have determined the mountain
whitefish in the Big Lost River are not
a species, subspecies, or DPS as defined
by section 3(16) of the Act, and
therefore are not eligible for listing. In
addition, we have further determined
the mountain whitefish in the Big Lost
River do not represent a significant
portion of the range of the species
Prosopium williamsoni. We therefore
find the mountain whitefish in the Big
Lost River are not eligible for the
protections of the Act. Consequently, we
are not proceeding with an evaluation of
the conservation status of mountain
whitefish in the Big Lost River relative
to the Act’s standards for listing as
endangered or threatened. This finding
concludes our status review and
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References Cited
A complete list of all references cited
in this document is available on the
Internet at http://www.regulations.gov
and upon request from the Idaho Fish
and Wildlife Office (see ADDRESSES
section).
Authors
Authority
The authority for this action is the
Endangered Species Act of 1973, as
amended
(16 U.S.C. 1531 et seq.).
Dated: March 9, 2010.
Daniel M. Ashe,
Acting Director, U.S. Fish and Wildlife
Service.
[FR Doc. 2010–7674 Filed 4–5–10; 8:45 am]
BILLING CODE 4310–55–S
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DEPARTMENT OF THE INTERIOR
Fish and Wildlife Service
50 CFR Part 17
[Docket No. FWS-R2-ES-2010-0022]
[MO 92210-0-0008]
Endangered and Threatened Wildlife
and Plants; 90-Day Finding on a
Petition to List a Stonefly (Isoperla
jewetti) and a Mayfly (Fallceon eatoni)
as Threatened or Endangered with
Critical Habitat
AGENCY: Fish and Wildlife Service,
Interior.
ACTION: Notice of 90–day petition
finding.
SUMMARY: We, the U.S. Fish and
Wildlife Service (Service), announce a
90–day finding on a petition to list a
stonefly (Isoperla jewetti) and a mayfly
(Fallceon eatoni) as threatened or
endangered under the Endangered
Species Act of 1973, as amended. Based
on our review, we find that the petition
does not present substantial information
indicating that listing either of the
species may be warranted at this time.
However, we ask the public to submit to
us any new information that becomes
available concerning the status of, or
threats to, the stonefly or the mayfly or
their habitat at any time.
DATES: The finding announced in this
document was made on April 6, 2010.
ADDRESSES: This finding is available on
the Internet at http://
www.regulations.gov at Docket No.
FWS-R2-ES-2010-0022. Supporting
documentation we used in preparing
this finding is available for public
inspection, by appointment, during
normal business hours at the U.S. Fish
and Wildlife Service, Southwest
Regional Ecological Services Office, 500
Gold Avenue SW, Albuquerque, NM
87102. Please submit any new
information, materials, comments, or
questions concerning this finding to the
above address.
FOR FURTHER INFORMATION CONTACT:
Nancy Gloman, Assistant Regional
Director, Southwest Regional Ecological
Services Office; telephone 505/2486920; facsimile 505/248-6788. If you use
a telecommunications device for the
deaf (TDD), please call the Federal
Information Relay Service (FIRS) at 800877-8339.
SUPPLEMENTARY INFORMATION:
Background
Section 4(b)(3)(A) of the Endangered
Species Act of 1973, as amended (Act)
(16 U.S.C. 1531 et seq.), requires that we
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https://cpw.cvlcollections.org/files/original/288b08998ccb08c3e5857b43e12172b1.pdf
5e85bd440df6c1f65bf389b5aacd121d
PDF Text
Text
COLORADO
Parks and Wildlife
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3a0134e841bc589ad7808a07a50019ff
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Rio Grande Cutthroat Trout
Bayesian Network tutorial
RGCT_BN tutorial
1
�A guide for estimating population persistence using
the Rio Grande Cutthroat Trout Bayesian Network
Manual Version 2.1
May 20, 2019
Kevin B. Rogers, Aquatic Research, Colorado Parks and Wildlife, PO Box 775777, Steamboat
Springs, CO 80477, kevin.rogers@state.co.us
Matt P. Zeigler, New Mexico Department of Game and Fish, Fisheries Management Division, 1
Wildlife Way, Santa Fe, New Mexico, 87507
James J. Roberts, U. S. Geological Survey, Colorado Water Science Center/Fort Collins Science
Center, Fort Collins, Colorado, 80526
Andrew S. Todd, U. S. Geological Survey, Crustal Geophysics and Geochemistry Science
Center, Box 25046, Mail Stop 964D, Denver Federal Center, Denver, Colorado, 80225
Kurt D. Fausch, Department of Fish, Wildlife, and Conservation Biology, Colorado State
University, Fort Collins, Colorado, 80523
____________________________________________________________________________
Overview
In the manuscript “Predicting persistence of Rio Grande Cutthroat Trout populations in an
uncertain future” Ziegler et al. (In press) present a Bayesian network (BN) model for evaluating
persistence in Rio Grande Cutthroat Trout (RGCT; Oncorhychus clarkii virginalis) populations.
This model was developed using Netica software (Norsys Software Corporation, Vancouver,
British Columbia) because of its straightforward and intuitive graphical user interface. It is
designed to be used by managers to not only estimate probability of persistence at different time
horizons, but also to evaluate the implications of employing different management strategies on
future persistence. This manual is provided to help facilitate that process.
Installing Netica
The software needed to run the RGCT_BN model can be installed off the Norsys website:
https://www.norsys.com/netica.html. Although there is a full featured free version of Netica for
small BNs, our model is unfortunately too large to run on it. The full version of Netica must
therefore be purchased online to run this RGCT_BN model.
RGCT_BN tutorial
2
�Loading the model file
Contact the authors to obtain the .neta model file. Double clicking on the file on a computer with
Netica installed will open the network which is ready to run (no further preparation necessary).
The opened network should look something like:
where parent nodes are colored either green, pink, or yellow. Most (green) are derived from the
RGCT assessment database (Alves et al. 2008). Those that can be influenced by management
actions are shown in pink, while yellow ones are modeled climate related nodes (see Appendix A
in Zeigler et al. In press). The final node shown in blue represents the probability of persistence
for that population given input parameters.
RGCT_BN tutorial
3
�Running the network
Network features are best explained with a worked example. Consider the Cat Creek
conservation population of RGCT in the headwaters of the Upper Rio Grande GMU for which
the following input parameters apply:
Patch Size (km) - 7.37 km
Barrier Presence - Partial
Population Connectivity - Isolated
Proximity of Competitor Source Population - Far (>10 km)
Proximity of Hybridizing Source Population - Far (>10 km)
Proximity of WD Source - Far (>10 km)
Nonnative Control - None
Demographic Support - None
Wildfire/Debris Flow Risk - Moderate
Drought Refugia Presence - Present
Evidence of Intermittency - Yes
Adult Population Estimate - 2868
Ne/N Ratio - 0.25
Baseflow Discharge - 0.0429 cms (Current); 0.0284 cms (2080)
M30AT - 13.16 C (Current); 14.16 C (2080)
MWMT - 16.97 C (Current); 17.38 C (2080)
For each input node, right click
(control click) on the node itself to
bring up the contextual menu, then
select “Enter Finding” and select the
state that is appropriate for that node.
RGCT_BN tutorial
4
�Once the state is changed, the ramifications of that change
are perpetuated through the network immediately, and the
effect of that change on the estimated probability of
persistence can be observed.
If entering a continuous value (e. g. modeled
maximum weekly maximum temperature MWMT), select “Numeric Value” following
“Enter Finding” from the dropdown menu
and enter that value in the pop-up box.
If there is some uncertainty as to which node
state is appropriate, a probability for each state
can be assigned by selecting “Enter Finding”,
then “Likelihood”, then populating the resulting
pop-up boxes (one for each state) with a value
between 0 and 1.
Where no information for a node exists, you can leave the
default of complete uncertainty (equal weight to each state),
thereby perpetuating that uncertainty through the network.
This can be achieved with the “Unknown (Retract)”
command from the “Enter Finding” dropdown.
RGCT_BN tutorial
5
�For the Cat Creek example, probability of persistence drops precipitously (down to 20.6%) when
values for 2080 are entered. Changing the Barrier node state to “Complete” from “Partial”
mitigates that drop with persistence remaining
high (at 79.5%), illustrating the merits of
employing that management action. Explore
implications of additional management actions on
persistence by modifying states of parent nodes
shown in pink.
Batch mode
If population persistence needs to be estimated for many populations, a case file can be
developed containing all the relevant information for each population. These are best prepared in
Excel, then converted to ASCI text. Additional information on generating and formatting case
files can be found on the web at : https://www.norsys.com/WebHelp/NETICA.htm. Once
created, the file can be processed within Netica using the “Cases” dropdown menu. Every case
(i.e., population) will be analyzed and the output saved to a text file.
Modifying or building your own network
Netica provides both a help system and context help from within the application to assist with
developing your own Bayes network or modifying this one. Additional information on building
networks can be found on the web at: https://www.norsys.com/WebHelp/NETICA.htm
Literature cited
Alves, J. E., K. A. Patten, D. E. Brauch, and P. M. Jones. 2008. Range-wide status assessment of
Rio Grande Cutthroat Trout (Oncorhynchus clarkii virginalis): 2008. Colorado Division
of Wildlife, Fort Collins. Available: http://cpw.state.co.us/learn/Pages/
ResearchRioGrandeCutthroatTrout.aspx (March 2018).
Zeigler, M. P., K. B. Rogers, J. J. Roberts, A. S. Todd, K. D. Fausch. In press. Predicting
persistence of Rio Grande Cutthroat Trout populations in an uncertain future. North
American Journal of Fisheries Management.
RGCT_BN tutorial
6
�
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2011
SONAR SURVEYS
Prepared by:
Michael Avery
03 Feb 2012
�Some notes on the 2011 summer sonar surveys:
I am the Research Associate with Colorado State University working with Jesse Lepak in the Colorado
Parks and Wildlife Research Division and with the help of Jesse and Estevan Vigil was able to complete
numerous historical surveys and some research surveys of Granby (late) and Horsetooth (Sep and Nov).
CPW coordinated with Wyoming Fish and Game to conduct a parallel survey of Horsetooth to evaluate
sounder setup and the use of a side scan sounder run simultaneously with the down looking transducer.
This event gathered a lot of data because of the increase in Rainbow Smelt since our shakedown survey
we conducted in the month of June.
Table 1.- Reservoirs surveyed in 2011 with hydroacoustics are listed along with survey date, reservoir
surface elevation (ft.) and crew.
Reservoir
Survey date
Cheesman
30-Jun-11
Vallecito
29-Jul-11
McPhee
30-Jul-11
Blue Mesa
31-Jul-11
Eleven Mile
1-Aug-11
Cheesman
2-Aug-11
Dillon
24-Aug-11
Green Mountain 25-Aug-11
Blue Mesa
28-Aug-11
Granby
29-Aug-11
Wolford
30-Aug-11
Williams Fork
31-Aug-11
Horsetooth
26-Sep-11
Carter
27-Sep-11
Granby
11-Oct-11
Horsetooth
8-Nov-11
Granby
16-Nov-11
Elevation (ft)
6841.09
7664.9
6916.9
7516.8
8597.6
6840.9
9017.1
7948.1
7512.4
8277.6
7488.2
7804.5
5405.7
5712.6
8272.8
5402.8
8269.4
Crew
Avery, Lepak
Avery, Lepak, Vigil
Avery, Lepak, Vigil
Avery,Lepak,Brauch,Matt
Avery, Lepak, Vigil,Cathcart
Avery, Lepak, Vigil
Avery, Lepak
Avery, Lepak
Avery, Lepak
Avery, Lepak, Vigil, Rogers
Avery, Lepak
Avery, Lepak
Avery, Lepak, Davies
Avery, Lepak, Black,
Avery, Lepak
Avery, Lepak, Morgan
Avery, Stacy
Specific comments: MCA reviews in red. KBR notes.
�Williams Fork CDOW-2010-M243-1xd-15degP1_KBR
T1 (K2432054) – clean – all targets look legit, best cut about 23m
T2 (K2432132) – clean. Some bubble tracks but not enough to worry about; no clear cut opportunity
Reanalyze all previous transects just looking at fish between 10-25m – really could have used 23m but probably
more difficult to process density numbers so stuck with 25? – need to revisit as break is really at 23m – not for
all
Really need to deliberate when to do this survey – 2007 had adults in COD by dam – as did single 2008 fish – yet
all fish captured in 2009 were immature – would it be better to do this in August? Better separation between
kokanee and lake trout; Could we do this survey in July? Would the lake stratify? – recommend doing this
survey throughout the summer – see if stratification necessary
Not as critical to crop T2 since shallow – not as many lake trout there as over in T1
Granby CDOW-2010-M243-1xd-15degP1_KBR
Would be good to go back and set a depth threshold on several transects from each year and just analyze those
targets within the appropriate dB range and between say 10-25m – how does that compare to the strength of
the run? Really need to set nets in Granby – on thermocline and at depth to confirm if deep targets are all lake
trout
Need to rewrite HAcK with multiple depth and size filters – reprocess to pull out spawners
Redid this looking at 20-45 bin? Fish above 25m – seemed to help the r-square
Would also be good to look at numbers of targets below 25m to see if any evidence for increase in lake trout
numbers in recent years
In 2010 did an analysis of fish above 25m – in both 2010 and 2011, that cutoff really should have been at 20m;
25m may have been more appropriate in 2006
T10 (K2412105) – Checked in Echoscape - clean,completed MCA 11/16
T9 (K2412125) Clean, fish on bottom, some noise flats on bottom.
T8 (K24121450) Clean, noise flats on bottom.
T7 (K2412208) Clean, couple noise flats.
T6 (K2412223) Clean, noise on bottom Some depth seperation around 10-12m,.
T5 (K2412241) Clean, noise on bottom Few fish off the bottom.
T4 (K2412302) Clean, bottom noise in what looks like a channel of sorts. One big fish CAME UP AT 80cm, verified
though echoscape.
T3 (K2412323) Clean, bottom noise on slopes
T2 (K2412344) Clean no noise
T1 (K2420006) Clean few fish
11 MILE August 01,2011 CDOW-2010-M243-1xd-15degP1_KBR
T1 (K2132318) Clean, shallow, few fish.
T2 (K2132254) Had to clean two bottom spikes, bottom noise showed on echoscape. cleaned FSHreader.
T3(K2132235) Cleaned a fish outa file, bottom looks good. There is a noise bloom on bottom around ping 900.
Quite a few stacked fish, they are are good in echoscape.
T4(K2132212) Had to groom out the first depth, lost bottom. Some bottom noise on depth xsitions. Cleaned a
19.0dB on fish file, clean.
�T5(K2132156) Some niose towers, there are fish in there, lotsa fish on the other side of a drop off. Looked into a
31dB tgt, it’s valid- left in.
Blue Mesa
Ran two sessions on Blue Mesa this year to explore moving standard transect to later
inthe year (fewer adults present in main basin)
Only ran transects in Sapinero and Cebolla again this year
Blue Mesa July – July 31, 2011 – new moon – CDOW-2010-M243-1xd15degP1_KBR.CFG
T1 (K2122145) – Clean 0 at start and 510 around 4250, review in Echoscape suggests 21 ottoms and a couple of
missed tracked fish due to tracking window limitations; no legit fish below 45 m – use filter in HAcK; also deleted
half dozen bogus targets in 30-50m depths
T2 (K2122208) – Clean in Echoscape
T3 (K2122234) – Clean in Echoscape – couple of noise towers at end
T4 (K2122255) – Echoscape review – lost bottom; noise tower at start; lost bottom 5x in Echoscape; only 1 in
HAcK – fixed; deleted targets below 70m after Ping 500 (about a dozen)
T5 (K2122318) – Cleaned 4 lost bottoms in HAcK – many more in Echoscape; filter targets below 50m after
inspect in Echoscape
T6 (K2122314) – Filter below 50m from Echoscape, otherwise clean
T7 (K2130032) – Cleaned 0 at start; look like legit perch type towers at around Ping 3500
T8 (K2130051) – Cleaned 510 around Ping 1439
T9 (K2130111) – What happened here? In Echoscape, file ends at 11600 but no echoes from 5730 to 11400 –
maybe stopped acquiring but didn’t close file? Only 5804 pings in August survey and about 5900 here – so
maybe OK; extra start/stop in both BOT and FSH that I deleted
T10 (K2130133) – Clean in Echoscape, but lots of noise/perch towers – look more like noise – may want to
delete
T11 (K2130153) – Double and lost bottom at start in Echoscape – fixed and deleted fish targets associated with
double bottom; noise towers around 2250
T1 (K2122145) KBR helped clean the start and showed me how to crop out the lost bottoms, didn’t use filters for
depth. Saved with 5cm cutoff, saved as BMRT1m
T2 (K2122318) Clean in echoscape.
T3 (K2122234) Clean in echoscape.
T4 (K2122255) Lost bottoms cleaned, saw the the noise towers, used Botmod files for bot and fsh.
T5 (K2122318) Used Botmod files, filter below 50m, just noise. Culled fish # 32 and 138 TS >19.
T6 (K2122314) Clean
T7 (K213032) clean in echoscape, saw the towers of noise, think density of fish causes this, filter >50m lose a few
fish 7 or 8 in the noise.
T8 (K2130051) cleaned 510, little noise on rises
T9 (K2130111) saw the end of file, weird, going with KBR mod files, some noise at bottom – couple fish in there.
T10 (K2130133) clean in echoscape, has the noise towers on bottom,
T11 (K2130153) saw the lost bottom, noise towers here again – there are fish in the top of the towers.?
Blue Mesa August – August 28, 2011 – new moon – CDOW-2010-M243-1xd15degP1_KBR.CFG
T1 (K2402220) – This had 8+ lost bottoms in Echoscape? – looks clean now in HAcK – same as last year; had to
delete Fish#12, 118, 146, 148, 151, 152, 153, 154 = large targets at depth; probably should have checked Fish#12
before cutting him – ckd in Echoscape – bogus (good cull)
�T2 (K2402241) – Ckd in Echoscape – delete Fish 84, 142, 143, 149; lost bottom 2x in Echoscape but BOT file OK
T3 (K2402306) – Ckd in Echoscape – large fish deep could be legit – left as is; lost bottom in Echoscape but not in
BOT file
T4 (K2402326) – Cleaned 510 at 4910
T5 (K2402350) – 7 lost bottoms in Echoscape but only 2 in HAcK; Delete Fish 96, 114; small targets at depth
could be legit (from Echoscape review)
T6 (K2410012) – Cleaned 510 toward end – otherwise looks clean
T7 (K2410103) – Cluster near bottom – perch cluster? At ping 3750; Clean 0 at start
T8 (K2410123) – Cleaned 510 and 0 at start
T9 (K2410143) – Cleaned 510; could there be perch towers at end? Otherwise clean in Echoscape
T10 (K2410204) – Clean 0 at start; perch towers/noise (trees?)
T11 (K2410224) - Delete all fish prior to Ping 965 as this was double bottom – also had to halve all depths up to
965 in BOT file, otherwise file OK (had same problem last year)
BMR August 28,2011 NEW MOON CDOW-2010-M243-1xd15degP1_KBR
T1 (K2402220) Looked at bot file, was saved over raw file, I added .mod to file ext. Checked the fish cull data and
culled fish #49 @ 65m, and #156 boggus fish. Noise on bottom xsitions, some fish in with the noise – seems like
the fish are on the top of the noise.
T2 (K2402241) OK’d deleting 49,142,143,149…. Also deleted fish # 171 and 212/ 213 – sitting on bottom saw
noise no good track.
T3 (K2402306) Bottom clean in FSH, echoscape lost bottom couple times. Cleaned fish #155 and 187 bottom
noise, bottom noise suspended off bottom. Cleaned fish #89, 21 ,219 and 221 for TS > -29, verified with
echoscape. Left the last six or so fish mixed in with the noise towers.
T4 (K2402326) Cleaned bottom, some noise flats with fish on upper meter, other bottom noise on depth
xsitions. NO high TS.
T5 (K2402350) Used BOTmod file, I looked at fish 96 and 114 >TS culled. echoscape showed small fish in the top
meter of a noise bloom – good.
T6 (K2410012) Fish 15 -28dB, checks with echoscape GOOD FISH. Some fish in with the bottom noise, clean.
T7 (K2410103) Cleaned bottom at start, noise bloom with depth xsition! Noise towers with fish throughout
(ping3750) depth range 53m – 62m, at least a dozen fish in there.
T8 (K2410123) Cleaned 510 at start. FSH file clean.
T9 (K2410143) Clean in echoscape, fish towers at end of run, TS’s in the 40’s, echoscape separated fish, I would
call one fish based on TMA and depth and echoscape called 3 fish?
T10 (K2410204) Bottom noise towers with fish in them, trees would be a good guess, looks like Xmas. Again –
echoscape called multiple fish and I’d call one fish! Culled fish #160 -30dB, too close too bottom and on edge of
beam with 4 pings.
T11 (K2410224) used KBR bot file, bummer too – there were fish in there.
Dillon Aug 24,2011 CDOW-2010-M243-1xd-15degP1_KBR
Cal File K2362016 Cal file echoscape cal @ -40.05dB, didn’t get all quadrants in full, will hafta get a better cal
later. Run xsects in reverse.
T7 (K2362124) Cleaned 1st bottom. One fish came in at -36dB, left them, looked good.
T6 (K2362143) Some bottom noise on xsition, clean.
T5 (K2362206) Lost bottom at beginning, averaged bottom. Two fish were deleted in the lost bottom a -17 and a
-21dB. Both files mod.
�T4 (K2362254) Cleaned up the bottom file, averaged the bottom, there were two fish detected above this point.
Took two -16dB tgts out of fsh. Cleaned.
T3 (K2362254) cleaned two FSH out, and Bottom losses. Clean
T2 (K2362321) Clean, some noise on bottom xsitions.
T1 (K2362346) Cleaned 1st bottom. Few fish.
Green Mnt 25Aug2011 CDOW-2010-M243-1xd-15degP1_KBR
T1 (K2372036) cleaned 2 510, fsh file looked clean
T2 (K2372059) Clean in echoscape, noise at bottom transitions with depth
T3 (K2372127) cleaned a 510, echoscape looked good.
T4 (K2372152) cleaned the beginning depth, echoscape looks good.
T5 (K2372216) Clean in echoscape.
Vallecito 2011 CDOW-2010-M243-1xd-15degP1_KBR
Transects were run in reverse.
T1 (K2102246) Clean in echoscape
T2 (K2102227) Clean in echoscape, cleaned 1st depth in reader.
T3 (K2102208) Clean in echoscape
T4 (K2102144) had a bottom drop out in echoscape but not in FSHreader, clean, lots of fish.
McPhee 2011 CDOW-2010-M243-1xd-15degP1_KBR
T1 (K2112213) clean, couple fish deep, verified through echoscape, definite LD @13m
T2 (K2112241) cleaned 1st bottom, clean on echoscape
T3 (K2112300) cleaned 1st bottom, noise along bottom at rises and falls. Echoscape showed a lost bottom,
however FSHreader showed clean bottom. One fish tower at ping 1818, echoscape showed multiple fish on top
of each other – left them in.
T4 (2112326) Clean
T5 (K2112348) Clean
T6 (K2120017) Clean
Horsetooth CDOW-2010-M243-1xd-15degP1_KBR
Ran two xsects down the middle from the swim beach, last two files auto saved 7.4Km. Used ACCESS file to
determine start/ stop, convert Lat/Long into UTM with www. T1 (K2702017) Averaged bottom at start.
Cleaned a -20dB fish ping 137.
T2 (K2702034) Clean in echoscape, over 9400 fish, taking some time in compute.
T3 (K2702134) this is the file that auto saved after 60mins, used UTM from conversion Lat/Long. Echoscape
looks good, 4648 fish over this xsect..
�Carter CDOW-2010-M243-1xd-15degP1_KBR
UTM transects are not correct in GPS file. Used the UTM’s from the boat. Need to look into this!
T1 (K2712016) Lost bottom – halved the bottom and saved. Two fish detected in the bottom loss mess KEPT #10
and 56, culled out to ping 1170.
T2 (K2712039) Lost bottom – halved the bottom and saved. Kept four fish out to ping 1200 something, #43, 45,
66 and 80. Noise mid depth at end of run, can’t see any fish in echoscape.
Wolford Aug 30,2011 Cal file CDOW-2010-M243-1xd-15degP1_KBR
Ran xsects out of order– going to limit the transects to WDT0 to WDT1 which is the run down to the damn pump
house.
T1 (K2422157) Clean in Echoscape ran with the new Strata2.1 and Interpret Fish 8.95 – looks good. Ran
summary OK
CHEESMAN CDOW-2010-M243-1xd-15degP1_KBR
Ran out of order, analyzed 0 to 6. Could not find the original data sheet, took UTM off of access and converted
with program Pat sent me in Xcel.
T1 (K1820106) Cleaned bot file false bottoms, fsh file looks good, one fish around 44cm, verified. Some bottom
noise with fish mixed in, left in.
T2 (K1820052) Cleaned a 510 out, fsh file OK
T3 (K1820041) Cleaned the start, Looks good in Echoscape. Few fish.
T4 (K1820026) looks good in Echoscape some noise on bottom.
T5 (K1820010) Cleaned 510, echoscape has some noise on transitions, and two more lost bottoms, FSH reader
didn’t read.
T6 (K1812359) Clean run shows layer of fish 15-25m.
CDOW-2010-M243-1xd-15degP1_KBR 02Aug 2011
Ran out ORDER analyzed 0-6.?
(T1) K2142325 Cleaned 510 at start. Deleted fish 1 and 2 > TS. Echoscape checked well.
(T2) K 2142312 FSH/Bot files look good, some noise at bottom transitions.
(T3) K2142302 echoscape checks, file was stopped and had to delete lines in .FSH and .BOT files.
(T4) K214245 Echoscape checks, air bubbles coming off the bottom. Smaller fish <5cm btwn 10-15m.
(T5) K2142233 Deleted fish #17 >15dB, Fish #75 -28.77, checked in echoscape good trace, left in. Noise at
bottom transitions.
(T6) K2142223 looks good, smaller fish.
Taylor
not surveyed in 2011
Ruedi
not surveyed in 2011
�Keep in mind that I am using start and stop UTMs to determine transect length. Jill and Harry used 5
second GPS locations - their transects will therefore appear longer (in some instances much longer).
New version of HAcK will allow distance calculation following this approach – the problem will be trying
to standardize with transects where communication with the GPS was not working – a problem that is
more common than you would think.
Would still like to see us get better bottom profiles for the "dead pool" in BMR – perhaps should spend
the time to map it with the sounder in 2012!
���INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT1m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT2m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT4m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT5m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT3m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT6m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT7m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT8m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT9m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT10m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011July:2011BMRT11m.out
Total length of transects (m): 18043
Number prey/acre: 2.347
95%CI (1.707, 2.987)
Biomass prey/acre (kg): 0.002
95%CI (0.001, 0.002)
Total prey biomass (MT): 0.015
95%CI (0.011, 0.018)
Number predators/acre: 31.554
95%CI (25.121, 37.987)
Biomass predators/acre (kg): 1.684
95%CI (0.901, 2.467)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
-0.000005
-10
-0.000003
-15
0.000005
-20
0.000017
-25
0.000015
-30
0.00001
-35
0.000007
-40
0.000004
-45
-0.000004
-50
-0.000007
-55
-0.000003
-60
-0.000001
-65
0
-70
0
-75
-0.000004
-80
0
-85
0
-90
0
-95
0
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0.000011
0.000007
0.000017
0.00003
0.000033
0.000025
0.00002
0.000014
0.000008
0.000005
0.000003
0.000001
0
0
0.000004
0
0
0
0
0
0.000027
0.000017
0.000029
0.000043
0.000051
0.000039
0.000033
0.000025
0.00002
0.000017
0.000009
0.000003
0
0
0.000012
0
0
0
0
0
-0.000002
-0.000003
0.000008
0.000023
0.000031
0.000018
0.000007
0.000004
-0.000007
-0.000007
-0.000007
-0.000002
0
-0.000003
-0.000004
0
0
0
0
0
0.000016
0.000007
0.000022
0.00004
0.000048
0.000032
0.000027
0.000016
0.000012
0.000005
0.000006
0.000002
0
0.000002
0.000004
0
0
0
0
0
0.000035
0.000017
0.000036
0.000057
0.000066
0.000045
0.000048
0.000029
0.000032
0.000017
0.000018
0.000006
0
0.000007
0.000012
0
0
0
0
0
-0.006951
0.001535
0.004151
0.009139
0.0102
0.007574
0.005323
0.006161
-0.003489
-0.008233
-0.014654
-0.031946
-0.002148
-0.006313
-0.003898
-0.000242
0
0
0
0
0.008346
0.00604
0.01917
0.021404
0.021412
0.01429
0.014597
0.039524
0.012441
0.018684
0.02585
0.029583
0.003363
0.004469
0.002482
0.000154
0
0
0
0
0.023643
0.010545
0.034189
0.033669
0.032624
0.021006
0.023871
0.072888
0.028371
0.0456
0.066354
0.091113
0.008874
0.015251
0.008861
0.00055
0
0
0
0
0.000035
0.000117
0.000241
0.000468
0.000504
0.000246
0.000131
0.000056
-0.000009
0.000008
0.000002
-0.000038
0.000003
-0.000003
-0.000039
-0.000003
0
0
0
0
0.000085
0.000178
0.000346
0.000612
0.000606
0.000396
0.00025
0.000204
0.000201
0.000226
0.000184
0.000113
0.000016
0.000008
0.000027
0.000002
0
0
0
0
0.000135
0.000239
0.000452
0.000755
0.000707
0.000547
0.000369
0.000352
0.00041
0.000445
0.000365
0.000265
0.000028
0.000019
0.000092
0.000008
0
0
0
11
11
11
11
11
11
11
11
11
11
11
11
10
8
6
6
6
5
4
2
Total per cubic meter
0.000009
0.000013
0.000017
0.000011
0.000018
0.000024
0.006234
0.016936
0.027638
0.000144
0.000255
0.000365
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/15/11 at 2:57 PM
Printed on 11/16/11 at 8:53 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
298696
297347
START UTM Y
END UTM Y
4258605
4259578
PREDATOR/PREY
CUTOFF (cm)
1
-40.0
-10
-50.0
TVG 40logR
-20
-20
-60.0
NONE
-30
-30
-40
-40
ALL
-50
-50
DEL>0
-60
-60
USE INT OR BOT
-70
-70
-80
LENGTH (cm)
-30.0
PREDATOR
-10
BOT
10
-10.0
5.0
INT
35
0.0
0
COLUMN 9
Length (cm)
DEPTH (m)
0
40logR
Depth
Filter
-20.0
2011
FISH PER ACRE
PREY
No Filter
-70.0
-80.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1663
139
0
-80
0
1
0 2 4 6 8
Blue2011:Blue2011July:K2122145.FSHModm
OUTPUT
Blue2011:Blue2011July:K2122145.FSHModm
Transect length (m): 1663 Total pings: 5995
Number prey/acre: 2.035
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.014
Number predators/acre: 24.801
Biomass predators/acre (kg): 1.367
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000583 0.000219
-15.000000 0.000026 0.000026 0.016288 0.000314
-20.000000 0.000041 0.000041 0.035836 0.000630
-25.000000 0.000033 0.000066 0.016212 0.000581
-30.000000 0.000028 0.000028 0.003203 0.000155
-35.000000 0.000025 0.000025 0.007049 0.000153
-40.000000 0.000013 0.000013 0.082753 0.000089
-45.000000 0.000000 0.000000 0.000012 0.000012
-50.000000 0.000000 0.000000 0.000000 0.000000
-55.000000 0.000000 0.000000 0.000089 0.000044
-60.000000 0.000000 0.000000 0.000168 0.000048
-65.000000 0.000000 0.000000 0.000000 0.000012
-70.000000 0.000000 0.000012 0.000111 0.000025
-75.000000 0.000000 0.000000 0.000000 0.000000
-80.000000 0.000000 0.000000 0.000000 0.000000
-85.000000 0.000000 0.000000 0.000000 0.000000
-90.000000 0.000000 0.000000 0.000000 0.000000
-95.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000008 0.000010 0.008567 0.000101
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
70000
65000
60000
55000
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/15/11 at 2:57 PM
Printed on 11/16/11 at 10:30 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
297356
298977
START UTM Y
END UTM Y
4259609
4260696
PREDATOR/PREY
CUTOFF (cm)
PREY
2
0
0
5.0
-10
-10
TVG 40logR
-20
-20
NONE
-30
-30
-40
-40
-50
-50
-60
-60
USE INT OR BOT
-70
-70
INT
BOT
-80
-80
40logR
COLUMN 9
ALL
DEL>0
0
1
Depth
Length (cm)
35
10
Filter
DEPTH (m)
0.0
-10.0
LENGTH (cm)
-20.0
-30.0
2011
FISH PER ACRE
No Filter
PREDATOR
-40.0
-50.0
-60.0
-70.0
-80.0
-90.0
0.0
0 2 4 6 8
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1952
238
0
Blue2011:Blue2011July:K2122208.FSH
OUTPUT
Blue2011:Blue2011July:K2122208.FSH
Transect length (m): 1952 Total pings: 7044
Number prey/acre: 1.964
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.011
Number predators/acre: 27.341
Biomass predators/acre (kg): 1.346
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000559 0.000155
-15.000000 0.000000 0.000000 0.010313 0.000200
-20.000000 0.000017 0.000035 0.015092 0.000485
-25.000000 0.000057 0.000057 0.026492 0.000722
-30.000000 0.000012 0.000012 0.017753 0.000420
-35.000000 0.000044 0.000087 0.037847 0.000513
-40.000000 0.000029 0.000049 0.024945 0.000214
-45.000000 0.000000 0.000000 0.045736 0.000071
-50.000000 0.000000 0.000000 0.000059 0.000008
-55.000000 0.000000 0.000000 0.000095 0.000055
-60.000000 0.000000 0.000000 0.000000 0.000000
-65.000000 0.000000 0.000000 0.000070 0.000014
-70.000000 0.000000 0.000000 0.000000 0.000000
-75.000000 0.000006 0.000006 0.000000 0.000006
-80.000000 0.000000 0.000000 0.000924 0.000013
-85.000000 0.000000 0.000000 0.000000 0.000000
-90.000000 0.000000 0.000000 0.000000 0.000000
-95.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000008 0.000012 0.009255 0.000125
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
70000
65000
60000
55000
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/3/12 at 2:18 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
299005
299309
START UTM Y
END UTM Y
4260705
4262250
PREDATOR/PREY
CUTOFF (cm)
10
LENGTH (cm)
-20.0
2011
-30.0
PREDATOR
-40.0
5.0
-10
-10
-50.0
TVG 40logR
-20
-20
-60.0
NONE
40logR
-30
-30
-40
-40
ALL
-50
-50
DEL>0
-60
-60
USE INT OR BOT
-70
-70
INT
BOT
-80
-80
1
35
-10.0
0
0
Length (cm)
0.0
0
COLUMN 9
Depth
Filter
DEPTH (m)
3
FISH PER ACRE
PREY
No Filter
-70.0
-80.0
0.0
0
2
4
6
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1575
128
0
Blue2011:Blue2011July:K2122234.FSH
OUTPUT
Blue2011:Blue2011July:K2122234.FSH
Transect length (m): 1575 Total pings: 5806
Number prey/acre: 0.893
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.008
Number predators/acre: 22.373
Biomass predators/acre (kg): 0.786
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
75000
70000
65000
Predator/prey cutoff: 5.0 cm
60000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
55000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000539 0.000154
-15.000000 0.000000 0.000000 0.002429 0.000248
-20.000000 0.000043 0.000043 0.005641 0.000493
-25.000000 0.000000 0.000000 0.019591 0.000561
-30.000000 0.000045 0.000045 0.030277 0.000282
-35.000000 0.000000 0.000000 0.006979 0.000180
-40.000000 0.000000 0.000000 0.018991 0.000125
-45.000000 0.000000 0.000000 0.002794 0.000041
-50.000000 0.000000 0.000000 0.000000 0.000000
-55.000000 0.000000 0.000000 0.000000 0.000000
-60.000000 0.000000 0.000000 0.000249 0.000021
-65.000000 0.000000 0.000000 0.018077 0.000046
-70.000000 0.000000 0.000000 0.025416 0.000016
-75.000000 0.000000 0.000000 0.000000 0.000000
-80.000000 0.000000 0.000000 0.000000 0.000000
-85.000000 0.000000 0.000000 0.000000 0.000000
50000
Total per cubic meter
0.000000 0.000005 0.000005 0.008756 0.000116
10000
45000
40000
35000
30000
25000
20000
15000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/15/11 at 2:57 PM
Printed on 11/22/11 at 10:56 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
299286
300093
START UTM Y
END UTM Y
4262244
4260624
PREDATOR/PREY
CUTOFF (cm)
2011
LENGTH (cm)
-30.0
PREDATOR
-40.0
-10
-10
-50.0
TVG 40logR
-20
-20
-60.0
NONE
40logR
-30
-30
-40
-40
ALL
-50
-50
DEL>0
-60
-60
USE INT OR BOT
-70
-70
-80
10
-20.0
5.0
BOT
35
-10.0
0
INT
Length (cm)
0.0
0
COLUMN 9
Depth
Filter
DEPTH (m)
4
FISH PER ACRE
PREY
No Filter
-70.0
-80.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1810
194
0
-80
0
1
2
0
5
10
Blue2011:Blue2011July:K2122255.FSHmod
OUTPUT
Blue2011:Blue2011July:K2122255.FSHmod
Transect length (m): 1810 Total pings: 6456
Number prey/acre: 2.921
Biomass prey/acre (kg): 0.003
Total prey biomass (MT): 0.023
Number predators/acre: 25.810
Biomass predators/acre (kg): 1.359
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000056 0.000056 0.000112 0.000112
-10.000000 0.000000 0.000000 0.001942 0.000100
-15.000000 0.000024 0.000024 0.005261 0.000168
-20.000000 0.000037 0.000037 0.007970 0.000485
-25.000000 0.000046 0.000046 0.016544 0.000778
-30.000000 0.000000 0.000013 0.008358 0.000337
-35.000000 0.000034 0.000045 0.014437 0.000181
-40.000000 0.000031 0.000031 0.146130 0.000204
-45.000000 0.000000 0.000000 0.003762 0.000020
-50.000000 0.000000 0.000000 0.000183 0.000027
-55.000000 0.000000 0.000000 0.001393 0.000157
-60.000000 0.000000 0.000000 0.000032 0.000008
-65.000000 0.000000 0.000000 0.000182 0.000023
-70.000000 0.000000 0.000000 0.001285 0.000007
-75.000000 0.000000 0.000000 0.000000 0.000000
-80.000000 0.000000 0.000000 0.000000 0.000000
-85.000000 0.000000 0.000000 0.000000 0.000000
-90.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000009 0.000010 0.012825 0.000122
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
85000
80000
75000
70000
65000
60000
55000
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/19/12 at 2:09 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
300115
301535
START UTM Y
END UTM Y
4260610
4261500
PREDATOR/PREY
CUTOFF (cm)
5
LENGTH (cm)
-30.0
PREDATOR
-40.0
-10
-10
-50.0
TVG 40logR
-20
-20
-60.0
NONE
40logR
-30
-30
-40
-40
ALL
-50
-50
DEL>0
-60
-60
USE INT OR BOT
-70
-70
INT
BOT
-80
-80
2
10
-10.0
5.0
1
35
0.0
0
0
Length (cm)
DEPTH (m)
0
COLUMN 9
Depth
Filter
-20.0
2011
FISH PER ACRE
PREY
No Filter
-70.0
-80.0
0.0
0 2 4 6 8
10.0
20.0
30.0
40.0
50.0
60.0
70.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1676
179
0
Blue2011:Blue2011July:K2122318.FSH.MOD
OUTPUT
Blue2011:Blue2011July:K2122318.FSH.MOD
Transect length (m): 1676 Total pings: 5848
Number prey/acre: 3.953
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.017
Number predators/acre: 25.654
Biomass predators/acre (kg): 3.146
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
60000
55000
50000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
45000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000060 0.076360 0.000121
-10.000000 0.000000 0.000000 0.019672 0.000072
-15.000000 0.000052 0.000052 0.009832 0.000285
-20.000000 0.000060 0.000101 0.013788 0.000383
-25.000000 0.000000 0.000000 0.031531 0.000609
-30.000000 0.000029 0.000043 0.023034 0.000389
-35.000000 0.000038 0.000050 0.016879 0.000315
-40.000000 0.000011 0.000011 0.065192 0.000251
-45.000000 0.000000 0.000000 0.001639 0.000062
-50.000000 0.000000 0.000000 0.000000 0.000000
-55.000000 0.000000 0.000000 0.000000 0.000000
-60.000000 0.000009 0.000018 0.018795 0.000082
-65.000000 0.000000 0.000000 0.008230 0.000012
-70.000000 0.000000 0.000000 0.000000 0.000000
-75.000000 0.000019 0.000019 0.000000 0.000000
-80.000000 0.000000 0.000000 0.000000 0.000000
-85.000000 0.000000 0.000000 0.000000 0.000000
-90.000000 0.000000 0.000000 0.000000 0.000000
40000
Total per cubic meter
0.000000 0.000012 0.000017 0.014400 0.000142
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/20/12 at 7:47 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
301553
302449
START UTM Y
END UTM Y
4261515
4260303
PREDATOR/PREY
CUTOFF (cm)
6
DEPTH (m)
35
10
LENGTH (cm)
-30.0
PREDATOR
-40.0
5.0
-10
-10
-50.0
TVG 40logR
-20
-20
-60.0
NONE
40logR
-30
-30
-40
-40
ALL
-50
-50
DEL>0
-60
-60
USE INT OR BOT
-70
-70
INT
BOT
-80
-80
1
Length (cm)
-10.0
0
0
Depth
0.0
0
COLUMN 9
Filter
-20.0
2011
FISH PER ACRE
PREY
No Filter
-70.0
-80.0
0.0
0
5 10 15
10.0
20.0
30.0
40.0
50.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1507
159
0
Blue2011:Blue2011July:K2122341.FSH
OUTPUT
Blue2011:Blue2011July:K2122341.FSH
Transect length (m): 1507 Total pings: 5660
Number prey/acre: 1.842
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.010
Number predators/acre: 38.062
Biomass predators/acre (kg): 1.288
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
130000
120000
110000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000067
-10.000000 0.000000 0.000000 0.006555 0.000362
-15.000000 0.000029 0.000058 0.017224 0.000635
-20.000000 0.000022 0.000022 0.047929 0.000829
-25.000000 0.000055 0.000073 0.020420 0.000660
-30.000000 0.000000 0.000000 0.012667 0.000403
-35.000000 0.000000 0.000000 0.002472 0.000161
-40.000000 0.000000 0.000000 0.000041 0.000014
-45.000000 0.000000 0.000000 0.000140 0.000016
-50.000000 0.000000 0.000000 0.000219 0.000015
-55.000000 0.000000 0.000000 0.000000 0.000000
-60.000000 0.000000 0.000000 0.000000 0.000000
-65.000000 0.000000 0.000000 0.000347 0.000019
-70.000000 0.000000 0.000000 0.000000 0.000000
-75.000000 0.000000 0.000000 0.014891 0.000154
-80.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000006 0.000009 0.007009 0.000192
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/19/12 at 1:46 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
305381
306220
START UTM Y
END UTM Y
4259661
4260874
PREDATOR/PREY
CUTOFF (cm)
7
0
5.0
-10
-10
TVG 40logR
-20
-20
NONE
40logR
-30
-30
-40
-40
ALL
-50
-50
DEL>0
-60
-60
USE INT OR BOT
-70
-70
INT
BOT
-80
-80
0
Length (cm)
35
10
DEPTH (m)
0.0
LENGTH (cm)
-10.0
-20.0
0
COLUMN 9
Depth
Filter
2011
FISH PER ACRE
PREY
No Filter
1
PREDATOR
-30.0
-40.0
-50.0
-60.0
-70.0
0.0
0 2 4 6 8
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1475
185
0
Blue2011:Blue2011July:K2130032.FSH
OUTPUT
Blue2011:Blue2011July:K2130032.FSH
Transect length (m): 1475 Total pings: 5303
Number prey/acre: 1.585
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.009
Number predators/acre: 34.441
Biomass predators/acre (kg): 2.110
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
95000
90000
85000
80000
Predator/prey cutoff: 5.0 cm
75000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
70000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.010341 0.000137
-10.000000 0.000000 0.000000 0.008588 0.000205
-15.000000 0.000000 0.000000 0.007929 0.000324
-20.000000 0.000000 0.000000 0.010465 0.000463
-25.000000 0.000021 0.000041 0.015212 0.000537
-30.000000 0.000036 0.000054 0.030943 0.000830
-35.000000 0.000036 0.000054 0.011007 0.000253
-40.000000 0.000000 0.000000 0.000346 0.000038
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000059 0.000059 0.007094 0.000500
-55.000000 0.000030 0.000061 0.200784 0.000606
-60.000000 0.000000 0.000000 0.273814 0.000333
-65.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000016 0.000024 0.040475 0.000349
65000
60000
55000
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/23/11 at 9:53 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
306241
307401
START UTM Y
END UTM Y
4260887
4259826
PREDATOR/PREY
CUTOFF (cm)
PREY
FISH PER ACRE
-10
-20
-20
0.0
40logR
-30
-30
COLUMN 9
-40
-40
ALL
DEL>0
-50
-50
USE INT OR BOT
-60
-60
-70
-70
0
LENGTH (cm)
-10.0
PREDATOR
1
-30.0
-40.0
-50.0
NONE
BOT
10
-20.0
-10
INT
Length (cm)
35
2011
0
TVG 40logR
Depth
Filter
DEPTH (m)
8
0
5.0
No Filter
-60.0
-70.0
0.0
0
5
10
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1572
78
0
Blue2011:Blue2011July:K2130051.FSH
OUTPUT
Blue2011:Blue2011July:K2130051.FSH
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
Transect length (m): 1572 Total pings: 5495
Number prey/acre: 1.623
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.011
Number predators/acre: 22.289
Biomass predators/acre (kg): 0.569
75000
Predator/prey cutoff: 5.0 cm
60000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
55000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.002082 0.000193
-15.000000 0.000028 0.000028 0.012723 0.000415
-20.000000 0.000022 0.000022 0.012401 0.000528
-25.000000 0.000069 0.000069 0.010920 0.000343
-30.000000 0.000000 0.000032 0.008275 0.000126
-35.000000 0.000000 0.000000 0.000142 0.000047
-40.000000 0.000000 0.000000 0.002817 0.000122
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
-55.000000 0.000000 0.000000 0.000000 0.000000
-60.000000 0.000000 0.000000 0.002776 0.000641
-65.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000017 0.000020 0.006452 0.000245
70000
65000
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/23/11 at 10:17 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
307441
307868
START UTM Y
END UTM Y
4259815
4261420
PREDATOR/PREY
CUTOFF (cm)
5.0
-20.0
-10
-10
-20
-20
COLUMN 9
-30
-30
ALL
-40
-40
-50
-50
-60
-60
PREDATOR
INT
BOT
0
1
10
LENGTH (cm)
-25.0
-30.0
-35.0
-40.0
-45.0
-50.0
-55.0
-60.0
0.0
DEL>0
USE INT OR BOT
35
-15.0
TVG 40logR
NONE
40logR
Length (cm)
0.0
2011
0
Depth
-5.0
9
0
Filter
DEPTH (m)
-10.0
FISH PER ACRE
PREY
No Filter
0
5
10
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1661
207
0
Blue2011:Blue2011July:K2130111.FSHmod
OUTPUT
Blue2011:Blue2011July:K2130111.FSHmod
Transect length (m): 1661 Total pings: 5919
Number prey/acre: 2.979
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.016
Number predators/acre: 38.869
Biomass predators/acre (kg): 0.988
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000122 0.000182
-10.000000 0.000036 0.000036 0.000000 0.000036
-15.000000 0.000000 0.000027 0.016560 0.000346
-20.000000 0.000045 0.000045 0.007668 0.000611
-25.000000 0.000000 0.000063 0.005558 0.000421
-30.000000 0.000070 0.000070 0.011717 0.000767
-35.000000 0.000000 0.000000 0.026149 0.000545
-40.000000 0.000039 0.000039 0.001890 0.000433
-45.000000 0.000000 0.000000 0.003105 0.000438
-50.000000 0.000000 0.000000 0.057935 0.000607
-55.000000 0.000000 0.000000 0.044481 0.000710
-60.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000019 0.000029 0.013995 0.000467
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
180000
170000
160000
150000
140000
130000
120000
110000
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/23/11 at 10:46 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
307891
309285
START UTM Y
END UTM Y
4261428
4260824
PREDATOR/PREY
CUTOFF (cm)
5.0
-20.0
-10
-10
-20
-20
COLUMN 9
-30
-30
ALL
-40
-40
-50
-50
-60
-60
PREDATOR
INT
BOT
0
1
10
LENGTH (cm)
-25.0
-30.0
-35.0
-40.0
-45.0
-50.0
-55.0
-60.0
0.0
DEL>0
USE INT OR BOT
35
-15.0
TVG 40logR
NONE
40logR
Length (cm)
0.0
2011
0
Depth
-5.0
10
0
Filter
DEPTH (m)
-10.0
FISH PER ACRE
PREY
No Filter
0
10
20
10.0
20.0
30.0
40.0
50.0
60.0
70.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1519
300
0
Blue2011:Blue2011July:K2130133.FSH
OUTPUT
Blue2011:Blue2011July:K2130133.FSH
Transect length (m): 1519 Total pings: 5427
Number prey/acre: 2.246
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.016
Number predators/acre: 54.099
Biomass predators/acre (kg): 4.490
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.003258 0.000133
-10.000000 0.000000 0.000000 0.011890 0.000199
-15.000000 0.000029 0.000029 0.082949 0.000630
-20.000000 0.000044 0.000044 0.060095 0.001134
-25.000000 0.000018 0.000055 0.066069 0.000873
-30.000000 0.000033 0.000033 0.008587 0.000425
-35.000000 0.000040 0.000040 0.037606 0.000403
-40.000000 0.000000 0.000000 0.091663 0.000751
-45.000000 0.000045 0.000045 0.071661 0.000864
-50.000000 0.000000 0.000000 0.127816 0.000424
-55.000000 0.000000 0.000000 0.037509 0.000448
-60.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000020 0.000025 0.055481 0.000589
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
180000
170000
160000
150000
140000
130000
120000
110000
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/23/11 at 10:53 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
309301
310019
START UTM Y
END UTM Y
4260811
4259344
PREDATOR/PREY
CUTOFF (cm)
5.0
COLUMN 9
ALL
INT
BOT
Length (cm)
35
10
0.0
LENGTH (cm)
-10.0
-15.0
2011
-20.0
PREDATOR
-25.0
0
0
-10
-10
-20
-20
-45.0
-30
-30
-50.0
-40
-40
-50
-50
-60
-60
-30.0
-35.0
-40.0
-55.0
0.0
DEL>0
USE INT OR BOT
Depth
-5.0
TVG 40logR
NONE
40logR
Filter
DEPTH (m)
11
FISH PER ACRE
PREY
No Filter
0
1
2
0
5
10
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1633
127
0
Blue2011:Blue2011July:K2130153.FSHmod
OUTPUT
Blue2011:Blue2011July:K2130153.FSHmod
Transect length (m): 1633 Total pings: 5779
Number prey/acre: 3.778
Biomass prey/acre (kg): 0.003
Total prey biomass (MT): 0.025
Number predators/acre: 33.357
Biomass predators/acre (kg): 1.075
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000062 0.000062 0.001608 0.000186
-10.000000 0.000037 0.000037 0.014029 0.000260
-15.000000 0.000000 0.000000 0.029363 0.000243
-20.000000 0.000000 0.000049 0.018562 0.000686
-25.000000 0.000062 0.000062 0.006982 0.000578
-30.000000 0.000019 0.000019 0.002376 0.000226
-35.000000 0.000000 0.000000 0.000000 0.000000
-40.000000 0.000036 0.000036 0.000000 0.000000
-45.000000 0.000045 0.000091 0.008001 0.000682
-50.000000 0.000000 0.000000 0.012215 0.000907
-55.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000024 0.000034 0.009085 0.000355
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
160000
150000
140000
130000
120000
110000
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT1m.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT2.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT4.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT5.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT3.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT6.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT7.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT8.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT10.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT9.out
WD60GIG:Users:Michael:Documents:Sonar:Blue2011:Blue2011August:2011BMRT11.out
Total length of transects (m): 18242
Number prey/acre: 2.379
95%CI (1.677, 3.080)
Biomass prey/acre (kg): 0.002
95%CI (0.001, 0.002)
Total prey biomass (MT): 0.015
95%CI (0.011, 0.019)
Number predators/acre: 29.094
95%CI (23.903, 34.284)
Biomass predators/acre (kg): 1.289
95%CI (0.928, 1.649)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
0
-10
0
-15
-0.000005
-20
0.000028
-25
0.000023
-30
0.000021
-35
0.000019
-40
0.000015
-45
-0.000009
-50
-0.000017
-55
0
-60
0
-65
-0.000003
-70
-0.000004
-75
-0.000008
-80
0
-85
0
-90
0
-95
0
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0
0
0.000007
0.000042
0.000037
0.000037
0.000036
0.000027
0.000026
0.000013
0
0
0.000002
0.000003
0.000012
0
0
0
0
0
0
0
0.000019
0.000056
0.00005
0.000054
0.000053
0.000039
0.00006
0.000043
0
0
0.000006
0.000009
0.000032
0
0
0
0
0
-0.000006
0
-0.000005
0.000027
0.000033
0.000026
0.000034
0.000021
-0.000009
-0.000019
0
-0.000004
-0.000003
-0.000011
-0.000013
0
0
0
0
0
0.000005
0
0.000007
0.000044
0.000052
0.000051
0.000055
0.000037
0.000033
0.000015
0
0.000003
0.000002
0.000008
0.000016
0
0
0
0
0
0.000016
0
0.000019
0.000061
0.000071
0.000077
0.000077
0.000054
0.000075
0.00005
0
0.000009
0.000006
0.000026
0.000044
0
0
0
0
0
-0.000054
-0.000454
0.007841
0.007871
0.008924
0.005132
0.008807
0.006377
-0.002545
-0.000862
-0.010347
-0.004456
-0.000039
-0.000184
-0.000048
-0.000013
0
0
0
0
0.000044
0.004742
0.0172
0.021273
0.017578
0.011335
0.016813
0.021104
0.039764
0.009355
0.019369
0.005531
0.000061
0.000221
0.000054
0.000008
0
0
0
0
0.000141
0.009938
0.026558
0.034675
0.026232
0.017538
0.024819
0.035831
0.082072
0.019572
0.049084
0.015517
0.000161
0.000627
0.000155
0.000029
0
0
0
0
-0.000007
0.000025
0.000133
0.000454
0.000425
0.000334
0.000388
0.000213
0.000055
0.000006
-0.000006
0
-0.000004
-0.000004
-0.000035
-0.000006
0
0
0
0
0.000005
0.000046
0.000253
0.000666
0.000581
0.000431
0.000575
0.000362
0.000263
0.000213
0.000168
0.000031
0.000006
0.000021
0.000038
0.000004
0
0
0
0
0.000018
0.000067
0.000373
0.000878
0.000736
0.000528
0.000762
0.00051
0.000472
0.00042
0.000342
0.000062
0.000016
0.000047
0.000112
0.000014
0
0
0
11
11
11
11
11
11
11
11
11
11
11
10
10
8
7
6
6
4
2
2
Total per cubic meter
0.000011
0.00002
0.000028
0.000014
0.000027
0.000039
0.009999
0.014625
0.01925
0.000205
0.000319
0.000432
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/5/11 at 9:11 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
298660
297355
START UTM Y
END UTM Y
4258549
4259573
PREDATOR/PREY
CUTOFF (cm)
5.0
-10
-10
TVG 40logR
-20
-20
NONE
40logR
-30
-30
-40
-40
-50
-50
-60
-60
USE INT OR BOT
-70
-70
INT
BOT
-80
-80
0
Length (cm)
35
10
0.0
LENGTH (cm)
-10.0
-20.0
0
ALL
DEL>0
Depth
2011
0
COLUMN 9
Filter
DEPTH (m)
1
FISH PER ACRE
PREY
No Filter
1
PREDATOR
-30.0
-40.0
-50.0
-60.0
-70.0
0.0
0
5
10
10.0
20.0
30.0
40.0
50.0
60.0
70.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1659
170
0
Blue2011:Blue2011August:K2402220.FSH.mod
OUTPUT
Blue2011:Blue2011August:K2402220.FSH.mod
Transect length (m): 1659 Total pings: 5931
Number prey/acre: 2.877
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.017
Number predators/acre: 27.000
Biomass predators/acre (kg): 1.290
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
100000
95000
90000
85000
Predator/prey cutoff: 5.0 cm
80000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
75000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000000 0.000037
-15.000000 0.000000 0.000000 0.011505 0.000210
-20.000000 0.000061 0.000061 0.010121 0.000692
-25.000000 0.000034 0.000051 0.020447 0.000549
-30.000000 0.000054 0.000090 0.009900 0.000306
-35.000000 0.000019 0.000058 0.022191 0.000637
-40.000000 0.000060 0.000060 0.078253 0.000319
-45.000000 0.000000 0.000020 0.025335 0.000142
-50.000000 0.000000 0.000000 0.002106 0.000021
-55.000000 0.000000 0.000000 0.000000 0.000000
-60.000000 0.000000 0.000029 0.011077 0.000057
-65.000000 0.000000 0.000000 0.000000 0.000000
-70.000000 0.000000 0.000000 0.000000 0.000000
-75.000000 0.000000 0.000000 0.000000 0.000000
-80.000000 0.000000 0.000000 0.000000 0.000000
-85.000000 0.000000 0.000000 0.000000 0.000000
-90.000000 0.000000 0.000000 0.000000 0.000000
-95.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000018 0.000029 0.014541 0.000231
70000
65000
60000
55000
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/5/11 at 10:35 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
297339
298966
START UTM Y
END UTM Y
4259642
4260695
PREDATOR/PREY
CUTOFF (cm)
2011
LENGTH (cm)
-30.0
PREDATOR
-40.0
-10
-10
-50.0
TVG 40logR
-20
-20
-60.0
NONE
40logR
-30
-30
-40
-40
-50
-50
-60
-60
USE INT OR BOT
-70
-70
INT
BOT
-80
-80
1
10
-20.0
5.0
0
Length (cm)
35
-10.0
0
ALL
DEL>0
Depth
0.0
0
COLUMN 9
Filter
DEPTH (m)
2
FISH PER ACRE
PREY
No Filter
-70.0
-80.0
0.0
0
5
10
10.0
20.0
30.0
40.0
50.0
60.0
70.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1938
302
0
Blue2011:Blue2011August:K2402241.FSH.mmod
OUTPUT
Blue2011:Blue2011August:K2402241.FSH.mmod
Transect length (m): 1938 Total pings: 6930
Number prey/acre: 2.590
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.019
Number predators/acre: 29.975
Biomass predators/acre (kg): 1.191
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000125 0.000094
-15.000000 0.000022 0.000022 0.014919 0.000224
-20.000000 0.000052 0.000052 0.016874 0.000662
-25.000000 0.000043 0.000043 0.006172 0.000413
-30.000000 0.000025 0.000025 0.007391 0.000405
-35.000000 0.000056 0.000089 0.027106 0.000793
-40.000000 0.000040 0.000050 0.037506 0.000578
-45.000000 0.000018 0.000027 0.030542 0.000181
-50.000000 0.000000 0.000000 0.039000 0.000051
-55.000000 0.000000 0.000000 0.000063 0.000008
-60.000000 0.000000 0.000000 0.000000 0.000000
-65.000000 0.000000 0.000000 0.000170 0.000028
-70.000000 0.000000 0.000000 0.000093 0.000026
-75.000000 0.000000 0.000000 0.000000 0.000000
-80.000000 0.000000 0.000000 0.000000 0.000000
-85.000000 0.000000 0.000000 0.000000 0.000000
-90.000000 0.000000 0.000000 0.000000 0.000000
-95.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000012 0.000015 0.010065 0.000165
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
110000
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/5/11 at 11:21 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
298984
299306
START UTM Y
END UTM Y
4260709
4262237
PREDATOR/PREY
CUTOFF (cm)
5.0
-10
-10
TVG 40logR
-20
-20
NONE
40logR
-30
-30
-40
-40
-50
-50
-60
-60
USE INT OR BOT
-70
-70
INT
BOT
-80
-80
0
Length (cm)
35
10
0.0
LENGTH (cm)
-10.0
-20.0
0
ALL
DEL>0
Depth
2011
0
COLUMN 9
Filter
DEPTH (m)
3
FISH PER ACRE
PREY
No Filter
1
PREDATOR
-30.0
-40.0
-50.0
-60.0
-70.0
0.0
0
646
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1562
213
0
Blue2011:Blue2011August:K2402306.FSH.mod
OUTPUT
Blue2011:Blue2011August:K2402306.FSH.mod
Transect length (m): 1562 Total pings: 5459
Number prey/acre: 2.104
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.016
Number predators/acre: 25.776
Biomass predators/acre (kg): 1.358
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
100000
95000
90000
85000
Predator/prey cutoff: 5.0 cm
80000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
75000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000466 0.000078
-15.000000 0.000000 0.000000 0.037995 0.000111
-20.000000 0.000043 0.000043 0.005472 0.000606
-25.000000 0.000053 0.000053 0.011973 0.000336
-30.000000 0.000045 0.000060 0.038023 0.000628
-35.000000 0.000052 0.000052 0.023055 0.000622
-40.000000 0.000023 0.000034 0.016131 0.000343
-45.000000 0.000000 0.000000 0.007140 0.000072
-50.000000 0.000000 0.000000 0.000387 0.000041
-55.000000 0.000000 0.000000 0.009653 0.000098
-60.000000 0.000000 0.000000 0.000055 0.000044
-65.000000 0.000000 0.000000 0.000000 0.000000
-70.000000 0.000000 0.000000 0.000000 0.000000
-75.000000 0.000000 0.000000 0.000000 0.000000
-80.000000 0.000000 0.000000 0.000000 0.000000
70000
65000
60000
55000
50000
45000
40000
35000
30000
25000
20000
Total per cubic meter
0.000000 0.000015 0.000017 0.010078 0.000205
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/6/11 at 9:01 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
299320
300086
START UTM Y
END UTM Y
4262283
4260630
PREDATOR/PREY
CUTOFF (cm)
35
10
LENGTH (cm)
-10.0
-20.0
2011
-30.0
PREDATOR
-40.0
0
-10
-10
-50.0
-20
-20
-60.0
40logR
-30
-30
-70.0
COLUMN 9
-40
-40
-80.0
-50
-50
-60
-60
TVG 40logR
Length (cm)
0.0
0
5.0
Depth
Filter
DEPTH (m)
4
FISH PER ACRE
PREY
No Filter
NONE
ALL
DEL>0
USE INT OR BOT
INT
BOT
-70
0.0
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1822
234
0
-70
0
1
2
0
2
4
6
Blue2011:Blue2011August:K2402326.FSH
OUTPUT
Blue2011:Blue2011August:K2402326.FSH
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
Transect length (m): 1822 Total pings: 6793
Number prey/acre: 2.784
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.011
Number predators/acre: 19.288
Biomass predators/acre (kg): 0.696
75000
Predator/prey cutoff: 5.0 cm
60000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
55000
70000
65000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000055 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000000 0.000000
-15.000000 0.000000 0.000000 0.005298 0.000191
-20.000000 0.000019 0.000019 0.001465 0.000278
-25.000000 0.000015 0.000030 0.003047 0.000258
-30.000000 0.000039 0.000052 0.009831 0.000426
-35.000000 0.000067 0.000079 0.033083 0.000674
-40.000000 0.000041 0.000061 0.020937 0.000458
-45.000000 0.000000 0.000000 0.044199 0.000139
-50.000000 0.000000 0.000000 0.000345 0.000082
-55.000000 0.000000 0.000000 0.000723 0.000009
-60.000000 0.000000 0.000000 0.000056 0.000032
-65.000000 0.000015 0.000015 0.000319 0.000022
-70.000000 0.000000 0.000000 0.001201 0.000008
-75.000000 0.000000 0.000000 0.000000 0.000000
-80.000000 0.000000 0.000000 0.000000 0.000000
-85.000000 0.000000 0.000000 0.000000 0.000000
50000
Total per cubic meter
0.000000 0.000012 0.000016 0.007995 0.000148
10000
45000
40000
35000
30000
25000
20000
15000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/6/11 at 9:21 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
300081
301525
START UTM Y
END UTM Y
4260612
4261499
PREDATOR/PREY
CUTOFF (cm)
PREDATOR
-40.0
-10
-60.0
-20
-20
-70.0
40logR
-30
-30
-80.0
COLUMN 9
-40
-40
-90.0
-50
-50
-60
-60
NONE
USE INT OR BOT
INT
BOT
-70
LENGTH (cm)
-30.0
2011
-10
DEL>0
10
-20.0
-50.0
ALL
35
-10.0
0
TVG 40logR
Length (cm)
0.0
0
5.0
Depth
Filter
DEPTH (m)
5
FISH PER ACRE
PREY
No Filter
0.0
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1695
228
0
-70
0
1
0
2
4
6
Blue2011:Blue2011August:K2402350.FSHmod
OUTPUT
Blue2011:Blue2011August:K2402350.FSHmod
Transect length (m): 1695 Total pings: 6043
Number prey/acre: 2.633
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.017
Number predators/acre: 19.918
Biomass predators/acre (kg): 0.952
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
60000
55000
50000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
45000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000858 0.000036
-15.000000 0.000000 0.000000 0.011440 0.000128
-20.000000 0.000040 0.000040 0.011082 0.000239
-25.000000 0.000065 0.000098 0.014260 0.000407
-30.000000 0.000028 0.000028 0.006996 0.000483
-35.000000 0.000064 0.000089 0.015235 0.000703
-40.000000 0.000035 0.000046 0.013305 0.000208
-45.000000 0.000021 0.000032 0.074001 0.000318
-50.000000 0.000000 0.000000 0.000084 0.000021
-55.000000 0.000000 0.000000 0.000010 0.000010
-60.000000 0.000000 0.000000 0.000011 0.000022
-65.000000 0.000000 0.000000 0.000000 0.000000
-70.000000 0.000018 0.000053 0.000211 0.000070
-75.000000 0.000043 0.000065 0.000239 0.000174
-80.000000 0.000000 0.000000 0.000048 0.000024
-85.000000 0.000000 0.000000 0.000000 0.000000
40000
35000
30000
25000
20000
15000
10000
Total per cubic meter
0.000000 0.000020 0.000028 0.011102 0.000187
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/6/11 at 9:37 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
301549
302434
START UTM Y
END UTM Y
4261512
4260294
PREDATOR/PREY
CUTOFF (cm)
35
10
LENGTH (cm)
-10.0
-20.0
2011
-30.0
PREDATOR
-40.0
0
-10
-10
-50.0
-20
-20
-60.0
40logR
-30
-30
-70.0
COLUMN 9
-40
-40
-80.0
-50
-50
-60
-60
TVG 40logR
Length (cm)
0.0
0
5.0
Depth
Filter
DEPTH (m)
6
FISH PER ACRE
PREY
No Filter
NONE
ALL
DEL>0
USE INT OR BOT
INT
BOT
-70
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1506
150
0
-70
0
1
0
2
4
6
Blue2011:Blue2011August:K2410012.FSH
OUTPUT
Blue2011:Blue2011August:K2410012.FSH
Transect length (m): 1506 Total pings: 5494
Number prey/acre: 1.392
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.010
Number predators/acre: 19.585
Biomass predators/acre (kg): 1.636
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
65000
60000
55000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.018270 0.000040
-15.000000 0.000000 0.000000 0.002858 0.000144
-20.000000 0.000045 0.000045 0.014851 0.000336
-25.000000 0.000055 0.000055 0.011923 0.000569
-30.000000 0.000016 0.000016 0.008331 0.000434
-35.000000 0.000000 0.000013 0.003670 0.000376
-40.000000 0.000013 0.000026 0.002259 0.000155
-45.000000 0.000000 0.000000 0.217401 0.000170
-50.000000 0.000000 0.000000 0.000383 0.000029
-55.000000 0.000000 0.000000 0.021850 0.000030
-60.000000 0.000000 0.000000 0.000096 0.000016
-65.000000 0.000000 0.000000 0.000000 0.000000
-70.000000 0.000000 0.000000 0.000045 0.000045
-75.000000 0.000028 0.000028 0.000083 0.000055
-80.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000010 0.000012 0.022629 0.000172
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/6/11 at 9:49 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
305260
306223
START UTM Y
END UTM Y
4259594
4260872
PREDATOR/PREY
CUTOFF (cm)
-25.0
PREDATOR
-30.0
-20
-35.0
-50.0
40logR
-30
-30
-55.0
COLUMN 9
-40
-40
-50
-50
-60
-60
-40.0
-45.0
NONE
INT
BOT
LENGTH (cm)
-20.0
2011
-20
USE INT OR BOT
10
-15.0
-10
DEL>0
35
-5.0
-10
ALL
Length (cm)
-10.0
0
TVG 40logR
Depth
0.0
0
5.0
Filter
DEPTH (m)
7
FISH PER ACRE
PREY
No Filter
-60.0
-70
-65.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1600
212
0
-70
0
1
0
5
10
Blue2011:Blue2011August:K2410103.FSH
OUTPUT
Blue2011:Blue2011August:K2410103.FSH
Transect length (m): 1600 Total pings: 5656
Number prey/acre: 0.582
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.005
Number predators/acre: 33.761
Biomass predators/acre (kg): 1.794
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.021364 0.000076
-15.000000 0.000000 0.000000 0.007566 0.000314
-20.000000 0.000000 0.000000 0.053326 0.000625
-25.000000 0.000000 0.000000 0.039830 0.000853
-30.000000 0.000034 0.000034 0.005949 0.000541
-35.000000 0.000018 0.000018 0.014934 0.000584
-40.000000 0.000039 0.000039 0.006959 0.000366
-45.000000 0.000000 0.000000 0.006888 0.000144
-50.000000 0.000000 0.000000 0.001638 0.000282
-55.000000 0.000000 0.000000 0.024902 0.000511
-60.000000 0.000000 0.000000 0.044013 0.000140
-65.000000 0.000000 0.000000 0.000000 0.000000
-70.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000010 0.000010 0.018634 0.000403
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
105000
100000
95000
90000
85000
80000
75000
70000
65000
60000
55000
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/6/11 at 10:11 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
306228
307397
START UTM Y
END UTM Y
4260894
4259825
PREDATOR/PREY
CUTOFF (cm)
5.0
TVG 40logR
-15.0
-20.0
PREDATOR
-25.0
-30.0
-10
-10
-40.0
-45.0
-30
-30
COLUMN 9
-40
-40
ALL
DEL>0
-50
-50
USE INT OR BOT
-60
-60
INT
BOT
-70
-70
0
1
LENGTH (cm)
-10.0
0
-20
10
0.0
0
-20
Length (cm)
35
-5.0
2011
NONE
40logR
Depth
Filter
DEPTH (m)
8
FISH PER ACRE
PREY
No Filter
-35.0
-50.0
-55.0
-60.0
0.0
0
10
20
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1584
141
0
Blue2011:Blue2011August:K2410123.FSH
OUTPUT
Blue2011:Blue2011August:K2410123.FSH
Transect length (m): 1584 Total pings: 5547
Number prey/acre: 1.614
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.014
Number predators/acre: 37.802
Biomass predators/acre (kg): 1.691
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.005510 0.000038
-15.000000 0.000000 0.000000 0.025198 0.000714
-20.000000 0.000064 0.000064 0.057309 0.001237
-25.000000 0.000024 0.000024 0.043686 0.000763
-30.000000 0.000038 0.000038 0.006081 0.000344
-35.000000 0.000053 0.000053 0.008338 0.000264
-40.000000 0.000000 0.000000 0.013628 0.000198
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
-55.000000 0.000000 0.000000 0.000000 0.000116
-60.000000 0.000000 0.000000 0.000000 0.000000
-65.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000022 0.000022 0.022217 0.000491
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
85000
80000
75000
70000
65000
60000
55000
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/6/11 at 10:21 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
307413
307868
START UTM Y
END UTM Y
4259815
4261414
PREDATOR/PREY
CUTOFF (cm)
5.0
0
-10
-10
-20
-20
COLUMN 9
-30
-30
ALL
DEL>0
-40
-40
USE INT OR BOT
-50
-50
INT
BOT
-60
Length (cm)
35
10
0.0
LENGTH (cm)
-10.0
-15.0
-20.0
PREDATOR
-25.0
-30.0
-35.0
-40.0
TVG 40logR
NONE
40logR
Depth
-5.0
2011
0
Filter
DEPTH (m)
9
FISH PER ACRE
PREY
No Filter
-45.0
-50.0
-55.0
-60.0
0.0
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1662
256
0
-60
0
1
2
0
5
10
Blue2011:Blue2011August:K2410143.FSH
OUTPUT
Blue2011:Blue2011August:K2410143.FSH
Transect length (m): 1662 Total pings: 5847
Number prey/acre: 3.297
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.019
Number predators/acre: 41.433
Biomass predators/acre (kg): 2.296
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
150000
140000
130000
Predator/prey cutoff: 5.0 cm
120000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
110000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.004850 0.000036
-15.000000 0.000000 0.000000 0.045545 0.000419
-20.000000 0.000044 0.000044 0.043080 0.000657
-25.000000 0.000021 0.000064 0.010381 0.000467
-30.000000 0.000098 0.000147 0.014389 0.000661
-35.000000 0.000045 0.000091 0.033575 0.001113
-40.000000 0.000021 0.000021 0.029581 0.000739
-45.000000 0.000081 0.000081 0.025451 0.000835
-50.000000 0.000000 0.000000 0.034133 0.000625
-55.000000 0.000000 0.000000 0.134485 0.000700
-60.000000 0.000000 0.000000 0.000000 0.000000
100000
Total per cubic meter
0.000000 0.000033 0.000049 0.027052 0.000607
40000
90000
80000
70000
60000
50000
30000
20000
10000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/6/11 at 10:44 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
307874
309274
START UTM Y
END UTM Y
4261452
4260821
PREDATOR/PREY
CUTOFF (cm)
10
0
0
5.0
-10
-10
TVG 40logR
-20
-20
NONE
40logR
-30
-30
-40
-40
COLUMN 9
-50
-50
ALL
DEL>0
-60
-60
-70
-70
USE INT OR BOT
-80
-80
-90
-90
INT
BOT
0
1
Filter
DEPTH (m)
Depth
Length (cm)
35
10
0.0
-5.0
LENGTH (cm)
-10.0
-15.0
-20.0
2011
FISH PER ACRE
PREY
No Filter
PREDATOR
-25.0
-30.0
-35.0
-40.0
-45.0
-50.0
-55.0
-60.0
0.0
0
5 10 15
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1536
287
0
Blue2011:Blue2011August:K2410204.FSH.mod
OUTPUT
Blue2011:Blue2011August:K2410204.FSH.mod
Transect length (m): 1536 Total pings: 5417
Number prey/acre: 4.469
Biomass prey/acre (kg): 0.003
Total prey biomass (MT): 0.027
Number predators/acre: 36.833
Biomass predators/acre (kg): 0.650
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000000 0.000000
-15.000000 0.000057 0.000057 0.006312 0.000113
-20.000000 0.000022 0.000022 0.011371 0.000968
-25.000000 0.000054 0.000091 0.015138 0.000835
-30.000000 0.000035 0.000052 0.011606 0.000345
-35.000000 0.000023 0.000068 0.003283 0.000502
-40.000000 0.000025 0.000074 0.013582 0.000615
-45.000000 0.000161 0.000206 0.006445 0.000895
-50.000000 0.000148 0.000169 0.024118 0.000953
-55.000000 0.000000 0.000000 0.002000 0.000200
-60.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000052 0.000073 0.009601 0.000547
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
180000
170000
160000
150000
140000
130000
120000
110000
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/6/11 at 10:51 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
BLUE MESA
controls before running VI
TRANSECT #
START UTM X
END UTM X
309278
310127
START UTM Y
END UTM Y
4260800
4259353
PREDATOR/PREY
CUTOFF (cm)
11
2011
NONE
40logR
COLUMN 9
ALL
DEL>0
0
0
-10
-10
-20
-20
PREDATOR
Length (cm)
35
10
0.0
-5.0
LENGTH (cm)
-10.0
-25.0
-30.0
-35.0
-40.0
-45.0
-50.0
-30
-30
-55.0
0.0
-40
-40
USE INT OR BOT
INT
BOT
DEPTH (m)
Depth
-20.0
5.0
TVG 40logR
Filter
-15.0
FISH PER ACRE
PREY
No Filter
-50
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1678
125
0
-50
0
1
2
0
5 10 15
Blue2011:Blue2011August:K2410224.FSHmod
OUTPUT
Blue2011:Blue2011August:K2410224.FSHmod
Transect length (m): 1678 Total pings: 5897
Number prey/acre: 1.825
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.010
Number predators/acre: 28.658
Biomass predators/acre (kg): 0.621
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
130000
120000
110000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000482 0.000060
-10.000000 0.000000 0.000000 0.000722 0.000072
-15.000000 0.000000 0.000000 0.020561 0.000219
-20.000000 0.000070 0.000094 0.009052 0.001029
-25.000000 0.000040 0.000060 0.016502 0.000936
-30.000000 0.000000 0.000021 0.006185 0.000166
-35.000000 0.000000 0.000000 0.000472 0.000059
-40.000000 0.000000 0.000000 0.000000 0.000000
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000713 0.000238
Total per cubic meter
0.000000 0.000015 0.000024 0.006958 0.000350
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:Carter2011:2011CarterT1.out
WD60GIG:Users:Michael:Documents:Sonar:Carter2011:2011CarterT2.out
Total length of transects (m): 3068
Number prey/acre: 3.583 95%CI (-41.943, 49.109)
Biomass prey/acre (kg): 0.003 95%CI (-0.035, 0.041)
Total prey biomass (MT): 0.003 95%CI (-0.035, 0.041)
Number predators/acre: 12.829 95%CI (-61.057, 86.715)
Biomass predators/acre (kg): 2.146 95%CI (-10.173, 14.464)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
-0.001516
-10
-0.000685
-15
0
-20
0
-25
0
-30
0
-35
0
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0.00013
0.000058
0
0
0
0
0
0
0.001775
0.000802
0
0
0
0
0
0
-0.001896
-0.000685
0
0
0
0
0
0
0.000162
0.000058
0
0
0
0
0
0
0.00222
0.000802
0
0
0
0
0
0
-0.828597
-0.211605
-0.000164
0
0
0
0
0
0.111055
0.018992
0.000014
0
0
0
0
0
1.050706
0.24959
0.000192
0
0
0
0
0
-0.004107
-0.000078
-0.000164
0
0
0
0
0
0.000632
0.000138
0.000014
0
0
0
0
0
0.005371
0.000354
0.000192
0
0
0
0
2
2
2
2
2
2
2
2
Total per cubic meter
-0.000135
0.000011
0.000158
-0.000152
0.000013
0.000178
-0.048226
0.009555
0.067337
-0.000334
0.00006
0.000454
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/8/11 at 10:37 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CARTER
controls before running VI
TRANSECT #
START UTM X
END UTM X
481469
481438
START UTM Y
END UTM Y
4463382
4464890
PREDATOR/PREY
CUTOFF (cm)
5.0
TVG 40logR
PREY
0
-5
-5
-10
-10
NONE
40logR
-15
-15
COLUMN 9
-20
-20
ALL
DEL>0
-25
-25
USE INT OR BOT
-30
-30
INT
BOT
-35
-35
0
1
Length (cm)
35
10
0.0
-1.0
LENGTH (cm)
-2.0
-3.0
-4.0
2011
FISH PER ACRE
Depth
Filter
DEPTH (m)
1
0
-1
No Filter
PREDATOR
-5.0
-6.0
-7.0
-8.0
-9.0
-10.0
-11.0
-12.0
0.0
0
10
20
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1508
18
0
Carter2011:Carter2011:K2712016.FSH.mod
OUTPUT
Carter2011:Carter2011:K2712016.FSH.mod
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
Transect length (m): 1508 Total pings: 6155
Number prey/acre: 0.000
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.000
Number predators/acre: 18.644
Biomass predators/acre (kg): 3.115
8000
Predator/prey cutoff: 5.0 cm
6500
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
6000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.185007 0.001005
-10.000000 0.000000 0.000000 0.000844 0.000121
-15.000000 0.000000 0.000000 0.000000 0.000000
-20.000000 0.000000 0.000000 0.000000 0.000000
-25.000000 0.000000 0.000000 0.000000 0.000000
-30.000000 0.000000 0.000000 0.000000 0.000000
-35.000000 0.000000 0.000000 0.000000 0.000000
7500
7000
5500
5000
4500
4000
3500
Total per cubic meter
0.000000 0.000000 0.000000 0.014103 0.000091
3000
2500
2000
1500
1000
500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/8/11 at 11:19 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CARTER
controls before running VI
TRANSECT #
START UTM X
END UTM X
481455
START UTM Y
END UTM Y
4464930
4466490
-6.0
PREDATOR
-8.0
-10.0
-5
-5
-12.0
TVG 40logR
-10
-10
NONE
40logR
-14.0
-15
-15
-16.0
COLUMN 9
-20
-20
ALL
DEL>0
-25
-25
USE INT OR BOT
-30
-30
INT
BOT
-35
-35
2
4
6
LENGTH (cm)
-4.0
0
0
10
-2.0
0
5.0
Length (cm)
35
0.0
2011
FISH PER ACRE
PREY
Depth
Filter
DEPTH (m)
2
481446
PREDATOR/PREY
CUTOFF (cm)
No Filter
-18.0
0.0
0
2
4
6
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1560
17
0
Carter2011:Carter2011:K2712039.FSH.mod
OUTPUT
Carter2011:Carter2011:K2712039.FSH.mod
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
Transect length (m): 1560 Total pings: 5717
Number prey/acre: 7.166
Biomass prey/acre (kg): 0.006
Total prey biomass (MT): 0.006
Number predators/acre: 7.014
Biomass predators/acre (kg): 1.176
7500
Predator/prey cutoff: 5.0 cm
6000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
5500
7000
6500
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000259 0.000324 0.037102 0.000259
-10.000000 0.000117 0.000117 0.037141 0.000155
-15.000000 0.000000 0.000000 0.000028 0.000028
-20.000000 0.000000 0.000000 0.000000 0.000000
-25.000000 0.000000 0.000000 0.000000 0.000000
-30.000000 0.000000 0.000000 0.000000 0.000000
-35.000000 0.000000 0.000000 0.000000 0.000000
5000
Total per cubic meter
0.000000 0.000023 0.000026 0.005008 0.000029
3000
4500
4000
3500
2500
2000
1500
1000
500
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011June:2011ChsT2.out
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011June:2011ChsT1.out
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011June:2011ChsT3.out
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011June:2011ChsT5.out
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011June:2011ChsT4.out
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011June:2011ChsT6.out
Total length of transects (m): 5073
Number prey/acre: 4.714
95%CI (0.075, 9.353)
Biomass prey/acre (kg): 0.004
95%CI (-0.001, 0.008)
Total prey biomass (MT): 0.003
95%CI (-0.001, 0.007)
Number predators/acre: 85.531
95%CI (23.529, 147.534)
Biomass predators/acre (kg): 2.849
95%CI (1.361, 4.338)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
0
-10
-0.000017
-15
-0.000011
-20
-0.000014
-25
-0.00001
-30
-0.000016
-35
-0.000018
-40
0
-45
-0.000006
-50
-0.00001
-55
0
-60
NaN
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0
0.000025
0.000096
0.000009
0.000006
0.000017
0.000017
0
0.000003
0.000006
0
0
0
0
0.000067
0.000202
0.000031
0.000023
0.000049
0.000052
0
0.000012
0.000022
0
NaN
0
0
-0.000023
0.000004
-0.000011
-0.00001
-0.000016
-0.000018
0
-0.000011
-0.00001
0
NaN
0
0
0.000051
0.000103
0.000017
0.000006
0.000017
0.000017
0
0.000006
0.000006
0
0
0
0
0.000126
0.000202
0.000046
0.000023
0.000049
0.000052
0
0.000024
0.000022
0
NaN
0
-0.000159
-0.006142
0.021878
-0.008508
0.002188
-0.004025
-0.00433
-0.001033
-0.002283
-0.00011
0
NaN
0
0.000101
0.011598
0.066567
0.025138
0.013062
0.016297
0.007783
0.001694
0.001285
0.000138
0
0
0
0.000361
0.029339
0.111256
0.058785
0.023935
0.036619
0.019895
0.004422
0.004854
0.000386
0
NaN
0
-0.00004
-0.000205
0.000823
0.000239
0.000033
-0.000058
-0.000092
-0.000064
-0.000074
-0.000032
0
NaN
0
0.000025
0.000596
0.00202
0.000545
0.000279
0.000288
0.000139
0.000086
0.000041
0.000037
0
0
0
0.00009
0.001396
0.003217
0.000852
0.000526
0.000634
0.000371
0.000237
0.000156
0.000105
0
NaN
6
6
6
6
6
6
6
6
6
5
5
3
1
Total per cubic meter
-0.000004
0.000018
0.00004
0.000001
0.000022
0.000044
0.00506
0.01524
0.025419
0.000092
0.000404
0.000717
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 12/30/11 at 10:06 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
476293
475976
START UTM Y
END UTM Y
4340441
4341028
PREDATOR/PREY
CUTOFF (cm)
NONE
40logR
COLUMN 9
ALL
DEL>0
Length (cm)
35
10
0.0
LENGTH (cm)
-10.0
-15.0
2011
0
0
-10
-10
-20
-20
-20.0
PREDATOR
-25.0
-30.0
-35.0
-40.0
-45.0
-50.0
-30
-30
-55.0
0.0
-40
-40
-50
-50
USE INT OR BOT
INT
BOT
Depth
-5.0
5.0
TVG 40logR
Filter
DEPTH (m)
1
FISH PER ACRE
PREY
No Filter
0 2 4 6 8
0
50
100
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
667
139
0
Sonar:Cheesman2011June:K1820106.FSH
OUTPUT
Sonar:Cheesman2011June:K1820106.FSH
Transect length (m): 667 Total pings: 2537
Number prey/acre: 13.149
Biomass prey/acre (kg): 0.011
Total prey biomass (MT): 0.010
Number predators/acre: 199.508
Biomass predators/acre (kg): 5.068
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
130000
120000
110000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000606 0.000151
-10.000000 0.000091 0.000182 0.020353 0.002090
-15.000000 0.000261 0.000261 0.070986 0.003911
-20.000000 0.000052 0.000052 0.088041 0.001045
-25.000000 0.000000 0.000000 0.029926 0.000649
-30.000000 0.000000 0.000000 0.050374 0.000821
-35.000000 0.000083 0.000083 0.007849 0.000165
-40.000000 0.000000 0.000000 0.004310 0.000094
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000250 0.000125
-55.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000053 0.000060 0.032880 0.000985
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 12/30/11 at 10:59 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
475997
476348
START UTM Y
END UTM Y
4339411
4340405
PREDATOR/PREY
CUTOFF (cm)
2
NONE
40logR
COLUMN 9
ALL
DEL>0
USE INT OR BOT
INT
BOT
Length (cm)
35
10
DEPTH (m)
0.0
-5.0
LENGTH (cm)
-10.0
2011
0
0
-10
-10
-20
-20
-20.0
PREDATOR
-25.0
-30.0
5.0
TVG 40logR
Depth
Filter
-15.0
FISH PER ACRE
PREY
No Filter
-35.0
-40.0
-45.0
-50.0
-30
-30
-55.0
0.0
-40
-40
-50
5.0
10.0
15.0
20.0
25.0
30.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1054
187
0
-50
0
1
2
0 20 40 60
Sonar:Cheesman2011June:K1820052.FSH
OUTPUT
Sonar:Cheesman2011June:K1820052.FSH
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
Transect length (m): 1054 Total pings: 3797
Number prey/acre: 4.240
Biomass prey/acre (kg): 0.004
Total prey biomass (MT): 0.004
Number predators/acre: 90.450
Biomass predators/acre (kg): 2.403
42000
Predator/prey cutoff: 5.0 cm
34000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000058 0.000058 0.005405 0.000460
-15.000000 0.000083 0.000083 0.035146 0.001939
-20.000000 0.000000 0.000000 0.025226 0.000673
-25.000000 0.000000 0.000000 0.019237 0.000262
-30.000000 0.000023 0.000023 0.028467 0.000565
-35.000000 0.000020 0.000020 0.029996 0.000572
-40.000000 0.000000 0.000000 0.005692 0.000368
-45.000000 0.000016 0.000032 0.006427 0.000207
-50.000000 0.000029 0.000029 0.000438 0.000058
-55.000000 0.000000 0.000000 0.000000 0.000000
-60.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000017 0.000019 0.012525 0.000371
40000
38000
36000
32000
30000
28000
26000
24000
22000
20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 12/30/11 at 11:07 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
475323
476012
START UTM Y
END UTM Y
4339006
4339391
PREDATOR/PREY
CUTOFF (cm)
0
-10
-10
NONE
40logR
COLUMN 9
ALL
DEL>0
USE INT OR BOT
INT
BOT
35
10
LENGTH (cm)
-5.0
-10.0
-15.0
PREDATOR
5.0
TVG 40logR
Length (cm)
0.0
2011
0
Depth
Filter
DEPTH (m)
3
FISH PER ACRE
PREY
No Filter
-20.0
-25.0
-30.0
-20
-20
-30
-30
-35.0
-40.0
0.0
-40
-40
-50
5.0
10.0
15.0
20.0
25.0
30.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
789
35
0
-50
0
2
4
0
10
20
Sonar:Cheesman2011June:K1820041.FSH
OUTPUT
Sonar:Cheesman2011June:K1820041.FSH
Transect length (m): 789 Total pings: 3057
Number prey/acre: 5.370
Biomass prey/acre (kg): 0.005
Total prey biomass (MT): 0.005
Number predators/acre: 33.039
Biomass predators/acre (kg): 0.771
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000845 0.000230
-15.000000 0.000165 0.000165 0.020114 0.000827
-20.000000 0.000000 0.000000 0.002770 0.000182
-25.000000 0.000039 0.000039 0.008926 0.000117
-30.000000 0.000077 0.000077 0.007131 0.000115
-35.000000 0.000000 0.000000 0.000615 0.000041
-40.000000 0.000000 0.000000 0.000000 0.000000
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
-55.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000030 0.000030 0.004271 0.000143
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
19000
18000
17000
16000
15000
14000
13000
12000
11000
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 12/30/11 at 11:10 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
475452
475339
START UTM Y
END UTM Y
4337979
4338980
PREDATOR/PREY
CUTOFF (cm)
0
-10
-10
NONE
40logR
COLUMN 9
ALL
DEL>0
USE INT OR BOT
INT
BOT
35
10
LENGTH (cm)
-5.0
-10.0
-15.0
PREDATOR
5.0
TVG 40logR
Length (cm)
0.0
2011
0
Depth
Filter
DEPTH (m)
4
FISH PER ACRE
PREY
No Filter
-20.0
-25.0
-30.0
-20
-20
-30
-30
-35.0
-40.0
0.0
-40
-40
-50
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1007
70
0
-50
0
1
2
0
20
40
Sonar:Cheesman2011June:K1820026.FSH
OUTPUT
Sonar:Cheesman2011June:K1820026.FSH
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
Transect length (m): 1007 Total pings: 4062
Number prey/acre: 1.017
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.000
Number predators/acre: 55.869
Biomass predators/acre (kg): 2.587
16000
Predator/prey cutoff: 5.0 cm
13000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
12000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000662 0.000181
-15.000000 0.000000 0.000043 0.078667 0.001338
-20.000000 0.000000 0.000000 0.020672 0.000504
-25.000000 0.000000 0.000000 0.012540 0.000471
-30.000000 0.000000 0.000000 0.005811 0.000184
-35.000000 0.000000 0.000000 0.008235 0.000058
-40.000000 0.000000 0.000000 0.000000 0.000000
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000000 0.000004 0.013049 0.000280
15000
14000
11000
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 12/30/11 at 11:17 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
474909
475431
START UTM Y
END UTM Y
4337236
4337965
PREDATOR/PREY
CUTOFF (cm)
NONE
40logR
COLUMN 9
ALL
DEL>0
USE INT OR BOT
INT
BOT
Length (cm)
35
10
0.0
-5.0
LENGTH (cm)
-10.0
-15.0
2011
PREDATOR
-20.0
0
0
-25.0
-10
-10
-30.0
-20
-20
-30
-30
5.0
TVG 40logR
Depth
Filter
DEPTH (m)
5
FISH PER ACRE
PREY
No Filter
-35.0
-40.0
-45.0
0.0
-40
-40
-50
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
897
47
0
-50
0
1
2
0
20
40
Sonar:Cheesman2011June:K1820010.FSH
OUTPUT
Sonar:Cheesman2011June:K1820010.FSH
Transect length (m): 897 Total pings: 3522
Number prey/acre: 1.981
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.000
Number predators/acre: 59.127
Biomass predators/acre (kg): 2.692
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000068 0.042326 0.000612
-15.000000 0.000000 0.000000 0.053233 0.001335
-20.000000 0.000000 0.000000 0.004910 0.000401
-25.000000 0.000000 0.000000 0.007610 0.000134
-30.000000 0.000000 0.000000 0.000000 0.000000
-35.000000 0.000000 0.000000 0.000000 0.000000
-40.000000 0.000000 0.000000 0.000165 0.000055
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
17000
16000
15000
14000
13000
12000
11000
10000
9000
8000
7000
6000
Total per cubic meter
0.000000 0.000000 0.000006 0.010805 0.000263
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 12/30/11 at 11:20 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
475183
474919
START UTM Y
END UTM Y
4336595
4337199
PREDATOR/PREY
CUTOFF (cm)
5.0
-5
-5
TVG 40logR
-10
-10
NONE
-15
-15
-20
-20
ALL
-25
-25
DEL>0
-30
-30
USE INT OR BOT
-35
-35
INT
BOT
35
10
0.0
LENGTH (cm)
-5.0
2011
0
COLUMN 9
Length (cm)
-10.0
0
40logR
Depth
Filter
DEPTH (m)
6
FISH PER ACRE
PREY
No Filter
-40
PREDATOR
-15.0
-20.0
-25.0
-30.0
-35.0
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
659
55
0
-40
0
1
2
0
50
100
Sonar:Cheesman2011June:K1812359.FSH
OUTPUT
Sonar:Cheesman2011June:K1812359.FSH
Transect length (m): 659 Total pings: 2669
Number prey/acre: 2.527
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.001
Number predators/acre: 75.195
Biomass predators/acre (kg): 3.574
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
26000
24000
22000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000000 0.000000
-15.000000 0.000066 0.000066 0.141255 0.002771
-20.000000 0.000000 0.000052 0.009210 0.000466
-25.000000 0.000000 0.000000 0.000132 0.000044
-30.000000 0.000000 0.000000 0.005999 0.000043
-35.000000 0.000000 0.000000 0.000000 0.000000
-40.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000007 0.000015 0.017907 0.000385
20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011Aug:2011CHST2.out
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011Aug:2011CHST3.out
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011Aug:2011CHST4.out
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011Aug:2011CHST5.out
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011Aug:2011CHST1.out
WD60GIG:Users:Michael:Documents:Sonar:Cheesman2011Aug:2011CHST6.out
Total length of transects (m): 5107
Number prey/acre: 42.513
95%CI (21.920, 63.106)
Biomass prey/acre (kg): 0.014
95%CI (0.010, 0.019)
Total prey biomass (MT): 0.013
95%CI (0.009, 0.018)
Number predators/acre: 100.657
95%CI (47.971, 153.343)
Biomass predators/acre (kg): 4.458
95%CI (0.255, 8.660)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
0.000016
-10
0.000057
-15
-0.00001
-20
0
-25
0.000005
-30
0.000008
-35
-0.000008
-40
-0.000006
-45
0
-50
-0.000008
-55
0
-60
NaN
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0.00009
0.000198
0.000053
0.000103
0.00006
0.000083
0.000012
0.000025
0
0.000004
0
0
0
0.000164
0.000339
0.000115
0.000206
0.000114
0.000159
0.000032
0.000057
0
0.000016
0
NaN
0
0.000031
0.000312
-0.000012
0.000001
0.000005
0.000021
-0.000008
-0.000013
0
-0.000008
0
NaN
0
0.000348
0.000817
0.000066
0.000128
0.00006
0.000098
0.000012
0.000031
0
0.000004
0
0
0
0.000665
0.001323
0.000145
0.000254
0.000114
0.000174
0.000032
0.000075
0
0.000016
0
NaN
0
-0.000117
-0.077946
0.008714
0.022754
0.000222
0.004359
-0.002276
-0.001288
-0.002016
-0.003585
-0.002218
NaN
0
0.000074
0.05026
0.043304
0.072486
0.027754
0.011747
0.005574
0.001355
0.001135
0.001643
0.000189
0
0
0.000265
0.178466
0.077893
0.122217
0.055287
0.019134
0.013424
0.003999
0.004285
0.00687
0.002597
NaN
0
-0.000029
-0.000043
0.000442
0.001016
0.000421
0.000178
-0.000039
-0.000073
-0.000063
-0.000159
-0.000527
NaN
0
0.000019
0.000181
0.001228
0.002315
0.000955
0.000481
0.000212
0.000084
0.000035
0.000073
0.000045
0
0
0.000067
0.000405
0.002015
0.003614
0.001489
0.000783
0.000462
0.000242
0.000133
0.000305
0.000617
NaN
6
6
6
6
6
6
6
6
6
5
4
2
1
Total per cubic meter
0.00004
0.000058
0.000076
0.00005
0.000128
0.000206
0.006019
0.021952
0.037886
0.000269
0.000607
0.000946
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/3/12 at 8:42 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
476297
475975
START UTM Y
END UTM Y
4340444
4341049
PREDATOR/PREY
CUTOFF (cm)
0
-10
-10
NONE
40logR
COLUMN 9
ALL
DEL>0
LENGTH (cm)
-10.0
-15.0
PREDATOR
-20.0
-25.0
-30.0
-20
-20
-30
-30
-35.0
-40.0
0.0
-40
-40
-50
-50
USE INT OR BOT
INT
BOT
10
-5.0
5.0
TVG 40logR
35
0.0
2011
0
Length (cm)
DEPTH (m)
1
FISH PER ACRE
PREY
Depth
Filter
No Filter
0 20 40 60
0
20
40
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
685
84
0
Sonar:Cheesman2011Aug:K2142325.FSH.mod
OUTPUT
Sonar:Cheesman2011Aug:K2142325.FSH.mod
Transect length (m): 685 Total pings: 2468
Number prey/acre: 71.116
Biomass prey/acre (kg): 0.019
Total prey biomass (MT): 0.018
Number predators/acre: 71.899
Biomass predators/acre (kg): 1.503
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000147 0.000590 0.000000 0.000000
-10.000000 0.000265 0.001504 0.000354 0.000088
-15.000000 0.000127 0.000127 0.020692 0.000889
-20.000000 0.000060 0.000060 0.029302 0.001390
-25.000000 0.000000 0.000000 0.012093 0.000949
-30.000000 0.000181 0.000181 0.019966 0.000632
-35.000000 0.000000 0.000000 0.004861 0.000103
-40.000000 0.000000 0.000000 0.000000 0.000000
-45.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000092 0.000266 0.012638 0.000593
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
70000
65000
60000
55000
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/3/12 at 8:50 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
476003
476293
START UTM Y
END UTM Y
4339407
4340420
PREDATOR/PREY
CUTOFF (cm)
2
0
0
-10
-10
NONE
40logR
COLUMN 9
ALL
DEL>0
10
0.0
-5.0
LENGTH (cm)
-20.0
PREDATOR
-25.0
-30.0
-35.0
-40.0
-45.0
-20
-50.0
-20
-55.0
-30
-30
-60.0
0.0
-40
-40
-50
-50
USE INT OR BOT
INT
BOT
35
DEPTH (m)
-15.0
5.0
TVG 40logR
Length (cm)
-10.0
2011
FISH PER ACRE
PREY
Depth
Filter
No Filter
0
5 10 15
0 25 50 75
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1054
332
0
Sonar:Cheesman2011Aug:K2142312.FSH
OUTPUT
Sonar:Cheesman2011Aug:K2142312.FSH
Transect length (m): 1054 Total pings: 3743
Number prey/acre: 25.598
Biomass prey/acre (kg): 0.010
Total prey biomass (MT): 0.010
Number predators/acre: 115.282
Biomass predators/acre (kg): 2.993
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
65000
60000
55000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000403 0.000115 0.000058
-15.000000 0.000083 0.000165 0.034238 0.000784
-20.000000 0.000288 0.000353 0.070196 0.002981
-25.000000 0.000105 0.000105 0.029800 0.001284
-30.000000 0.000046 0.000068 0.014687 0.000911
-35.000000 0.000039 0.000039 0.020202 0.000671
-40.000000 0.000071 0.000106 0.006405 0.000388
-45.000000 0.000000 0.000000 0.005674 0.000176
-50.000000 0.000015 0.000015 0.006570 0.000292
-55.000000 0.000000 0.000000 0.000379 0.000090
-60.000000 0.000000 0.000000 0.000000 0.000000
50000
45000
40000
35000
30000
25000
20000
Total per cubic meter
0.000000 0.000051 0.000081 0.014871 0.000623
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 2/1/12 at 9:57 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
475337
475975
START UTM Y
END UTM Y
4339038
4339395
PREDATOR/PREY
CUTOFF (cm)
3
NONE
40logR
COLUMN 9
ALL
DEL>0
PREDATOR
LENGTH (cm)
-5.0
-15.0
-10
-10
-25.0
-20
-20
-30.0
-30
-30
-35.0
-20.0
0.0
-40
-40
-50
-50
5
10
0.0
0
0
35
DEPTH (m)
0
USE INT OR BOT
INT
BOT
Length (cm)
-10.0
5.0
TVG 40logR
Depth
Filter
2011
FISH PER ACRE
PREY
No Filter
10
0 10 20 30
5.0
10.0
15.0
20.0
25.0
30.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
731
65
0
Sonar:Cheesman2011Aug:K2142302.FSHmod
OUTPUT
Sonar:Cheesman2011Aug:K2142302.FSHmod
Transect length (m): 731 Total pings: 2356
Number prey/acre: 16.386
Biomass prey/acre (kg): 0.014
Total prey biomass (MT): 0.013
Number predators/acre: 52.632
Biomass predators/acre (kg): 1.512
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000138 0.000138 0.000000 0.000000
-10.000000 0.000166 0.000249 0.000000 0.000000
-15.000000 0.000000 0.000000 0.016198 0.000942
-20.000000 0.000103 0.000103 0.034762 0.000930
-25.000000 0.000089 0.000089 0.027391 0.000620
-30.000000 0.000082 0.000082 0.006319 0.000328
-35.000000 0.000000 0.000000 0.000000 0.000000
-40.000000 0.000000 0.000000 0.000000 0.000000
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
-55.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000045 0.000050 0.008434 0.000272
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
28000
26000
24000
22000
20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/3/12 at 9:45 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
475460
475340
START UTM Y
END UTM Y
4337986
4338993
PREDATOR/PREY
CUTOFF (cm)
0
-10
-10
NONE
40logR
-20
-20
COLUMN 9
ALL
-30
-30
DEL>0
LENGTH (cm)
-10.0
-15.0
PREDATOR
-20.0
-25.0
-30.0
-35.0
-40.0
-45.0
0.0
-40
-40
-50
-50
USE INT OR BOT
INT
BOT
10
-5.0
5.0
TVG 40logR
35
0.0
2011
0
Length (cm)
DEPTH (m)
4
FISH PER ACRE
PREY
Depth
Filter
No Filter
0
20
40
0
20
40
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1014
134
0
Sonar:Cheesman2011Aug:K2142245.FSH
OUTPUT
Sonar:Cheesman2011Aug:K2142245.FSH
Transect length (m): 1014 Total pings: 3566
Number prey/acre: 41.349
Biomass prey/acre (kg): 0.009
Total prey biomass (MT): 0.008
Number predators/acre: 67.320
Biomass predators/acre (kg): 2.294
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
40000
38000
36000
34000
Predator/prey cutoff: 5.0 cm
32000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
30000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000100 0.000000 0.000000
-10.000000 0.000179 0.001136 0.000359 0.000060
-15.000000 0.000000 0.000000 0.039619 0.000815
-20.000000 0.000072 0.000107 0.056098 0.001719
-25.000000 0.000000 0.000000 0.007341 0.000580
-30.000000 0.000157 0.000188 0.011799 0.000282
-35.000000 0.000033 0.000033 0.004791 0.000230
-40.000000 0.000034 0.000034 0.001242 0.000034
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
28000
26000
24000
22000
20000
18000
16000
14000
Total per cubic meter
0.000000 0.000049 0.000127 0.013436 0.000422
12000
10000
8000
6000
4000
2000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/3/12 at 9:59 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
474911
475441
START UTM Y
END UTM Y
4337234
4337967
PREDATOR/PREY
CUTOFF (cm)
5
0
0
-10
-10
NONE
40logR
-20
-20
COLUMN 9
ALL
-30
-30
DEL>0
PREDATOR
10
0.0
-5.0
LENGTH (cm)
-20.0
-25.0
-30.0
-35.0
-40.0
-45.0
0.0
-40
-40
-50
-50
USE INT OR BOT
INT
BOT
35
DEPTH (m)
-15.0
5.0
TVG 40logR
Length (cm)
-10.0
2011
FISH PER ACRE
PREY
Depth
Filter
No Filter
0
20
40
0 20 40 60
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
905
123
0
Sonar:Cheesman2011Aug:K2142233.FSH.mod
OUTPUT
Sonar:Cheesman2011Aug:K2142233.FSH.mod
Transect length (m): 905 Total pings: 3258
Number prey/acre: 53.086
Biomass prey/acre (kg): 0.019
Total prey biomass (MT): 0.018
Number predators/acre: 106.070
Biomass predators/acre (kg): 11.519
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
50000
47500
45000
42500
Predator/prey cutoff: 5.0 cm
40000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
37500
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000112 0.000558 0.000446 0.000112
-10.000000 0.000408 0.001020 0.299636 0.000544
-15.000000 0.000106 0.000106 0.041834 0.001216
-20.000000 0.000000 0.000000 0.085477 0.002547
-25.000000 0.000045 0.000045 0.011906 0.000494
-30.000000 0.000000 0.000000 0.000937 0.000122
-35.000000 0.000000 0.000000 0.000209 0.000084
-40.000000 0.000047 0.000047 0.000047 0.000047
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
35000
32500
30000
27500
25000
22500
20000
17500
Total per cubic meter
0.000000 0.000058 0.000127 0.037852 0.000522
15000
12500
10000
7500
5000
2500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/3/12 at 10:07 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
CHEESMAN
controls before running VI
TRANSECT #
START UTM X
END UTM X
475213
474917
START UTM Y
END UTM Y
4336558
4337212
PREDATOR/PREY
CUTOFF (cm)
0
5.0
-5
-5
TVG 40logR
-10
-10
NONE
40logR
-15
-15
-20
-20
ALL
-25
-25
DEL>0
-30
-30
USE INT OR BOT
-35
-35
INT
BOT
-40
-40
COLUMN 9
0
20
40
35
10
0.0
-5.0
LENGTH (cm)
-10.0
-15.0
2011
0
Length (cm)
DEPTH (m)
6
FISH PER ACRE
PREY
Depth
Filter
No Filter
PREDATOR
-20.0
-25.0
-30.0
-35.0
-40.0
-45.0
0.0
0
50
100
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
718
231
0
Sonar:Cheesman2011Aug:K2142223.FSH
OUTPUT
Sonar:Cheesman2011Aug:K2142223.FSH
Transect length (m): 718 Total pings: 2623
Number prey/acre: 47.544
Biomass prey/acre (kg): 0.014
Total prey biomass (MT): 0.013
Number predators/acre: 190.739
Biomass predators/acre (kg): 6.924
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
60000
55000
50000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
45000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000141 0.000703 0.000000 0.000000
-10.000000 0.000169 0.000591 0.001097 0.000338
-15.000000 0.000000 0.000000 0.107242 0.002725
-20.000000 0.000095 0.000143 0.159080 0.004323
-25.000000 0.000118 0.000118 0.077996 0.001804
-30.000000 0.000034 0.000068 0.016773 0.000609
-35.000000 0.000000 0.000000 0.003381 0.000181
-40.000000 0.000000 0.000000 0.000439 0.000037
40000
35000
30000
25000
Total per cubic meter
0.000000 0.000052 0.000115 0.044484 0.001212
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:Dillon2011August:2011DillonT5m.out
WD60GIG:Users:Michael:Documents:Sonar:Dillon2011August:2011DillonT4m.out
WD60GIG:Users:Michael:Documents:Sonar:Dillon2011August:2011DillonT6m.out
WD60GIG:Users:Michael:Documents:Sonar:Dillon2011August:2011DillonT1m.out
WD60GIG:Users:Michael:Documents:Sonar:Dillon2011August:2011DillonT2m.out
WD60GIG:Users:Michael:Documents:Sonar:Dillon2011August:2011DillonT3m.out
WD60GIG:Users:Michael:Documents:Sonar:Dillon2011August:2011DillonT7m.out
Total length of transects (m): 11680
Number prey/acre: 0.306
95%CI (0.187, 0.425)
Biomass prey/acre (kg): 0.000
95%CI (0.000, 0.000)
Total prey biomass (MT): 0.001
95%CI (0.001, 0.001)
Number predators/acre: 7.481
95%CI (3.579, 11.382)
Biomass predators/acre (kg): 0.482
95%CI (0.225, 0.740)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
0
-10
0
-15
-0.000006
-20
-0.000003
-25
-0.000004
-30
-0.000002
-35
0
-40
-0.000003
-45
0
-50
-0.0001
-55
0
-60
NaN
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0
0
0.000009
0.000006
0.000003
0.000013
0
0.000002
0
0.000008
0
0
0
0
0
0.000023
0.000015
0.00001
0.000028
0
0.000007
0
0.000117
0
NaN
0
0
0
-0.000003
-0.000003
-0.000004
-0.000002
0
-0.000003
0
-0.0001
0
NaN
0
0
0
0.000013
0.000006
0.000003
0.000013
0
0.000002
0
0.000008
0
0
0
0
0
0.000028
0.000015
0.00001
0.000028
0
0.000007
0
0.000117
0
NaN
0
-0.002625
-0.00278
0.004346
-0.000266
0.001668
-0.003548
0.000745
-0.000594
-0.000694
-0.003618
0
NaN
0
0.001815
0.00549
0.011264
0.007972
0.011842
0.011867
0.004185
0.000804
0.000253
0.000791
0
0
0
0.006255
0.013761
0.018183
0.016211
0.022016
0.027282
0.007624
0.002203
0.001201
0.0052
0
NaN
0
-0.000012
0.000036
0.000057
0.000014
0.000076
-0.000018
-0.000004
-0.000014
-0.000019
-0.000076
0
NaN
0
0.000009
0.000071
0.000153
0.000119
0.000187
0.000222
0.00013
0.000032
0.000016
0.000026
0
0
0
0.00003
0.000106
0.000248
0.000225
0.000297
0.000461
0.000264
0.000079
0.000051
0.000128
0
NaN
7
7
7
7
7
7
7
7
6
3
2
2
1
Total per cubic meter
0.000004
0.000005
0.000007
0.000004
0.000005
0.000007
0.002564
0.008023
0.013483
0.000052
0.000132
0.000212
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/2/11 at 1:56 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
DILLON
controls before running VI
TRANSECT #
START UTM X
END UTM X
409032
407930
START UTM Y
END UTM Y
4384127
4383029
PREDATOR/PREY
CUTOFF (cm)
10
0.0
LENGTH (cm)
-5.0
-10.0
0
5.0
-5
-5
TVG 40logR
-10
-10
NONE
40logR
-15
-15
-20
-20
ALL
-25
-25
DEL>0
-30
-30
USE INT OR BOT
-35
-35
INT
BOT
-40
-40
0
Length (cm)
35
2011
0
COLUMN 9
Depth
Filter
DEPTH (m)
1
FISH PER ACRE
PREY
No Filter
1
PREDATOR
-15.0
-20.0
-25.0
-30.0
-35.0
0.0
0
129
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1556
37
0
Sonar:Dillon2011August:K2362346.FSH
OUTPUT
Sonar:Dillon2011August:K2362346.FSH
Transect length (m): 1556 Total pings: 5522
Number prey/acre: 0.207
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.001
Number predators/acre: 9.290
Biomass predators/acre (kg): 0.694
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
10500
10000
9500
9000
8500
8000
7500
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.004596 0.000117
-15.000000 0.000000 0.000000 0.017855 0.000363
-20.000000 0.000000 0.000000 0.020740 0.000139
-25.000000 0.000000 0.000000 0.027305 0.000232
-30.000000 0.000031 0.000031 0.008241 0.000154
-35.000000 0.000000 0.000000 0.000000 0.000000
-40.000000 0.000000 0.000000 0.000000 0.000000
7000
Total per cubic meter
0.000000 0.000005 0.000005 0.013974 0.000169
4000
6500
6000
5500
5000
4500
3500
3000
2500
2000
1500
1000
500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/2/11 at 1:57 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
DILLON
controls before running VI
TRANSECT #
START UTM X
END UTM X
409911
409052
START UTM Y
END UTM Y
4382302
4384088
PREDATOR/PREY
CUTOFF (cm)
10
LENGTH (cm)
-10.0
2011
-15.0
PREDATOR
-20.0
5.0
-5
-5
-25.0
TVG 40logR
-10
-10
-30.0
NONE
40logR
-15
-15
-20
-20
ALL
-25
-25
DEL>0
-30
-30
USE INT OR BOT
-35
-35
INT
BOT
-40
-40
1
Length (cm)
35
-5.0
0
0
Depth
0.0
0
COLUMN 9
Filter
DEPTH (m)
2
FISH PER ACRE
PREY
No Filter
-35.0
-40.0
0.0
0
129
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1982
45
0
Sonar:Dillon2011August:K2362321.FSH
OUTPUT
Sonar:Dillon2011August:K2362321.FSH
Transect length (m): 1982 Total pings: 6918
Number prey/acre: 0.428
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.001
Number predators/acre: 9.605
Biomass predators/acre (kg): 0.425
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
9500
9000
8500
8000
Predator/prey cutoff: 5.0 cm
7500
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
7000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000063 0.000031
-15.000000 0.000023 0.000023 0.003951 0.000162
-20.000000 0.000021 0.000021 0.006380 0.000170
-25.000000 0.000000 0.000000 0.027471 0.000357
-30.000000 0.000000 0.000000 0.009830 0.000206
-35.000000 0.000000 0.000000 0.008420 0.000337
-40.000000 0.000000 0.000000 0.000000 0.000000
6500
6000
5500
5000
4500
4000
Total per cubic meter
0.000000 0.000008 0.000008 0.008790 0.000179
3500
3000
2500
2000
1500
1000
500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 3/20/12 at 6:18 PM
Printed on 3/20/12 at 6:30 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
DILLON
controls before running VI
TRANSECT #
START UTM X
END UTM X
0
START UTM Y
END UTM Y
0
1874
-20.0
-5
-5
-25.0
TVG 40logR
-10
-10
-30.0
NONE
40logR
-15
-15
-20
-20
ALL
-25
-25
DEL>0
-30
-30
USE INT OR BOT
-35
-35
INT
BOT
-40
-40
4
6
LENGTH (cm)
-15.0
PREDATOR
42.5
2
10
-10.0
0
0
35
-5.0
0
COLUMN 9
Length (cm)
0.0
2011
FISH PER ACRE
PREY
Depth
Filter
DEPTH (m)
3
0
PREDATOR/PREY
CUTOFF (cm)
No
-35.0
-40.0
0.0
0
1
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1874
80
0
Sonar:Dillon2011August:K2362254.FSHmod
OUTPUT
Sonar:Dillon2011August:K2362254.FSHmod
Transect length (m): 1874 Total pings: 7021
Number prey/acre: 14.615
Biomass prey/acre (kg): 1.031
Total prey biomass (MT): 3.368
Number predators/acre: 0.242
Biomass predators/acre (kg): 0.185
Predator/prey cutoff: 42.5 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.005595 0.000065 0.000000 0.000000
-15.000000 0.009034 0.000116 0.017858 0.000023
-20.000000 0.028093 0.000344 0.000000 0.000000
-25.000000 0.013353 0.000315 0.000000 0.000000
-30.000000 0.067184 0.000790 0.000000 0.000000
-35.000000 0.011786 0.000326 0.000000 0.000000
-40.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.020012 0.000285 0.002768 0.000004
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
14000
13000
12000
11000
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/2/11 at 2:00 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
DILLON
controls before running VI
TRANSECT #
START UTM X
END UTM X
408858
409888
START UTM Y
END UTM Y
4385429
4384183
PREDATOR/PREY
CUTOFF (cm)
2011
-20.0
PREDATOR
-25.0
-10
-35.0
-20
-20
NONE
40logR
-30
-30
COLUMN 9
-40
-40
-50
-50
USE INT OR BOT
-60
-60
INT
BOT
-70
-70
0
LENGTH (cm)
-15.0
-10
DEL>0
10
-10.0
-30.0
ALL
Length (cm)
35
0.0
0
TVG 40logR
Depth
-5.0
0
5.0
Filter
DEPTH (m)
4
FISH PER ACRE
PREY
No Filter
1
-40.0
-45.0
-50.0
-55.0
0.0
0
129
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1617
28
0
Sonar:Dillon2011August:K2362229.FSH
OUTPUT
Sonar:Dillon2011August:K2362229.FSH
Transect length (m): 1617 Total pings: 5991
Number prey/acre: 0.193
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.001
Number predators/acre: 2.434
Biomass predators/acre (kg): 0.138
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
2000
1900
1800
1700
Predator/prey cutoff: 5.0 cm
1600
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
1500
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.000187 0.000037
-15.000000 0.000000 0.000000 0.004840 0.000027
-20.000000 0.000000 0.000000 0.000000 0.000000
-25.000000 0.000000 0.000000 0.003314 0.000051
-30.000000 0.000029 0.000029 0.001011 0.000058
-35.000000 0.000000 0.000000 0.005971 0.000063
-40.000000 0.000000 0.000000 0.003280 0.000099
-45.000000 0.000000 0.000000 0.000692 0.000021
-50.000000 0.000000 0.000000 0.001138 0.000018
-55.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000003 0.000003 0.002251 0.000043
1400
1300
1200
1100
1000
900
800
700
600
500
400
300
200
100
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/2/11 at 2:02 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
DILLON
controls before running VI
TRANSECT #
START UTM X
END UTM X
410551
408881
START UTM Y
END UTM Y
4385318
4385429
PREDATOR/PREY
CUTOFF (cm)
-15.0
2011
-20.0
PREDATOR
-25.0
-10
-10
-35.0
-20
-20
NONE
40logR
-30
-30
COLUMN 9
-40
-40
-50
-50
USE INT OR BOT
-60
-60
INT
BOT
-70
-70
DEL>0
0
LENGTH (cm)
-10.0
-30.0
ALL
10
0.0
0
TVG 40logR
Length (cm)
35
-5.0
0
5.0
Depth
Filter
DEPTH (m)
5
FISH PER ACRE
PREY
No Filter
1
-40.0
-45.0
-50.0
-55.0
0.0
0
129
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1674
30
0
Sonar:Dillon2011August:K2362206.FSH.mod
OUTPUT
Sonar:Dillon2011August:K2362206.FSH.mod
Transect length (m): 1674 Total pings: 6009
Number prey/acre: 0.267
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.001
Number predators/acre: 3.297
Biomass predators/acre (kg): 0.179
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
6000
5500
5000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
4500
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.001014 0.000036
-15.000000 0.000000 0.000000 0.011610 0.000104
-20.000000 0.000020 0.000020 0.001655 0.000061
-25.000000 0.000000 0.000000 0.001007 0.000033
-30.000000 0.000000 0.000000 0.001340 0.000028
-35.000000 0.000000 0.000000 0.001318 0.000048
-40.000000 0.000011 0.000011 0.001408 0.000078
-45.000000 0.000000 0.000000 0.000068 0.000027
-50.000000 0.000017 0.000017 0.000444 0.000034
-55.000000 0.000000 0.000000 0.000000 0.000000
-60.000000 0.000000 0.000000 0.000000 0.000000
4000
Total per cubic meter
0.000000 0.000005 0.000005 0.001504 0.000041
3500
3000
2500
2000
1500
1000
500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 12/2/11 at 2:03 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
DILLON
controls before running VI
TRANSECT #
START UTM X
END UTM X
409579
410563
START UTM Y
END UTM Y
4386695
4385336
PREDATOR/PREY
CUTOFF (cm)
LENGTH (cm)
-15.0
2011
PREDATOR
-20.0
-5
-5
TVG 40logR
-10
-10
NONE
40logR
-15
-15
-35.0
-20
-20
-40.0
COLUMN 9
-25
-25
ALL
-30
-30
DEL>0
-35
-35
-40
-40
-45
-45
1
10
-10.0
5.0
0
Length (cm)
35
-5.0
0
INT
BOT
Depth
0.0
0
USE INT OR BOT
Filter
DEPTH (m)
6
FISH PER ACRE
PREY
No Filter
-25.0
-30.0
-45.0
0.0
0
129
5.0
10.0
15.0
20.0
25.0
30.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1678
45
0
Sonar:Dillon2011August:K2362143.FSH
OUTPUT
Sonar:Dillon2011August:K2362143.FSH
Transect length (m): 1678 Total pings: 6355
Number prey/acre: 0.479
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.001
Number predators/acre: 7.566
Biomass predators/acre (kg): 0.470
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.012702 0.000060
-10.000000 0.000000 0.000000 0.003251 0.000108
-15.000000 0.000000 0.000026 0.008395 0.000155
-20.000000 0.000000 0.000000 0.001369 0.000060
-25.000000 0.000000 0.000000 0.008292 0.000191
-30.000000 0.000031 0.000031 0.006363 0.000126
-35.000000 0.000000 0.000000 0.005207 0.000135
-40.000000 0.000000 0.000000 0.000139 0.000017
-45.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000005 0.000007 0.004679 0.000102
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
8000
7500
7000
6500
6000
5500
5000
4500
4000
3500
3000
2500
2000
1500
1000
500
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:ElevenMile2011:2011ElevenmileT5m.out
WD60GIG:Users:Michael:Documents:Sonar:ElevenMile2011:2011ElevenmileT4m.out
WD60GIG:Users:Michael:Documents:Sonar:ElevenMile2011:2011ElevenmileT3m.out
WD60GIG:Users:Michael:Documents:Sonar:ElevenMile2011:2011ElevenmileT2m.out
WD60GIG:Users:Michael:Documents:Sonar:ElevenMile2011:2011ElevenmileT1m.out
Total length of transects (m): 8658
Number prey/acre: 1.774
95%CI (-0.031, 3.580)
Biomass prey/acre (kg): 0.001
95%CI (-0.000, 0.003)
Total prey biomass (MT): 0.006
95%CI (0.000, 0.011)
Number predators/acre: 12.421
95%CI (-0.712, 25.554)
Biomass predators/acre (kg): 0.533
95%CI (0.181, 0.886)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
-0.000062
-10
-0.000031
-15
-0.000147
-20
-0.00019
-25
-0.001311
-30
NaN
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0.000075
0.000076
0.000236
0.000109
0.000112
0
0
0.000212
0.000183
0.000619
0.000408
0.001535
NaN
0
-0.000062
-0.000032
-0.000152
-0.00019
-0.001838
NaN
0
0.000075
0.000082
0.000299
0.000109
0.000157
0
0
0.000212
0.000197
0.00075
0.000408
0.002152
NaN
-0.000134
-0.010405
0.003744
-0.134094
-0.202916
-0.006304
NaN
0.000075
0.014283
0.038605
0.088811
0.06165
0.000539
0
0.000284
0.038971
0.073467
0.311715
0.326215
0.007381
NaN
-0.000134
0.000047
0.000152
-0.003742
-0.009238
-0.001838
NaN
0.000075
0.000275
0.00048
0.002833
0.00293
0.000157
0
0.000284
0.000504
0.000808
0.009409
0.015098
0.002152
NaN
5
5
5
4
3
2
1
Total per cubic meter
0.000009
0.000114
0.000219
0.000006
0.000134
0.000263
-0.007808
0.038648
0.085105
-0.000758
0.001099
0.002957
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 2:58 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
11 MILE
controls before running VI
TRANSECT #
START UTM X
END UTM X
454677
452424
START UTM Y
END UTM Y
4310149
4310820
PREDATOR/PREY
CUTOFF (cm)
LENGTH (cm)
-2.0
-3.0
2011
-4.0
PREDATOR
-5.0
-6.0
5.0
-3
-3
-7.0
TVG 40logR
-4
-4
-8.0
NONE
40logR
-5
-5
-9.0
-6
-6
-10.0
-7
-7
-11.0
-8
-8
USE INT OR BOT
-9
-9
INT
BOT
-10
-10
0
10
-1.0
-2
ALL
DEL>0
Length (cm)
35
0.0
-2
COLUMN 9
Depth
Filter
DEPTH (m)
1
FISH PER ACRE
PREY
No Filter
1
0.0
0
2
4
6
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
2351
15
0
Sonar:ElevenMile2011:K2132318.FSH
OUTPUT
Sonar:ElevenMile2011:K2132318.FSH
Transect length (m): 2351 Total pings: 8485
Number prey/acre: 0.421
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.002
Number predators/acre: 5.504
Biomass predators/acre (kg): 0.503
Predator/prey cutoff: 5.0 cm
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
12000
11000
10000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
9000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000043 0.000043 0.048636 0.000473
-10.000000 0.000000 0.000000 0.004976 0.000166
8000
7000
Total per cubic meter
0.000000 0.000021 0.000021 0.025487 0.000292
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 2:59 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
11 MILE
controls before running VI
TRANSECT #
START UTM X
END UTM X
454702
START UTM Y
END UTM Y
4309132
4310143
-6.0
PREDATOR
-8.0
-10.0
-4
-4
-12.0
TVG 40logR
-6
-6
NONE
40logR
-14.0
-8
-8
-16.0
COLUMN 9
-10
-10
ALL
DEL>0
-12
-12
USE INT OR BOT
-14
-14
INT
BOT
-16
-16
1
2
3
LENGTH (cm)
-4.0
-2
0
10
-2.0
-2
5.0
Length (cm)
35
0.0
2011
FISH PER ACRE
PREY
Depth
Filter
DEPTH (m)
2
456311
PREDATOR/PREY
CUTOFF (cm)
No Filter
-18.0
0.0
0
2
4
6
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1900
41
0
Sonar:ElevenMile2011:K2132254.FSH
OUTPUT
Sonar:ElevenMile2011:K2132254.FSH
Transect length (m): 1900 Total pings: 6806
Number prey/acre: 3.631
Biomass prey/acre (kg): 0.003
Total prey biomass (MT): 0.012
Number predators/acre: 10.597
Biomass predators/acre (kg): 0.244
Predator/prey cutoff: 5.0 cm
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
24000
22000
20000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
18000
-2.000000 0.000000 0.000000 0.000376 0.000376
-5.000000 0.000266 0.000266 0.012068 0.000478
-10.000000 0.000128 0.000159 0.023030 0.000415
-15.000000 0.000042 0.000084 0.000587 0.000210
16000
Total per cubic meter
0.000000 0.000126 0.000151 0.012164 0.000366
12000
14000
10000
8000
6000
4000
2000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 3:01 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
11 MILE
controls before running VI
TRANSECT #
START UTM X
END UTM X
456833
456320
START UTM Y
END UTM Y
4307682
4309113
PREDATOR/PREY
CUTOFF (cm)
-6.0
2011
-8.0
PREDATOR
-10.0
-4
-4
-12.0
TVG 40logR
-6
-6
-14.0
NONE
40logR
-8
-8
-16.0
-10
-10
-18.0
COLUMN 9
-12
-12
ALL
DEL>0
-14
-14
-16
-16
-18
-18
-20
-20
1
LENGTH (cm)
-4.0
5.0
0
10
-2.0
-2
INT
BOT
Length (cm)
35
0.0
-2
USE INT OR BOT
Depth
Filter
DEPTH (m)
3
FISH PER ACRE
PREY
No Filter
2
-20.0
0.0
0
2
4
6
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1520
63
0
Sonar:ElevenMile2011:K2132235.FSH.mod
OUTPUT
Sonar:ElevenMile2011:K2132235.FSH.mod
Transect length (m): 1520 Total pings: 5364
Number prey/acre: 2.582
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.008
Number predators/acre: 7.680
Biomass predators/acre (kg): 0.417
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000066 0.000066 0.000199 0.000133
-10.000000 0.000199 0.000199 0.078429 0.000877
-15.000000 0.000287 0.000395 0.001185 0.000790
-20.000000 0.000000 0.000000 0.000000 0.000000
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
19000
18000
17000
16000
15000
14000
13000
12000
11000
10000
Total per cubic meter
0.000000 0.000164 0.000200 0.023527 0.000540
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 3:02 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
11 MILE
controls before running VI
TRANSECT #
START UTM X
END UTM X
458242
456856
START UTM Y
END UTM Y
4306597
4307673
PREDATOR/PREY
CUTOFF (cm)
0
-5
-5
NONE
40logR
-10
-10
COLUMN 9
-15
-15
ALL
DEL>0
USE INT OR BOT
INT
BOT
10
-2.0
LENGTH (cm)
-4.0
-6.0
-8.0
-10.0
PREDATOR
-12.0
-14.0
-16.0
5.0
TVG 40logR
Length (cm)
35
0.0
2011
0
Depth
Filter
DEPTH (m)
4
FISH PER ACRE
PREY
No Filter
-18.0
-20.0
-22.0
-24.0
-26.0
0.0
-20
-20
-25
-25
0
1
0
1
2
3
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1755
75
0
Sonar:ElevenMile2011:K2132212.FSH.mod
OUTPUT
Sonar:ElevenMile2011:K2132212.FSH.mod
Transect length (m): 1755 Total pings: 6337
Number prey/acre: 0.206
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.001
Number predators/acre: 7.268
Biomass predators/acre (kg): 0.497
Predator/prey cutoff: 5.0 cm
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
12000
11000
10000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
9000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.009439 0.000115
-10.000000 0.000000 0.000000 0.051952 0.000566
-15.000000 0.000060 0.000060 0.058525 0.001341
-20.000000 0.000088 0.000088 0.000321 0.000205
-25.000000 0.000000 0.000000 0.000000 0.000000
8000
7000
6000
Total per cubic meter
0.000000 0.000038 0.000038 0.027323 0.000530
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 3:04 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
11 MILE
controls before running VI
TRANSECT #
START UTM X
END UTM X
458708
458269
START UTM Y
END UTM Y
4305565
4306608
PREDATOR/PREY
CUTOFF (cm)
5
0
0
-5
-5
-10
-10
-15
-15
-20
-20
USE INT OR BOT
-25
-25
INT
BOT
-30
-30
5.0
COLUMN 9
ALL
DEL>0
0
1
2
Length (cm)
35
10
DEPTH (m)
0.0
-2.5
LENGTH (cm)
-7.5
-10.0
PREDATOR
-12.5
-15.0
-17.5
-20.0
TVG 40logR
NONE
40logR
Depth
Filter
-5.0
2011
FISH PER ACRE
PREY
No Filter
-22.5
-25.0
-27.5
-30.0
0.0
0 10 20 30
10.0
20.0
30.0
40.0
50.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1132
400
0
Sonar:ElevenMile2011:K2132156.FSH
OUTPUT
Sonar:ElevenMile2011:K2132156.FSH
Transect length (m): 1132 Total pings: 4257
Number prey/acre: 2.032
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.006
Number predators/acre: 31.057
Biomass predators/acre (kg): 1.006
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
55000
50000
Predator/prey cutoff: 5.0 cm
45000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
40000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.001071 0.000178
-10.000000 0.000054 0.000054 0.034640 0.000375
-15.000000 0.000556 0.000657 0.294946 0.008993
-20.000000 0.000238 0.000238 0.184628 0.008585
-25.000000 0.000224 0.000314 0.001077 0.000314
-30.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000222 0.000262 0.104740 0.003769
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:Granby2011:2011GranbyT4m.out
WD60GIG:Users:Michael:Documents:Sonar:Granby2011:2011GranbyT5m.out
WD60GIG:Users:Michael:Documents:Sonar:Granby2011:2011GranbyT6m.out
WD60GIG:Users:Michael:Documents:Sonar:Granby2011:2011GranbyT3m.out
WD60GIG:Users:Michael:Documents:Sonar:Granby2011:2011GranbyT2m.out
WD60GIG:Users:Michael:Documents:Sonar:Granby2011:2011GranbyT7m.out
WD60GIG:Users:Michael:Documents:Sonar:Granby2011:2011GranbyT8m.out
WD60GIG:Users:Michael:Documents:Sonar:Granby2011:2011GranbyT9m.out
WD60GIG:Users:Michael:Documents:Sonar:Granby2011:2011GranbyT1m.out
WD60GIG:Users:Michael:Documents:Sonar:Granby2011:2011GranbyT10m.out
Total length of transects (m): 15008
Number prey/acre: 1.335
95%CI (0.677, 1.992)
Biomass prey/acre (kg): 0.001
95%CI (0.000, 0.002)
Total prey biomass (MT): 0.007
95%CI (0.003, 0.010)
Number predators/acre: 24.164
95%CI (18.481, 29.847)
Biomass predators/acre (kg): 1.897
95%CI (1.233, 2.560)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
-0.000008
-10
-0.000001
-15
-0.000001
-20
-0.000002
-25
0
-30
-0.000009
-35
-0.000004
-40
-0.000015
-45
-0.000009
-50
-0.000137
-55
0
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0.000006
0.00003
0.000008
0.000004
0.000009
0.000021
0.000026
0.000013
0.000069
0.000051
0
0
0.00002
0.000062
0.000017
0.000011
0.000018
0.00005
0.000055
0.000042
0.000148
0.000239
0
0
-0.000008
0.000003
-0.000003
0
0.000003
-0.000007
-0.000012
-0.000015
0.000004
-0.00027
-0.00015
0
0.000006
0.000042
0.000013
0.000011
0.000016
0.000022
0.000033
0.000013
0.000082
0.000154
0.000045
0
0.00002
0.000081
0.000029
0.000021
0.000028
0.000051
0.000077
0.000042
0.000159
0.000579
0.00024
0
-0.000126
0.017892
0.009093
0.008828
0.012708
0.017452
0.012528
-0.00168
-0.021563
-0.032426
-0.008185
0
0.003471
0.040736
0.03231
0.030497
0.032325
0.040335
0.035728
0.019883
0.084725
0.010675
0.002478
0
0.007068
0.063581
0.055528
0.052166
0.051943
0.063218
0.058928
0.041447
0.191013
0.053776
0.013142
0
0.00005
0.000451
0.000136
0.000092
0.000154
0.000209
0.00042
-0.000045
0.000168
-0.000122
-0.000401
0
0.000141
0.000674
0.000278
0.000275
0.000348
0.000351
0.000597
0.000218
0.000398
0.000151
0.000121
0
0.000231
0.000897
0.00042
0.000457
0.000543
0.000492
0.000775
0.000481
0.000628
0.000423
0.000643
10
10
10
10
10
10
8
7
6
4
3
3
Total per cubic meter
0.000008
0.000017
0.000025
0.000016
0.000025
0.000034
0.022243
0.033272
0.0443
0.000288
0.000371
0.000455
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/30/11 at 12:00 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GRANBY
controls before running VI
TRANSECT #
START UTM X
END UTM X
424978
424951
START UTM Y
END UTM Y
4445942
4444933
PREDATOR/PREY
CUTOFF (cm)
0
-5
-5
NONE
40logR
-10
-10
COLUMN 9
-15
-15
ALL
DEL>0
USE INT OR BOT
INT
BOT
10
-2.0
LENGTH (cm)
-4.0
-6.0
-8.0
-10.0
PREDATOR
-12.0
-14.0
-16.0
5.0
TVG 40logR
Length (cm)
35
0.0
2011
0
Depth
Filter
DEPTH (m)
1
FISH PER ACRE
PREY
No Filter
-18.0
-20.0
-22.0
-24.0
-26.0
0.0
-20
-20
-25
-25
0
1
0
5
10
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1009
34
0
Sonar:Granby2011:K2420006.FSH
OUTPUT
Sonar:Granby2011:K2420006.FSH
Transect length (m): 1009 Total pings: 3603
Number prey/acre: 0.358
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.000
Number predators/acre: 16.799
Biomass predators/acre (kg): 0.690
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
65000
60000
55000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000200 0.000100
-10.000000 0.000000 0.000000 0.011893 0.000300
-15.000000 0.000000 0.000000 0.006593 0.000215
-20.000000 0.000000 0.000035 0.042100 0.000780
-25.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000000 0.000010 0.014773 0.000316
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/30/11 at 11:58 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GRANBY
controls before running VI
TRANSECT #
START UTM X
END UTM X
424994
START UTM Y
END UTM Y
4447285
4445965
PREDATOR/PREY
CUTOFF (cm)
-15.0
PREDATOR
-20.0
5.0
-5
-5
-25.0
TVG 40logR
-10
-10
-30.0
NONE
40logR
-15
-15
-20
-20
-25
-25
-30
-30
USE INT OR BOT
-35
-35
INT
BOT
-40
-40
0
1
2
3
LENGTH (cm)
-10.0
0
ALL
DEL>0
10
-5.0
0
COLUMN 9
Length (cm)
35
0.0
2011
FISH PER ACRE
Depth
Filter
DEPTH (m)
2
426077
PREY
No Filter
-35.0
-40.0
0.0
0
5
10
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1707
109
0
Sonar:Granby2011:K2412344.FSH
OUTPUT
Sonar:Granby2011:K2412344.FSH
Transect length (m): 1707 Total pings: 6177
Number prey/acre: 3.001
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.015
Number predators/acre: 28.381
Biomass predators/acre (kg): 2.437
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000355 0.000118
-10.000000 0.000142 0.000178 0.009231 0.000568
-15.000000 0.000000 0.000000 0.049591 0.000280
-20.000000 0.000000 0.000000 0.055178 0.000574
-25.000000 0.000000 0.000046 0.086833 0.000580
-30.000000 0.000000 0.000000 0.075952 0.000583
-35.000000 0.000000 0.000000 0.029226 0.000490
-40.000000 0.000000 0.000000 0.000000 0.000000
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
95000
90000
85000
80000
75000
70000
65000
60000
55000
50000
45000
40000
Total per cubic meter
0.000000 0.000018 0.000031 0.047297 0.000453
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/30/11 at 11:57 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GRANBY
controls before running VI
TRANSECT #
START UTM X
END UTM X
425664
426064
START UTM Y
END UTM Y
4445683
4447267
PREDATOR/PREY
CUTOFF (cm)
-20.0
PREDATOR
-25.0
-5
-30.0
TVG 40logR
-10
-10
-35.0
NONE
40logR
-15
-15
-40.0
-20
-20
-45.0
COLUMN 9
-25
-25
ALL
DEL>0
-30
-30
-35
-35
-40
-40
-45
-45
2
LENGTH (cm)
-15.0
2011
-5
1
10
-10.0
5.0
0
Length (cm)
35
-5.0
0
INT
BOT
Depth
0.0
0
USE INT OR BOT
Filter
DEPTH (m)
3
FISH PER ACRE
PREY
No Filter
-50.0
0.0
0
5
10
10.0
20.0
30.0
40.0
50.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1634
171
0
Sonar:Granby2011:K2412323.FSH
OUTPUT
Sonar:Granby2011:K2412323.FSH
Transect length (m): 1634 Total pings: 5874
Number prey/acre: 2.408
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.011
Number predators/acre: 33.525
Biomass predators/acre (kg): 2.220
Predator/prey cutoff: 5.0 cm
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
120000
110000
100000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
90000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.001298 0.000433
-10.000000 0.000037 0.000074 0.035125 0.000482
-15.000000 0.000027 0.000053 0.045873 0.000399
-20.000000 0.000021 0.000021 0.019621 0.000372
-25.000000 0.000034 0.000034 0.054606 0.000592
-30.000000 0.000000 0.000000 0.035054 0.000537
-35.000000 0.000024 0.000024 0.073802 0.000970
-40.000000 0.000000 0.000000 0.010558 0.000163
-45.000000 0.000128 0.000128 0.135893 0.000384
80000
Total per cubic meter
0.000000 0.000022 0.000028 0.041045 0.000512
70000
60000
50000
40000
30000
20000
10000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/30/11 at 11:55 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GRANBY
controls before running VI
TRANSECT #
START UTM X
END UTM X
427270
425695
START UTM Y
END UTM Y
4445983
4445694
PREDATOR/PREY
CUTOFF (cm)
-15.0
2011
-20.0
PREDATOR
-25.0
-10
-20
-20
-45.0
-30
-30
-50.0
-40
-40
USE INT OR BOT
-50
-50
INT
BOT
-60
-60
-30.0
-35.0
-40.0
TVG 40logR
ALL
DEL>0
LENGTH (cm)
-10.0
-10
COLUMN 9
10
-5.0
0
NONE
40logR
Length (cm)
35
0.0
0
5.0
Depth
Filter
DEPTH (m)
4
FISH PER ACRE
PREY
No Filter
0
1
-55.0
0.0
0
5
10
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1601
110
0
Sonar:Granby2011:K2412302.FSH
OUTPUT
Sonar:Granby2011:K2412302.FSH
Transect length (m): 1601 Total pings: 5688
Number prey/acre: 0.526
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.003
Number predators/acre: 18.357
Biomass predators/acre (kg): 1.948
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.010221 0.000063
-10.000000 0.000000 0.000000 0.042208 0.000644
-15.000000 0.000000 0.000000 0.013904 0.000081
-20.000000 0.000021 0.000021 0.018485 0.000084
-25.000000 0.000000 0.000000 0.018859 0.000328
-30.000000 0.000000 0.000000 0.079113 0.000360
-35.000000 0.000020 0.000020 0.016353 0.000347
-40.000000 0.000000 0.000000 0.043863 0.000126
-45.000000 0.000049 0.000097 0.144813 0.000390
-50.000000 0.000138 0.000345 0.030705 0.000276
-55.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000013 0.000024 0.038560 0.000266
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
47500
45000
42500
40000
37500
35000
32500
30000
27500
25000
22500
20000
17500
15000
12500
10000
7500
5000
2500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/30/11 at 11:53 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GRANBY
controls before running VI
TRANSECT #
START UTM X
END UTM X
426357
427268
START UTM Y
END UTM Y
4444722
4445947
PREDATOR/PREY
CUTOFF (cm)
LENGTH (cm)
-10.0
-15.0
-20.0
2011
PREDATOR
-25.0
-30.0
-10
-10
-40.0
TVG 40logR
-20
-20
-45.0
NONE
40logR
-30
-30
COLUMN 9
-40
-40
ALL
DEL>0
-50
-50
USE INT OR BOT
-60
-60
INT
BOT
-70
-70
1
10
-5.0
0
0
Length (cm)
35
0.0
0
5.0
Depth
Filter
DEPTH (m)
5
FISH PER ACRE
PREY
No Filter
-35.0
-50.0
-55.0
-60.0
0.0
0
2
4
6
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1527
151
0
Sonar:Granby2011:K2412241.FSH
OUTPUT
Sonar:Granby2011:K2412241.FSH
Transect length (m): 1527 Total pings: 5501
Number prey/acre: 0.705
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.005
Number predators/acre: 15.322
Biomass predators/acre (kg): 0.459
Predator/prey cutoff: 5.0 cm
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
60000
55000
50000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
45000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000992 0.000198
-10.000000 0.000040 0.000040 0.004763 0.000397
-15.000000 0.000000 0.000000 0.001367 0.000114
-20.000000 0.000000 0.000000 0.001416 0.000044
-25.000000 0.000000 0.000000 0.006874 0.000145
-30.000000 0.000015 0.000015 0.021008 0.000153
-35.000000 0.000000 0.000000 0.061148 0.000591
-40.000000 0.000012 0.000012 0.019340 0.000375
-45.000000 0.000013 0.000013 0.007102 0.000233
-50.000000 0.000015 0.000015 0.001047 0.000073
-55.000000 0.000000 0.000000 0.007435 0.000364
40000
35000
30000
25000
20000
Total per cubic meter
0.000000 0.000009 0.000009 0.015482 0.000252
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/30/11 at 11:51 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GRANBY
controls before running VI
TRANSECT #
START UTM X
END UTM X
427567
426386
START UTM Y
END UTM Y
4443982
4444719
PREDATOR/PREY
CUTOFF (cm)
6
0
0
-10
-10
-20
-20
-30
-30
-40
-40
USE INT OR BOT
-50
-50
INT
BOT
-60
-60
5.0
COLUMN 9
ALL
DEL>0
0
1
Length (cm)
35
10
DEPTH (m)
0.0
-5.0
LENGTH (cm)
-15.0
-20.0
PREDATOR
-25.0
-30.0
-35.0
-40.0
TVG 40logR
NONE
40logR
Depth
Filter
-10.0
2011
FISH PER ACRE
PREY
No Filter
-45.0
-50.0
-55.0
-60.0
0.0
0 10 20 30
10.0
20.0
30.0
40.0
50.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1392
194
0
Sonar:Granby2011:K2412223.FSH
OUTPUT
Sonar:Granby2011:K2412223.FSH
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
Transect length (m): 1392 Total pings: 4997
Number prey/acre: 1.074
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.002
Number predators/acre: 36.668
Biomass predators/acre (kg): 2.448
75000
Predator/prey cutoff: 5.0 cm
60000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
55000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.007547 0.000145
-10.000000 0.000000 0.000044 0.076846 0.001437
-15.000000 0.000000 0.000000 0.019084 0.000250
-20.000000 0.000000 0.000000 0.021552 0.000218
-25.000000 0.000000 0.000000 0.038043 0.000258
-30.000000 0.000035 0.000035 0.041918 0.000489
-35.000000 0.000000 0.000000 0.045568 0.000644
-40.000000 0.000069 0.000069 0.045538 0.000645
-45.000000 0.000088 0.000088 0.051091 0.000585
-50.000000 0.000000 0.000103 0.000274 0.000103
-55.000000 0.000000 0.000136 0.000000 0.000000
70000
65000
50000
45000
40000
35000
30000
25000
Total per cubic meter
0.000000 0.000020 0.000033 0.035704 0.000460
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/30/11 at 11:50 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GRANBY
controls before running VI
TRANSECT #
START UTM X
END UTM X
428633
427586
START UTM Y
END UTM Y
4444487
4443984
PREDATOR/PREY
CUTOFF (cm)
7
-15.0
PREDATOR
-20.0
-5
-5
-25.0
TVG 40logR
-10
-10
-30.0
NONE
40logR
-15
-15
-20
-20
-25
-25
-30
-30
USE INT OR BOT
-35
-35
INT
BOT
-40
-40
1
LENGTH (cm)
-5.0
5.0
0
10
0.0
0
ALL
DEL>0
Length (cm)
35
DEPTH (m)
0
COLUMN 9
Depth
Filter
-10.0
2011
FISH PER ACRE
PREY
No Filter
-35.0
-40.0
0.0
0
5 10 15
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1162
77
0
Sonar:Granby2011:K2412208.FSH
OUTPUT
Sonar:Granby2011:K2412208.FSH
Transect length (m): 1162 Total pings: 4195
Number prey/acre: 1.893
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.011
Number predators/acre: 19.428
Biomass predators/acre (kg): 1.772
Predator/prey cutoff: 5.0 cm
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
60000
55000
50000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
45000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000052 0.000052 0.044855 0.000678
-15.000000 0.000000 0.000000 0.052009 0.000412
-20.000000 0.000000 0.000029 0.000378 0.000058
-25.000000 0.000024 0.000024 0.019256 0.000071
-30.000000 0.000101 0.000101 0.051253 0.000302
-35.000000 0.000053 0.000053 0.016443 0.000612
-40.000000 0.000000 0.000000 0.000000 0.000000
40000
35000
30000
25000
Total per cubic meter
0.000000 0.000040 0.000044 0.027708 0.000298
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/30/11 at 11:48 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GRANBY
controls before running VI
TRANSECT #
START UTM X
END UTM X
429716
428668
START UTM Y
END UTM Y
4443050
4444482
PREDATOR/PREY
CUTOFF (cm)
8
LENGTH (cm)
-5.0
-15.0
PREDATOR
-20.0
-5
-5
TVG 40logR
-10
-10
-30.0
NONE
40logR
-15
-15
-35.0
COLUMN 9
-20
-20
ALL
DEL>0
-25
-25
USE INT OR BOT
-30
-30
INT
BOT
-35
-35
1
10
0.0
0
0
Length (cm)
35
DEPTH (m)
0
5.0
Depth
Filter
-10.0
2011
FISH PER ACRE
PREY
No Filter
-25.0
-40.0
0.0
0
5 10 15
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1775
100
0
Sonar:Granby2011:K2412145.FSH
OUTPUT
Sonar:Granby2011:K2412145.FSH
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
Transect length (m): 1775 Total pings: 6376
Number prey/acre: 1.389
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.008
Number predators/acre: 19.660
Biomass predators/acre (kg): 2.036
75000
Predator/prey cutoff: 5.0 cm
60000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
55000
70000
65000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.013544 0.000228
-10.000000 0.000034 0.000034 0.043739 0.000683
-15.000000 0.000024 0.000024 0.001739 0.000147
-20.000000 0.000000 0.000000 0.100324 0.000057
-25.000000 0.000016 0.000016 0.004902 0.000109
-30.000000 0.000013 0.000027 0.011303 0.000199
-35.000000 0.000082 0.000132 0.007555 0.000528
50000
Total per cubic meter
0.000000 0.000026 0.000038 0.024565 0.000252
30000
45000
40000
35000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/30/11 at 11:46 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GRANBY
controls before running VI
TRANSECT #
START UTM X
END UTM X
431167
429744
START UTM Y
END UTM Y
4443679
4443047
PREDATOR/PREY
CUTOFF (cm)
9
0
-5
-5
-10
-10
-15
-15
-20
-20
USE INT OR BOT
-25
-25
INT
BOT
-30
-30
PREDATOR
COLUMN 9
ALL
DEL>0
10
DEPTH (m)
0.0
LENGTH (cm)
-5.0
-15.0
-20.0
-25.0
TVG 40logR
NONE
40logR
Length (cm)
35
-10.0
0
5.0
Depth
Filter
2011
FISH PER ACRE
PREY
No Filter
-30.0
0
1
-35.0
0.0
0
5 10 15
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1557
80
0
Sonar:Granby2011:K2412125.FSH
OUTPUT
Sonar:Granby2011:K2412125.FSH
Transect length (m): 1557 Total pings: 5603
Number prey/acre: 0.268
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.001
Number predators/acre: 20.270
Biomass predators/acre (kg): 1.293
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.030245 0.000740
-15.000000 0.000000 0.000000 0.026416 0.000140
-20.000000 0.000000 0.000000 0.008310 0.000130
-25.000000 0.000018 0.000035 0.051647 0.000692
-30.000000 0.000000 0.000000 0.007078 0.000183
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
42500
40000
37500
35000
32500
30000
27500
25000
22500
20000
Total per cubic meter
0.000000 0.000004 0.000009 0.023037 0.000335
17500
15000
12500
10000
7500
5000
2500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/22/11 at 3:22 PM
Printed on 11/30/11 at 11:42 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GRANBY
controls before running VI
TRANSECT #
START UTM X
END UTM X
432654
431196
START UTM Y
END UTM Y
4442909
4443668
PREDATOR/PREY
CUTOFF (cm)
10
2011
NONE
40logR
COLUMN 9
ALL
DEL>0
USE INT OR BOT
INT
BOT
Length (cm)
35
10
DEPTH (m)
0.0
-2.5
LENGTH (cm)
-5.0
0
0
-5
-5
-10
-10
-10.0
PREDATOR
-12.5
-15.0
5.0
TVG 40logR
Depth
Filter
-7.5
FISH PER ACRE
PREY
No Filter
-17.5
-20.0
-22.5
-25.0
-15
-15
-27.5
0.0
-20
-20
-25
-25
0
1
2
0
5 10 15
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1644
84
0
Sonar:Granby2011:K2412105.FSH
OUTPUT
Sonar:Granby2011:K2412105.FSH
Transect length (m): 1644 Total pings: 5782
Number prey/acre: 1.724
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.010
Number predators/acre: 33.231
Biomass predators/acre (kg): 3.664
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
65000
60000
55000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000061 0.000061 0.000553 0.000123
-10.000000 0.000000 0.000000 0.108457 0.000811
-15.000000 0.000026 0.000053 0.106527 0.000741
-20.000000 0.000000 0.000000 0.037608 0.000431
-25.000000 0.000000 0.000000 0.042232 0.000709
Total per cubic meter
0.000000 0.000014 0.000021 0.064545 0.000570
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:GrnMtn2011:GrnMtn2011:2011GrnMtnT1.out
WD60GIG:Users:Michael:Documents:Sonar:GrnMtn2011:GrnMtn2011:2011GrnMtnT2.out
WD60GIG:Users:Michael:Documents:Sonar:GrnMtn2011:GrnMtn2011:2011GrnMtnT3.out
WD60GIG:Users:Michael:Documents:Sonar:GrnMtn2011:GrnMtn2011:2011GrnMtnT4.out
WD60GIG:Users:Michael:Documents:Sonar:GrnMtn2011:GrnMtn2011:2011GrnMtnT5.out
Total length of transects (m): 8645
Number prey/acre: 0.947
95%CI (0.333, 1.561)
Biomass prey/acre (kg): 0.001
95%CI (0.000, 0.001)
Total prey biomass (MT): 0.001
95%CI (0.000, 0.003)
Number predators/acre: 15.522
95%CI (9.227, 21.817)
Biomass predators/acre (kg): 1.560
95%CI (0.011, 3.108)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
-0.000019
-10
-0.000032
-15
-0.000014
-20
-0.000006
-25
-0.000011
-30
0
-35
-0.000062
-40
0
-45
-0.000129
-50
0
-55
NaN
-60
NaN
-65
NaN
-70
NaN
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0.000011
0.000018
0.000017
0.000004
0.000011
0
0.00004
0
0.000011
0
0
0
0
0
0
0.00004
0.000068
0.000048
0.000014
0.000034
0
0.000141
0
0.000151
0
NaN
NaN
NaN
NaN
0
-0.000019
-0.000032
-0.000014
-0.000006
-0.000013
-0.000068
-0.000062
0
-0.000263
0
NaN
NaN
NaN
NaN
0
0.000011
0.000018
0.000017
0.000004
0.000015
0.000037
0.00004
0
0.000023
0
0
0
0
0
0
0.00004
0.000068
0.000048
0.000014
0.000043
0.000142
0.000141
0
0.000308
0
NaN
NaN
NaN
NaN
0
-0.000185
-0.000898
0.003479
-0.000584
0.003376
-0.098013
-0.210463
-0.056063
-0.114071
-0.075587
NaN
NaN
NaN
NaN
0
0.000264
0.010387
0.027687
0.019092
0.027004
0.099083
0.130852
0.021251
0.009744
0.006457
0.002746
0
0
0
0
0.000712
0.021671
0.051895
0.038768
0.050631
0.296179
0.472167
0.098565
0.13356
0.088501
NaN
NaN
NaN
NaN
0
-0.000015
0.000056
0.00012
0.000119
0.00015
0.000212
0.000061
-0.000135
-0.000392
-0.000263
NaN
NaN
NaN
NaN
0
0.000022
0.00028
0.00043
0.000386
0.000296
0.000338
0.000318
0.000103
0.000034
0.000023
0.000043
0
0
0
0
0.000059
0.000503
0.00074
0.000652
0.000442
0.000464
0.000575
0.000342
0.000459
0.000308
NaN
NaN
NaN
NaN
5
5
5
5
5
4
4
4
3
2
2
1
1
1
1
Total per cubic meter
0.000001
0.000012
0.000023
0.000004
0.000015
0.000025
0.00644
0.032023
0.057606
0.000139
0.00031
0.000481
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/15/11 at 2:57 PM
Printed on 11/22/11 at 2:28 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GREEN MTN
controls before running VI
TRANSECT #
START UTM X
END UTM X
386580
388260
START UTM Y
END UTM Y
4414927
4415609
PREDATOR/PREY
CUTOFF (cm)
0
-10
-10
NONE
40logR
COLUMN 9
ALL
DEL>0
10
LENGTH (cm)
-10.0
-15.0
-20.0
PREDATOR
-25.0
-30.0
-35.0
-40.0
-45.0
-20
-50.0
-20
-55.0
-30
-30
-60.0
0.0
-40
-40
-50
-50
USE INT OR BOT
INT
BOT
Length (cm)
35
0.0
5.0
TVG 40logR
Depth
-5.0
2011
0
Filter
DEPTH (m)
1
FISH PER ACRE
PREY
No Filter
0
1
0
2
4
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1813
84
0
GrnMtn2011:GrnMtn2011:K2372036.FSH
OUTPUT
GrnMtn2011:GrnMtn2011:K2372036.FSH
Transect length (m): 1813 Total pings: 6641
Number prey/acre: 0.732
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.001
Number predators/acre: 12.948
Biomass predators/acre (kg): 3.657
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
9500
9000
8500
8000
Predator/prey cutoff: 5.0 cm
7500
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
7000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.002111 0.000277
-15.000000 0.000055 0.000055 0.015874 0.000275
-20.000000 0.000000 0.000000 0.008779 0.000175
-25.000000 0.000000 0.000000 0.006298 0.000178
-30.000000 0.000000 0.000000 0.282424 0.000271
-35.000000 0.000025 0.000025 0.452110 0.000518
-40.000000 0.000000 0.000000 0.057019 0.000214
-45.000000 0.000022 0.000045 0.019489 0.000067
-50.000000 0.000000 0.000000 0.012914 0.000045
-55.000000 0.000000 0.000000 0.002746 0.000043
-60.000000 0.000000 0.000000 0.000000 0.000000
-65.000000 0.000000 0.000000 0.000000 0.000000
-70.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000008 0.000010 0.066784 0.000155
6500
6000
5500
5000
4500
4000
3500
3000
2500
2000
1500
1000
500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/15/11 at 2:57 PM
Printed on 11/22/11 at 2:39 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GREEN MTN
controls before running VI
TRANSECT #
START UTM X
END UTM X
388281
389593
START UTM Y
END UTM Y
4415632
4414452
PREDATOR/PREY
CUTOFF (cm)
0
-10
-10
NONE
40logR
-20
-20
COLUMN 9
ALL
DEL>0
-30
-30
10
LENGTH (cm)
-10.0
-15.0
PREDATOR
-20.0
-25.0
-30.0
-35.0
-40.0
-45.0
0.0
-40
-40
-50
-50
USE INT OR BOT
INT
BOT
Length (cm)
35
-5.0
5.0
TVG 40logR
Depth
0.0
2011
0
Filter
DEPTH (m)
2
FISH PER ACRE
PREY
No Filter
0
1
0
2
4
5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1765
73
0
GrnMtn2011:GrnMtn2011:K2372059.FSH
OUTPUT
GrnMtn2011:GrnMtn2011:K2372059.FSH
Transect length (m): 1765 Total pings: 6632
Number prey/acre: 0.207
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.000
Number predators/acre: 8.479
Biomass predators/acre (kg): 0.801
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000630 0.000057
-10.000000 0.000000 0.000000 0.007142 0.000034
-15.000000 0.000000 0.000000 0.006060 0.000123
-20.000000 0.000000 0.000000 0.003101 0.000172
-25.000000 0.000016 0.000032 0.031670 0.000275
-30.000000 0.000000 0.000000 0.062616 0.000429
-35.000000 0.000000 0.000000 0.019845 0.000133
-40.000000 0.000000 0.000000 0.006392 0.000042
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
5500
5000
4500
4000
3500
3000
2500
2000
Total per cubic meter
0.000000 0.000003 0.000005 0.021844 0.000190
1500
1000
500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/15/11 at 2:57 PM
Printed on 11/22/11 at 3:05 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GREEN MTN
controls before running VI
TRANSECT #
START UTM X
END UTM X
389556
391269
START UTM Y
END UTM Y
4414595
4413751
PREDATOR/PREY
CUTOFF (cm)
0
5.0
-5
-5
TVG 40logR
-10
-10
NONE
40logR
-15
-15
-20
-20
-25
-25
-30
-30
USE INT OR BOT
-35
-35
INT
BOT
-40
-40
COLUMN 9
ALL
DEL>0
0
1
Depth
Length (cm)
35
10
0.0
-5.0
LENGTH (cm)
-10.0
-15.0
2011
0
Filter
DEPTH (m)
3
FISH PER ACRE
PREY
No Filter
PREDATOR
-20.0
-25.0
-30.0
-35.0
-40.0
-45.0
0.0
0
2
4
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1910
139
0
GrnMtn2011:GrnMtn2011:K2372127.FSH
OUTPUT
GrnMtn2011:GrnMtn2011:K2372127.FSH
Transect length (m): 1910 Total pings: 7029
Number prey/acre: 1.144
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.002
Number predators/acre: 16.654
Biomass predators/acre (kg): 1.304
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000053 0.000053 0.000688 0.000053
-10.000000 0.000000 0.000000 0.006346 0.000190
-15.000000 0.000000 0.000000 0.037332 0.000387
-20.000000 0.000018 0.000018 0.037109 0.000442
-25.000000 0.000029 0.000029 0.028608 0.000391
-30.000000 0.000000 0.000012 0.037848 0.000379
-35.000000 0.000000 0.000000 0.039822 0.000354
-40.000000 0.000000 0.000000 0.000342 0.000054
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
8500
8000
7500
7000
6500
6000
5500
5000
4500
4000
3500
Total per cubic meter
0.000000 0.000009 0.000012 0.027276 0.000311
3000
2500
2000
1500
1000
500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 11/15/11 at 2:57 PM
Printed on 11/22/11 at 3:02 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GREEN MTN
controls before running VI
TRANSECT #
START UTM X
END UTM X
391279
392751
START UTM Y
END UTM Y
4413786
4412733
PREDATOR/PREY
CUTOFF (cm)
5.0
TVG 40logR
4
0
0
-5
-5
10
0.0
LENGTH (cm)
-5.0
-15.0
PREDATOR
-20.0
-25.0
-10
-10
-30.0
-15
-15
-35.0
COLUMN 9
-20
-20
ALL
DEL>0
-25
-25
USE INT OR BOT
-30
-30
INT
BOT
-35
-35
1
Length (cm)
35
DEPTH (m)
NONE
40logR
0
Depth
Filter
-10.0
2011
FISH PER ACRE
PREY
No Filter
-40.0
0.0
0 2 4 6 8
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1810
68
0
GrnMtn2011:GrnMtn2011:K2372152.FSH
OUTPUT
GrnMtn2011:GrnMtn2011:K2372152.FSH
Transect length (m): 1810 Total pings: 6560
Number prey/acre: 1.495
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.002
Number predators/acre: 21.921
Biomass predators/acre (kg): 1.563
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
13000
12000
11000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000000 0.000000 0.025716 0.000402
-15.000000 0.000029 0.000029 0.055972 0.000657
-20.000000 0.000000 0.000000 0.035141 0.000677
-25.000000 0.000000 0.000000 0.041439 0.000339
-30.000000 0.000000 0.000136 0.013444 0.000272
-35.000000 0.000134 0.000134 0.011632 0.000267
Total per cubic meter
0.000000 0.000013 0.000020 0.031240 0.000434
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/20/12 at 8:51 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
GREEN MTN
controls before running VI
TRANSECT #
START UTM X
END UTM X
392758
393995
START UTM Y
END UTM Y
4412757
4412225
PREDATOR/PREY
CUTOFF (cm)
LENGTH (cm)
-6.0
2011
-8.0
PREDATOR
-10.0
5.0
-4
-4
-14.0
TVG 40logR
-6
-6
-16.0
NONE
40logR
-8
-8
-18.0
-10
-10
COLUMN 9
-12
-12
ALL
-14
-14
DEL>0
-16
-16
-18
-18
-20
-20
1
10
-4.0
-12.0
0
35
0.0
-2
INT
BOT
Length (cm)
-2.0
-2
USE INT OR BOT
Depth
Filter
DEPTH (m)
5
FISH PER ACRE
PREY
No Filter
2
-20.0
-22.0
0.0
0
5
10
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1347
37
0
GrnMtn2011:GrnMtn2011:K2372216.FSH
OUTPUT
GrnMtn2011:GrnMtn2011:K2372216.FSH
Transect length (m): 1347 Total pings: 4711
Number prey/acre: 1.159
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.002
Number predators/acre: 17.609
Biomass predators/acre (kg): 0.473
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
19000
18000
17000
16000
Predator/prey cutoff: 5.0 cm
15000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
14000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000090 0.000090 0.010618 0.000495
-15.000000 0.000000 0.000000 0.023196 0.000709
-20.000000 0.000000 0.000000 0.011330 0.000462
13000
12000
11000
10000
Total per cubic meter
0.000000 0.000026 0.000026 0.012970 0.000459
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:Horsetooth2011:HorsetoothNov2011:2011HstT1.out
WD60GIG:Users:Michael:Documents:Sonar:Horsetooth2011:HorsetoothNov2011:2011HstT2.out
Total length of transects (m): 6188
Number prey/acre: 312.110
95%CI (173.644, 450.575)
Biomass prey/acre (kg): 0.000
95%CI (0.000, 0.000)
Total prey biomass (MT): 0.000
95%CI (0.000, 0.000)
Number predators/acre: 651.851
95%CI (536.981, 766.720)
Biomass predators/acre (kg): 6.290
95%CI (4.404, 8.177)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
0
-10
0
-15
0
-20
0
-25
0
-30
0
-35
0
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-0.004627
-0.000071
0.007583
-0.003737
-0.00649
0.000078
-0.000228
0
0.00102
0.009643
0.011236
0.00653
0.001966
0.000535
0.000019
0
0.006668
0.019356
0.01489
0.016797
0.010421
0.000992
0.000267
-0.019883
-0.278219
-0.255849
0.092427
-0.141558
0.099995
0.102929
-0.062591
0.001698
0.064168
0.097776
0.136505
0.094693
0.166308
0.260873
0.114183
0.02328
0.406554
0.451401
0.180583
0.330945
0.232621
0.418816
0.290958
-0.000661
-0.004403
-0.021018
-0.002328
-0.027975
-0.003103
0.008642
-0.001903
0.000056
0.001315
0.009763
0.029069
0.017176
0.008606
0.009805
0.003942
0.000774
0.007033
0.040543
0.060466
0.062328
0.020314
0.010967
0.009787
2
2
2
2
2
2
2
2
0
0
0.003515
0.005097
0.006678
0.124044
0.137596
0.151147
0.006593
0.013282
0.019972
Total per cubic meter
0
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/15/11 at 3:34 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
HORSETOOTH
controls before running VI
TRANSECT #
START UTM X
END UTM X
486678
END UTM Y
4486659
4489594
0
0
5.0
-5
-5
TVG 40logR
-10
-10
NONE
40logR
-15
-15
-20
-20
COLUMN 9
-25
-25
ALL
-30
-30
DEL>0
-35
-35
-40
-40
-45
-45
USE INT OR BOT
INT
BOT
0
425
Depth
Length (cm)
35
10
0.0
LENGTH (cm)
-5.0
-10.0
2011
FISH PER ACRE
PREY
Filter
DEPTH (m)
1
487447
START UTM Y
PREDATOR/PREY
CUTOFF (cm)
No Filter
-15.0
PREDATOR
-20.0
-25.0
-30.0
-35.0
-40.0
0.0
0
858
10.0
20.0
30.0
40.0
50.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
3034
6518
0
Horsetooth2011:HorsetoothNov2011:K3121736.FSH
OUTPUT
Horsetooth2011:HorsetoothNov2011:K3121736.FSH
Transect length (m): 3034 Total pings: 13200
Number prey/acre: 323.007
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.000
Number predators/acre: 642.810
Biomass predators/acre (kg): 6.142
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.001465 0.037221 0.001765
-10.000000 0.000000 0.010407 0.125607 0.012185
-15.000000 0.000000 0.010949 0.133036 0.026598
-20.000000 0.000000 0.005722 0.076100 0.013623
-25.000000 0.000000 0.002631 0.171527 0.009527
-30.000000 0.000000 0.000499 0.273303 0.009713
-35.000000 0.000000 0.000000 0.128096 0.004402
Total per cubic meter
0.000000 0.000000 0.005221 0.138662 0.012756
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
1050000
1000000
950000
900000
850000
800000
750000
700000
650000
600000
550000
500000
450000
400000
350000
300000
250000
200000
150000
100000
50000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/15/11 at 3:22 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
HORSETOOTH
controls before running VI
TRANSECT #
START UTM X
END UTM X
487382
END UTM Y
4489594
4486520
5.0
TVG 40logR
0
0
-5
-5
10
LENGTH (cm)
-10.0
-15.0
PREDATOR
-20.0
-25.0
-10
-10
-30.0
-15
-15
-35.0
COLUMN 9
-20
-20
ALL
DEL>0
-25
-25
USE INT OR BOT
-30
-30
INT
BOT
-35
-35
425
Length (cm)
35
-5.0
NONE
40logR
0
Depth
0.0
2011
FISH PER ACRE
PREY
Filter
DEPTH (m)
2
486678
START UTM Y
PREDATOR/PREY
CUTOFF (cm)
No Filter
-40.0
0.0
0
858
10.0
20.0
30.0
40.0
50.0
60.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
3154
7894
0
Horsetooth2011:HorsetoothNov2011:K3121824.FSH.mod
OUTPUT
Horsetooth2011:HorsetoothNov2011:K3121824.FSH.mod
Transect length (m): 3154 Total pings: 11030
Number prey/acre: 301.212
Biomass prey/acre (kg): 0.000
Total prey biomass (MT): 0.000
Number predators/acre: 660.891
Biomass predators/acre (kg): 6.439
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.003397 0.000113
-5.000000 0.000000 0.000576 0.091114 0.000865
-10.000000 0.000000 0.008878 0.069945 0.007340
-15.000000 0.000000 0.011524 0.139974 0.031540
-20.000000 0.000000 0.007338 0.113287 0.020730
-25.000000 0.000000 0.001300 0.161089 0.007684
-30.000000 0.000000 0.000571 0.248442 0.009896
-35.000000 0.000000 0.000039 0.100271 0.003482
Total per cubic meter
0.000000 0.000000 0.004972 0.136529 0.013809
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
1050000
1000000
950000
900000
850000
800000
750000
700000
650000
600000
550000
500000
450000
400000
350000
300000
250000
200000
150000
100000
50000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:McPhee2011:2011McPheeT1m.out
WD60GIG:Users:Michael:Documents:Sonar:McPhee2011:2011McPheeT2m.out
WD60GIG:Users:Michael:Documents:Sonar:McPhee2011:2011McPheeT3m.out
WD60GIG:Users:Michael:Documents:Sonar:McPhee2011:2011McPheeT4m.out
WD60GIG:Users:Michael:Documents:Sonar:McPhee2011:2011McPheeT6m.out
WD60GIG:Users:Michael:Documents:Sonar:McPhee2011:2011McPheeT5m.out
Total length of transects (m): 10723
Number prey/acre: 4.712
95%CI (0.431, 8.994)
Biomass prey/acre (kg): 0.008
95%CI (-0.001, 0.017)
Total prey biomass (MT): 0.036
95%CI (0.002, 0.071)
Number predators/acre: 67.843
95%CI (33.622, 102.064)
Biomass predators/acre (kg): 2.893
95%CI (1.120, 4.666)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
0
-10
-0.000023
-15
-0.000039
-20
-0.000008
-25
-0.00004
-30
-0.000008
-35
0
-40
0
-45
0
-50
0
-55
0
-60
NaN
-65
NaN
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0
0.000158
0.000385
0.000096
0.00003
0.000005
0
0
0
0
0
0
0
0
0
0.000339
0.000809
0.0002
0.0001
0.000018
0
0
0
0
0
NaN
NaN
0
0
-0.000011
0.000029
0.000002
-0.000017
-0.000004
0
0
0
0
0
NaN
NaN
0
0
0.000081
0.000226
0.000053
0.000015
0.000003
0
0
0
0
0
0
0
0
0
0.000173
0.000423
0.000104
0.000047
0.00001
0
0
0
0
0
NaN
NaN
0
-0.000169
0.01393
0.034961
0.001906
0.000383
-0.000542
-0.000024
0
0
0
0
NaN
NaN
0
0.000381
0.082039
0.121241
0.014361
0.003036
0.000717
0.000034
0
0
0
0
0.002244
0
0
0.000932
0.150149
0.207521
0.026816
0.005689
0.001975
0.000092
0
0
0
0
NaN
NaN
0
0.000006
0.000735
0.001248
0.000162
0.000006
-0.000036
-0.000001
0
0
0
0
NaN
NaN
0
0.000037
0.001369
0.003113
0.000609
0.000121
0.000047
0.000012
0
0
0
0
0.000022
0
0
0.000068
0.002002
0.004977
0.001057
0.000236
0.00013
0.000026
0
0
0
0
NaN
NaN
6
6
6
6
6
6
6
4
4
3
3
2
1
1
Total per cubic meter
-0.000006
0.00007
0.000147
0.000003
0.000037
0.000071
0.000845
0.027387
0.053929
0.00029
0.00057
0.00085
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 1:18 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
MCPHEE
controls before running VI
TRANSECT #
START UTM X
END UTM X
716298
717243
START UTM Y
END UTM Y
4160539
4158640
PREDATOR/PREY
CUTOFF (cm)
1
DEPTH (m)
Length (cm)
35
10
-5.0
LENGTH (cm)
-10.0
-20.0
-25.0
PREDATOR
-30.0
0
-10
-10
TVG 40logR
-20
-20
NONE
40logR
-50.0
-30
-30
-55.0
COLUMN 9
-40
-40
ALL
DEL>0
-50
-50
USE INT OR BOT
-60
-60
INT
BOT
-70
-70
0 1 2 3 4
Depth
0.0
0
5.0
Filter
-15.0
2011
FISH PER ACRE
PREY
No Filter
-35.0
-40.0
-45.0
-60.0
-65.0
0.0
0 25 50 75
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
2121
354
0
Sonar:McPhee2011:K2112213.FSH
OUTPUT
Sonar:McPhee2011:K2112213.FSH
Transect length (m): 2121 Total pings: 7762
Number prey/acre: 4.728
Biomass prey/acre (kg): 0.011
Total prey biomass (MT): 0.043
Number predators/acre: 78.813
Biomass predators/acre (kg): 2.878
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000048 0.000048
-10.000000 0.000057 0.000029 0.045919 0.001057
-15.000000 0.000676 0.000287 0.162372 0.004243
-20.000000 0.000191 0.000080 0.021376 0.000940
-25.000000 0.000039 0.000013 0.005522 0.000260
-30.000000 0.000000 0.000000 0.000837 0.000044
-35.000000 0.000000 0.000000 0.000057 0.000019
-40.000000 0.000000 0.000000 0.000000 0.000000
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
-55.000000 0.000000 0.000000 0.000000 0.000000
-60.000000 0.000000 0.000000 0.003183 0.000022
-65.000000 0.000000 0.000000 0.000000 0.000000
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
105000
100000
95000
90000
85000
80000
75000
70000
65000
60000
55000
50000
45000
40000
35000
30000
Total per cubic meter
0.000000 0.000043 0.000018 0.010152 0.000286
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 1:20 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
MCPHEE
controls before running VI
TRANSECT #
START UTM X
END UTM X
717252
717566
START UTM Y
END UTM Y
4158594
4157197
PREDATOR/PREY
CUTOFF (cm)
2
0
0
-10
-10
-20
-20
-30
-30
-40
-40
USE INT OR BOT
-50
-50
INT
BOT
-60
-60
5.0
COLUMN 9
ALL
DEL>0
0 1 2 3 4
DEPTH (m)
Depth
Length (cm)
35
10
0.0
LENGTH (cm)
-5.0
-15.0
PREDATOR
-20.0
-25.0
TVG 40logR
NONE
40logR
Filter
-10.0
2011
FISH PER ACRE
PREY
No Filter
-30.0
-35.0
-40.0
0.0
0 25 50 75
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1432
319
0
Sonar:McPhee2011:K2112241.FSH
OUTPUT
Sonar:McPhee2011:K2112241.FSH
Transect length (m): 1432 Total pings: 5156
Number prey/acre: 6.318
Biomass prey/acre (kg): 0.010
Total prey biomass (MT): 0.041
Number predators/acre: 111.291
Biomass predators/acre (kg): 4.936
Predator/prey cutoff: 5.0 cm
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
120000
110000
100000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
90000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000254 0.000127 0.095480 0.001862
-15.000000 0.000486 0.000334 0.260748 0.005829
-20.000000 0.000094 0.000047 0.036969 0.001250
-25.000000 0.000000 0.000000 0.006173 0.000212
-30.000000 0.000000 0.000000 0.000783 0.000033
-35.000000 0.000000 0.000000 0.000085 0.000014
-40.000000 0.000000 0.000000 0.000000 0.000000
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
-55.000000 0.000000 0.000000 0.000000 0.000000
80000
70000
60000
50000
40000
Total per cubic meter
0.000000 0.000043 0.000027 0.021207 0.000503
30000
20000
10000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 1:22 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
MCPHEE
controls before running VI
TRANSECT #
START UTM X
END UTM X
717562
716989
START UTM Y
END UTM Y
4157158
4155331
PREDATOR/PREY
CUTOFF (cm)
3
0
0
-10
-10
NONE
40logR
COLUMN 9
ALL
DEL>0
USE INT OR BOT
INT
BOT
DEPTH (m)
Depth
Length (cm)
35
10
0.0
LENGTH (cm)
-5.0
-15.0
PREDATOR
5.0
TVG 40logR
Filter
-10.0
2011
FISH PER ACRE
PREY
No Filter
-20.0
-25.0
-30.0
-20
-20
-30
-30
-35.0
-40.0
0.0
-40
-40
-50
-50
0 2 4 6 8
0 20 40 60
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1915
309
0
Sonar:McPhee2011:K2112300.FSH
OUTPUT
Sonar:McPhee2011:K2112300.FSH
Transect length (m): 1915 Total pings: 6939
Number prey/acre: 11.448
Biomass prey/acre (kg): 0.024
Total prey biomass (MT): 0.094
Number predators/acre: 73.751
Biomass predators/acre (kg): 2.701
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
130000
120000
110000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000411 0.000222 0.070860 0.001487
-15.000000 0.001158 0.000522 0.124373 0.003587
-20.000000 0.000267 0.000124 0.012438 0.000622
-25.000000 0.000166 0.000076 0.003465 0.000182
-30.000000 0.000031 0.000016 0.003076 0.000203
-35.000000 0.000000 0.000000 0.000031 0.000016
-40.000000 0.000000 0.000000 0.000000 0.000000
-45.000000 0.000000 0.000000 0.000000 0.000000
-50.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000198 0.000093 0.019035 0.000572
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 1:23 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
MCPHEE
controls before running VI
TRANSECT #
START UTM X
END UTM X
716956
715515
START UTM Y
END UTM Y
4155304
4154457
PREDATOR/PREY
CUTOFF (cm)
-6.0
-8.0
2011
PREDATOR
-10.0
-12.0
-5
-5
TVG 40logR
-10
-10
-18.0
NONE
40logR
-15
-15
-20.0
-20
-20
-22.0
-25
-25
-24.0
-30
-30
USE INT OR BOT
-35
-35
INT
BOT
-40
-40
1
2
LENGTH (cm)
-4.0
5.0
0
10
-2.0
0
ALL
DEL>0
Length (cm)
35
0.0
0
COLUMN 9
Depth
Filter
DEPTH (m)
4
FISH PER ACRE
PREY
No Filter
-14.0
-16.0
0.0
0
20
40
5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1671
172
0
Sonar:McPhee2011:K2112326.FSH
OUTPUT
Sonar:McPhee2011:K2112326.FSH
Transect length (m): 1671 Total pings: 6063
Number prey/acre: 3.513
Biomass prey/acre (kg): 0.007
Total prey biomass (MT): 0.028
Number predators/acre: 64.746
Biomass predators/acre (kg): 4.894
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000242 0.000060
-10.000000 0.000254 0.000109 0.195601 0.002104
-15.000000 0.000182 0.000104 0.156844 0.002342
-20.000000 0.000134 0.000067 0.012499 0.000468
-25.000000 0.000000 0.000000 0.000000 0.000000
-30.000000 0.000000 0.000000 0.000000 0.000000
-35.000000 0.000000 0.000000 0.000000 0.000000
-40.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000117 0.000058 0.076393 0.001055
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
70000
65000
60000
55000
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 1:25 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
MCPHEE
controls before running VI
TRANSECT #
START UTM X
END UTM X
715471
717227
START UTM Y
END UTM Y
4154454
4153606
PREDATOR/PREY
CUTOFF (cm)
Length (cm)
35
10
0.0
-2.5
LENGTH (cm)
-5.0
-7.5
2011
-10.0
PREDATOR
-12.5
0
0
-15.0
-10
-10
-17.5
TVG 40logR
-20
-20
NONE
40logR
-30
-30
COLUMN 9
-40
-40
ALL
DEL>0
-50
-50
USE INT OR BOT
-60
-60
INT
BOT
-70
-70
5.0
Depth
Filter
DEPTH (m)
5
FISH PER ACRE
PREY
No Filter
-20.0
-22.5
0
1
-25.0
-27.5
0.0
0
10
20
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1950
95
0
Sonar:McPhee2011:K2112348.FSH
OUTPUT
Sonar:McPhee2011:K2112348.FSH
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
Transect length (m): 1950 Total pings: 7614
Number prey/acre: 0.681
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.004
Number predators/acre: 38.531
Biomass predators/acre (kg): 1.952
50000
Predator/prey cutoff: 5.0 cm
40000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
37500
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.001243 0.000052
-10.000000 0.000000 0.000000 0.089974 0.001294
-15.000000 0.000086 0.000057 0.037503 0.001291
-20.000000 0.000000 0.000000 0.010568 0.000273
-25.000000 0.000000 0.000000 0.005314 0.000043
-30.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000020 0.000013 0.029487 0.000614
47500
45000
42500
35000
32500
30000
27500
25000
22500
20000
17500
15000
12500
10000
7500
5000
2500
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/12/11 at 1:26 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
MCPHEE
controls before running VI
TRANSECT #
START UTM X
END UTM X
717199
717380
START UTM Y
END UTM Y
4153601
4151977
PREDATOR/PREY
CUTOFF (cm)
-7.5
2011
-10.0
PREDATOR
-12.5
-5
-10
-10
-22.5
-15
-15
-25.0
-20
-20
USE INT OR BOT
-25
-25
INT
BOT
-30
-30
-15.0
-17.5
-20.0
TVG 40logR
ALL
DEL>0
LENGTH (cm)
-5.0
-5
COLUMN 9
10
-2.5
0
NONE
40logR
Length (cm)
35
0.0
0
5.0
Depth
Filter
DEPTH (m)
6
FISH PER ACRE
PREY
No Filter
0
1
-27.5
0.0
0
10
20
5.0
10.0
15.0
20.0
25.0
30.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1634
72
0
Sonar:McPhee2011:K2120017.FSH
OUTPUT
Sonar:McPhee2011:K2120017.FSH
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
Transect length (m): 1634 Total pings: 6067
Number prey/acre: 0.632
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.006
Number predators/acre: 24.858
Biomass predators/acre (kg): 0.751
30000
Predator/prey cutoff: 5.0 cm
24000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
22000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000804 0.000062
-10.000000 0.000000 0.000000 0.011832 0.000408
-15.000000 0.000133 0.000053 0.045873 0.001384
-20.000000 0.000000 0.000000 0.001427 0.000103
-25.000000 0.000000 0.000000 0.000295 0.000029
-30.000000 0.000000 0.000000 0.000000 0.000000
28000
26000
20000
18000
16000
14000
Total per cubic meter
0.000000 0.000028 0.000011 0.011904 0.000390
12000
10000
8000
6000
4000
2000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:Vallecito2011:2011VallecitoT4m.out
WD60GIG:Users:Michael:Documents:Sonar:Vallecito2011:2011VallecitoT3m.out
WD60GIG:Users:Michael:Documents:Sonar:Vallecito2011:2011VallecitoT2m.out
WD60GIG:Users:Michael:Documents:Sonar:Vallecito2011:2011VallecitoT1m.out
Total length of transects (m): 6039
Number prey/acre: 4.570 95%CI (0.940, 8.201)
Biomass prey/acre (kg): 0.005 95%CI (0.000, 0.009)
Total prey biomass (MT): 0.011 95%CI (0.001, 0.020)
Number predators/acre: 75.731 95%CI (17.841, 133.622)
Biomass predators/acre (kg): 2.236 95%CI (0.275, 4.198)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
0
-10
0.00005
-15
-0.00012
-20
-0.000047
-25
-0.000111
-30
NaN
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0
0.000104
0.000245
0.000298
0.00001
0
0
0
0.000158
0.000609
0.000643
0.00013
NaN
0
0
0.00005
-0.000086
-0.000047
-0.000111
NaN
0
0
0.000104
0.000262
0.000298
0.00001
0
0
0
0.000158
0.000609
0.000643
0.00013
NaN
0
-0.000399
-0.001068
0.046161
-0.080791
-0.264668
NaN
0
0.000183
0.005489
0.175625
0.189975
0.023012
0
0
0.000764
0.012045
0.305088
0.460742
0.310692
NaN
0
-0.000033
0.000452
0.002233
-0.002185
-0.007227
NaN
0
0.000015
0.000606
0.005611
0.005786
0.000657
0
0
0.000064
0.00076
0.008989
0.013757
0.008542
NaN
4
4
4
4
4
2
1
Total per cubic meter
0.000004
0.000162
0.00032
0.000011
0.000166
0.000322
0.001278
0.101999
0.20272
0.000358
0.003251
0.006144
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 2/1/12 at 8:18 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
VALLECITO
controls before running VI
TRANSECT #
START UTM X
END UTM X
272804
274367
START UTM Y
END UTM Y
4141561
4141225
PREDATOR/PREY
CUTOFF (cm)
-2
5.0
-4
-4
TVG 40logR
-6
-6
NONE
40logR
-8
-8
-10
-10
COLUMN 9
-12
-12
ALL
-14
-14
DEL>0
-16
-16
-18
-18
-20
-20
USE INT OR BOT
INT
BOT
0
1
Length (cm)
35
10
0.0
-2.0
LENGTH (cm)
-4.0
-6.0
-8.0
2011
-2
Depth
Filter
DEPTH (m)
1
FISH PER ACRE
PREY
No Filter
PREDATOR
-10.0
-12.0
-14.0
-16.0
-18.0
-20.0
-22.0
-24.0
0.0
0
20
40
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1599
319
0
Sonar:Vallecito2011:K2102246.FSH
OUTPUT
Sonar:Vallecito2011:K2102246.FSH
Transect length (m): 1599 Total pings: 5991
Number prey/acre: 1.360
Biomass prey/acre (kg): 0.001
Total prey biomass (MT): 0.003
Number predators/acre: 38.504
Biomass predators/acre (kg): 1.082
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000076 0.000076 0.005231 0.000606
-15.000000 0.000149 0.000149 0.192884 0.006109
-20.000000 0.000029 0.000029 0.073804 0.002638
Total per cubic meter
0.000000 0.000070 0.000070 0.079822 0.002719
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
36000
34000
32000
30000
28000
26000
24000
22000
20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 2/1/12 at 8:20 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
VALLECITO
controls before running VI
TRANSECT #
START UTM X
END UTM X
272097
272808
START UTM Y
END UTM Y
4140465
4141545
PREDATOR/PREY
CUTOFF (cm)
-2
5.0
-4
-4
TVG 40logR
-6
-6
NONE
40logR
-8
-8
-10
-10
COLUMN 9
-12
-12
ALL
-14
-14
DEL>0
-16
-16
-18
-18
-20
-20
USE INT OR BOT
INT
BOT
0
1
2
Length (cm)
35
10
0.0
-2.0
LENGTH (cm)
-4.0
-6.0
-8.0
2011
-2
Depth
Filter
DEPTH (m)
2
FISH PER ACRE
PREY
No Filter
PREDATOR
-10.0
-12.0
-14.0
-16.0
-18.0
-20.0
-22.0
-24.0
0.0
0
10
20
5.0
10.0
15.0
20.0
25.0
30.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1293
144
0
Sonar:Vallecito2011:K2102227.FSH
OUTPUT
Sonar:Vallecito2011:K2102227.FSH
Transect length (m): 1293 Total pings: 4938
Number prey/acre: 2.638
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.006
Number predators/acre: 26.399
Biomass predators/acre (kg): 0.896
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000150 0.000150 0.011323 0.000499
-15.000000 0.000164 0.000205 0.129479 0.003900
-20.000000 0.000226 0.000226 0.098941 0.002110
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
21000
20000
19000
18000
17000
16000
15000
14000
13000
12000
11000
Total per cubic meter
0.000000 0.000135 0.000148 0.063348 0.001795
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 2/1/12 at 8:23 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
VALLECITO
controls before running VI
TRANSECT #
START UTM X
END UTM X
272123
START UTM Y
END UTM Y
4141134
4140479
NONE
40logR
COLUMN 9
ALL
DEL>0
10
0.0
LENGTH (cm)
-5.0
2011
0
0
-5
-5
-10
-10
-10.0
PREDATOR
-12.5
-15.0
-17.5
-20.0
-22.5
-25.0
-15
-15
-27.5
0.0
-20
-20
-25
-25
USE INT OR BOT
INT
BOT
35
-2.5
5.0
TVG 40logR
Length (cm)
-7.5
FISH PER ACRE
PREY
Depth
Filter
DEPTH (m)
3
273460
PREDATOR/PREY
CUTOFF (cm)
No Filter
0
1
2
3
0
20
40
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1489
924
0
Sonar:Vallecito2011:K2102208.FSH
OUTPUT
Sonar:Vallecito2011:K2102208.FSH
Transect length (m): 1489 Total pings: 5481
Number prey/acre: 4.447
Biomass prey/acre (kg): 0.004
Total prey biomass (MT): 0.011
Number predators/acre: 72.149
Biomass predators/acre (kg): 2.262
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
60000
55000
50000
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
45000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000081 0.000081 0.003500 0.000733
-15.000000 0.000584 0.000584 0.282302 0.008409
-20.000000 0.000522 0.000522 0.441254 0.012978
-25.000000 0.000000 0.000000 0.000371 0.000037
40000
35000
30000
Total per cubic meter
0.000000 0.000303 0.000303 0.196382 0.005909
25000
20000
15000
10000
5000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 2/1/12 at 8:25 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
VALLECITO
controls before running VI
TRANSECT #
START UTM X
END UTM X
272683
273495
START UTM Y
END UTM Y
4139697
4141142
PREDATOR/PREY
CUTOFF (cm)
0
-5
-5
NONE
40logR
COLUMN 9
ALL
DEL>0
10
LENGTH (cm)
-5.0
-7.5
-10.0
PREDATOR
-12.5
-15.0
-17.5
-20.0
-22.5
-10
-25.0
-10
-27.5
-15
-15
-30.0
0.0
-20
-20
-25
-25
USE INT OR BOT
INT
BOT
35
0.0
5.0
TVG 40logR
Length (cm)
-2.5
2011
0
Depth
Filter
DEPTH (m)
4
FISH PER ACRE
PREY
No Filter
0
1
0
10
20
5.0
10.0
15.0
20.0
25.0
30.0
35.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1658
507
0
Sonar:Vallecito2011:K2102144.FSH
OUTPUT
Sonar:Vallecito2011:K2102144.FSH
Transect length (m): 1658 Total pings: 6269
Number prey/acre: 2.281
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.005
Number predators/acre: 36.165
Biomass predators/acre (kg): 0.806
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
38000
36000
34000
32000
Predator/prey cutoff: 5.0 cm
30000
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
28000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000731 0.000061
-10.000000 0.000110 0.000110 0.001901 0.000585
-15.000000 0.000082 0.000109 0.097833 0.004025
-20.000000 0.000414 0.000414 0.145903 0.005419
-25.000000 0.000019 0.000019 0.045653 0.001278
-30.000000 0.000000 0.000000 0.000000 0.000000
26000
24000
22000
20000
18000
Total per cubic meter
0.000000 0.000140 0.000145 0.068444 0.002582
16000
14000
12000
10000
8000
6000
4000
2000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:WmsFk2011:2011WmsFkT1m.out
WD60GIG:Users:Michael:Documents:Sonar:WmsFk2011:2011WmsFkT2m.out
Total length of transects (m): 4708
Number prey/acre: 3.611
95%CI (-4.031, 11.254)
Biomass prey/acre (kg): 0.003
95%CI (-0.004, 0.009)
Total prey biomass (MT): 0.004
95%CI (-0.009, 0.017)
Number predators/acre: 22.053
95%CI (-28.848, 72.954)
Biomass predators/acre (kg): 1.224
95%CI (-3.770, 6.218)
Strata (top)
LCL
Per cubic meter by strata
-2
0
-5
-0.000211
-10
-0.000267
-15
-0.000742
-20
-0.000454
-25
-0.000562
-30
-0.000263
-35
-0.000299
-40
NaN
-45
NaN
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0.000018
0.00007
0.000116
0.000061
0.000048
0.000023
0.000025
0.000048
0
0
0.000247
0.000406
0.000973
0.000575
0.000658
0.000308
0.00035
NaN
NaN
0
-0.000211
-0.000491
-0.000413
-0.000406
-0.000377
0.000062
-0.000299
NaN
NaN
0
0.000018
0.000112
0.00014
0.000077
0.00008
0.000068
0.000025
0.000048
0
0
0.000247
0.000716
0.000692
0.00056
0.000537
0.000075
0.00035
NaN
NaN
-0.020076
-0.01472
-0.100053
-0.167256
-0.129946
-0.082316
0.019588
-0.052127
NaN
NaN
0.001715
0.001257
0.015725
0.044664
0.022368
0.092889
0.035738
0.004453
0.005388
0
0.023506
0.017235
0.131503
0.256583
0.174683
0.268094
0.051888
0.061033
NaN
NaN
-0.000743
-0.001475
0.000399
-0.00126
-0.002548
-0.000664
-0.000272
-0.002248
NaN
NaN
0.000063
0.000126
0.000622
0.00078
0.000603
0.000505
0.000269
0.000192
0.000191
0
0.00087
0.001727
0.000844
0.002819
0.003754
0.001674
0.000809
0.002632
NaN
NaN
2
2
2
2
2
2
2
2
1
1
Total per cubic meter
-0.000032
0.000051
0.000133
0.000017
0.000074
0.000132
-0.119458
0.035653
0.190763
-0.00074
0.000467
0.001674
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/9/11 at 9:49 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
WILLIAMS
controls before running VI
FORK
TRANSECT #
START UTM X
END UTM X
396780
395802
START UTM Y
END UTM Y
4432002
4430376
PREDATOR/PREY
CUTOFF (cm)
-15.0
2011
PREDATOR
-20.0
-5
-5
TVG 40logR
-10
-10
NONE
40logR
-15
-15
-35.0
-20
-20
-40.0
COLUMN 9
-25
-25
ALL
DEL>0
-30
-30
-35
-35
-40
-40
-45
-45
1
2
LENGTH (cm)
-10.0
5.0
0
10
-5.0
0
INT
BOT
Length (cm)
35
0.0
0
USE INT OR BOT
Depth
Filter
DEPTH (m)
1
FISH PER ACRE
PREY
No Filter
-25.0
-30.0
-45.0
0.0
0
5
10
10.0
20.0
30.0
40.0
50.0
60.0
70.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
1897
166
0
Sonar:WmsFk2011:K2432054.FSH
OUTPUT
Sonar:WmsFk2011:K2432054.FSH
Transect length (m): 1897 Total pings: 6745
Number prey/acre: 4.213
Biomass prey/acre (kg): 0.003
Total prey biomass (MT): 0.005
Number predators/acre: 18.047
Biomass predators/acre (kg): 0.831
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.000000 0.000000
-10.000000 0.000096 0.000160 0.006613 0.000639
-15.000000 0.000183 0.000183 0.027985 0.000619
-20.000000 0.000020 0.000039 0.010381 0.000355
-25.000000 0.000096 0.000116 0.079100 0.000597
-30.000000 0.000000 0.000069 0.034467 0.000311
-35.000000 0.000051 0.000051 0.008906 0.000384
-40.000000 0.000048 0.000048 0.005388 0.000191
-45.000000 0.000000 0.000000 0.000000 0.000000
Total per cubic meter
0.000000 0.000057 0.000079 0.023445 0.000372
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
17000
16000
15000
14000
13000
12000
11000
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 1/30/12 at 2:04 PM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
WILLIAMS
controls before running VI
TRANSECT #
START UTM X
END UTM X
395961
397904
START UTM Y
END UTM Y
4431333
4429301
PREDATOR/PREY
CUTOFF (cm)
NONE
40logR
COLUMN 9
ALL
DEL>0
10
LENGTH (cm)
-10.0
2011
PREDATOR
-15.0
0
0
-10
-10
-25.0
-20
-20
-30.0
-30
-30
-35.0
-20.0
0.0
-40
-40
-50
-50
0
35
-5.0
USE INT OR BOT
INT
BOT
Length (cm)
0.0
5.0
TVG 40logR
Depth
Filter
DEPTH (m)
2
FISH PER ACRE
PREY
No Filter
1
0
5
10
10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
2811
216
0
Sonar:WmsFk2011:K2432132.FSH
OUTPUT
Sonar:WmsFk2011:K2432132.FSH
Transect length (m): 2811 Total pings: 10160
Number prey/acre: 3.010
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.003
Number predators/acre: 26.059
Biomass predators/acre (kg): 1.617
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.003430 0.000127
-5.000000 0.000036 0.000036 0.002515 0.000252
-10.000000 0.000043 0.000065 0.024837 0.000604
-15.000000 0.000048 0.000096 0.061342 0.000940
-20.000000 0.000101 0.000115 0.034356 0.000851
-25.000000 0.000000 0.000044 0.106678 0.000413
-30.000000 0.000045 0.000068 0.037009 0.000226
-35.000000 0.000000 0.000000 0.000000 0.000000
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
18000
17000
16000
15000
14000
13000
12000
11000
10000
9000
8000
Total per cubic meter
0.000000 0.000044 0.000070 0.047860 0.000562
7000
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�Page 1
INTERPRET FSH 8.94b BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.94b BW.vi
Last modified on 12/8/11 at 9:26 AM
Printed on 12/9/11 at 9:53 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
WILLIAMS
controls before running VI
FORK
TRANSECT #
START UTM X
END UTM X
395961
397904
START UTM Y
END UTM Y
4431333
4429301
PREDATOR/PREY
CUTOFF (cm)
NONE
40logR
COLUMN 9
ALL
DEL>0
USE INT OR BOT
INT
BOT
10
LENGTH (cm)
-5.0
-10.0
2011
PREDATOR
-15.0
0
0
-10
-10
-25.0
-20
-20
-30.0
-30
-30
-35.0
-20.0
0.0
-40
-40
-50
-50
0
Length (cm)
35
0.0
5.0
TVG 40logR
Depth
Filter
DEPTH (m)
3
FISH PER ACRE
PREY
No Filter
1
0
5
10
10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
2811
216
0
Sonar:WmsFk2011:K2432132.FSH
OUTPUT
Sonar:WmsFk2011:K2432132.FSH
Transect length (m): 2811 Total pings: 10160
Number prey/acre: 3.010
Biomass prey/acre (kg): 0.002
Total prey biomass (MT): 0.003
Number predators/acre: 26.059
Biomass predators/acre (kg): 1.617
Predator/prey cutoff: 5.0 cm
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
-2.000000 0.000000 0.000000 0.003430 0.000127
-5.000000 0.000036 0.000036 0.002515 0.000252
-10.000000 0.000043 0.000065 0.024837 0.000604
-15.000000 0.000048 0.000096 0.061342 0.000940
-20.000000 0.000101 0.000115 0.034356 0.000851
-25.000000 0.000000 0.000044 0.106678 0.000413
-30.000000 0.000045 0.000068 0.037009 0.000226
-35.000000 0.000000 0.000000 0.000000 0.000000
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
18000
17000
16000
15000
14000
13000
12000
11000
10000
9000
8000
Total per cubic meter
0.000000 0.000044 0.000070 0.047860 0.000562
7000
6000
5000
4000
3000
2000
1000
0
cm
0
25
50
75
100
125
�INPUT FILES:
WD60GIG:Users:Michael:Documents:Sonar:Wolford2011:2011WolfordT1.out
Total length of transects (m): 2866
Number prey/acre: 4.455
95%CI (NaN, NaN)
Biomass prey/acre (kg): 0.004
95%CI (NaN, NaN)
Total prey biomass (MT): 0.006
95%CI (NaN, NaN)
Number predators/acre: 105.523
95%CI (NaN, NaN)
Biomass predators/acre (kg): 7.086
95%CI (NaN, NaN)
Strata (top)
LCL
Per cubic meter by strata
-2
NaN
-5
NaN
-10
NaN
-15
NaN
-20
NaN
-25
NaN
-30
NaN
g PREY
UCL
LCL
# PREY
UCL
LCL
g PRED
UCL
LCL
# PRED
UCL
n
0
0
0.000127
0.000076
0.000035
0
0
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0
0
0.000148
0.000106
0.000035
0
0
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0
0.005815
0.262915
0.105449
0.075654
0.008511
0
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0
0.000176
0.003976
0.001608
0.000837
0.000099
0
NaN
NaN
NaN
NaN
NaN
NaN
NaN
1
1
1
1
1
1
1
0.000048
NaN
NaN
0.000058
NaN
NaN
0.090511
NaN
NaN
0.001286
NaN
Total per cubic meter
NaN
�Page 1
INTERPRET FSH 8.95 BW.vi
WD60GIG:Users:Michael:Documents:Sonar:ANALYSIS VIs:INTERPRET FSH 8.95 BW.vi
Last modified on 12/30/11 at 9:46 AM
Printed on 12/30/11 at 9:24 AM
This program analyzes the *.FSH files from the HTI
software
Enter values in blue
WOLFORD
controls before running VI
TRANSECT #
START UTM X
END UTM X
379480
START UTM Y
END UTM Y
4444361
4441515
5.0
COLUMN 9
ALL
INT
BOT
10
0.0
LENGTH (cm)
-5.0
2011
-10.0
PREDATOR
-12.5
0
0
-5
-5
-10
-10
-22.5
-15
-15
-25.0
-20
-20
-25
-25
-30
-30
-15.0
-17.5
-20.0
-27.5
0.0
DEL>0
USE INT OR BOT
35
-2.5
TVG 40logR
NONE
40logR
Length (cm)
-7.5
FISH PER ACRE
PREY
Depth
Filter
DEPTH (m)
1
379822
PREDATOR/PREY
CUTOFF (cm)
No Filter
0
1
2
3
0
50
100
5.0
10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
TRANSECT LENGTH (M)
NUMBER OF TARGETS
PERCENT LOST BOTTOM
2866
392
0
Sonar:Wolford2011:K2422157.FSH
OUTPUT
Sonar:Wolford2011:K2422157.FSH
Transect length (m): 2866 Total pings: 10399
Number prey/acre: 4.455
Biomass prey/acre (kg): 0.004
Total prey biomass (MT): 0.006
Number predators/acre: 105.523
Biomass predators/acre (kg): 7.086
LENGTH FREQUENCY PLOT - LAKEWIDE ESTIMATE (all fish)
47500
45000
42500
40000
Predator/prey cutoff: 5.0 cm
37500
Strata top (M) Prey (g) Prey # Predator (g) Predator #
Per cubic meter by strata:
35000
-2.000000 0.000000 0.000000 0.000000 0.000000
-5.000000 0.000000 0.000000 0.005815 0.000176
-10.000000 0.000127 0.000148 0.262915 0.003976
-15.000000 0.000076 0.000106 0.105449 0.001608
-20.000000 0.000035 0.000035 0.075654 0.000837
-25.000000 0.000000 0.000000 0.008511 0.000099
-30.000000 0.000000 0.000000 0.000000 0.000000
32500
30000
27500
25000
22500
Total per cubic meter
0.000000 0.000048 0.000058 0.090511 0.001286
20000
17500
15000
12500
10000
7500
5000
2500
0
cm
0
25
50
75
100
125
�
https://cpw.cvlcollections.org/files/original/b7f78833f70ef81e5a0b707e33a2f9d2.pdf
25097e91b7a2ebf59a9994d0fc334e58
PDF Text
Text
Guidance for Reviewing 404 Projects
COLORADO PARKS & WILDLIFE • 6060 Broadway, Denver, CO 80216 • (303) 291 -7227 • www.wildlife.state.co.us • www.parks.state.co.us
�COLORADO PARKS AND WILDLIFE
Dan Prenzlow, Director
DIRECTOR’S STAFF
Reid DeWalt, Assistant Director for Aquatics, Terrestrial and Natural Resources; Heather
Dugan, Assistant Director for Field Services; Justin Rutter, Assistant Director for Financial
Services; Lauren Truitt, Assistant Director for Information and Education; Jeff Ver Steeg,
Assistant Director for Research, Policy, and Planning
REGIONAL MANAGERS
Brett Ackerman, Southeast Region Manager; Cory Chick, Southwest Region Manager; Mark
Leslie, Northeast Region Manager; JT Romatzke, Northwest Region Manager
STUDY FUNDED BY
Colorado Parks and Wildlife
SUGGESTED CITATION
Richer, E. E., M. C. Kondratieff, B. F. Atkinson, and K. R. Bakich. 2020. Stream
Restoration, Fish Passage, and Stream Stabilization Projects: Guidance for Reviewing 404
Projects. Colorado Parks and Wildlife Aquatic Research Section, Fort Collins, CO. 13 pp.
�Introduction
Colorado Parks and Wildlife (CPW) is responsible for the management and conservation of
wildlife resources within the state. In support of this mission, CPW staff provide design
reviews to the ACOE for a variety of projects permitted under Section 404 of the Clean Water
Act. The intent of this document is to provide recommendations from CPW with regard to
project design and review to assure that the least environmentally damaging practicable
alternative (LEDPA) is identified and implemented. Requests to review and comment on
permit applications are primarily related to stream restoration, fish passage, and bank
stabilization projects that fall under the following Nationwide (NWP) and Regional General
Permits (RGP):
1)
2)
3)
4)
RGP 12 – Aquatic Habitat Improvement for Stream Channels in Colorado
RGP 37 – Stream Stabilization Projects in Colorado
NWP 13 – Bank Stabilization
NWP 27 – Aquatic Habitat Restoration, Establishment, and Enhancement Activities
CPW recommends that adequate environmental safeguards be included in the design and
construction of stream restoration, fish passage, and bank stabilization projects to assure that
stream functions and fisheries are not adversely impacted. Provided below are separate
guidelines for stream restoration, fish passage, and bank stabilization projects, in addition to
general guidelines and best management practices for all river projects. Most projects should
consider these general recommendations but will likely require site-specific considerations as
well. As appropriate, the following guidelines should be considered and incorporated during
project design to maximize the benefits of restoration activities while minimizing adverse
effects associated with channel modification and bank stabilization.
These recommendations are based on the best available science, but are subject to revision
as more information becomes available. Failure to demonstrate that the following guidelines
were evaluated with due diligence during the design process could result in categorical
opposition to the project from CPW.
General Guidelines and Best Management Practices
1) CPW Fisheries Data: CPW conducts hundreds of fish population surveys on streams and
rivers throughout Colorado each year. Survey results are used to inform our guidance
regarding species assemblages and management objectives at a proposed project site.
Project proponents should contact the local Area Aquatic Biologist early in the design
process to obtain fisheries information for their project site. A map of CPW management
areas with contact information for Aquatic Biologists is included in Appendix A and
available at the CPW Aquatic Management webpage. Instructions for submitting formal
data requests are available at the CPW Aquatics Data Management webpage.
2) Spawning Periods: Construction activities that cause streambed disturbance should not be
scheduled during periods when adult fish spawning migrations, egg incubation, or fry
swim-up are occurring. Fish eggs and fry may die if construction activities mobilize fine
sediment that smothers the streambed in which they reside. Repetitive and cumulative
streambed disturbances during critical reproductive periods can significantly affect
population dynamics and resiliency of local fisheries. In general, instream construction
should be targeted for the months of August and September when flows are lower and
1
�impacts to spawning fish and/or incubating eggs are less likely. Early communication with
CPW is encouraged as this suggested window could vary based on local considerations such
as elevation, environmental variability, and fish species present.
3) Invasive and Nuisance Species: To prevent the spread of invasive and/or nuisance species
(e.g., Asian Clam, Green River Mud Snail, New Zealand Mud Snail), we strongly encourage
that heavy equipment be cleaned prior to and after construction. The following methods
are recommended for preventing the spread of invasive aquatic organisms:
a) Disinfection with QAC: Remove all mud and debris from equipment (tracks, turrets,
buckets, drags, teeth, etc…) and spray/soak equipment with a disinfection solution
containing quaternary ammonia compound (QAC). Treated equipment must be kept
moist for at least 10 minutes. The recommended concentration for any commercially
available QAC product used to disinfect equipment is 6 ounces of QAC solution per
gallon of clean water. The following QAC products have been tested by CPW and are
listed in order from highest to lowest concentration of active QAC: Green Solutions
High Dilution Disinfectant 256, Super HDQ Neutral, Quat 4, Vedco 128, and Quat 128.
Disposal of QAC: Wastewater treatment plants are capable of processing water
containing small amounts of QAC. Therefore, rinsing used QAC solutions down a
sanitary sewer is a safe method of disposal. However, QACs should be kept out of
storm sewers and other waterways. Always dilute the old product before rinsing down
sanitary sewers directly from the container, and follow MSDS and label
recommendations regarding rinsing and disposal of empty containers. Small amounts of
QAC from spray disinfection may come in contact with the environment with few
negative effects. However, it is not recommended to dump large amounts of QAC
solutions directly on the ground. More detailed instructions for disinfection with QAC
products can be provided upon request.
b) Disinfection with Hot Water: Spray/soak equipment with water heated to a
temperature greater than 140 degrees Fahrenheit for at least 10 minutes.
4) Turbidity: Instream construction should be conducted in a manner that will minimize
turbidity of the water in the work area.
5) Petroleum Products and Chemicals: No petroleum products, chemicals, or other
deleterious materials should be allowed to enter or be disposed of in such a manner in
which they could enter the waterway or adjacent wetlands. Accordingly, we recommend
that oil absorbent “booms” be installed downstream of the project site during
construction activities.
6) Closure of Fishing Waters: CPW may request that instream construction activities be
restricted or suspended when it is determined that environmental conditions could result
in unacceptable levels of fish mortality. Such requests may be enacted, depending on the
fish species present, when any one of the following criteria are met:
a) Daily maximum temperature exceeds 71 degrees Fahrenheit;
b) Measured stream flows are 50% or less of the daily average flow;
2
�c) Fish condition is deteriorating such that fungus and other visible signs of deterioration
and/or stress may be present;
d) Daily minimum dissolved oxygen levels are below six (6) parts per million (ppm);
e) When a natural or anthropogenic environmental event such as wildlife, mudslides, oil
spills, or other similar event has occurred, resulting in the need for recovery time or
remedial action for a fish population.
Stream Restoration Projects
Stream restoration projects offer unique opportunities to improve aquatic and riparian
habitats for the enhancement or conservation of fishery resources. However, our ability to
validate the effectiveness of stream restoration projects remains limited, despite investments
of more than $1 billion per year (Bernhardt et al. 2005). CPW recommends that the following
guidelines be used to inform the design and review of stream restoration projects:
1) Design Report and Plan Set: Requests for design reviews must include complete permit
applications with all pertinent information, including a design report and plan set. Review
requests for Stream Mitigation Bank projects must be accompanied by all materials
required under the latest version of the Colorado Mitigation Procedures (COMP). The
design report should include a comparison of restoration alternatives that were used to
inform the selection of proposed restoration treatments. The design report and plan set
should clearly detail restoration treatments, design criteria, and design methods. CPW
will only provide technical design review for projects that submit complete applications.
2) Project Goals and Objectives: Applications must clearly state project goals and
objectives, and describe the cause of degradation, limiting factors, and context for the
project. Goals and objectives for aquatic habitat restoration should address the fishery
and ecological benefits expected from the project.
3) Process-Based Design: Project proposals should clearly address the connection between
physical processes and aquatic habitat, as well as project-related risks to species and
habitat (Skidmore et al. 2011). Restoration designs must consider the preservation of
functional riverine and aquatic processes and maintain the natural aesthetic quality of the
river.
4) Site Selection and Approach: Site selection and restoration approach are critically
important considerations. Stream restoration projects should not target highly functioning
streams, and alternative restoration approaches should be considered during the
conceptual design phase. Passive restoration techniques, such as riparian fencing and
revegetation, should be considered during the evaluation of alternatives, as they may be
more cost-effective than intensive channel alterations.
5) Biostabilization: Restoration designs should utilize biostabilization techniques to stabilize
disturbed streambanks as outlined in Living Streambanks: a Manual for Bioengineering
Treatments for Colorado Streams (Giordanengo et al. 2016).
3
�6) Riparian Vegetation: Revegetation plans that utilize native riparian species should be
provided for all projects. Riparian exclosures and irrigation may be necessary for effective
revegetation, and should be a consideration in these plans.
7) Floodplain Connectivity: Restoration designs should utilize multi-stage (or nested)
channels with functional floodplains to provide diverse habitat, convey water, transport
sediment, and dissipate energy during floods.
8) Large Wood: Restoration designs should incorporate large woody materials when
appropriate to improve geomorphic function and habitat diversity.
9) Monitoring and Evaluation: Project objectives should be measurable and monitoring of
pre- and post-restoration conditions should be used to evaluate project effectiveness and
inform adaptive management. CPW recommends a minimum monitoring period of five
years following restoration activities, with an emphasis on documenting baseline
conditions, as-built conditions, and project effectiveness with at least two monitoring
events during the five-year period after restoration.
10) Maintenance and Stewardship: Stream restoration plans should address maintenance and
stewardship considerations for at least five years following project completion.
Fish Passage Projects
Aquatic habitat fragmentation is ubiquitous throughout Colorado, contributing to the decline
in native species diversity and abundance (CPW 2015). Instream structures, such as culverts,
grade control, water diversions and dams, can negatively affect fish by fragmenting
populations, reducing migratory ranges, and limiting access to seasonally available habitat for
spawning, feeding and refuge (Schlosser and Angermeir 1995). Trout populations are also
adversely affected by habitat fragmentation, as some populations move long distances (>25
miles) during upstream migrations to access spawning habitat. CPW recommends that the
following guidelines be incorporated into the design of fish passage projects:
1) CPW Fisheries Data: CPW should be contacted early in the design process to provide
important information regarding resident species assemblages and fishery management
objectives for a project site.
2) Target Species and Life Stages: Fish passage structures (fishways) will be expected to pass
all fish species present at the project site, unless there are specific management
objectives that would require exclusion of particular species. Fishways should be designed
to pass juvenile and adult life stages whenever feasible (Forty et al. 2016).
3) Design Flows: Fishways should be designed to provide fish passage across a range of
typical flows. The average daily discharge that is exceeded 95% and 5% of the time should
be selected for the low and high fishway design flows, respectively (NMFS 2008).
4) Attraction Flows: Sufficient attraction flows at the downstream fishway entrance is a
critical factor that will affect the efficiency of the fish passage structure. The velocity,
quantity, and location of attraction flows are all important design considerations. In
general, increasing the amount of attraction flow will increase the effectiveness of the
4
�fishway for providing upstream passage, and 5-10% of the total river flow should be
considered the minimum amount of attraction flow (NMFS 2008).
5) Passage Criteria: Fishway designs should compare hydraulic conditions within the fishway
to species-specific design criteria for swimming speeds, minimum water depths, and
vertical drops to evaluate the effectiveness of the proposed design. Continuity of passage
conditions through the fishway should be evaluated both laterally and longitudinally.
Swimming speeds and jumping heights for common Colorado fishes are included in a CPW
fact sheet on Fish Passage at River Structures (see Appendix B).
6) Recommended Designs: CPW recommends that constructed riffles, rock ramps, and
vertical slot fishways be considered as design alternatives during the conceptual design
phase of a fish passage project.
Bank Stabilization Projects
Although bank stabilization activities can help stabilize streams and reduce sediment inputs,
some activities may have adverse impacts on aquatic habitat and stream functions. There are
a variety of approaches to bank stabilization, including armoring, flow training structures,
and biostabilization techniques. CPW recommends that the following guidelines be
incorporated into the design of bank stabilization projects:
1) CPW Consultation: CPW primarily reviews bank stabilization projects when they occur on
streams designated as Gold Medal Waters, but consultation with CPW should also occur
when projects affect locations that are considered high priority habitats.
2) Biostabilization: Biostabilization techniques should be evaluated for bank stabilization
projects as outlined in Living Streambanks: a Manual for Bioengineering Treatments for
Colorado Streams (Giordanengo et al. 2016) to identify the LEDPA.
3) Armoring Setback: Hard armoring treatments (e.g., riprap, gabions, concrete) should be
setback from the stream channel whenever possible, so that stabilization is adjacent to
the infrastructure it is protecting rather than the streambank. Soil-filled riprap should be
utilized if armoring must be placed along the streambank to support the establishment of
riparian vegetation.
4) Best Management Practices: Erosion and water control measures should be implemented
to reduce the risk of sedimentation and water pollution during construction activities.
5) Floodplain Connectivity: Multi-stage channels with functional floodplains should be
utilized to convey water and dissipate energy during floods rather than single-stage
oversized channels that increase stream power and shear stress on the channel boundary.
6) Riparian Vegetation: Riparian vegetation composed of native species is the primary
control for bank stability in many stream types and should be utilized to improve longterm stability and resilience. Revegetation plans should be included with the plan set for
the project, including success criteria, planting protocols, irrigation needs, weed control,
and post-construction stewardship.
5
�References
Bernhardt, E. S., M. A. Palmer, J. D. Allan, G. Alexander, K. Barnas, et al. 2005. Synthesizing
U.S. river restoration efforts. Science 308:636-637.
CPW (Colorado Parks and Wildlife). 2015. State Wildlife Action Plan. Denver, Colorado.
Forty, M., J. Spees, and M. C. Lucas. 2016. Not just for adults! Evaluating the performance of
multiple fish passage designs at low-head barriers for the upstream movement of juvenile
and adult trout Salmo trutta. Ecological Engineering 94:214-224.
Giordanengo, J. H., R. H. Mandel, W. J. Spitz, M. C. Bossler, M. J. Blazewicz, S. E. Yochum,
K. R. Jagt, W. J. LaBarre, G. E. Gurnee, R. Humphries, and K. T. Uhing. 2016. Living
Streambanks: a Manual of Bioengineering Treatments for Colorado Streams. Colorado
Water Conservation Board, Denver.
NMFS (National Marine Fisheries Service). 2008. Anadromous Salmonid Passage Facility Design.
NMFS, Northwest Region, Portland, Oregon.
Schlosser, I. J., and P. L. Angermeier. 1995. Spatial variation in demographic processes for
lotic fishes: conceptual models, empirical evidence, and implications for conservation.
American Fisheries Society Symposium 17:392-401.
Skidmore, P. B., C. R. Thorne, B. L. Cluer, G. R. Pess, J. M Castro, T. J. Beechie, and C. C.
Shea. 2011. Science base and tools for evaluating stream engineering, management, and
restoration proposals. U.S. Department of Commerce, NOAA Technical Memo. NMFSNWFSC-112, 255 p.
6
�Appendix A
CPW Aquatic Biologist Contact Information
�I
MOFFAT
Tory Eyre
Meeker
(970)878-6074
----y _ _...,,,..-------- er- -
JACKSON
LARIMER
Steamboat
Springs Office
ROUTT
!
_______ _______________ J__
e Riv
Meeker
Office
:---'
GRAND
!
J
GARFIELD
Co
70
Ben Felt
_____Grand
..,_,_ _ __
_Junction
(970)255-6126
.
Glenwood
Springs '
Office
-·---
------..--
~
_._._...,_ __ _
EAGLE
mp
Unco
e River
a hgr
n
el
gu
Mi
Ri
ve
SAN MIGUEL
r
OURAY
TELLER
SW
Jim White
Durango
(970)375-6712
Durango Regional LA PLATA
Administrative Office
Ri o Grande Ri v
CUSTER
er
RIO Monte
GRANDE Vista
EL PASO
ARA PAHOE
t
S ou
Cory Noble
Colorado Springs
(719)227-5222
_____ __J
I
I
nR
KIT
CARSON
Smoky H
il
CHEYENNE
l River
OTERO
COSTILLA
Purgatoire R
- -- 50
LAS ANIMAS
25
Miles
75
100
NATIVE AQUATIC SPECIES
BIOLOGISTS
NORTHEAST REGION
Boyd Wright
(970)472-4366
BENT
PUEBLO
HUERFANO
r
NORTHWEST REGION
Lori Martin
(970)255-6186
SOUTHEAST REGION
Josh Nehring
(719)227-5224
r
i ve
LINCOLN
o
rf an
Hue
AQUATIC BIOLOGISTS
COLORADO PARKS AND WILDLIFE
25
ub
a
lic
Lamar Office
PROWERS
Jim Ramsay
Lamar
(719)336-6607
SE
mo s
aR
i ve
r
i ve
Conejos R
0
p
Re
NORTHEAST REGION
Jeff Spohn
(303)981-3634
SOUTHWEST REGION
John Alves
(970)375-6721
iver
ree R
ork
hF
SENIOR AQUATIC BIOLOGISTS
KIOWA
Carrie Tucker
Pueblo
(719)561-5312
ALAMOSA
CONEJOS
ARCHULETA
YUMA
WASHINGTON
Office
Ala
Durango
Office
NE
____ j
CROWLEY
Estevan Vigil
Monte Vista
(719)587-6908
MI NERAL
\
i
I
-Lake Pueblo
-Pueblo Office
SAGUACHE
SAN
JUAN
DOLORES
*
Dan Brauch
Gunnison
(970)641-7070
HINSDALE
,
I
ELBERT
DOUG LAS
PHILLIPS
•
Brush
Office
70
r
iv e
i ver
es R
l or
Sa
Littleton Administrative Office
as R
ans
Do
MONTROSE
MONTEZUMA
JEFFERSON
Mike Atwood
Salida
(719)530-5525FREMONT
Salida
Office
Gunnison
Office
G unn
ison Ri ver
76
Headquarters
CHAFFEE
Montrose
Office
I
,
a
Arik
Colorado Springs
Office
GUNNISON
Eric Gardunio
Montrose
(970)252-6017
er
Ri v
Mandi Brandt
Brush
(970)842-6330
ADAMS
A rk
DELTA
\
Denver Administrative Office
Northeast Regional Office
PARK
Grand
Junction
Office
I
Paul Winkle
Denver
(303)291-7232
th Pla tt e
____ _ _____ L_
Tyler Swarr
South Park
(720)576-9782
LAKE
PITKIN
MESA
CLEAR
CREEK
S UMMIT
Kendall Bakich
Glenwood Springs
(970)947-2924
S ou
i
I
-------'---1
MORGAN
BOULDER
GILPIN
e River
Blu
---, _____ ___ r ________ ____ ___
iver
lorad o R
Fort Collins
Office
Ben Swigle
Fort Collins
(970)472-4364
Hot Sulphur
Springs
Office
I
, --~-- -
LOGAN
WELD
Thompson Riv er
Bi g
Jon Ewert
Hot Sulphur
(970)725-6214
'i
!--
~
RIO BLANCO
25
Poudre River
ve
r
Whit
er
l; ---------------
Ri
en
River
Bill Atkinson
Steamboat
Springs
r'
re-'
a River
p
(970)870-2868
m
Ya
i'\.--•~~
SEDGWICK
Kyle Battige
Fort Collins
(970)472-4396
ian
Gr e
d
na
Ca
NW
Ri v
i
NORTHWEST REGION
Jenn Logan
(970)947-2923
SOUTHWEST REGION
Dan Cammack
(970)275-9617
SOUTHEAST REGION
Paul Foutz
(719)227-5217
BACA
r
ve
D CPW Region Boundary
Created by CPW GIS 2/12/2020
314 W. Prospect St
Fort Collins, CO 80526
G:\Projects\Publications\Boundaries\AquaticBoundaries\CPW_AquaticBiologists_2020_11x17.mxd
�Appendix B
CPW Fish Passage at River Structures Fact Sheet
�C O L O R A D O
P A R K S
&
W I L D L I F E
Fish Passage at River Structures
RESEARCH AND DESIGN GUIDELINES
Introduction
Instream structures, such as culverts, water diversions and dams, can negatively affect fish by
fragmenting populations, reducing migratory ranges, and limiting access to habitat for spawning, feeding and refugia.
Many rivers in Colorado contain man-made structures that create partial (obstacles) or complete barriers depending on
the fish species and life stage. Habitat fragmentation associated with instream barriers is a serious threat to Colorado’s
Species of Greatest Conservation Need (SGCN) and sport
fisheries. Therefore, it is important that fisheries managers
(A)
identify and evaluate the influence of instream structures on
fish populations.
Fish Passage Research Objectives
The primary goal of fish passage research is to restore
connectivity in fragmented river systems by: (1) evaluating the
effectiveness of existing fishways; (2) evaluating the barrierpotential of common river structures; and (3) establishing fish
swim performance criteria for native and sport fishes.
Current Fish Passage Research Projects
Active fish passage research projects include: (1) evaluation of
native fish passage at existing fishways located on Front Range
transition zone streams; (2) evaluation of fish passage at
instream whitewater park structures; (3) laboratory studies to
develop fish swim and jump performance criteria for Colorado
fishes where data is lacking; and (4) development of new
techniques and technologies for investigating fish movement
and passage in rivers.
(B)
Fishway Design
Fishways, or “fish ladders”, are engineered structures
designed to facilitate passage around an obstacle or barrier.
Fishways attempt to incorporate species- and life stagespecific swimming and jumping abilities into designs. Common
elements of successful fishways include: (1) low velocity
pathways that do not exceed burst speeds or endurance
capabilities for target species (Figure A); (2) water depths that
do not limit swimming performance (Figure B); (3) vertical
drops that do not exceed the jumping ability for target species
- note that many species native to Colorado do not exhibit
jumping behaviors (Figure C); (4) sufficient attraction flow, or
the flow that emanates from a fishway entrance, to ensure
that fish can locate the fishway; and (5) maintenance of the
above design elements over the expected range of
streamflows.
Fin Depth
(Alaska)
Depth Criteria = 5 to 8 in
(C)
Vertical Drop> Jumping Height
COLORADO PARKS & WILDLIFE • 1313 Sherman St., Denver, CO 80203 • (303) 297-1192 • cpw.state.co.us
�Fishway Examples
Some examples of successful fishways include engineered rock ramps (Figure D), constructed riffles (Figure E), and
vertical slot fishways (Figure F). Each type of fishway has advantages and disadvantages related to which fish species
and life stages are present and the conditions of the project site.
Engineered Rock Ramp
Constructed Riffle
Vertical Slot
Diversion Crest
Piney Creek,
Wyoming
Fossil Creek Reservoir
Inlet Diversion,
Cache la Poudre River
(D)
Rock Weirs
CCC Ditch,
San Miguel River
(E)
(F)
Aquatic Habitat Types
From the high-gradient, boulder-dominated, step-pool
channels of snowmelt fed mountain streams to the lowgradient, well-vegetated, pool-riffle rivers of the eastern
plains to the majestic, vertically-confined canyons on the
arid Colorado Plateau, aquatic habitats in Colorado are as
diverse as the geographic regions where they are found.
Native Colorado fishes have unique morphological
characteristics that are adapted to the natural conditions
found in each aquatic habitat type. These adaptations affect
the swimming abilities of fish, influencing how they move
through and use diverse habitats. Fisheries managers must
take the diversity of fish species into consideration when
evaluating river structures and designing fishways.
... .,,...
-
SGCN (#)
Fundulidae (Topminnows)
Cottidae (Sculpin)
Ictaluridae (Catfish)
Cyprinidae (Minnows)
Catostomidae (Suckers)
Centrarchidae (Sunfish)
"""<"~
----a..·1
-~~
COlORAOO STATE WILDLIFE
ACTION Pt.AN 2015
Tr~Zone
W,onw,g8'tirV'ColoncloPlll. .lJ
Fish Swimming Performance by Family
Family Name
Percidae (Perches)
_ o , ___ _
Enl9fnf'IN-.
~ n s t r. .mt
All illustrations of fish © Joseph R. Tomelleri
3
Prolonged Speed (ft/s)
0.4 - 1.2
Burst Speed (ft/s)
NA - 2.4
Jump Height (ft)
0*
Habitat Types
EP
1
0
1
13
5
1
1.3 - 1.6
1.4 - 1.7
1.3 - 2.0
1.3 - 2.4
1.3 - 2.5
1.1 - 2.9
2.6 - 3.4
3.3 - 3.9
2.0 - NA
2.4 - 4.4
2.2 - 3.2
2.6 - NA
0.1 - 0.2
0*
NA - 0.2
0* - 0.5
NA - 0.8
0.4 - NA
EP
CP, MS
EP, TZ
CP, EP, MS, RG, TZ
CP, EP, MS, RG, TZ
EP
Salmonidae (Trout)
3
2.3 - 4.0
4.5 - 7.5
1.0 - 7.0
MS, RG, TZ
SGCN = Species of Greatest Conservation Need, # of species/subspecies; * = fish species does not exhibit jumping behavior; NA =
data were not available; CP = Colorado Plateau, EP = Eastern Plains, MS = Mountain Streams, RG = Rio Grande; TZ = Transition Zone
The values reported above are summarized from multiple species within each family and are intended to support passage
for juvenile life stages. Swim speeds and jumping abilities within species are size dependent. Species-specific performance
criteria should be used whenever possible. The selection of target species for individual projects should be based on the
management objectives for the site in question. Consultation with the local Area Aquatic Biologist at CPW is strongly
encouraged during the early planning stages for any fish passage project in Colorado. The information in this fact sheet is
based on the best available data and knowledge, but is subject to revision as more information becomes available.
COLORADO PARKS & WILDLIFE • 1313 Sherman St., Denver, CO 80203 • (303) 297-1192 • cpw.state.co.us
�
https://cpw.cvlcollections.org/files/original/8c65d55b1bf3a12f6081326387a39fce.pdf
955ec692050ab1fbbecf3fca5cba1195
PDF Text
Text
Environmental Toxicology and Chemistry, Vol. 26, No. 8, pp. 1666–1671, 2007
䉷 2007 SETAC
Printed in the USA
0730-7268/07 $12.00 ⫹ .00
TOXICITY OF CADMIUM TO EARLY LIFE STAGES OF BROWN TROUT
(SALMO TRUTTA) AT MULTIPLE WATER HARDNESSES
STEPHEN F. BRINKMAN* and DARIA L. HANSEN
Aquatic Research, Colorado Division of Wildlife, 317 West Prospect Road, Ft. Collins, Colorado 80526, USA
( Received 24 July 2006; Accepted 7 February 2007)
Abstract—Toxicity of cadmium to early life stages of brown trout (Salmo trutta) was determined at multiple water hardnesses.
Increasing water hardness decreased cadmium toxicity. Postswimup fry were much more sensitive than embryos and larvae. Chronic
values from early life stage tests initiated with eyed embryos were 3.52, 6.36, and 13.6 g Cd/L at water hardnesses of 30.6, 71.3,
and 149 mg/L, respectively. In tests initiated with 30-d postswimup fry, chronic values were 1.02, 1.83, and 6.54 g Cd/L at water
hardnesses of 29.2, 67.6, and 151 mg/L, respectively. Higher chronic values from the early life stage tests compared to tests initiated
with swimup fry likely are caused by acclimation during cadmium-tolerant embryo and larval stages. Growth was not affected by
cadmium in the early life stage tests but was negatively affected in tests initiated with fry at water hardnesses of 29.2 and 67.6
mg/L. Concentrations of cadmium that reduced growth were higher than those that increased mortality. Median lethal concentrations
for swimup fry after 96 h were 1.23, 3.90, and 10.1 g Cd/L at water hardnesses of 29.2, 67.6, and 151 mg/L, respectively. Test
results enable prediction of acute mortality of brown trout swimup fry based on cadmium concentration and water hardness.
Keywords—Cadmium
Brown trout
Hardness
Acclimation
MATERIAL AND METHODS
INTRODUCTION
Organisms
An estimated 2,080 km of streams in Colorado, USA are
affected by metals [1]. Cadmium is commonly found as a
contaminant in the Colorado mineral belt and often is associated with waters affected by historic mining activities. Brown
trout (Salmo trutta) are an important component of Colorado
ecosystems in many headwater streams, but their densities
often are reduced because of metal contamination [2]. Limited
cadmium toxicity data indicate that brown trout is perhaps the
most acutely sensitive aquatic species tested [3]. Median lethal
concentrations (LC50s) after 96 h were 1.4, 2.39, and 1.87 g
Cd/L in water hardnesses of 43.5, 37.6, and 36.9 mg/L, respectively, as CaCO3 [4,5]. The chronic value was 16.49 g
Cd/L at a water hardness of 250 mg/L from a life-cycle test
with brown trout [6]. A brown trout early life stage (ELS) test
resulted in a chronic value of 6.67 g Cd/L at a water hardness
of 44 mg/L [7]. Curiously, hardness-adjusted, 96-h LC50s are
much lower than chronic values derived from life-cycle and
ELS tests. Life-cycle and ELS tests typically start with a tolerant life stage. Acclimation that occurs during a tolerant life
stage results in reduced toxicity during a subsequent, sensitive
life stage [4,8,9,10]. In contrast, acute toxicity tests usually
are conducted using unacclimated organisms during a sensitive
life stage.
The first objective of the present study was to develop a
relationship that could predict mortality of brown trout fry
based on cadmium concentration and water hardness. The second objective was to compare toxicity of cadmium in tests
initiated with embryo and larval life stages and postswimup
fry. To achieve these test objectives, toxicity tests were conducted using both life stages at water hardnesses of 30, 75,
and 150 mg/L as CaCO3.
Brown trout embryos were obtained as newly eyed eggs
from the Colorado Division of Wildlife Research Hatchery
(Bellevue, CO, USA). The source of the eggs was a Colorado
Division of Wildlife spawning operation using feral brown
trout in the North Delaney Butte Reservoir (Colorado, USA).
Ten eggs were placed into each exposure chamber for the ELS
tests. Additional eggs were placed in 90-L glass aquaria,
hatched, and later used in the fry toxicity tests. Eggs began
hatching approximately 14 d after initiation of exposure.
Brown trout embryos remained as sac fry for approximately
27 d before reaching the swimup stage. Fry were fed appropriately sized trout food (Silver Cup; Nelson and Sons, Murray,
UT, USA) four times daily (twice daily on weekends and holidays) at an estimated rate of 3% body weight/d on absorption
of the yolk sac. Trout food was supplemented with a concentrated suspension of brine shrimp nauplii (age, ⬍24 h; San
Francisco Bay Brand, Newark, CA, USA). The ELS test exposure continued for an additional 14 d postswimup. Total
exposure duration for the ELS tests was 55 d.
The fry toxicity tests used 34-d postswimup fry from the
same lot of eggs as the ELS tests. Fry were not fed during the
initial 96 h of exposure but were subsequently fed twice daily
(once on weekends and holidays) at an estimated rate of 3%
body weight/d. Exposure for the fry toxicity tests was 30 d.
Exposure apparatus
Water from an on-site well was diluted with either dechlorinated Fort Collins municipal tap water or reverse-osmosis
water to obtain nominal water hardnesses of 30, 75, and 150
mg/L as CaCO3 (designated 30H, 75H, and 150H, respectively). Each water mixture was maintained at a constant hardness through the use of conductivity controllers. Identical modified continuous-flow diluters [11] were constructed of Teflon威,
* To whom correspondence may be addressed
(steve.brinkman@state.co.us).
1666
�Environ. Toxicol. Chem. 26, 2007
Toxicity of cadmium to brown trout
1667
Table 1. Water-quality characteristics (mean [SD]) used for early life stage (ELS) and fry testsa
30 Hardness
Hardness (mg/L)
Alkalinity (mg/L)
pH (S.U.)
Temperature (⬚C)
Conductivity (S/L)
Dissolved oxygen (mg/L)
a
75 Hardness
150 Hardness
ELS
Fry
ELS
Fry
ELS
Fry
30.6 (2.1)
22.9 (1.3)
7.72 (0.12)
11.6 (0.4)
52.9 (2.0)
8.49 (0.58)
29.2 (0.9)
21.7 (0.8)
7.54 (0.13)
11.7 (0.1)
51.5 (0.5)
8.61 (0.22)
71.3 (2.7)
51.5 (1.6)
7.75 (0.14)
12.0 (0.3)
123
(5)
8.61 (0.67)
67.6 (1.5)
47.9 (1.1)
7.60 (0.10)
11.4 (0.2)
115
(2)
8.88 (0.17)
149
(7)
107
(5)
7.83 (0.14)
11.8 (0.4)
255
(8)
8.32 (0.64)
151
(2)
107
(2)
7.51 (0.12)
11.8 (0.4)
260
(2)
8.58 (0.14)
30 Hardness, 75 Hardness, and 150 Hardness refer to 30, 75, and 150 mg/L, respectively, as CaCO3.
polyethylene, and polypropylene components. The diluters delivered five exposures with a 50% dilution ratio and an exposure control. A flow splitter allocated each concentration
equally among four replicate exposure chambers at a rate of
40 ml/min each. Exposure chambers consisted of polyethylene
containers with a capacity of 2.8 L. Test solutions overflowed
from exposure chambers into water baths, which were maintained at 12⬚C using temperature-controlled recirculators.
Chemical stock solutions were prepared by dissolving a calculated amount of reagent-grade cadmium sulfate (CdSO4) in
deionized water. The chemical stock solutions were delivered
to the diluters via peristaltic pumps at a rate of approximately
2.0 ml/min. New stock solutions were prepared as needed
during the toxicity tests. Dim fluorescent lighting provided a
12:12-h light:dark photoperiod. Diluters and toxicant flow
rates were monitored daily to ensure proper operation. Fish
loading during the ELS test was less than 0.63 g/L of tank
volume and less than 0.04 g/L of flow per 24 h. During the
fry tests, loading never exceeded 2.2 g/L of tank volume and
was less than 0.11 g/L of flow per 24 h. Fish loading was
much less than the suggested maximum levels [12].
ELS test methods
The number of hatched eggs and the mortality of eggs and
fry were monitored and recorded daily. Dead fry were blotted
dry with a paper towel, and total length (to the nearest mm)
and weight (to the nearest 0.001 g) were measured and recorded. At the end of the tests, surviving fish from each exposure chamber were terminally anesthetized and blotted dry
with a paper towel, and total lengths and weights were measured and recorded.
Water-quality characteristics of exposure water were measured weekly in all treatment levels within a replicate. Different replicates were selected each week for sampling. Hardness and alkalinity were determined according to standard
methods [13]. A Thermo Orion 635 meter (ThermoFisher, Waltham, MA, USA) was used to measure pH and conductivity.
Dissolved oxygen was measured using an Orion 1230 dissolved oxygen meter (ThermoFisher). The conductivity, pH,
and dissolved oxygen meters were calibrated before each use.
Water samples for cadmium analyses were collected weekly
from each exposure level with surviving fry. Exposure water
was passed through a 0.45-m filter (Acrodisc; Pall Life Sciences, Ann Arbor, MI, USA), collected in disposable polystyrene tubes (Falcon, Franklin Lakes, NJ, USA), and immediately preserved with high-purity nitric acid to pH less than 2.
Water samples were analyzed using a SH4000 atomic absorption spectrometer with CTF 188 graphite furnace (Thermo
Jarrell Ash, Waltham, MA, USA) and Smith-Hieftje background correction. Dibasic ammonium phosphate (0.1%) was
used as a matrix modifier. The spectrometer was calibrated
before each use and the calibration verified using a certified
standard (High Purity Standards, Charleston SC, USA). Sample splits and spikes were collected at each sampling event to
verify analytical reproducibility and recovery.
Fry test methods
Brown trout fry experiments utilized the same exposure
apparatus as the ELS tests. Test methods were identical to the
ELS test methods with the following exceptions: Water-quality
characteristics were determined daily, and cadmium concentrations were measured three times during the initial 96 h and
weekly thereafter. Fry were not fed during the initial 96 h of
exposure but were fed twice daily thereafter (once daily on
weekends). Cadmium exposure lasted for a total of 30 d.
Water-quality characteristics of both ELS and fry tests were
near target levels and consistent over the duration of the experiments, as evidenced by relatively low standard deviations
(Table 1). Mean recovery was 99% for quality assurance standard and 101% for spiked samples. Mean percentage difference
between sample splits was 7%. The detection limit was less
than 0.08 g Cd/L.
Statistical analysis
Statistical analyses of data were conducted using Toxstat
Version 3.5 software [14]. Analysis of variance (ANOVA) was
used to test toxicity end points that included hatching success,
sac fry survival, swimup survival, mean time to hatch, and
lengths, weights, and biomass of surviving fish at test termination. Hatching success and survival data were arcsine square
root transformed before ANOVA [15]. Normality and homogeneity of variances were tested using chi-square and Levene’s
test, respectively. Treatment means were compared to the control using Williams’ one-tailed test [16,17] at p ⬍ 0.05. Mortality data from the 30H fry test did not meet the assumption
of homogeneity of variance and were analyzed using Steel’s
many-one rank test. The highest cadmium concentration not
associated with a treatment effect (e.g., decreased survival or
decreased body weight) was designated as the no-observedeffect concentration (NOEC). The lowest concentration of cadmium associated with a treatment effect was designated as the
lowest-observed-effect concentration (LOEC). Chronic values
were calculated as the geometric mean of the LOEC and
NOEC. The concentration estimated to cause a 20% reduction
in organism performance compared with the control (IC20)
[18] was calculated using the combined weight of surviving
organisms from each treatment (biomass or standing crop).
The 96-h LC50s were estimated by the trimmed SpearmanKarber technique [19] using log-transformed cadmium concentrations and 10% trim. Regressions of end points and hard-
�1668
Environ. Toxicol. Chem. 26, 2007
S.F. Brinkman and D.L. Hansen
Table 2. End points and associated cadmium chronic values (g/L) of early life stage (ELS) and fry testsa
30 Hardness
ELS
Time to hatch
⬎4.87 (4.87, ND)
Hatch success
⬎4.87 (4.87, ND)
Sac fry survival
⬎4.87 (4.87, ND)
Swimup fry survival 3.52 (2.54, 4.87)
Weight
⬎4.87 (4.87, ND)
IC20
2.22
96-h LC50
—
a
75 Hardness
Fry
—
—
—
1.02 (0.74, 1.40)
1.95 (1.40, 2.72)
0.87
1.23
ELS
150 Hardness
Fry
⬎8.64 (8.64, ND)
—
⬎8.64 (8.64, ND)
—
⬎8.64 (8.64, ND)
—
6.36 (4.68, 8.64) 1.83 (1.30, 2.58)
⬎8.64 (8.64, ND) 3.4 (2.58, 4.49)
4.01
2.18
—
3.9
ELS
Fry
⬎19.1 (19.1, ND)
—
⬎19.1 (19.1, ND)
—
⬎19.1 (19.1, ND)
—
13.6 (9.62, 19.1)
6.54 (4.81, 8.88)
⬎19.1 (19.1, ND) ⬎16.4 (16.4, ND)
13.6
6.62
—
10.1
30 Hardness, 75 Hardness, and 150 Hardness refer to 30, 75, and 150 mg/L, respectively, as CaCO3. LOEC ⫽ lowest-observed-effect concentration; ND ⫽ not detected; NOEC ⫽ no-observed-effect concentrations; NOEC and LOEC in parentheses.
ness were performed using the Statistical Analysis System Proc
GLM and assuming a log–log relationship [20]. Proc Genmod
was used for the logistic regression of mortality with hazard
quotient (HQ).
RESULTS
ELS tests
Mean time to hatch, hatching success, and sac fry survival
were not significantly affected at any cadmium concentrations
in any of the tests. Hatching success was 70 to 95% and exceeded 80% in the controls. Mortality during the sac fry stage
was very low. Metal-related mortality occurred shortly after
swimup, after absorption of the yolk sac, and when fry began
exogenous feeding. In the 30H test, mortality was significant
at 4.87 g Cd/L (LOEC) but not at 2.54 g Cd/L (NOEC).
The LOEC and NOEC for the 75H test was 8.64 and 4.68 g
Cd/L, respectively. Mortality in the 150H test was significant
at 19.1 g Cd/L (LOEC) but not at 9.62 g Cd/L (NOEC).
The chronic values based on survival were 3.52, 6.36, and
13.6 g Cd/L in water hardnesses of 30.6, 71.3, and 149
mg/L, respectively, as CaCO3 (Table 2). No significant effects
on growth, as measured by lengths and weights of fry at test
termination, were detected. The IC20s based on biomass at
test termination were 2.22, 4.71, and 13.6 g Cd/L in water
hardnesses of 30.6, 71.3, and 149 mg/L, respectively (Table
2).
Acute fry tests
No mortality occurred in the control or lowest exposure
concentration during the 96-h acute exposures. Mortality increased with increasing cadmium concentration, resulting in
complete mortality at 5.64 g Cd/L in 30H. In 75H, 97.5%
mortality was observed at 8.86 g Cd/L, and in 150H, 90%
mortality was observed at 16.4 g Cd/L. The slopes of the
concentration–response curves appeared to decrease as the water hardness increased. The 96-h LC50s were 1.23, 3.90, and
10.1 g Cd/L at water hardnesses of 29.2, 67.6, and 151
mg/L, respectively (Table 2).
Chronic fry tests
Little additional metal-related mortality occurred after the
initial 96 h of exposure. In the 30H exposures, low levels of
mortality were observed at 0.42 and 0.74 g Cd/L, but this
was not significantly greater than control at p ⫽ 0.05. In 30H,
mortality was significant at 1.40 g Cd/L (LOEC) but not at
0.74 g Cd/L (NOEC). The LOEC and NOEC for the 75H
exposures were 2.58 and 1.30 g Cd/L, respectively. Mortality
in the 150H test was significant at 8.88 g Cd/L (LOEC) but
not at 4.81 g Cd/L (NOEC). The chronic values based on
survival were 1.02, 1.83, and 6.54 g Cd/L at water hardnesses
of 29.2, 67.6, and 151 mg/L, respectively (Table 2). Reduced
growth, as measured by weight at test termination, was detected in the 30H and 75H tests. The weight of the single
surviving fish at 2.72 g Cd/L in the 30H test was significantly
less than control. In the 75H test, mean weights of surviving
fish in 4.49 and 8.86 g Cd/L were significantly less than
controls. No effect on growth was detected in the 150H test.
The IC20s based on biomass at test termination were 0.87,
2.18, and 6.62 g Cd/L in water hardnesses of 30.6, 71.3, and
149 mg/L, respectively (Table 2).
DISCUSSION
A break in a water line leading to the toxicology laboratory
led to premature termination of the ELS tests after 41 d posthatch (14 d postswimup). The recommended duration of salmonid ELS tests is 60 d posthatch [20] or at least 30 d postswimup [12]. A majority of metal-related mortality occurred
shortly after swimup and then quickly tapered off. It is unlikely
that significant additional mortality would have taken place
had the test continued for an additional 20 d. Negative effects
on growth in the ELS tests may have occurred if the exposure
continued for a longer duration.
Cadmium exposure to brown trout eggs did not affect mean
time to hatch. Time to hatch of brown trout eggs has been
altered by exposure to zinc [9,10] and to manganese [21].
Exposure to silver accelerated hatching of rainbow trout (Oncorhynchus mykiss) eggs [22]. Hatching success and sac fry
mortality were unaffected by the cadmium concentrations used
in the ELS tests. Egg and sac fry life stages of salmonids
generally are more tolerant to metal exposure than the subsequent swimup fry stage [23,24]. Metal-related mortality in
the ELS tests occurred shortly after brown trout embryos
reached the swimup stage and began exogenous feeding. No
effect of cadmium exposure on growth was detected in any of
the ELS tests. In contrast, reduced growth in the fry tests was
detected at 30H and 75H but not at 150H. Growth impacts
occurred at cadmium concentrations greater than those that led
to increased mortality.
The most sensitive end point tested was the IC20. The
inhibitory concentration is interpolated from a concentration–
response relationship and provides an estimate for a reduction
of biological performance—in this case, a reduction of 20%
biomass. Biomass at test termination reflects the effects of
exposure on both survival and growth. Chronic values based
on NOEC and LOEC are determined using hypothesis testing
and can be influenced by selection of exposure concentrations
�Toxicity of cadmium to brown trout
Environ. Toxicol. Chem. 26, 2007
1669
Fig. 1. Brown trout cadmium chronic values from brown trout life cycle–early life stage tests and fry at different water hardnesses.
and variability of the data set. Furthermore, chronic values
provide little information regarding the magnitude of the effect
at the LOEC. For fry but not ELS tests, the IC20 and the
chronic value based on mortality were in close agreement. In
contrast, chronic values from the 30H and 75H ELS tests were
considerably greater than the corresponding IC20s. High variability inherent to ELS tests may decrease statistical power
to detect reduced survival or biomass.
The ELS chronic values from the present study, along with
previously reported values from ELS and life-cycle tests, show
decreasing chronic toxicity with increasing hardness (Fig. 1).
Results from the present study are in good agreement with
those in the existing literature. The regression of the ELS
chronic values, including an ELS test at a water hardness of
44 mg/L [6] and a life-cycle test at a water hardness of 250
mg/L [7], provides a good fit, with a correlation coefficient of
0.97. The regression equation for the ELS/life-cycle tests is
brown trout ELS/life cycle chronic Cd
⫽ exp{0.7033[ln(hardness)] ⫺ 1.017}
Chronic values from tests initiated with fry are substantially
lower than chronic values derived from ELS and life-cycle
tests (Fig. 1). The equation describing the regression line for
the fry tests (correlation coefficient, 0.97) is
brown trout fry chronic Cd
⫽ exp{1.093[ln(hardness)] ⫺ 3.734}
Chronic end points of the ELS tests were consistently greater than those in the tests initiated with fry and even exceeded
96-h LC50s (Table 2). Exposure during cadmium-tolerant egg
and larval stages probably resulted in acclimation. Consequently, exposed organisms were more tolerant to lethal effects
during the subsequent, sensitive swimup fry stage
[8,10,25,26]. Similarly, the U.S. Environmental Protection
Agency (EPA) cadmium criteria document derived a brown
trout species mean chronic value of 5.004 g Cd/L, which is
much greater that the reported species mean chronic value of
1.613 g Cd/L [3]. The U.S. EPA water-quality criteria are
intended to protect all life stages of an organism; however,
chronic criteria derived from tests in which acclimation occurred may not protect sensitive life stages. The U.S. EPA
criteria guidance document acknowledges that acclimation
during chronic tests could lead to an acute to chronic ratio of
less than two. In such cases, an acute to chronic ratio of two
is assumed, because acclimation and continuous exposure in
field situations cannot be assured.
Unacclimated brown trout fry from clean tributaries or upstream of a cadmium source could migrate into, or be washed
into, cadmium-contaminated reaches. Those fry likely will experience cadmium toxicity in a manner similar to the tests
initiated with fry rather than to that of the ELS tests. Also,
brown trout fry can lose acclimation to metals once exposure
to metals is discontinued [9,27] (Lara L. Gasser, 1998, Master’s
thesis, Colorado State University, Fort Collins, CO, USA).
Migration into a clean tributary could lead to a loss of acclimation, followed by toxicity on return to a contaminated
stream reach. Loss of acclimation also could occur during
spring runoff, when dilution from spring snowmelt substantially reduces metal concentrations in streams.
Acute toxicity of cadmium decreased as hardness increased
(Fig. 2). In addition to data from the present study, the regression of LC50s with hardness included three previous studies (1.4, 2.39, and 1.87 g Cd/L at water hardnesses of 43.5,
37.6, and 36.9 mg/L, respectively) [4,5]. The regression equation estimating the brown trout cadmium LC50 based on water
hardness is (correlation coefficient, 0.95)
brown trout Cd LC50 ⫽ exp{1.258[ln(hardness)] ⫺ 3.999}
The equation above, relating the cadmium LC50 and water
hardness, can be used to normalize cadmium exposure concentrations. Assuming that half the LC50 is a safe concentration [20], a HQ for brown trout can be calculated by dividing
a cadmium exposure concentration at a given hardness ([Cd]h)
by half the estimated LC50 at that hardness (LC50h):
�1670
Environ. Toxicol. Chem. 26, 2007
S.F. Brinkman and D.L. Hansen
Fig. 2. Brown trout cadmium median lethal concentrations (LC50) at different water hardnesses.
brown trout HQ ⫽ [Cd]h /(0.5·LC50h)
Percentage mortality plotted against the HQ exhibits a characteristic sigmoid-shaped curve (Fig. 3). Acute mortality data
from the three tests reported here as well as from two previous
tests [5] are included. The fit of the curve is reasonable considering the range of hardness (30–150 mg/L) and size of
organisms (0.48–7.00 g). Exposure concentrations and associated mortality were not reported by Spehar and Carlson [4]
and, consequently, were not used in the regression. That particular study is represented by a single point with 50% mortality at the reported LC50 divided by the hardness-predicted
LC50. The equation for the line relating cadmium HQ and
brown trout mortality is
96-h brown trout mortality (%)
⫽ 100/[1 ⫹ exp(⫺2.4011HQ ⫹ 5.067)]
Figure 3 and the associated regression equation can be used
to predict brown trout swimup fry mortality given cadmium
concentration and hardness. Alternatively, hardness-based
concentrations of cadmium can be calculated for the protection
of brown trout based on an acceptable level of mortality.
CONCLUSIONS
Cadmium is highly toxic to brown trout swimup fry. Embryos and larvae are less sensitive. Chronic tests initiated with
tolerant life stages may lead to acclimation, resulting in lower
Fig. 3. The 96-h brown trout mortality (%) as a function of cadmium hazard quotient (HQ).
�Toxicity of cadmium to brown trout
mortality during more sensitive life stages. In such instances,
ELS tests may underestimate chronic toxicity. Cadmium toxicity is decreased by water hardness in a predictable manner.
The LC50s of cadmium to brown trout fry can be estimated
from water hardness. The ratio of measured cadmium concentration to the estimated LC50 can be used to estimate acute
brown trout mortality.
Acknowledgement—Funding was provided by the U.S. Fish and Wildlife Service Federal Aid Grant F-243. The authors wish to thank
Patrick Davies for his mentorship and advice.
REFERENCES
1. Water Quality Control Division. 1988. Colorado Nonpoint Source
Management Program. Prepared to fulfill the requirements of Section 319 of the Clean Water Act. Colorado Department of Public
Health and Environment, Denver Colorado, USA.
2. Davies PH, Woodling JD. 1980. The importance of laboratoryderived metal toxicity results in predicting in-stream response of
resident salmonids. In Eaton JG, Parrish PR, Hendricks AC, eds,
Aquatic Toxicology. STP 707. American Society for Testing and
Materials, Philadelphia, PA, pp 281–299.
3. Smith GJ, Roberts C. 2001. Update of ambient water-quality criteria for cadmium. EPA-822-R-01-001. Technical Report. U.S.
Environmental Protection Agency, Washington, DC.
4. Spehar RL, Carlson AR. 1984. Derivation of site-specific waterquality criteria for cadmium and the St. Louis River basin, Duluth,
Minnesota. Environ Toxicol Chem 3:651–665.
5. Davies PH, Brinkman SF. 1994. Federal Aid in Fish and Wildlife
Restoration. Job Final Report F-33. Colorado Division of Wildlife, Fort Collins, CO, USA.
6. Brown V, Shurben D, Miller W, Crane M. 1994. Cadmium toxicity
to rainbow trout Oncorhynchus mykiss Walbaum and brown trout
Salmo trutta L. overextended exposure periods. Ecotoxicol Environ Saf 29:38–46.
7. Eaton JG, McKim JM, Holcombe GW. 1978. Metal toxicity to
embryos and larvae of seven freshwater species–I. Cadmium. Bull
Environ Contam Toxicol 19:95–103.
8. Sinley JR, Goettl JP, Davies PH. 1974. The effects of zinc on
rainbow trout (Salmo gairdneri) in hard and soft water. Bull Environ Contam Toxicol 12:193–201.
9. Davies PH, Brinkman SF, Hansen DL. 2002. Federal aid in fish
and wildlife restoration. Job Progress Report F-243R-9. Colorado
Division of Wildlife, Fort Collins, CO, USA.
10. Davies PH, Brinkman SF, Hansen DL. 2003. Federal aid in fish
and wildlife restoration. Job Progress Report F-243R-10. Colorado Division of Wildlife, Fort Collins, CO, USA.
Environ. Toxicol. Chem. 26, 2007
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11. Benoit DA, Mattson VR, Olsen DC. 1982. A continuous flow
mini-diluter system for toxicity testing. Water Res 16:457–464.
12. American Society for Testing and Materials. 1997. Standard guide
for conducting early life stage toxicity tests with fishes. E1241.
In Annual Book of ASTM Standards, Vol 11.05. Philadelphia,
PA, pp 941–968.
13. American Public Health Association. 1998. Standard Methods
for the Examination of Water and Wastewater, 16th ed. American
Public Health Association, American Water Works Association,
and Water Pollution Control Federation. Washington, DC.
14. Western EcoSystems Technology. 1996. Toxstat, Ver 3.5. Cheyenne WY, USA.
15. Snedecor GW, Cochran WG. 1980. Statistical Methods. Iowa
State University Press, Ames, IA, USA.
16. Williams DA. 1971. A test for differences between treatment
means when several dose levels are compared with a zero dose
control. Biometrics 27:103–117.
17. Williams DA. 1972. The comparison of several dose levels with
a zero dose control. Biometrics 27:103–11.
18. Norberg-King T. 1993. A linear interpolation method for sublethal
toxicity: The inhibition concentration (ICp) approach. National
Effluent Toxicity Assessment Center Technical Report 03-93. U.S.
Environmental Protection Agency, Duluth, MN.
19. Hamilton MA, Russo RC, Thurston RV. 1977. Trimmed Spearman-Karber method for estimating median lethal concentrations
in toxicity bioassays. Environ Sci Technol 11:714–719. Correction 12:417 (1978).
20. Stephan CE, Mount DI, Hansen DJ, Gentile JH, Chapman GA,
Brungs WA. 1985. Guidelines for deriving numerical standards
for the protection of aquatic organisms and their uses. PB85227049. Technical Report. National Technical Information Service, Springfield, VA.
21. Stubblefield WA, Brinkman SF, Davies PH, Garrison TD, Hockett
JR, McIntyre MW. 1997. Effects of water hardness on the toxicity
of manganese to developing brown trout (Salmo trutta). Environ
Toxicol Chem 16:2082–2089.
22. Davies PH, Goettl JP, Sinley JR. 1978. Toxicity of silver to rainbow trout (Salmo gairdneri). Water Res 12:113–117.
23. Chapman GA. 1978. Toxicities of cadmium, copper, and zinc to
four juvenile stages of Chinook salmon and steelhead. Trans Am
Fish Soc 107:841–847.
24. Van Leeuwen CJ, Griffioen PS, Vergouw WHA, Mass-Diepeveen
JL. 1985. Difference in susceptibility of early life stages of rainbow trout (Salmo gairdneri) to environmental pollutants. Aquat
Toxicol 7:59–78.
25. Spehar RL. 1976. Cadmium and zinc toxicity to flagfish, Jordanella floridae. J Fish Res Board Can 33:1939–1945.
26. Beattie JH, Pascoe D. 1978. Cadmium uptake by rainbow trout,
Salmo gairdneri eggs and alevins. J Fish Biol 13:631–637.
27. Davies PH, Brinkman SF. 1999. Federal aid in fish and wildlife
restoration. Job Progress Report F-243R-6. Colorado Division of
Wildlife, Fort Collins, CO, USA.
�
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Piecing
Together
the
Past
Using DNA to resolve the
To learn more about the
Bear Creek greenback
cutthroat trout, watch an
interview with CPW Senior
Aquatic Biologist Doug
Krieger at the following
link: Bit.ly/bcgreenback
Map by Grant Wilcox
heritage of our state fish
By Dr. Kevin Rogers
© Kevin Rogers/CPW
The cutthroat trout in Bear Creek are the only remaining fish that share the genetic fingerprint with
specimens collected in the late 1800s from across the South Platte Basin (approximate collection
locations shown with yellow stars).
28
Colorado Outdoors
�Several years ago, researchers at the University of
Colorado (CU) in Boulder created quite a stir when
they published a paper in the journal Molecular
Ecology suggesting that half of the greenback cutthroat trout populations in the state were actually
Colorado River cutthroat trout, native to the Western Slope. The resulting media coverage focused on how biologists could possibly have
confused Colorado River with greenback cutthroat
trout, but indeed the two were always difficult to
separate. In fact, experienced taxonomists reported
major overlap in visual characteristics between the
two, and even the world’s foremost salmonid expert, Robert Behnke, Ph.D., maintained they could
not clearly be separated. This news received
both national and international media coverage,
in part because the story of the greenback cutthroat
trout was held as one of the shining stars
of the Endangered Species Act (ESA).
AN ELUSIVE
FionaTRAIL
McAliney (front)
The greenback was thought to be extinct
and
Claire
James, eighth
by 1937, but several relict populations were
graders
at St.
discovered
and used
in aColumba
recovery effort
that spanned
three
decades.
The species
School in Durango,
was downlisted
to
“threatened”
work on River Watchstatus
in in
1978, and the Greenback Recovery Team
the Animas
River.
was approaching
the goal
of having the 20
self-sustaining populations necessary to remove the greenback from the ESA list. The
new assertion that most of these populations were not greenback, but rather Colorado River cutthroat trout, dealt a
significant blow to recovery efforts.
The desire to clearly distinguish Colorado’s native cutthroats spawned extensive
genetic testing in the mid-’90s with the
hope of finding molecular markers that
would make the distinction clear. Unable to
identify any, the recovery team had to continue to rely on existing science to guide
management decisions. Ultimately, geographic location was used to assign native
trout to either subspecies.
A clearer picture of native trout taxonomy in Colorado began to emerge when
the team at CU suggested that — in fact —
good molecular markers were apparent, but
they were being masked by a jumbled distribution of the fish.
They proposed that stocking in the early
part of the 20th century was responsible for
the presence of Colorado River cutthroats
in Eastern Slope waters. They also identi-
© Kevin Rogers/cpw
Trappers Lake with the Colorado Parks and Wildlife cabin and the Cabin Creek
weir in the foreground where the bulk of fertilized eggs were produced and sent
to state hatcheries.
September/October 2012
29
�Otto Peterson and crew prepare to strip eggs from a
large female trout on the
Grand Mesa in the early
1900s.
The scale of production of wild trout native to Colorado was
dramatically underappreciated until the U.S. Fish and Wildlife
Service’s Chris Kennedy dug up everything he could about the
production of native trout in Colorado.
In addition to his regular duties as a fish biologist, Kennedy
spent five years scouring the state in search of information
about the stocking of “blackspotted” or “natives” as they used
to be called, by state, federal and private hatcheries in Colorado’s past.
He stitched together a history that includes a minimum
estimate of native cutthroat trout produced in the state and
released back into its waters from 1872-1951. Kennedy
scanned state and federal fish commissioner reports, state archives, records from agencies around the country,
and local newspaper archives to compile a comprehensive cutthroat trout
Outlet weir at Trappers Lake used to collect
stocking database for the
spawning cutthroat trout.
state.
While Colorado Parks
and Wildlife (CPW) has a robust digital stocking database that
covers activities back to 1952, what was produced by the
hatchery system before then was much less clear.
Initial efforts producing cutthroat trout appear to have
started with private residents, around the same time as movement of trout between waters was first documented, in 1873.
Then, two men named Cushman and Barrett collected trout in
Bear Creek and “brought over one hundred live ones, which
were placed in Green Lake… In a few summers our favorite
lake will be stocked to repletion with delicious trout, and they will become as cheap
and common as potatoes.” (Colorado
Miner, July 8, 1873). Actions soon escalated rapidly to include state and federal
efforts to establish trout fishing opportunities for the public good by the late 1880s.
Some of Kennedy’s research results are
startling. He discovered that, in a 12-year
fied an alleged greenback population west
of the Continental Divide.
Also at this time, biologists with Colorado
Parks and Wildlife (CPW) partnered with
Pisces Molecular, in Boulder, to develop another molecular test. It also suggested a genetic basis for differences between
Colorado’s native trout. Major survey efforts
30
© Photo courtesy of betty Kendrick
Chris Kennedy — Fish Sleuth
period from 1914-1925, the state fish commission not only produced at least 26 million trout from Trappers and Marvine lakes,
but stocked them in virtually every county that could support
trout in the state.
While the state busied itself producing eggs in these areas
at the headwaters of the White River, federal fish culturists
were obtaining eggs from several lakes on the Grand Mesa
— through an agreement with a British gentleman who
owned a hatchery and numerous lakes there.
William Radcliffe, who purchased the property in 1896,
took offense when Delta County locals considered it their right
to descend on his lakes each spring to seine and snag — even
dynamite — his spawning runs of cutthroat trout to secure
fish for the year. To curb this behavior, he hired game wardens
to patrol the grounds. A confrontation at Island Lake resulted
in one game warden shooting several locals, killing one of
them. The incensed community sent a lynch mob to Alexander Lake to get even, burning Radcliffe’s buildings to the
ground. Fearing for his life, Radcliffe returned to England, then
received restitution from the U.S. government for his losses.
Though Radcliffe was gone, fish culturists at the new Federal hatchery near Leadville continued to take spawn from
those same lakes. With good records from that operation, they
produced 29 million eggs during an 11-year period from 18991909. Like the state-led operation at Trappers Lake, these fish
were distributed around Colorado in streams that could support them.
These two wild spawn operations alone provide a clear
mechanism for how cutthroat trout strains — native to the
Colorado and Yampa River basins — found their way east of
the Continental Divide. It appears that descendants of these efforts remain up and
down Colorado’s Front Range, persisting in
waters where barriers to migration have
protected them from invasion by non-native brook, brown and rainbow trout.
U.S. Fish and Wildlife Service fisheries biologist Chris Kennedy. © Kevin Rogers/CPW
of cutthroat populations on the Western
Slope also identified many more of these
“greenback” populations using this test.
By 2010, more than 50 populations of
“greenback” were discovered west of the
Divide, casting doubt on the notion that
fish with this genetic fingerprint were actually native to the Eastern Slope.
STOCKING WAS PERVASIVE
Researchers suggested stocking played a
role in the distribution of cutthroat trout
because their DNA indicated populations
on opposite ends of the state were often
more closely related than those in neighboring drainages — a phenomenon not seen in
distributions of other native fish species.
Although biologists recognized that
trout stocking was an integral part of Colorado’s past, it was clear that a more thorough understanding of what actually went
on in the early 1900s was needed.
Enter Chris Kennedy — biologist and fish
genealogist for the U.S. Fish and Wildlife Service (see sidebar). Kennedy’s sleuthing skills
and passion for digging through old archives
revealed valuable findings. Specifically, he
was able to recreate a stocking history that the
records at the time only hinted at.
Indeed, stocking was pervasive.
Although wild spawn operations took
place in a number of waters around Colorado, the primary egg source for the state in
the early years was Trappers Lake, at the
headwaters of the White River.
Biologists began taking eggs from there
in 1903, sending 750,000 to the hatchery in
Steamboat Springs that year. In 1908, they
took a record 10 million eggs out of Trappers and neighboring Marvine Lakes —
even using those eggs to establish a brood
source for native cutthroat trout on the
south slope of Pikes Peak that produced
many more.
They stopped taking eggs from Trappers
Lake after a population crash in 1938 then
started again after World War II, when hybridizing trout species were introduced into
the lake. By then, spawning runs in the
headwaters of the White River had likely
produced more than 80 million fertilized
pure cutthroat trout eggs for hatcheries
around the state.
Federal fish culturists based out of the
Leadville National Fish Hatchery were not
idle during that time either, collecting large
numbers of fertilized eggs from native cutthroat trout on the Grand Mesa. Despite it
being a rather spartan operation, they were
able to produce as many as 7 million fish a
year from that facility. These fish were scattered widely around the state as well.
A LEGACY IS TRACED
The stocking records made it clear that,
to get a firm understanding of the distribution of native cutthroat trout in Colorado,
specimens housed in museums that had
been collected prior to the bulk of stocking
activities needed to be examined.
Colorado Outdoors
�Fortunately, trout have long held the interest of naturalists and, in fact, there are
fairly extensive collections in museums
around the country, collected by notable
individuals like David Starr Jordan, Louis
Agassiz, Ferdinand Hayden and others who
had a hand in exploring the West.
Although some of these specimens are
more than 150 years old and have very
degraded DNA, the CU team was able to
use cutting-edge molecular methods —
both here in Colorado and at the Australian Center for Ancient DNA — to piece
together fragments long enough to classify these specimens into different
groups.
The study proved that genetically distinct
cutthroat trout lineages could be found in
virtually every major drainage basin in
Colorado. Two distinct lineages of Colorado River cutthroat trout were found on
the west side of the Divide — one called the
White and Yampa rivers home, the other
centered around the Grand Mesa. Both lineages are established on both sides of the
Continental Divide today, likely as a result
of long-bygone stocking efforts originating
from eggs taken from Trappers Lake and
the Grand Mesa Lakes.
The study also showed a third lineage
was historically found on the western side
of the Divide, native to the San Juan basin.
Unfortunately, CPW biologists have not
been able to find any descendants of that
lineage in current cutthroat trout populations.
Maps by Grant Wilcox
from the Bulletin of the United States
Bureau of Fisheries, 1908, Volume XXVIII)
Cutthroat trout hatchery on the shores of the Grand Mesa Lakes in June,
1907 (from the Bulletin of the United States Bureau of Fisheries, 1908,
Volume XXVIII)
Historically, native cutthroat trout could be found in streams allocated among eight
major drainage basins (colored areas) in Colorado. The traditional view (left) was that
all five drainages west of the Continental Divide were home to Colorado River cutthroat trout, while greenback cutthroat trout lived in the South Platte and Arkansas
basins, and the headwaters of the Rio Grande contained its own namesake. This
study suggests that outside of the Colorado/Gunnison/Dolores complex, each major
basin supported its own distinct lineage.
September/October 2012
A GIANT GOES MISSING
Museum specimens of the extinct yellowfin cutthroat trout were also easily distinguished by their DNA. It appears that
this regal fish, routinely topping the scales
at more than 10 pounds, did indeed go extinct shortly after it was discovered. Twin
Lakes fish surveys in 1902 and 1903 failed
to find any remaining individuals.
Many hoped that since fertilized eggs
were taken from Twin Lakes, that they may
have become established elsewhere — even
as far away as France. Unfortunately, despite extensive testing, no descendants of
this fish living today have been found.
The museum data challenges the longheld belief that the yellowfin were native to
just Twin Lakes, as early taxonomists had
suggested. Rather, data tells us they could
be found up and down the Arkansas River
basin.
GREENBACKS: AN ACCIDENTAL
PRESERVATION
The most intriguing news from the study
centers on the greenback cutthroat trout —
Colorado’s state fish.
The “type specimens” — those used by E.
D. Cope to describe the subspecies in 1871
— are not greenbacks at all, but rather Rio
Grande cutthroat trout (see Hammond sidebar).
A future president of Stanford University,
David Starr Jordan, was the first to coin the
term “greenback” to describe these fish. It’s
clear in his 1891 writings that he intended
the name to apply to “trout of the Platte”
— thought to have gone extinct in 1937.
While the greenback cutthroat trout appeared to have been rediscovered in 1969
in a few small streams isolated from nonnative trout, only the fish in Bear Creek
share the genetic fingerprint of those collected across the South Platte basin in the
late 1800s, prior to large-scale stocking activities.
Affectionately called “weird” Bear Creek
because the fish look a little odd, with spots
on the belly and large parr marks, even on
adults, the DNA obtained from this population was analyzed in 2002.
Despite showing no evidence of hybridization with rainbow trout or Yellowstone
cutthroat trout, they were not included in
the greenback broodstock or recovery efforts because they just didn’t look quite
right. These descendants of the South Platte
natives are actually found in the Arkansas
basin, above several large waterfalls that
have protected them from invasion by
other trout species.
31
�This stream was likely fishless historically.
But in 1873, J. C. Jones (who homesteaded
160 acres in the headwater area) — in hopes
of establishing a hotel to take advantage of
tourist traffic traveling up Bear Creek to the
summit of Pikes Peak — may have also been
culturing trout. In 1882, a visitor related that
Jones “strode back to the work of digging big
stones out of his fish pond.”
Only two hatcheries were producing natives at that time — one on Trout Creek in the
South Platte basin north of Woodland Park,
and a facility in Colorado Springs, owned by
Col. George De La Vergne, who reportedly
collected his broodstock “in the mountains.”
The closest, most easily accessible wild
trout population to both De La Vergne and
Jones would have been the same Trout Creek.
While the true greenback cutthroat trout may
have indeed gone extinct across its native
range in 1937, these early propagation efforts
seem to have inadvertently preserved the
legacy of our state fish in another drainage.
There I was… floating in my belly boat on South Delaney
Butte Lake, when I got a call from an exasperated Jessica Metcalf. As one of the leaders of the University of Colorado research
effort, she had spent the weekend working on DNA from
greenback cutthroat trout “type”specimens.
Historically significant, these were the specimens gathered
by Army surgeon William Hammond, stationed at Fort Riley,
Kan. In 1856, he sent them to the Academy of Natural Sciences
in Philadelphia. In 1871, Edwin Cope used these same specimens to define what an “O. c. stomias” (greenback cutthroat
trout) was.
Though degraded over time, Metcalf pieced together the
DNA sequence of a mitochondrial gene used to identify the
different cutthroat trout subspecies. Her exasperation? Rather
than greenback cutthroat trout, the genetic fingerprint looked
like that of a Rio Grande cutthroat trout instead.
Given her unexpected results, I set out to find more about
these collections. What I discovered was a fascinating tale of
life in the West, prior to the Civil War, decades before Colorado
became a state.
THE ROAD AHEAD
While this work will certainly make the
U.S. Fish and Wildlife Service reevaluate the
greenback cutthroat trout recovery program
goals and objectives, it is important to recognize that past recovery efforts were not in
vain.
A large part of those efforts involved developing and protecting secure habitats where
cutthroat trout can persist without being invaded by non-native salmonids that displace
or hybridize with them.
Thanks to the work of dozens of dedicated
biologists, there are now many more populations of native cutthroat trout than when the
program started. Their efforts helped secure
the pieces of our cutthroat legacy while classification uncertainties were sorted out. Now,
the job remains to continue protecting and
securing the genetic diversity bestowed on us
for future generations.
© kevin rogers/CPW
Dr. Kevin Rogers is an aquatic research scientist for Colorado Parks and Wildlife, specializing in cutthroat trout.
32
MYSTERIOUS ORIGINS
As a former student of salmonid expert, Robert Behnke, I
remember him regaling us with stories of the mystery surrounding these greenback specimens.
In his writings, he suggests all labels on specimens Hammond collected on the 1856 expedition said “Fort Riley, Kansas.” However, in an 1872 description of greenbacks, the
location was listed as “South Platte River, Kansas,” but the
South Platte does not enter Kansas, nor could trout persist in
any of the warm streams around Fort Riley — even back in
1856.
Behnke surmised they could have been collected on an
expedition to chart a wagon road from Fort Riley to Fort
Bridger. The officer in command, Lt. Francis T. Bryan, supervised the building of roads in the Kansas and Nebraska territories from 1855 to 1858. That expedition would have
encountered the South Platte and could therefore have collected the specimens there and merely shipped them from
Fort Riley in 1856. Yet this explanation falls apart when compared with Hammond’s actual field notes at the Academy of
Natural Sciences in Philadelphia, which are clearly dated 1857,
rather than 1856.
After encountering resistance from Native Americans on
the first expedition in 1856, Lt. Bryan had difficulty recruiting
laborers to go along on the 1857 expedition. It wasn’t until he
guaranteed a military escort and a surgeon would accompany
them that he was able to launch the expedition.
Fortunately for cutthroat trout enthusiasts everywhere,
Hammond was that surgeon. A diligent naturalist, Hammond
took detailed notes of all the specimens of fish, amphibians
and insects he collected along the way — so detailed I was
able to assign map coordinates to each of the specimens. Plotting those points on a map of the Kansas and Nebraska territories revealed that the 1857 journey went out and back from
photo courtesy of the
National Museum of
Health and Medicine, AFIP
Fishing through History
Army surgeon
William Hammond
pictured in 1862
Fort Riley. It is apparent Hammond never made it anywhere
close to the South Platte River. Additionally, his notes suggest
that trout were only collected at one location on the journey
—“in streams on Pacific slope”of the Continental Divide near
Bridger’s Pass“706 miles west of Fort Riley,”which would have
been Colorado River cutthroat trout.
RIO GRANDE CONNECTION
A more likely explanation is alluded to in letters Hammond
wrote to several esteemed scientists at the academy in Philadelphia. On June 18, 1855, he wrote to Joseph Leidy, “I expect
to leave in a few weeks for the plains, having been designated
to accompany a topographical party who are ordered to survey
a route from this post [Fort Riley] to Santa Fe, New Mexico. I
will be absent about two months.”
A year later he followed that letter with another to a beetle
aficionado named John LeConte. On Aug. 24, 1856, Hammond
wrote “I sent a large box of specimens in Natural History a
month since to the Academy. Has it been received yet?”
Perhaps, these samples showed up in Philadelphia in the
fall of 1856 and were then simply labeled as Fort Riley, 1856.
The most compelling evidence for this explanation comes
from museum data. The closest present-day genetic match to
Hammond’s greenback cutthroat trout specimens come from
the Rio Mora, just outside of Santa Fe.
Though not discussed in his more recent writings, Behnke
suspected the type specimens could indeed be Rio Grande
cutthroat trout. In a letter to the curator at the academy, dated
Jan. 20, 1967, he mentions the specimens had fewer scales
than expected“for the native greenback cutthroat trout of the
South Platte.”This led him to believe these were not the specimens collected by Hammond, or, if they were, they did not
come from the South Platte.
Further curiosities were noted by one of Behnke’s masterdegree students who suggested “some populations of Pecos
cutthroat trout exhibited a striking similarity to greenback cutthroat trout in their spotting pattern.”
Metcalf’s work seems to have vindicated Behnke’s questions regarding the type specimens, and illustrates another
reason why it was so difficult to visually separate greenback
cutthroat trout from Colorado’s other native cutthroat trout
subspecies.
More specific details from Hammond’s collections and
transcriptions of letters to others at the Academy of Natural
Sciences at Philadelphia can be found at http://wildlife.state.
co.us/research/aquatic/CutthroatTrout
This image: Locations of specimens collected by William Hammond on his 1857 expedition to Fort Bridger from Fort
Riley with current state boundaries in gray. At left: Leaders of the CU research effort, Dr. Jessica Metcalf and Dr. Andrew
Martin prepare samples in the lab.
Colorado Outdoors
�
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919713f81a51821cc07d1d9e398a7e19
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Text
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THOMPSON, G. E., AND R. W. DAVIES. 1976. Observations on the age, growth,
reproduction, and feeding of mountain whitefish (Prosopium williamsoni) in the
Sheep River, Alberta. Transactions of the American Fisheries Society 105:208219.
WHITELEY, A. R., P. SPRUELL, AND F. W. ALLENDORF. 2006. Can common species
provide valuable information for conservation? Molecular Ecology 15:27672786.
WYDOSKI, R. S. 2001. Life history and fecundity of mountain whitefish from Utah
streams. Transactions of the American Fisheries Society 130: 692-698.
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Whitewater Park Projects
Guidance for Reviewing 404 Projects
COLORADO PARKS & WILDLIFE • 6060 Broadway, Denver, CO 80216 • (303) 291-7227 • www.wildlife.state.co.us
�COLORADO PARKS AND WILDLIFE
Dan Prenzlow, Director
DIRECTOR’S STAFF
Reid DeWalt, Assistant Director for Aquatics, Terrestrial and Natural Resources; Heather
Dugan, Assistant Director for Field Services; Justin Rutter, Assistant Director for Financial
Services; Lauren Truitt, Assistant Director for Information and Education; Jeff Ver Steeg,
Assistant Director for Research, Policy, and Planning
REGIONAL MANAGERS
Brett Ackerman, Southeast Region Manager; Cory Chick, Southwest Region Manager; Mark
Leslie, Northeast Region Manager; JT Romatzke, Northwest Region Manager
STUDY FUNDED BY
Colorado Parks and Wildlife
SUGGESTED CITATION
Kondratieff, M. C., K. R. Bakich, E. E. Richer, D. A. Kowalski, and B. F. Atkinson. 2020.
Whitewater Park Projects: Guidance for Reviewing 404 Projects. Colorado Parks and
Wildlife Aquatic Research Section, Fort Collins, CO. 26 pp.
�Introduction
Colorado Parks and Wildlife’s (CPW) statutory mission is to perpetuate the wildlife resources
of the State, to provide a quality State Parks system, and to provide enjoyable and
sustainable outdoor recreation opportunities that educate and inspire current and future
generations to serve as strategic stewards of Colorado’s natural resources (C.R.S. § 33-9-101
(12) (b)). As CPW is responsible for the management and conservation of aquatic resources
within the State, we are asked to review projects that may affect aquatic habitats or
populations. Specifically, CPW staff is often engaged by the Army Corps of Engineers (USACE)
to review permit applications related to the design, construction, and monitoring of
whitewater parks (WWPs) regulated under Section 404 of the Clean Water Act. WWP projects
typically fall under the following permits:
NWP 27 - Aquatic Habitat Restoration, Establishment, and Enhancement Activities
IP - An individual, or standard permit, is issued when projects have more than minimal
individual or cumulative impacts, are evaluated using additional environmental
criteria, and involve a more comprehensive public interest review.
Recreational in-channel WWPs (Figure 1) are gaining popularity throughout the United States
with Colorado being the epicenter for WWP development. Although WWPs provide economic
and recreational benefits for local communities (Hagenstad et al. 2000; Loomis and McTernan
2011), they can have unintended impacts on aquatic biota, habitat, and river functions. This
is especially true when the hydraulic conditions formed by the WWP differ substantially from
those naturally found in the surrounding river. Natural unmodified river channels are not good
candidates for locating WWPs (American Whitewater 2007). Rather, WWP projects should be
located in areas that have already been substantially modified by past human activities.
A
B
Figure 1. Two typical whitewater park structures include chute-type (A) and drop-type
structures (B)
CPW recommends that adequate environmental safeguards be included in the design and
construction of WWPs to assure that impacts to river functions (Harman et al. 2012),
fisheries, and recreational angling opportunities are minimized. The intent of this document
is to provide USACE with uniform guidance from CPW with regard to project review to assure
that the least environmentally damaging practicable alternative (LEDPA) is followed when
WWPs are proposed, designed, constructed, and maintained over time. CPW offers the
following guidelines to maximize the benefits of recreational WWP opportunities while
1
�minimizing adverse impacts to fisheries and river functions. These are general
recommendations and each project should be reviewed on a case-by-case basis prior to
issuing permits. Failure to demonstrate that the following guidelines were implemented with
due diligence will result in categorical opposition to the project from CPW.
General Recommendations
WWPs are constructed in a wide variety of stream locations utilizing a diverse array of design
elements that are unique to the particular design firm and project engineer, project goals
and expectations, and river conditions. General recommendations for all WWP projects should
include:
1) Early Consultation with CPW: Contact the local CPW Area Aquatic Biologist as early as
possible in the design process to obtain information regarding the species presence, fish
populations, and fisheries management objectives for a proposed project site. CPW
conducts hundreds of fish population surveys on streams and rivers throughout Colorado
annually and uses survey results to inform fisheries population management. Instructions
for submitting formal requests for CPW fisheries data are available at the CPW Aquatics
Data Management webpage. A map of CPW management areas with contact information
for Aquatic Biologists is included in Appendix A and available at the CPW Aquatic
Management webpage.
2) Monitoring and Adaptive Management: Monitoring efforts may focus on physical aspects of
habitat, biological aspects of fish populations, or a combination of both. Monitoring
efforts should be tailored specifically with the goal of detecting undesired or unintended
impacts to the aquatic environment or community. CPW recommends a minimum
monitoring period that includes two years of baseline and five years following project
construction. Data collection should focus on documenting baseline conditions, as-built
conditions, and project effectiveness with at least two monitoring events occurring during
the five year post-construction monitoring period. Adaptive Management provides a
framework that incorporates measurable, relevant monitoring criteria and predetermined
thresholds for acceptable change to assess and address undesired or unintended impacts
to the aquatic environment and communities (Bouwes et al. 2016). Every WWP design
package should include a detailed Adaptive Management Plan (AMP). An AMP should
identify quantifiable monitoring criteria and anticipated impacts to the aquatic
environment that incorporates review and input from CPW and other management
agencies to the USACE. A robust AMP will include a remediation strategy that identifies
stakeholders, resolution processes, and funding sources to engage if project objectives are
not met and thresholds are exceeded.
3) Thresholds for Mitigation Actions: As part of the permitting process prior to issuing permits
and project implementation, regulators should work with CPW to establish the level of
allowable impairment to the natural resource and develop objective thresholds to trigger
mitigation actions, such as requiring structural modifications or off-site mitigation.
Objective and measurable thresholds for changes to river condition and function will
provide enforceable triggers for mitigation or remediation actions.
4) Cumulative Impacts: The potential for cumulative impacts exist when a WWP has two or
more structures. Projects consisting of multiple structures should be reviewed as having
the potential for cumulative impacts. Cumulative impacts should be viewed as more
serious than impacts from a single structure. WWPs have the potential to cause
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�cumulative impacts to fish passage, fish habitat or both within a single project location or
when a project is located in proximity to other existing manmade river structures (e.g.,
diversion structures, dams, etc.). Some examples of cumulative impacts from WWP
development include: degradation of State-identified high priority habitats and creation
of fish movement obstacles or barriers that limit access by fish to critical forage, refugia,
or reproductive habitats.
Popular whitewater park recreation activities on a Colorado stream.
A CPW fact sheet that provides an overview of WWP research, impacts on fisheries, and
design guidelines has been included as Appendix B.
Fish Passage
WWP structures have the potential to negatively affect fish by fragmenting populations,
reducing migratory ranges, and limiting access to habitat for spawning, feeding, and refuge
(Schlosser and Angermeir 1995). Aquatic habitat fragmentation is ubiquitous throughout
Colorado, contributing to the decline of native aquatic species diversity and abundance (CPW
2015). The elements that create and maintain a desirable play wave (hydraulic jump,
increased velocity, decreased depth, steep-sloping long chutes, abrupt vertical drops, and
grouted smooth stream channel) can create hydraulic conditions that can impede or prevent
upstream fish passage. Suppression of upstream fish movement has been documented at WWP
structures, but the degree of impact varies by fish species, fish size, depths, velocities,
characteristics of individual structures, and variability in flow conditions (Stephens et al.
2015; Fox et al. 2016; Richer et al. 2018). As trout are among the strongest swimming and
jumping species found in Colorado, small-bodied and weaker-swimming fish native to
Colorado streams are even more susceptible to suppression of upstream movement at WWP
structures. Migratory populations of native Colorado suckers, minnows, and trout are also
adversely affected by habitat fragmentation, with some individuals moving long distances (25
or more miles) during upstream migrations to access spawning habitat (Kondratieff et al.
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�2017; Thompson et al. 2019). To minimize loss of fish passage functions, CPW recommends
the following guidelines be incorporated into the design of WWP projects:
1) Target Species and Life Stages: Design WWP structures to allow upstream fish passage for
all species present at the project site, unless there are specific management objectives
that warrant exclusion of particular fish species. Fish passage elements are expected to
pass juvenile and adult life stages (Forty et al. 2016).
2) Design Flows: Fish passage design elements of WWP structures should be designed to
provide passage across a range of typical flows, including flows corresponding with the
timing of critical life history movement events such as spawning migrations or access to
refugia. The average daily discharge that is exceeded 95% and 5% of the time should be
selected for the low and high fishway design flows, respectively (NMFS 2008).
3) Fishway Invert Elevations: Fishways are engineered pathways specifically designed to
accommodate fish movement around or through WWP structures. Fishways should provide
passable conditions over a range of flow conditions. Fish passage design elements should
be constructed so that the upstream invert of the fishway exit is located at a lower
elevation than the upstream invert of the WWP recreation structure crest to ensure that
the fishway functions during extreme drought or low flow conditions.
4) Instream Flows: Fishways should have sufficient capacity for carrying either: 1) the
decreed instream flow (if a Colorado Water Conservation Board (CWCB) instream flow
water right exists for the stream or river in question), or 2) where no decreed instream
flow exists, a minimum flow volume that is reasonably necessary for maintaining fish
passage in the stream or river in question.
5) Attraction Flows: Sufficient attraction flows at the downstream fishway entrance is a
critical factor that will affect efficiency of the fish passage structure. The hydraulic
conditions (i.e., velocity, depth, and turbulence), quantity, and location of attraction
flows are all important design considerations. In general, increasing the amount of
attraction flow relative to the total river flow will increase the effectiveness of the
fishway for providing upstream passage. The minimum attraction flow necessary to
provide adequate attraction conditions for fish is 5-10% of the total river flow (NMFS
2008).
6) Passage Criteria: WWP designs should provide comparisons of hydraulic conditions within
the fishway to species-specific design criteria for identifying limiting swimming speeds,
water depths, and vertical drops that ultimately provide evidence for the effectiveness of
fish passage conditions. Hydraulic modeling results should include depths, velocities, and
locations of hydraulic jumps for existing and proposed conditions so that fish passage
hydraulic conditions can be evaluated before the project is implemented. Fish passage
criteria including the swimming speeds and jumping heights for Colorado fishes are
included in a CPW fact sheet on Fish Passage at River Structures (Appendix C).
7) Incorporation of Natural Channel Forms and Processes: Fish passage design elements
should function to enhance, maintain or mimic the pre-existing natural stream conditions
(gradient, depth, velocity, and channel roughness) found at the proposed site of each
recreational drop structure. This is especially important when there is a lack of speciesspecific swim passage criteria.
8) Monitoring Fish Passage: Various methods have been used to evaluate fish passage at
instream obstacles or barriers. Fish passage efficiency through WWPs has been monitored
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�using hydraulic modeling by 3-dimensional hydraulic models (Stephens et al. 2016), 2dimensional hydraulic modeling (Hardee 2017), and a least-cost path approach combining
known swim speeds and 2-dimensional hydraulic modeling (Brubaker et al. 2018). Fishway
evaluations can also be conducted by marking individual fish and monitoring their
movements over time (i.e., PIT tag or Mark-Recapture studies; Fox et al. 2016). A
combination of hydraulic modeling and validation studies using marked fish provide the
strongest support for monitoring fishways by utilizing multiple lines of evidence. Ideally
fish passage evaluations collect fish passage data from a) the pre- project reach, b) a
nearby control site (up or downstream of the project reach) that is representative of a
natural condition, c) the post-project reach, or d) a combination of some (Before/After or
Control/Impact) or all sites (i.e., a full BACI study design). Project objectives should be
measureable and monitoring of pre- and post-project conditions should be used to
evaluate project effectiveness and inform adaptive management. CPW recommends a
minimum monitoring period of one year of baseline and three years following WWP
project construction, with an emphasis on documenting baseline conditions, as-built
conditions, and project effectiveness with at least two monitoring events during the postconstruction three-year period.
9) Adaptive Management: AMPs should evaluate proposed and post-project changes to
hydraulics and topographic conditions including water depth, velocities, hydraulic jumps,
and bed drops at each constructed WWP feature over the range of design flows. These
criteria should be used to evaluate project objectives and thresholds for requiring
mitigation actions. AMPs should be included as part of the design package for each WWP
project.
Whitewater park structure with engineered fish bypass
Fish Habitat
WWP structures and their placement within a stream channel have the potential to degrade
aquatic habitat quality. Many factors influence aquatic habitat quality and should be
5
�incorporated into WWP designs. The placement of WWPs in channels should follow published
geomorphic criteria for physical relationships related to channel width, pool spacing, and
riffle lengths to minimize the potential for channel instability and habitat impairment
(Leopold et al. 1964, Dunne and Leopold 1978). The valley type, process domain, stream
gradient, stream hydrology, and substrate characteristics should be used to inform WWP
designs and the placement of structures within the proposed reach. Fish behavioral traits, life
history characteristics, physiological tolerances, and swimming and jumping capabilities are
directly related to the physical habitat characteristics found in the natural channels which
they occupy. Low gradient stream channels in unconfined valleys or plains are typically
occupied by fish species that are incapable of jumping over vertical obstacles and have
resident fish with weaker swimming capabilities. High gradient mountain streams are typically
occupied by fish species that are capable of jumping and have swimming capabilities that
enable them to burst through high velocities and turbulence. Some weaker swimming, smallbodied fishes have behavioral traits that cause them to avoid swimming over deep pools
where they are vulnerable to predation. Instead, they utilize the lateral edges of stream
channels (Swarr 2018). Research has shown that impacts of WWPs on rivers and fisheries is
very specific and will depend on the specific conditions at a river site as well as the fish
populations present (Kowalski 2019). Ultimately, design and construction of WWP structures
should provide for fish and aquatic invertebrate habitat; such structures must take account of
the preservation of functional riverine and aquatic processes and maintain the natural
aesthetic qualities of the river to the greatest extent possible. CPW recommends the
following guidelines be incorporated into the design of WWP projects:
1) Minimize Extreme Hydraulic Conditions in WWP Pools: Natural pools located in unconfined
valleys with low channel bed slopes are characterized by predictable and relatively stable
hydraulic conditions that provide a balance between feeding and resting for fish. Fish feed
on aquatic prey drifting into pools from upstream riffles and find low velocity resting
areas close to the bed within pools that minimize energetic demands for fish swimming
and maintaining equilibrium. Although WWPs create deep pools, observed fish densities
and biomass were higher in natural pools than in WWP pools for trout and native fish
(Kolden et al. 2015). A combination of hydraulic modeling and direct field measurement
of hydraulic conditions present in WWP pools found higher turbulence (6×), vorticity (2×),
velocity (3×), surging (40×), and depth (2×) were observed in WWP pools as compared to
natural pools. Habitat suitability scores incorporating depths and velocities for Rainbow
Trout (Oncorhynchus mykiss) and Brown Trout (Salmo trutta) were higher for pools
located in WWP reaches than natural pools. However, fish abundance estimates (biomass
and densities) for WWPs were lower, providing evidence that the use of habitat suitability
scoring to quantify habitat conditions for pools located in WWPs may be inappropriate.
Direct measurements of fish abundance (biomass and densities) are preferred over habitat
suitability modeling for evaluating WWP pool quality until more research can be done to
incorporate additional information to improve model performance. Lower fish abundance
may be explained by conversion of food producing riffles to impervious grouted drops over
WWP structures, increased hydraulic variability (turbulence, vorticity, velocity, and
surging) characteristic of WWP pools, or a combination of these factors. Based on results
from Kolden et al. (2015), habitat suitability scoring through use of hydraulic models for
pools may not be as reliable an indicator of overall habitat quality as direct estimation of
fish abundance. Additional studies in Colorado have indicated that impacts to fish
populations are site-specific and can be subtle (Kowalski 2019). If structures are designed
and spaced properly, impacts to fish populations can be reduced. In some rivers, WWP
structures have been shown to increase habitat suitability and density of non-native and
6
�non-game fish species like White Sucker (Catostomus commersonii) and Longnose Sucker
(Catostomus catostomus) while large scale impacts to trout populations can be minimized.
2) Design Pool-to-Pool Spacing to Match Expected Ranges from Geomorphic Relations: Pool to
pool spacing within WWPs are often outside the range of natural variability found in
natural channels of the same valley and stream type (Leopold et al. 1964, Dunne and
Leopold 1978). Most often, pools in WWPs are more closely spaced than what would be
found in natural stream reaches of the same geomorphic context. This can result in
increased channel instability from accelerated erosion or deposition with pools filling with
sediment and the need for frequent maintenance and removal of sediments from WWP
pools. Pool spacing also can have an impact on aquatic invertebrate populations.
Improperly designed and spaced WWP structures can remove natural riffles from river
reaches and reduce the diversity of aquatic invertebrates (Kowalski 2019). Designing river
channel features that are in balance with the stream flow and sediment supply of each
specific site is important in preserving natural hydraulic and biological functions of riffles.
3) Preservation of Riffle Habitats: WWP structures are commonly constructed using concrete
grout, pre-cast concrete blocks, and large boulders used to direct flow and manipulate
hydraulics. The materials used for WWP structures either fill-in or replace interstitial
spaces normally found in coarse riffle habitat where macroinvertebrates reside, juvenile
trout find refuge, and native fish such as Mottled Sculpin (Cottus bairdii), dace, and
suckers live out most of their life cycles. Large, grouted WWP structures have been shown
to support less diverse aquatic invertebrate communities then natural riffles (Kowalski
2019). WWP designs should preserve some riffles within the project reach instead of
converting all riffles to WWP drops. Individual WWP structures require a drop in elevation
to function optimally and thus WWP drop structures often replace natural riffle features.
As a consequence, WWP reaches typically have proportionally less riffle habitat as
compared to adjacent natural stream reaches within the same valley and stream type. A
reduction in overall riffle habitat (area) could result in less macroinvertebrate habitat and
consequently less food for fishes residing in WWP reaches. Research has shown that in
some rivers in Colorado, improperly spaced structures degrade riffle habitat and reduce
the diversity of aquatic invertebrates while properly designed structures that include
riffle habitat can be as diverse and productive as natural riffles (Kowalski 2019). Riffle
habitat converted to impervious, grouted structures may result in a loss of interstitial
habitat critical for providing habitat for macroinvertebrates, native benthic fishes like
sculpin and dace, and juvenile rearing habitat for trout.
4) Monitoring Fish Habitat: A variety of methods have been used to evaluate fish habitat at
WWPs including 2-dimensional and 3-dimensional hydraulic modeling of the natural
(control) and project reach incorporating habitat suitability criteria (Kolden et al. 2015).
Fish habitat conditions can also be evaluated by directly surveying fish populations (fish
density and biomass) before and after project construction and/or within and outside of
the constructed WWP reach. Ideally fish habitat evaluations collect data from a) the preproject reach, b) a nearby control site (up or downstream of the project reach) that is
representative of a natural condition, c) the post-project reach, or d) a combination of
some (Before/After or Control/Impact) or all sites (i.e., a full BACI study design). Project
objectives should be measureable and monitoring of pre- and post-project conditions
should be used to evaluate project effectiveness and inform adaptive management. CPW
recommends a minimum monitoring period of two years for baseline and five years
following construction, with an emphasis on documenting baseline conditions, as-built
7
�conditions, and project effectiveness with at least two monitoring events during the postconstruction five-year period.
5) Adaptive Management: AMPs should evaluate proposed and post-project changes to the
river environment including pool-to-pool spacing, hydraulic variability (turbulence,
vorticity, velocity, and surging), changes to the proportion of riffle habitat, changes in
fish population or habitat suitability, and riparian area. These criteria can be used to
inform and develop project objectives and thresholds.
Sediment Deposition
The placement of WWPs in river channels should follow established geomorphic criteria
(Leopold et al. 1964; Dunne and Leopold 1978) for physical relationships of channel width,
pool spacing, and riffle lengths to minimize the potential for channel instability, habitat
impairment, as well as decrease the frequency of structure maintenance and in-channel
disturbance. Sediment characteristics and related processes will vary by valley type, process
domain, stream gradient, and stream hydrology. These factors should be incorporated WWP
designs and inform the placement of structures within the proposed reach.
1) Minimize Sediment Deposition: WWP structures should not disrupt or curtail sediment
transport by inducing sediment deposition upstream or downstream of the structure.
Sediment deposition can eliminate preferred fish and benthic macroinvertebrate habitats,
as well as create favorable conditions (finer substrate) for the spread of whirling disease
in trout. Sediment deposition could also result in reduced channel capacity which could
increase flooding risk to surrounding areas. Sediment deposition will likely be inevitable at
WWP due to the loss of energy over the structure, so maintenance plans to periodically
remove excess sediment are needed.
2) Avoid Rapid Contraction and Expansion in WWP designs: WWPs can create a sequence of
rapidly contracting and expanding riverbank conditions that lead to problems of
sedimentation in pools and a need for more frequent maintenance to remove the excess
sediment. WWP designs should incorporate knowledge of channel maintenance flows
(bankfull conditions) and the potential for contraction/expansion to induce sediment
deposition within WWP reaches.
3) Adaptive Management: AMPs should evaluate proposed, pre-, and post-project changes to
the river environment in the longitudinal profile and representative cross sections
including changes to streambed substrate characteristics. Monitoring should document
areas of sediment deposition, fine sediment deposition areas, and bank erosion. Projects
should consider seeking Colorado 401 Water Quality Certification from the Colorado Water
Quality Control Division and conduct pebble counts at critical cross sections before and
during the post-project monitoring period. Pre-project monitoring data should be used to
inform project objectives and establish thresholds.
8
�Sediment deposition in whitewater park pools
Site Selection
Properly locating WWPs within river systems is one of the best ways of minimizing physical,
ecological, and social impacts to rivers and streams including channel stability, sediment
deposition, fish passage, fish habitat, and recreational angling. Site locations that have been
identified as existing barriers to fish movement (e.g. diversion structures or dams) and that
been heavily modified by past human activities are preferred locations for WWPs.
1) Step-Wise Hierarchical Decision Making Framework for Site Selection: CPW proposes the
following steps be carried out in a step-wise fashion according to the following
hierarchical framework to ensure that the LEDPA is selected during the site selection and
design process. The level of risk with respect to impairment of fish passage and habitat
increases with each successive step. Therefore, more intensive monitoring evaluations
should be commensurate with increasing levels of risk. WWP designs must provide
justification for the following:
a. High Priority Habitat and Special Management Reaches: WWP projects proposed in the
following designated river reaches will result in categorical opposition from CPW
including the following: 1) Designated Cutthroat Trout Waters, 2) Critical Habitat for
Threatened and Endangered Species as well as reaches identified as sensitive habitat
for State Species of Concern, and 3) Gold Medal Waters.
b. Geomorphic Setting: Provide justification for a WWP design alternative that is located
in an unconfined valley setting (unconfined valleys have an Entrenchment Ratio (ER)
>2.2) and stream channel slopes that are 2 % or less. Geomorphic settings consisting of
artificially or naturally confined valleys and Rosgen A, B (step-pool), F, and G stream
types have hydraulic characteristics more similar to those produced by WWP structures
and therefore contain fish species and assemblages that are adapted to living in similar
hydraulic conditions as those commonly associated with WWPs.
c. Partially Channel-Spanning Structure: If a site location cannot be identified within the
appropriate geomorphic setting, provide justification for a WWP design alternative
9
�that requires full channel-spanning structures. Partially channel-spanning structure
designs should be used unless project goals or site constraints dictate that a fully
channel-spanning structure is required.
d. Natural Channel Split: If a partial channel-spanning structure is not possible, provide
justification for a WWP site location on a single-thread channel site. Channel splits can
serve dual functions with one split providing WWP recreation while the other channel
split is left as natural and unmodified. A split branch of an existing channel (side
channel or one side of an existing island) should be used unless project goals or site
constraints dictate that a single-thread channel site is required.
e. Artificial Channel Split: If a suitable site location cannot be found on a natural split
branch of an existing channel, provide justification for a WWP site location on an
artificially-constructed split branch channel (constructed side channel or one side of
an artificially-constructed island). Artificial channel splits can serve dual functions
with one split providing WWP recreation while the other channel split is designed to
mimic natural, reference-like conditions. An artificially-constructed split flow channel
(constructed side channel or one side of an artificially-constructed island) should be
used unless project goals or site constraints dictate that a single-thread channel site is
required.
f. Technical Fishway: If the site location is constrained such that an artificiallyconstructed split flow channel is not possible, technical fishway concepts (such as a
constructed bypass channels or riffles, rock ramps, or vertical slots) must be
incorporated into WWP structure designs.
g. No Fish Passage Elements: WWP designs that do not incorporate fish passage elements
into structures are not acceptable and will result in categorical opposition from CPW.
2) Minimize WWP Recreation Conflicts with Anglers and Non-Whitewater Recreation Boaters:
WWP sites should be located to avoid recreational conflicts with anglers and nonwhitewater recreational boaters (i.e., drift boats and canoes). Hydraulic conditions
formed by WWP structures can impede safe boat travel for non-whitewater recreational
boaters. Within WWPs there is an increased potential for whitewater recreational boaters
to displace stream anglers, especially during the summer months. Incompatibilities
between stream anglers and recreational boaters exist. Creel survey data from Colorado
and Wyoming suggest that stream anglers prefer to fish in locations that are uncrowded,
provide pleasant conditions close to nature, and are relaxing. The conditions commonly
encountered at and in the vicinity of WWPs include artificially armored and terraced
banks with minimal vegetation and encourage spectating crowds.
3) Mitigation for Lost Angler Opportunity and Access: Mitigation should be considered to
replace lost angler access, infrastructure, and fishing opportunity. There is a history of
new WWP construction within or replacing existing Fishing Is Fun (FIF) habitat projects
funded through Federal sportfish dollars at sites in Colorado including Pagosa Springs,
Basalt, Ridgway, and Montrose. When new WWPs are proposed within heavily used urban
fishing areas, intensively managed fisheries (those with special harvest restriction
regulations), Gold Medal designated fisheries, FIF-funded habitat projects, or locations
with existing amenities (such as parking access, trails, boat launches, picnic areas, etc...)
funded by Federal sportfish dollars or other fishing interest groups (i.e., Trout Unlimited),
10
�reasonable mitigation is necessary. Mitigation may consist of replacing lost or degraded
infrastructure and amenities, increasing infrastructure to accommodate the new users,
and providing reasonable additional access points or developing alternative locations for
anglers nearby.
4) Off-Site Mitigation: Mitigation locations for offsetting loss of fish habitat from WWP
development should not occur within WWP project reaches, but should occur in separate
locations up- or downstream within the same river watershed if possible. Mitigation
possibilities include developing new areas open to fishing access or enhancing fish habitat
in an area that is not heavily impacted by recreational boating. Fish passage cannot be
mitigated off-site and must be accommodated through a WWP project.
Whitewater Park Project Applications
CPW will only provide technical design review for projects that submit complete applications.
Requests for design reviews must include complete permit applications with all pertinent
information, including project goals and objectives, a design report and plan set, assessment
of existing conditions, list of river stakeholders, revegetation plan, monitoring plans, and a
description of how the project will be maintained over time.
1) Early Consultation with CPW: Contact the local CPW Area Aquatic Biologist as early as
possible in the design process to obtain information regarding the species presence, fish
populations and fisheries management objectives for a proposed project site. CPW
conducts hundreds of fish population surveys on streams and rivers throughout Colorado
annually and uses survey results to inform fisheries population management. Instructions
for submitting formal data requests are available at the CPW Aquatics Data Management
webpage and contact information for CPW Aquatic Biologists is included in Appendix A.
2) Project Goals and Objectives: Applications must clearly identify project goals and
objectives, and describe the context and analysis leading up to the established LEDPA (if
already developed). The applicant should address the potential for fishery and ecological
impacts from the project and how they relate to the project goals and objectives.
3) Design Report and Plan Set: The design report should include a comparison of WWP project
alternatives that were used to inform the selection of the proposed WWP design. The
design report and plan set should clearly detail existing conditions of the proposed WWP
reach, description and layout of the proposed WWP reach, detailed description of fish
passage design elements proposed for each structure, description of existing hydrology and
design flows as they relate to fish passage design elements, and modeled hydraulic
conditions through each WWP structure and fish passage design elements.
4) Assessment of Existing Conditions: An assessment of existing conditions within the
proposed project reach should be conducted in order to determine the level of
anthropogenic impacts at the proposed site. What is the level of departure from a
reference or historic condition with respect to existing hydrology, hydraulics (floodplain
connectivity), geomorphology (sediment supply), physicochemical, and biological
condition? Consider application of the Colorado Stream Quantification Tool (SQT) (CSQT SC
2019) as a means to assign proposed project reach as Functioning, Not Functioning, or
Functioning at Risk. CPW advocates installation of WWPs in reaches that rate as Not
Functioning or Functioning at Risk to minimize impacts to “natural, unmodified” river
11
�channels. Ultimately, is the proposed site located in a natural or already significantly
modified site?
5) Other River Users and Stakeholders: A complete list of river user groups (stakeholders)
should be provided with the project application materials, or at least made aware of the
proposed WWP project.
6) CPW Consultation and Supervision: Early consultation with CPW area staff including a
description of the longitudinal extent of the project, whether or not water rights are a
part of the project (i.e., RCID), and a complete list of project goals. WWPs almost always
involve significant instream structures; both CPW and the CWCB believe that these
structures should be designed and their construction supervised by a Colorado registered
professional engineer and/or a professional hydrologist in consultation with both agencies.
7) Grout: Minimize the use of grout for construction of WWP structures except as needed to
maintain recreation function, human safety, and fish passage elements associated with
the WWP and as part of the criteria for selecting the LEDPA. If grout is used, recess the
grout elevation so it is not flush with the top of the structure elements, leaving spaces
between boulders or blocks for increased roughness and cover for small aquatic organisms.
Recessing grout and spacing boulders to create continuous pathways in the wing walls may
improve conditions for upstream fish passage at WWP structures.
8) Revegetation Plans: Riparian vegetation composed of native species is the primary control
for bank stability in many stream types and should be used to improve long-term stability
of the project. Revegetation plans should be included with the plan set for the project,
including success criteria, planting protocols, irrigation needs, weed control, and postconstruction stewardship. Designs should utilize biostabilization techniques to stabilize
disturbed streambanks as outlined in Living Streambanks: a Manual for Bioengineering
Treatments for Colorado Streams (Giordanengo et al. 2016).
9) Grade Control other than WWP Structures: If grade control is needed for proper function
of the WWP structure, hardened riffles comprised of boulder sills buried in native
substrate is suggested as an alternative to in-channel grout. Hardened riffles can also be
used to protect downstream riffle heads. All proposed structures (recreational or
otherwise) within a project that are necessary to the successful function of the proposed
WWP project are expected to meet LEDPA criteria in the project reach. We expect USACE
to consider all structures associated with a WWP project to be regulated as part of the
project and not subject to exemption.
10) RICDs: Recreational In-channel Diversion (RICD) water rights can be acquired for WWPs in
Colorado to provide recreational experiences in and on the water. RICDs should be
designed, constructed, and managed to minimize or avoid impacts to native and sport
fish. Flows deviating from the natural flow regime, such as water calls during spawning
periods or when young-of-the-year fish are emerging from spawning gravels, could have
adverse impacts on stream ecology (Poff et al. 1997). Meeting with CPW should be
conducted prior to applying for a water right tied to a specified location in the river
system (i.e., RICD). RICD proponents are strongly encouraged to contact USACE to
conducting a feasibility assessment for WWP development at a specific site location prior
to pursuing a water right. Federal regulations do not account for or prioritize permitting
of RICD water rights. This will improve efficiency of State resources and time for a project
12
�that is not federally permittable due to either location or design that does not meet
LEDPA criteria.
11) Post-Construction Site Visit: Require a post-construction site visit prior to rewatering of
structures when possible to verify as-built design and include CPW to identify any aquatic
resource concerns prior to rewatering.
12) Monitoring and Evaluation: Develop monitoring objectives that are measureable and use
objective monitoring criteria for pre- and post-project conditions to evaluate project
effectiveness and inform adaptive management. Comparisons between the proposed and
as-built conditions should be made to define allowable impacts and without exceeding
thresholds for requiring mitigation action.
13) Maintenance and Stewardship: WWP design plans should address structure maintenance,
sedimentation, and debris removal as part of stewardship considerations for at least five
years following project completion.
Whitewater park kayakers on a popular Colorado mountain river
Best Management Practices
1) Spawning Periods: Construction activities that cause streambed disturbance should not be
scheduled during periods when adult spawning migrations, egg incubation, or fry swim-up
are occurring. Fish eggs and fry may die if construction activities mobilize fine sediment
that smothers the streambed in which they reside. Repetitive and cumulative streambed
disturbances during critical reproductive periods can significantly affect population
dynamics and resiliency of local fisheries. In general, instream construction should be
13
�targeted for the months of August and September when flows are lower and impacts to
spawning fish and incubating eggs are less likely. Early communication with CPW is
encouraged as this suggested window could vary based on local considerations such as
elevation, environmental variability, and fish species present.
2) Invasive and Nuisance Species: To prevent the spread of invasive and/or nuisance species
(e.g., Asian Clam, Green River Mud Snail, New Zealand Mud Snail), we strongly encourage
that heavy equipment be cleaned prior to and after construction if the equipment was
previously used in another stream, river, lake, pond, or wetland within ten days of
initiating work. The following methods are recommended for preventing the spread of
invasive aquatic organisms:
a. Disinfection with QAC: Remove all mud and debris from equipment (tracks, turrets,
buckets, drags, teeth, etc…) and spray/soak equipment with a disinfection solution
containing quaternary ammonia compound (QAC). Treated equipment must be kept
moist for at least 10 minutes. The recommended concentration for any commercially
available QAC product used to disinfect equipment is 6 ounces of QAC solution per
gallon of clean water. The following QAC products have been tested by CPW and are
listed in order from highest to lowest concentration of active QAC: Green Solutions
High Dilution Disinfectant 256, Super HDQ Neutral, Quat 4, Vedco 128, and Quat 128.
b. Disposal of QAC: Wastewater treatment plants are capable of processing water
containing small amounts of QAC. Therefore, rinsing used QAC solutions down a
sanitary sewer is a safe method of disposal. However, QACs should be kept out of
storm sewers and other waterways. Always dilute old product before rinsing down
sanitary sewers directly from the container, and follow MSDS and label
recommendations regarding rinsing and disposal of empty containers. Small amounts of
QAC from spray disinfection may come in contact with the environment with few
negative effects. However, it is not recommended to dump large amounts of QAC
solutions directly on the ground. More detailed instructions for disinfection with QAC
products can be provided upon request.
c. Disinfection with Hot Water: Spray/soak equipment with water heated to a
temperature greater than 140 degrees Fahrenheit for at least 10 minutes.
3) Turbidity: Instream construction should be conducted in a manner that will minimize
turbidity of the water in the work area.
4) Petroleum Products and Chemicals: No petroleum products, chemicals, or other
deleterious materials should be allowed to enter or be disposed of in such a manner in
which they could enter the waterway or adjacent wetlands. Accordingly, we recommend
that oil absorbent “booms” be installed downstream of the project site during
construction activities.
References
American Whitewater, 2007. Whitewater parks-considerations and case studies.
https://www.americanwhitewater.org/content/Wiki/stewardship:whitewater_parks
Bouwes, N., S. Bennett, and Joe Wheaton. 2016. Adapting adaptive management for testing
the effectiveness of stream restoration: An intensively monitored watershed example.
Fisheries, 41:2, 84-91, DOI: 10.1080/03632415.2015.1127806.
14
�Brubaker, A., E. E. Richer, D.A. Kowalski, and M.C. Kondratieff. 2018. Making waves: The
effects of whitewater parks on fish passage. 43rd Annual Meeting of the Western Division
of the American Fisheries Society. Anchorage, Alaska. May 22, 2018.
Colorado Stream Quantification Tool Steering Committee (CSQT SC). 2019. Colorado Stream
Quantification Tool and Debit Calculator (CSQT) User Manual, Beta Version. U.S.
Environmental Protection Agency, Office of Wetlands, Oceans and Watersheds (Contract #
EPC-17-001), Washington, D.C.
CPW (Colorado Parks and Wildlife). 2015. State Wildlife Action Plan. Denver, Colorado.
Dunne, T., & Leopold, L. (1978). Water in environmental planning. San Francisco, California:
W.H. Freeman and Company. 818 pp.
Forty, M., J. Spees, and M. C. Lucas. 2016. Not just for adults! Evaluating the performance of
multiple fish passage designs at low-head barriers for the upstream movement of juvenile
and adult trout Salmo trutta. Ecological Engineering 94:214-224.
Fox, B.D., B.P. Bledsoe, E. Kolden, M.C. Kondratieff and C.A. Myrick. 2016. Ecohydraulic
evaluation of whitewater parks as a fish passage barrier. Journal of the American Water
Resources Association. DOI: 10.1111/1752-1688.12397.
Giordanengo, J. H., R. H. Mandel, W. J. Spitz, M. C. Bossler, M. J. Blazewicz, S. E. Yochum,
K. R. Jagt, W. J. LaBarre, G. E. Gurnee, R. Humphries, and K. T. Uhing. 2016. Living
streambanks: A manual of bioengineering treatments for Colorado streams. Colorado
Water Conservation Board, Denver.
Hagenstad, M., J. Henderson. R. S. Rauncher, J. Whitcomb. 2000. Preliminary evaluation of
the beneficial value of waters diverted in the Clear Creek whitewater park in the city of
Golden, Stratus Consulting.
Hardee, T.L. 2017. Evaluating fish passage at whitewater parks using a spatially explicit 2D
hydraulic modeling approach. M.S. Thesis, Department of Civil and Environmental
Engineering, Colorado State University. 107 pp.
Harman, W., R. Starr, M. Carter, K. Tweedy, M. Clemmons, K. Suggs, C. Miller. 2012. A
function-based framework for stream assessment and restoration projects. US
Environmental Protection Agency, Office of Wetlands, Oceans, and Watersheds,
Washington, DC EPA 843-K-12-006.
Kolden, E., B.D. Fox, B.P. Bledsoe, and M.C. Kondratieff. 2015. Modelling whitewater park
hydraulics and fish habitat in Colorado. River Research and Applications. DOI:
10.1002/rra.2931.
Kondratieff, M. C. and E. E. Richer. 2017. Stream Habitat Investigations and Assistance.
Federal Aid Project F-161-R23. Colorado Parks and Wildlife, Aquatic Research Section.
Fort Collins, Colorado.
15
�Kowalski, D.A. 2019. Colorado River aquatic resource investigations. Federal Aid Project F237-R26. Colorado Parks and Wildlife, Aquatic Wildlife Research Section. Fort Collins,
Colorado.
Leopold, L., Wolman, G., & Miller, J. (1964). Fluvial processes in geomorphology. San
Francisco, California: W.H. Freeman and Company. 544 pp.
Loomis, J., and J. McTernan. 2011. Fort Collins whitewater park economic assessment.
Department of Agricultural and Resource Economics, Colorado State University.
NMFS (National Marine Fisheries Service). 2008. Anadromous salmonid passage facility design.
NMFS, Northwest Region, Portland, Oregon.
Poff, N. L., J. D. Allan, M. B. Bain, J. R. Karr, K. L. Prestegaard, B. D. Richter, R. E. Sparks,
and J. C. Stromberg. 1997. The natural flow regime: a paradigm for river conservation and
restoration. BioScience 47(11): 769-784.
Richer, E.E., E.R. Fetherman, M.C. Kondratieff and T.A. Barnes. 2017. Incorporating GPS and
Mobile Radio Frequency Identification to Detect PIT-Tagged Fish and Evaluate Habitat
Utilization in Streams. North American Journal of Fisheries Management. DOI:
10.1080/02755947.2017.1374312.
Richer, E. E., A. B. Brubaker, D. A. Kowalski, and M.C Kondratieff. 2018. Making waves: the
effects of whitewater parks on fisheries. Sustaining Colorado Watersheds Conference,
Avon, Colorado. October 10, 2018.
Schlosser, I. J., and P. L. Angermeier. 1995. Spatial variation in demographic processes for
lotic fishes: conceptual models, empirical evidence, and implications for conservation.
American Fisheries Society Symposium 17:392-401.
Stephens, T. A., B. P. Bledsoe, B. D. Fox, E. Kolden, and M. C. Kondratieff. 2015. Effects of
whitewater parks on fish passage: a spatially explicit hydraulic analysis. Ecological
Engineering 83: 305–318.
Swarr, T.R. 2018. Improving rock ramp fishways for small-bodied Great Plains fishes. M.S.
Thesis, Department of Fish, Wildlife, and Conservation Biology, Colorado State University.
89 pp.
Thompson, K.G., and Z.E. Hooley-Underwood. 2019. Present distribution of three Colorado
River Basin native non-game fishes, and their use of tributary streams. Colorado Parks and
Wildlife Technical Publication 52.
16
�Appendix A
CPW Aquatic Biologist Contact Information
�I
MOFFAT
Tory Eyre
Meeker
(970)878-6074
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JACKSON
LARIMER
Steamboat
Springs Office
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Meeker
Office
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GARFIELD
Co
70
Ben Felt
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(970)255-6126
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Springs '
Office
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TELLER
SW
Jim White
Durango
(970)375-6712
Durango Regional LA PLATA
Administrative Office
Ri o Grande Ri v
CUSTER
er
RIO Monte
GRANDE Vista
EL PASO
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Cory Noble
Colorado Springs
(719)227-5222
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COSTILLA
Purgatoire R
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LAS ANIMAS
25
Miles
75
100
NATIVE AQUATIC SPECIES
BIOLOGISTS
NORTHEAST REGION
Boyd Wright
(970)472-4366
BENT
PUEBLO
HUERFANO
r
NORTHWEST REGION
Lori Martin
(970)255-6186
SOUTHEAST REGION
Josh Nehring
(719)227-5224
r
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LINCOLN
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Hue
AQUATIC BIOLOGISTS
COLORADO PARKS AND WILDLIFE
25
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lic
Lamar Office
PROWERS
Jim Ramsay
Lamar
(719)336-6607
SE
mo s
aR
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Conejos R
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p
Re
NORTHEAST REGION
Jeff Spohn
(303)981-3634
SOUTHWEST REGION
John Alves
(970)375-6721
iver
ree R
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hF
SENIOR AQUATIC BIOLOGISTS
KIOWA
Carrie Tucker
Pueblo
(719)561-5312
ALAMOSA
CONEJOS
ARCHULETA
YUMA
WASHINGTON
Office
Ala
Durango
Office
NE
____ j
CROWLEY
Estevan Vigil
Monte Vista
(719)587-6908
MI NERAL
\
i
I
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-Pueblo Office
SAGUACHE
SAN
JUAN
DOLORES
*
Dan Brauch
Gunnison
(970)641-7070
HINSDALE
,
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as R
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JEFFERSON
Mike Atwood
Salida
(719)530-5525FREMONT
Salida
Office
Gunnison
Office
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76
Headquarters
CHAFFEE
Montrose
Office
I
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Colorado Springs
Office
GUNNISON
Eric Gardunio
Montrose
(970)252-6017
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Ri v
Mandi Brandt
Brush
(970)842-6330
ADAMS
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DELTA
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Denver Administrative Office
Northeast Regional Office
PARK
Grand
Junction
Office
I
Paul Winkle
Denver
(303)291-7232
th Pla tt e
____ _ _____ L_
Tyler Swarr
South Park
(720)576-9782
LAKE
PITKIN
MESA
CLEAR
CREEK
S UMMIT
Kendall Bakich
Glenwood Springs
(970)947-2924
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iver
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Office
Ben Swigle
Fort Collins
(970)472-4364
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Springs
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Thompson Riv er
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Jon Ewert
Hot Sulphur
(970)725-6214
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Bill Atkinson
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Kyle Battige
Fort Collins
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Ri v
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NORTHWEST REGION
Jenn Logan
(970)947-2923
SOUTHWEST REGION
Dan Cammack
(970)275-9617
SOUTHEAST REGION
Paul Foutz
(719)227-5217
BACA
r
ve
D CPW Region Boundary
Created by CPW GIS 2/12/2020
314 W. Prospect St
Fort Collins, CO 80526
G:\Projects\Publications\Boundaries\AquaticBoundaries\CPW_AquaticBiologists_2020_11x17.mxd
�Appendix B
CPW Whitewater Park Fact Sheet
�C O L O R A D O
P A R K S
&
W I L D L I F E
Whitewater Park Studies
RESEARCH RESULTS AND DESIGN GUIDELINES
Whitewater Park Research
With over 30 whitewater parks (WWPs) either completed or in the
planning phases, Colorado is the epicenter for WWP development in the
United States. Although WWPs provide economic and recreational
benefits for local communities (Hagenstad et al. 2000; Loomis and
McTernan 2011), they may have unintended impacts on instream biota
and stream functions, particularly when the hydraulic conditions formed
by the WWP are different from those naturally found in the surrounding
river. The impact of WWPs on habitat connectivity and instream habitat
quality have been the focus of several recent studies. Although these
studies have primarily focused on fish passage and habitat, impacts to
aquatic insects and sediment transport may also occur at WWPs.
Fish Passage Impacts
The elements that create a desirable surf wave (increased velocity,
decreased depth, a hydraulic jump, and a stable, often grouted stream
channel) create conditions that can impede fish movement. Swimming
speeds and jumping ability vary greatly between fish species.
Suppression of upstream trout movement has been documented at WWP
structures, but the degree of impact varied by fish size and characteristics
of the individual structure (Stephens et al. 2015; Fox et al. 2016). As trout
are among the strongest swimming and jumping fish species in Colorado,
small-bodied and weaker-swimming fish native to Colorado streams are
even more susceptible to habitat fragmentation associated with WWP
development.
Brown Trout
Mottled Sculpin
Fish Habitat Impacts
Although WWPs create deep pools, observed fish densities were significantly higher in natural pools than in WWP pools
(Kolden et al. 2015; Kondratieff et al. in preparation). Habitat degradation in WWPs was associated with the unnatural
hydraulics created by the recreational features and conversion of riffle habitat to drops over the wave structures.
Design Guidelines
CPW recommends that adequate environmental safeguards be included in the design and construction of WWPs to ensure
that stream functions, fisheries, and recreational fishing are not adversely impacted. Each structure must be examined on a
case-by-case basis, and monitoring and adaptive management should be included in the proposed project budget.
COLORADO PARKS & WILDLIFE • 1313 Sherman St., Denver, CO 80203 • (303) 297-1192 • cpw.state.co.us
�,.~
Site Selection
Design and construction of WWPs should preserve the
natural aesthetic qualities of the river. WWPs should be
located in degraded reaches when possible and should aim
to improve the natural functions of the reach rather than
maintain degraded conditions. WWPs should not be
constructed in natural, un-modified river channels
(American Whitewater 2007).
WWP sites should be selected to minimize recreational
conflicts with anglers. There is increased potential for
boaters to displace anglers at WWP sites, especially during
the summer months. If WWP construction affects a popular
fishing location, mitigation such as new fishing access or
habitat improvements should be considered.
Ecological Design Considerations
Whitewater 'Parks in-Colorado
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. . Colorado Plateau
WWP structures must be designed to allow upstream fish passage for all life stages of native and sport fishes present
throughout the annual hydrologic cycle. Fish passage is dependent on water velocity, water depth, vertical height of
structures, linear distance of the passage corridor, surface roughness, and attraction flow.
Hydraulic characteristics at WWP features generally conflict with ideal conditions for fish passage. Therefore, a fish
passage channel separate from the WWP structure may be necessary. The passage channel should meet hydraulic design
criteria for target species across a range of flows.
Hydraulic modeling of the proposed structure should be conducted during the initial design phase to evaluate potential
impacts to fish passage and habitat.
Streambed and bank disturbance due to construction activities should be scheduled for a time of year when egg
incubation is not occurring. An increase in fine sediment to the stream during incubation can suffocate developing
embryos. Erosion control and revegetation plans utilizing native riparian species should be required for each project.
WWP structures should not cause sediment deposition upstream or downstream of the structure. Sediment deposition
can eliminate fish and benthic macroinvertebrate habitats, create favorable conditions for the spread of whirling disease
in trout, and increase flooding risk if sediment deposition decreases channel capacity.
Recreational In-channel Diversion (RICD) water rights can be acquired for WWPs to provide recreational experiences
in and on the water. These protected flows should be managed to benefit boating recreation as well as conservation and
management of native and sport fish. Flows deviating from the natural flow regime, such as water calls during spawning
periods, could have adverse impacts on stream ecology (Poff et al. 1997).
References
American Whitewater, 2007. Whitewater Parks – Considerations and Case Studies.
https://www.americanwhitewater.org/content/Wiki/stewardship:whitewater_parks
Fox, B. D., B. P. Bledsoe, E. Kolden, M. C. Kondratieff, and C. A. Myrick. 2016. Ecohydraulic evaluation of whitewater parks as a fish passage barrier. Journal of the American
Water Resources Association. DOI: 10.1111/1752-1688.12397.
Hagenstad, M., J. Henderson, R. S. Raucher, J. Whitcomb. 2000. Preliminary evaluation of
the beneficial value of waters diverted in the Clear Creek Whitewater Park in the City of
Golden. Stratus Consulting.
Kolden, E., B. D. Fox, B. P. Bledsoe, and M. C. Kondratieff. 2016. Modelling whitewater
park hydraulics and fish habitat in Colorado. River Research and Applications. DOI:
10.1002/rra.2931.
Kondratieff, M. C., K. Kinzli, and E. R. Fetherman. In preparation. Eco-hydraulic evaluation
of whitewater parks as fish habitat in Colorado.
Loomis, J., and J. McTernan. 2011. Fort Collins Whitewater Park economic assessment.
Department of Agricultural and Resource Economics, Colorado State University.
Poff, N. L., J. D. Allan, M. B. Bain, J. R. Karr, K. L. Prestegaard, B. D. Richter, R. E. Sparks,
and J. C. Stromberg. 1997. The natural flow regime: a paradigm for river conservation and
restoration. BioScience 47(11): 769-784.
Stephens, T. A., B. P. Bledsoe, B. D. Fox, E. Kolden, and M. C. Kondratieff. 2016. Effects
of whitewater parks on fish passage: a spatially explicit hydraulic analysis. Ecological
Engineering 83: 305–318.
�Appendix C
CPW Fish Passage at River Structures Fact Sheet
�C O L O R A D O
P A R K S
&
W I L D L I F E
Fish Passage at River Structures
RESEARCH AND DESIGN GUIDELINES
Introduction
Instream structures, such as culverts, water diversions and dams, can negatively affect fish by
fragmenting populations, reducing migratory ranges, and limiting access to habitat for spawning, feeding and refugia.
Many rivers in Colorado contain man-made structures that create partial (obstacles) or complete barriers depending on
the fish species and life stage. Habitat fragmentation associated with instream barriers is a serious threat to Colorado’s
Species of Greatest Conservation Need (SGCN) and sport
fisheries. Therefore, it is important that fisheries managers
(A)
identify and evaluate the influence of instream structures on
fish populations.
Fish Passage Research Objectives
The primary goal of fish passage research is to restore
connectivity in fragmented river systems by: (1) evaluating the
effectiveness of existing fishways; (2) evaluating the barrierpotential of common river structures; and (3) establishing fish
swim performance criteria for native and sport fishes.
Current Fish Passage Research Projects
Active fish passage research projects include: (1) evaluation of
native fish passage at existing fishways located on Front Range
transition zone streams; (2) evaluation of fish passage at
instream whitewater park structures; (3) laboratory studies to
develop fish swim and jump performance criteria for Colorado
fishes where data is lacking; and (4) development of new
techniques and technologies for investigating fish movement
and passage in rivers.
(B)
Fishway Design
Fishways, or “fish ladders”, are engineered structures
designed to facilitate passage around an obstacle or barrier.
Fishways attempt to incorporate species- and life stagespecific swimming and jumping abilities into designs. Common
elements of successful fishways include: (1) low velocity
pathways that do not exceed burst speeds or endurance
capabilities for target species (Figure A); (2) water depths that
do not limit swimming performance (Figure B); (3) vertical
drops that do not exceed the jumping ability for target species
- note that many species native to Colorado do not exhibit
jumping behaviors (Figure C); (4) sufficient attraction flow, or
the flow that emanates from a fishway entrance, to ensure
that fish can locate the fishway; and (5) maintenance of the
above design elements over the expected range of
streamflows.
Fin Depth
(Alaska)
Depth Criteria = 5 to 8 in
(C)
Vertical Drop> Jumping Height
COLORADO PARKS & WILDLIFE • 1313 Sherman St., Denver, CO 80203 • (303) 297-1192 • cpw.state.co.us
�Fishway Examples
Some examples of successful fishways include engineered rock ramps (Figure D), constructed riffles (Figure E), and
vertical slot fishways (Figure F). Each type of fishway has advantages and disadvantages related to which fish species
and life stages are present and the conditions of the project site.
Engineered Rock Ramp
Constructed Riffle
Vertical Slot
Diversion Crest
Piney Creek,
Wyoming
Fossil Creek Reservoir
Inlet Diversion,
Cache la Poudre River
(D)
Rock Weirs
CCC Ditch,
San Miguel River
(E)
(F)
Aquatic Habitat Types
From the high-gradient, boulder-dominated, step-pool
channels of snowmelt fed mountain streams to the lowgradient, well-vegetated, pool-riffle rivers of the eastern
plains to the majestic, vertically-confined canyons on the
arid Colorado Plateau, aquatic habitats in Colorado are as
diverse as the geographic regions where they are found.
Native Colorado fishes have unique morphological
characteristics that are adapted to the natural conditions
found in each aquatic habitat type. These adaptations affect
the swimming abilities of fish, influencing how they move
through and use diverse habitats. Fisheries managers must
take the diversity of fish species into consideration when
evaluating river structures and designing fishways.
... .,,...
-
SGCN (#)
Fundulidae (Topminnows)
Cottidae (Sculpin)
Ictaluridae (Catfish)
Cyprinidae (Minnows)
Catostomidae (Suckers)
Centrarchidae (Sunfish)
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COlORAOO STATE WILDLIFE
ACTION Pt.AN 2015
Tr~Zone
W,onw,g8'tirV'ColoncloPlll. .lJ
Fish Swimming Performance by Family
Family Name
Percidae (Perches)
_ o , ___ _
Enl9fnf'IN-.
~ n s t r. .mt
All illustrations of fish © Joseph R. Tomelleri
3
Prolonged Speed (ft/s)
0.4 - 1.2
Burst Speed (ft/s)
NA - 2.4
Jump Height (ft)
0*
Habitat Types
EP
1
0
1
13
5
1
1.3 - 1.6
1.4 - 1.7
1.3 - 2.0
1.3 - 2.4
1.3 - 2.5
1.1 - 2.9
2.6 - 3.4
3.3 - 3.9
2.0 - NA
2.4 - 4.4
2.2 - 3.2
2.6 - NA
0.1 - 0.2
0*
NA - 0.2
0* - 0.5
NA - 0.8
0.4 - NA
EP
CP, MS
EP, TZ
CP, EP, MS, RG, TZ
CP, EP, MS, RG, TZ
EP
Salmonidae (Trout)
3
2.3 - 4.0
4.5 - 7.5
1.0 - 7.0
MS, RG, TZ
SGCN = Species of Greatest Conservation Need, # of species/subspecies; * = fish species does not exhibit jumping behavior; NA =
data were not available; CP = Colorado Plateau, EP = Eastern Plains, MS = Mountain Streams, RG = Rio Grande; TZ = Transition Zone
The values reported above are summarized from multiple species within each family and are intended to support passage
for juvenile life stages. Swim speeds and jumping abilities within species are size dependent. Species-specific performance
criteria should be used whenever possible. The selection of target species for individual projects should be based on the
management objectives for the site in question. Consultation with the local Area Aquatic Biologist at CPW is strongly
encouraged during the early planning stages for any fish passage project in Colorado. The information in this fact sheet is
based on the best available data and knowledge, but is subject to revision as more information becomes available.
COLORADO PARKS & WILDLIFE • 1313 Sherman St., Denver, CO 80203 • (303) 297-1192 • cpw.state.co.us
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Environmental Toxicology and Chemistry, Vol. 24, No. 6, pp. 1515–1517, 2005
q 2005 SETAC
Printed in the USA
0730-7268/05 $12.00 1 .00
Short Communication
ZINC TOXICITY TO THE MOTTLED SCULPIN (COTTUS BAIRDI) IN
HIGH-HARDNESS WATER
STEPHEN BRINKMAN* and JOHN WOODLING
Colorado Division of Wildlife, 317 West Prospect Road, Fort Collins, Colorado 80526, USA
( Received 5 May 2004; Accepted 14 December 2004)
Abstract—The median 96-h lethal zinc concentration (LC50) was 439 mg Zn/L (hardness of 154 mg/L as CaCO3) for feral mottled
sculpin (Cottus bairdi), decreasing to a median incipient lethal level of 266 mg Zn/L after 13 d. The 30-d chronic value was 255
mg Zn/L. The acute toxicity–hardness (ln-ln) slope of 1.022 exceeded that of the current U.S. Environmental Protection Agency
zinc criteria. The mottled sculpin is the second most sensitive fish species for which toxicity data are available.
Keywords—Zinc
Mottled sculpin
Toxicity test
Acute toxicity
Chronic toxicity
centrations of 800, 400, 200, 100, 50, and 0 mg Zn/L. A continuous-flow diluter [5] was used along with a flow splitter to
deliver exposure concentrations. Seven fish were randomly
chosen and placed in each exposure and each control chamber.
Fish were fed a concentrated suspension of brine shrimp nauplii (San Francisco Bay Brand, Newark, CA, USA) mixed with
starter trout chow (Silver Cup, Hanford CA, USA). Fish were
not fed during the 96-h acute toxicity test.
All median lethal concentrations to 50% (LC50) of the test
organisms were estimated by the trimmed Spearman–Karber
technique [6,7] with Toxstatt software (Ver 3.5; Western EcoSystems Technology, Cheyenne, WY, USA). The median incipient lethal level concentrations (ILL50) were the LC50 values derived at the time mortality ceased. Lengths, weights, and
survival of sculpin among treatments used in the chronic test
were analyzed by analysis of variance [8]. Treatment means
were compared to the control by Williams’s one-tailed test (p
, 0.05). Sculpin length and weight data were normal with
homogeneity of variance according to Shapiro–Wilk’s test and
Bartletts’s test, respectively. Lengths and weights of fish at the
beginning and end of the 30-d test were compared using a t
test (p , 0.05) to determine if the organisms grew during the
test period.
INTRODUCTION
Cottidae were absent from waters in the western United
States with elevated zinc concentrations, although trout populations were present [1–4]. Existing U.S. Environmental Protection Agency (U.S. EPA) criteria and various stream restoration objectives may not be adequate to protect diverse aquatic
communities if sculpin are more sensitive to zinc than trout
species. Laboratory tests demonstrated the mottled sculpin,
Cottus bairdi, was extremely sensitive to zinc in soft water
[3]. Sensitive species must be protected to ensure that appropriate water quality criteria and restoration objectives are chosen for zinc-contaminated stream reaches. The current study
had two objectives: first, to develop acute and chronic toxicity
data for recently hatched wild C. bairdi in high-hardness water,
and, second, to determine if the relationship between water
hardness and zinc toxicity for sculpin was similar to other
species for which zinc toxicity data are available.
MATERIALS AND METHODS
Recently emerged C. bairdi were collected from the White
River approximately 5 km east of Meeker, Colorado, USA, on
August 8, 2002, using a backpack electrofishing unit with
pulsed DC current. Hardness, conductivity, and dissolved zinc
levels at the collection site were 240 mg/L as CaCO3, 454 ms/
cm, and ,10 mg Zn/L, respectively. The fish were collected,
transported, received, and maintained at the Colorado Division
of Wildlife Toxicology Laboratory in Fort Collins, Colorado,
USA, as previously described [3]. After a 26-d holding period,
well water was added to dechlorinated Fort Collins municipal
tap water to increase the water hardness to 150 mg/L as CaCO3.
The organisms were acclimated to this hardness for 18 d before
starting the 30-d toxicity test. Toxicant diluter, test methods,
water quality analyses, and zinc analyses were the same as in
a previous C. bairdi toxicity test [3] except that dilution water
consisted of dechlorinated Fort Collins municipal tap water
and on-site well water mixed to create a nominal hardness of
150 mg/L as CaCO3. The photoperiod was 12:12-h light:dark.
Four replicates were used with nominal zinc exposure con-
RESULTS
Exposure water hardness averaged 154 mg/L as CaCO3
(Table 1). Measured zinc concentrations were consistent for
the duration of the test in each of the treatments and close to
the desired nominal concentrations (Table 2). The estimated
96-h LC50 was 439 mg Zn/L. All sculpin exposed to dissolved
778 mg Zn/L (the highest concentration) died by the ninth day.
Mortality at 379 mg Zn/L increased from 46% at 96 h to 85%
at 13 d. No mortality was observed at an exposure of 50 mg
Zn/L or in the controls. No additional mortality occurred after
13 d through the end of the 30-d test. The LC50 values declined
with time to an ILL50 of 266 mg Zn/L at 13 d (Table 3).
Mortality at the no-observed-effect concentration of 172 mg
Zn/L was statistically similar to the controls. The statistically
significant no-observed-effect concentration and lowest-observed-effect concentration were 172 and 379 mg Zn/L, respectively. A 30-d chronic value (the geometric mean of the
* To whom correspondence may be addressed
(steve.brinkman@state.co.us).
1515
�1516
Environ. Toxicol. Chem. 24, 2005
S. Brinkman and J. Woodling
Table 1. Mean, standard deviation, and range of water quality characteristics of exposure water used for zinc toxicity tests conducted with mottled
sculpin. n 5 18
Mean
Standard deviation
Range
a
pH (SU)a
Temp. (8C)
Hardness
(mg/L CaCO3)
Alkalinity
(mg/L CaCO3)
Conductivity
(ms/ cm)
Oxygen (mg/L)
7.5
0.09
7.4–7.7
12.4
0.4
11.7–13.1
154
8.9
138–167
110
7.1
95–118
254
20
229–2284
8.2
0.32
7.6–8.8
SU 5 standard unit.
no-observed-effect concentration and lowest-observed-effect
concentration) was estimated to be 255 mg Zn/L for mottled
sculpin in water of hardness 154 mg/L as CaCO3.
The average length of the mottled sculpin was 27 mm at
time of capture as determined from the fish that died in transit
to the laboratory. The average length of mottled sculpin used
in the acute test was 35 mm with a range of 30 to 42 mm.
These fish were considered to be young-of-the-year [3]. The
average length of fish surviving the 30-d exposure was 38 mm.
Significant growth was observed in the test organisms during
both acclimation and the 30-d test. No differences in length
or weight were seen in fish surviving the 30-d exposure period
among the different exposure levels (Table 2).
DISCUSSION
Use of feral fish did not appear to influence results of the
current study. Mortality occurred (37 died) during the 24-h
transportation period from point of collection to the laboratory.
However, no additional mortality was observed during acclimation of the more than 300 surviving test organisms or to
control fish during the toxicity test. Nonlethal differences in
growth were not observed at any zinc concentration where test
organisms survived the toxicity test.
The sculpin averaged 27 mm total length and average
weight of 0.289 g when first collected. Fish grew significantly
during the acclimation period to an average total length of 35
mm total length and average weight of 0.442 g, indicating that
feed, health, and holding conditions were adequate for the test
organisms. The mottled sculpin continued to grow through the
30-d test.
The relative sensitivity of mottled sculpin to zinc to other
aquatic species was assessed by comparing zinc toxicity data
determined in this study to current U.S. EPA zinc criteria [9].
All mottled sculpin toxicity data from the current study and
two prior studies [3,10] were normalized to a hardness of 50
mg/L as CaCO3, and a genus mean acute value was calculated.
The genus mean acute value for mottled sculpin is 182 mg Zn/
L. The mottled sculpin appears to be the third most sensitive
aquatic species to zinc for which data are available [9,11] based
on a comparison of genus mean acute values. The striped bass
(Morone saxatillis) was the only fish species that appeared
more sensitive to acute zinc exposure than the mottled sculpin.
The mottled sculpin was more sensitive to zinc than any salmonid species.
The mottled sculpin was sensitive to the acute toxic effect
of zinc in relatively hard water (154 mg/L as CaCO3), the same
result previously found in soft water (49 mg/L as CaCO3) [3].
A third toxicity test on mottled sculpin found a 96-h LC50 of
590 mg Zn/L at a hardness of 156 mg/L as CaCO3 [10] in an
exposure test limited to 4 d. An acute toxicity–hardness (lnln) slope of 1.022 (r2 5 0.95) resulted from a combination of
all three 96-h LC50 values available for the mottled sculpin.
The slope of 1.022 lies within the range of 0.5603 reported
for bluegill (Lepomis macrochirus) and 1.644 for the guppy
(Poecilia reticulata) but exceeds the pooled mean slope of
0.8473 in the current U.S. EPA, acute zinc criteria [9].
Comparing the relative chronic toxicity of mottled sculpin
to zinc with other fishes was not possible because of a paucity
of data in the literature. Neither the original U.S. EPA zinc
criteria document [11] nor the 1995 zinc update [9] contained
references to chronic zinc toxicity tests with fish in water in
hardness greater than 45 mg/L as CaCO3.
Calculation of a chronic value from this study (255 mg Zn/
L) suggested that the U.S. EPA–recommended chronic exposure of 165 mg Zn/L at a hardness of 150 mg/L as CaCO3
would be protective of mottled sculpin. However, zinc criteria
would not be protective of mottled sculpin in lower-hardness
water [3]. Apparently, the toxicity of zinc to sculpin is attenuated by hardness to a greater degree than other species used
to determine the existing U.S. EPA criteria. Mottled sculpin
may not be protected at hardness levels less than 109 mg/L
as CaCO3 based on a comparison of the hardness response of
this species with the current zinc criteria [9]. We expect acute
mortality to wild mottled sculpin exposed to zinc concentrations deemed safe using the current U.S. EPA criteria at hardness levels less than 109 mg/L as CaCO3. Additional toxicity
tests to mottled sculpin or other Cottus species are needed to
validate the hardness response of the genus to zinc. Also, zinc
toxicity tests are needed to determine how protective the U.S.
EPA zinc criteria are to a wide variety of fish species for which
data are not currently available at hardness concentrations in
excess of 50 mg/L as CaCO3.
The sensitivity of mottled sculpin, relative to trout species,
was evident in field observations of the Eagle River in Colorado, USA. Brook trout and brown trout but not sculpin inhabited three Eagle River sampling sites where dissolved zinc
concentrations ranged from 315 to 711 mg Zn/L at hardness
concentrations reaching 130 mg/L as CaCO3 (John Woodling,
Table 2. Mean zinc concentrations (mg/L), mortality (%), total length (mm), and weight (g) of mottled sculpin after 30 d of exposure. Standard
deviations are in parentheses. * 5 significantly different than control at p , 0.05. n 5 9, five in first 4 d and weekly thereafter
Nominal Zn
Dissolved Zn
Mortality
Length
Weight
0
,5 (3)
0
938.2 (1)
0.47 (0.042)
50
50 (6)
0
38.1 (1.5)
0.50 (0.060)
100
94 (9)
7 (8)
37.1 (1.9)
0.49 (0.04)
200
172 (17)
8 (9)
38.6 (2.1)
0.51 (0.08)
400
379 (16)
86 (20)*
40.4 (0.5)
0.65 (0.06)
800
778 (21)
100 (0)*
—
—
�Zinc toxicity to C. bairdi
Environ. Toxicol. Chem. 24, 2005
Table 3. Median lethal concentrations to 50% of test organisms (LC50)
of zinc and 95% confidence intervals (mg/L) to mottled sculpin at
different durations of exposure
Duration of
exposure
LC50 estimate
(mg/L)
95%
confidence interval
4 d (96 h)
5d
6d
7d
8d
9d
13 d
15 d
30 d
439
302
283
278
279
273
266
266
266
290–664
245–372
243–328
239–324
243–321
242–309
240–295
240–295
240–295
personal communication). As such, lower in-stream zinc concentrations are required for mottled sculpin to recolonize the
portion of the Eagle River where zinc concentrations have not
eliminated trout species. In this instance, sculpin serve as an
indicator species for water quality in waters where the both
groups are expected to be present.
The 96-h LC50 concentration (439 mg Zn/L) decreased to
302 mg Zn/L (35%) by day 5. The LC50 decreased to 266 mg
Zn/L by day 13. No mortality occurred following day 12. The
use of ILL50 data may be preferable to describe acute toxicity
in instances where high levels of mortality are measured for
a few days past the initial 96-h exposure. Additional toxicity
tests are required with mottled sculpin, including early life
stage testing, to determine sublethal effects of zinc at incipiently lethal levels.
Acknowledgement—Funding for this study was provided in part by
1517
the U.S. Fish and Wildlife Service Federal Aid Grant F-243-R10. We
wish to acknowledge the assistance of Shannon Albeke and Daria
Hansen and the editing efforts of Brighid Kelly and two anonymous
reviewers.
REFERENCES
1. McCormick FH, Hill BH, Parrish LP, Willingham WT. 1994. Mining impacts on fish assemblages in the Eagle and Arkansas Rivers,
Colorado. J Freshw Ecol 9:175–179.
2. Maret TR, MacCoy DE. 2002. Fish assemblages and environmental variables associated with hard-rock mining in the Coeur
d’Alene River basin, Idaho. Trans Am Fish Soc 131:865–884.
3. Woodling J, Brinkman S, Albeke S. 2002. Acute and chronic
toxicity of zinc to the mottled sculpin (Cottus bairdi). Environ
Toxicol Chem 21:1922–1926.
4. Farag AM, Skaar D, Nimick E, MacConnell E, Hogstrand C.
2003. Characterizing aquatic health using salmonid mortality,
physiology, and biomass estimates in streams with elevated concentrations of arsenic, cadmium, copper, lead, and zinc in the
Boulder Creek watershed, Montana. Trans Am Fish Soc 132:450–
467.
5. Benoit DA, Mattson VR, Olsen DC. 1982. A continuous flow
mini-diluter system for toxicity testing. Water Res 16:457–464.
6. Hamilton MA, Russo RC, Thurston RV. 1977. Trimmed Spearman-Karber method for estimating median lethal concentrations
in toxicity bioassays. Environ Sci Technol 11:714–719.
7. Hamilton MA, Russo RC, Thurston RV. 1978. Correction. Environ Sci Technol 12:417.
8. Snedecor GW, Cochran WG. 1980. Statistical Methods. Iowa
State University Press, Ames, IA, USA.
9. U.S. Environmental Protection Agency. 1996. 1995 updates: Water quality criteria documents for the protection of aquatic life in
ambient water. EPA-820- B-96-001. Washington, DC.
10. Davies PH, Brinkman SF, Hansen D. 2002. Water pollution studies. Federal Aid Project F-243-R9. Colorado Division of Wildlife,
Fort Collins, CO, USA.
11. U.S. Environmental Protection Agency. 1987. Ambient water
quality criteria for zinc. EPA-440/5-87-003. Washington, DC.
�
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FINAL
SUMMARY REPORT
Greenback Cutthroat Trout Genetics and Meristics Studies
Facilitated Expert Panel Workshop
REGION 6 OFFICE
US FISH AND WILDLIFE SERVICE
May 12, 2014
Prepared for:
U.S. Fish and Wildlife Service
Region 6, Mountain-Prairie Region
Ecological Services - Colorado Field Office
134 Union Boulevard
Lakewood, Colorado 80228-1807
Prepared by:
AMEC Environment & Infrastructure, Inc.
1819 Denver West Drive
Suite 100
Golden, CO 80401
USFWS Order No. F13PB00113
AMEC Project No. 32106C002
�Summary Report
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�Summary Report
TABLE OF CONTENTS
Executive Summary .................................................................................................... 1
1.0 Background ......................................................................................................... 3
2.0 Expert Panel ........................................................................................................ 3
3.0 Workshop ............................................................................................................. 2
3.1 Essential Reading ........................................................................................... 2
3.2 Day One Summary ......................................................................................... 3
3.3 Day Two Summary ......................................................................................... 3
3.4 Day Three Summary ....................................................................................... 3
4.0 Summary of Expert Panel Responses ................................................................. 5
4.1 Evaluation of the Science ............................................................................... 6
4.2 Biodiversity Implications ............................................................................... 13
4.3 Management Implications ............................................................................ 21
4.4 Public Comments ......................................................................................... 30
5.0 Overall Summary ............................................................................................... 31
6.0 Management and Research Recommendations ................................................ 32
Appendix A: Workshop Agenda, Attendees and Suggested Reading
Appendix B: Workshop Meeting Notes
Appendix C: Discussion Questions and Fact Sheet
Appendix D: Expert Panel Reviewer’s Responses
Appendix E: Other Attendee’s Responses
Appendix F: Public Comments
(Courtesy Shiozawa Presentation at Workshop)
US Fish and Wildlife Service - Greenback Trout Expert Panel Workshop
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US Fish and Wildlife Service - Greenback Trout Expert Panel Workshop
Page 0 of 37
�Summary Report
Executive Summary
Subspecies of cutthroat trout in Colorado were believed to follow geographic boundaries within
the state until recently. With the completion of a genetic study comparing mitochondrial DNA of
extant Colorado cutthroat trout populations with museum specimens (Metcalf et al. 2012) and a
meristic study of cutthroat trout collected from all major drainages in Colorado (Bestgen et al.
2013). The purpose of this review was to provide a thorough scientific review and evaluation
prior to taxonomic, listing, and management decisions. Toward that purpose, the US Fish and
Wildlife Service hosted an expert panel Workshop that included a group of experts in the field of
native trout genetics, meristics, and taxonomy.
The Workshop was held July 30 – August 1, 2013 and was facilitated by Dr. Tom Turner from
the University of New Mexico. The goals of the Workshop were to: 1) evaluate science of recent
genetics and meristics studies and reach consensus about implications for management and 2)
develop recommendations for future efforts, including both additional research and
management activities. The participants included the expert panel, members of the Greenback
Cutthroat Trout Recovery Team, agency representatives, and authors. Following the workshop,
the expert panel and other attendees provided responses to 17 discussion questions. This
report summarizes those responses, with Workshop material and complete responses provided
in the appendices.
Panelists generally believed both studies were well-designed and informative, given limitations
of sample size and available specimens. The studies both supported the same hypotheses and
provided insight into the relationships among Colorado cutthroat trout and relative to historic
specimens. Both studies support the existence of four extant and two extinct lineages of
cutthroat trout in Colorado. Yellowfin cutthroat trout and the native cutthroat trout in the San
Juan River (red lineage) appear to be extinct. Rio Grande cutthroat trout continue to stand as a
distinct lineage, as in previous studies. Colorado River cutthroat trout (blue lineage) still occur
on the West Slope but only on the northern end of it; East Slope populations appear to be a
result of stocking. Greenback cutthroat trout could refer to two different lineages: green lineage
and Bear Creek. Green lineage trout occur on both the West and East Slopes, but the reason
for their presence on the East Slope is unclear. In addition, the Bear Creek population is a
unique lineage and appears to represent the native South Platte River cutthroat trout, although
that population does not occur in that drainage now.
While some conclusions were strongly supported, there remain topics that require further
research. Additional genetics and meristics research is required to further clarify the status and
relationship of the green lineage to other lineages. Additional genetics research is required to
provide a more complete phylogeny among the lineages. Confirmation of the extinction of the
San Juan River native cutthroat trout is needed. Taxonomic revisions are required to resolve
issues associated with the green lineage and the Bear Creek population. Research is needed to
evaluate a number of issues associated with the hatchery stock for the Bear Creek population.
The Bear Creek population merits protection and additional management efforts. The individual
responses provided a thorough and comprehensive review of these studies and their taxonomic
and management implications.
US Fish and Wildlife Service - Greenback Trout Expert Panel Workshop
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�Summary Report
1.0 Background
Until recently, delineations of subspecies of cutthroat trout in Colorado were believed to follow
geographic boundaries within the state, with greenback cutthroat trout (Oncorhynchus clarkii
stomias) on the eastern side of the Continental Divide and Colorado River cutthroat trout (O. c.
pleuriticus) on the western side. Rio Grande cutthroat trout (O. c. virginalis) occur within the Rio
Grande drainage; their range and genetic identity does not appear to be in question. The
recently published genetic study by the University of Colorado - Boulder genetics lab (Metcalf et
al. 2012) compared mitochondrial DNA of extant Colorado cutthroat trout populations with
cutthroat trout museum specimens collected in the late 1890s to early 1900s, thereby providing
an understanding of the native ranges of cutthroat trout in Colorado prior to fish stocking efforts.
The conclusions of this genetic study have significant implications under the Endangered
Species Act (ESA) and for management decisions as the data indicate that only one greenback
cutthroat trout population remains in existence; this population is present in Bear Creek on
Pikes Peak in the Arkansas River drainage. The other “greenback” streams that are present on
the eastern side of the Continental Divide are cutthroat trout that had been stocked from the
West Slope of the Continental Divide at earlier times. Another significant conclusion of the
genetic study is the identification of two separate distinct lineages of the Colorado River
cutthroat trout, which had previously been considered to consist of one lineage across the entire
West Slope of Colorado.
The genetic study complements a concurrent meristic study of cutthroat trout in Colorado. The
meristic study was conducted by the Larval Fish Laboratory at Colorado State University and
included cutthroat trout specimens collected from all major drainages in Colorado, Wyoming,
Utah, and New Mexico. Meristic and genetic analyses are being conducted on the specimens in
a “double-blind” test in which neither group of researchers is aware of the origin of the
specimens. The meristic study was completed in the spring of 2013, with the report available for
the Workshop. Both of these studies were initiated and funded by the Greenback Cutthroat
Trout Recovery Team, which is comprised of the following agencies: Colorado Division of Parks
and Wildlife, US Forest Service (USFS), Bureau of Land Management (BLM), National Park
Service (NPS), and the US Fish and Wildlife Service (FWS or Service).
The purpose of this review was to provide a thorough scientific review and evaluation prior to
taxonomic, listing, and management decisions. Toward that purpose, the Service‟s Colorado
Field Office, in concert with our partners in the Greenback Cutthroat Trout Recovery Team,
coordinated a facilitated expert panel Workshop that included a group of experts in the field of
native trout genetics, meristics, and taxonomy.
(Courtesy Krieger Presentation at Workshop)
US Fish and Wildlife Service - Greenback Trout Expert Panel Workshop
Page 3 of 35
�Summary Report
2.0 Expert Panel
Expert panel members were selected by the Service and were invited to attend a Workshop and
provide answers to Discussion Questions. The panel included individuals with professional
qualifications and experience related to as many as possible of the following areas: greenback
and other cutthroat trout genetics, cutthroat trout meristics, taxonomy, and other related fields.
In addition, the Service invited the authors of the two studies to attend and other agency
representatives. The Workshop was facilitated by Tom Turner, PhD (University of New Mexico)
in Lakewood, Colorado from 30 July – 1 August 2013 (see Section 3.0 for summary, Appendix A
for agenda, and Appendix B for the meeting notes).
The independent expert panel members are all experienced, senior-level fish conservation
biologists, fish geneticists, and/or fish taxonomists. There were four groups of attendees at the
Workshop: expert panelists, members of the greenback cutthroat trout recovery team, agency
representatives, and authors. Each panelist attended the Workshop and provided individual
responses to the discussion questions (Appendix C) provided by the Service (Appendix D). In
addition, other attendees were also given the opportunity to provide responses (Appendix E).
Facilitator
Dr. Tom Turner – University of New Mexico
Expert Panel Members
Dr. Marlis Douglas – University of Illinois
Dr. Richard Mayden - St. Louis University (presenter, public comment period)
Dr. Jeffrey Olsen - FWS Conservation Genetics Program
Mr. Bruce Rosenlund - retired, FWS fisheries
Dr. Dennis Shiozawa – Brigham Young University (presenter, cutthroat trout genetics generally)
Dr. Robin Waples – Northwest Fisheries Science Center, NOAA Fisheries
Dr. Andrew Whiteley – University of Massachusetts Amherst
Greenback Cutthroat Trout Recovery Team
Ms. Leslie Ellwood – FWS
Mr. Doug Krieger - Colorado Parks and Wildlife (presenter)
Mr. Jay Thompson - BLM
Ms. Mary Kay Watry - NPS
Mr. David Winters - USFS
Agency Representatives
Mr. Dirk Miller - Representative Colorado River Cutthroat Trout Conservation Team
Ms. Pam Sponholtz - Representative FWS Fisheries Program
Authors
Mr. Chris Kennedy – Fishery Biologist, FWS, Estes Park, Colorado (presenter)
Dr. Andrew Martin – University of Colorado, Boulder (presenter)
Dr. Jessica Metcalf – University of Colorado, Boulder (presenter)
Dr. Kevin Bestgen – Colorado State University, Ft. Collins (presenter)
Dr. Kevin Rogers – Aquatic Research Scientist, Colorado Parks and Wildlife
US Fish and Wildlife Service - Greenback Trout Expert Panel Workshop
Page 1 of 33
�Summary Report
3.0 Workshop
The Workshop was held at the Service‟s regional offices in Lakewood, Colorado. The Workshop
started at 8:00 am on Tuesday, July 30, 2013 and finished at 5:00 pm on Thursday, August 1,
2013. Dr. Tom Turner from the University of New Mexico facilitated the Workshop. The goals of
the Workshop were to: 1) Evaluate science of recent genetics and meristics studies and reach
consensus about implications for management and 2) Develop recommendations for future
efforts, including both additional research and management activities.
3.1 Essential Reading
The Service provided the following documents as essential reading during the expert panel
review (Appendix A contains full citations and the complete list of suggested reading):
BESTGEN, K.R., K.B. ROGERS AND R. GRANGER. 2013. Phenotype predicts genotype for lineages
of native cutthroat trout in the Southern Rocky Mountains. Final Report to US Fish and
Wildlife Service, Colorado Field Office, Denver Federal Center (MS 65412), Denver, CO.
Larval Fish Laboratory Contribution 177.
BRUNELLI, J.P., J.M. MALLATT, R.F. LEARY, M. ALFAQIH, R.B. PHILLIPS, G.H. THORGAARD. 2013. Y
chromosome phylogeny for cutthroat trout (Oncorhynchus clarkii) subspecies is
generally concordant with those of other markers. Molecular Phylogenetics and
Evolution 66:592-602.
HOUSTON, D. D., D. B. ELZINGA, P. J. MAUGHAN, S. M. SMITH, J. S. KAUWE, R. P. EVANS, R. B.
STINGER, AND D. K. SHIOZAWA. 2012. Single nucleotide polymorphism discovery in
cutthroat trout subspecies using genome reduction, barcoding, and 454 pyrosequencing. BMC Genomics 13: 724- 740.
LOXTERMAN, J. L., AND E. R. KEELEY. 2012. Watershed boundaries and geographic isolation:
patterns of diversification in cutthroat trout from western North America. BMC
Evolutionary Biology 12:38.
METCALF, J. L., V. L. PRITCHARD, S. M. SILVESTRI, J. B. JENKINS, J. S. W OOD, D. E. COWLEY, R. P.
EVANS, D. K. SHIOZAWA, AND A. P. MARTIN. 2007. Across the great divide: genetic
forensics reveals misidentification of endangered cutthroat trout populations. Molecular
Ecology 16:4445-4454.
METCALF, J. L., S. L. STOWELL, C. M. KENNEDY, K. B. ROGERS, D. MCDONALD, J. EPP, K.
KEEPERS, A. COOPER, J. J. AUSTIN, AND A. P. MARTIN. 2012. Historical stocking data and
19th century DNA reveal human-induced changes to native diversity and distribution of
cutthroat trout. Molecular Ecology 21:5194-5207.
PRITCHARD, V. L., J. L. METCALF, K. JONES, A. P. MARTIN, AND D. E. COWLEY. 2008. Population
structure and genetic management of Rio Grande cutthroat trout (Oncorhynchus clarkii
virginalis). Conservation Genetics.
ROGERS, K. B. 2010. Cutthroat trout taxonomy: exploring the heritage of Colorado‟s state fish.
Pages 152-157 in R. F. Carline and C. LoSapio, editors. Wild Trout X: Sustaining wild
trout in a changing world. Wild Trout Symposium, Bozeman, Montana.
SHIOZAWA, D. K., R. P. EVANS, P. UMACK, A. JOHNSON, AND J. MATHIS. 2010. Cutthroat trout
phylogenetic relationships with an assessment of associations among several
subspecies. Pages 158-166 in R. F. Carline and C. LoSapio, editors. Wild Trout X:
Sustaining wild trout in a changing world. Wild Trout Symposium, Bozeman, Montana.
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3.2 Day One Summary
Mr. Doug Krieger presented on background information on behalf of the Greenback Cutthroat
Trout Recovery Team. The attendees discussed the purpose and goal of the Workshop. Mr.
Chris Kennedy presented the history of cutthroat trout stocking in Colorado. Dr. Jessica Metcalf
and Dr. Andrew Martin presented on the genetics of cutthroat trout in Colorado and the Metcalf
et al. 2012 study. Dr. Kevin Bestgen presented on the meristics study of cutthroat trout. All
presentations were followed by discussion amongst the panelists.
3.3 Day Two Summary
Dr. Dennis Shiozawa presented on cutthroat trout genetics in general. Dr. Behnke‟s research
was discussed. Dr. Tom Turner led a review and discussion of the different hypotheses. Dr.
Richard Mayden presented on species concepts during the Public Comment session. One
public comment was provided by a recreational off highway vehicle (OHV) group.
3.4 Day Three Summary
Attendees reviewed the Factsheet (Appendix C) and made revisions. Attendees then reviewed
the Discussion Questions (Appendix C). Attendees discussed management implications of the
studies.
The following section summarizes the terminology used for common and scientific names and
geography throughout this report and the individual memoranda.
Lineage
Common Name
Scientific Name
Notes
Blue
Colorado River cutthroat
trout
O. c. pleuriticus
May require revision of
historical range
Green
Greenback cutthroat trout?
O. c. stomias?
May require taxonomic
revision and new
subspecies name
Purple
Greenback cutthroat trout?
O. c. stomias?
Bear Creek fish, see
green lineage
Yellow
Yellowfin cutthroat trout
O. c. macdonaldi
Presumed extinct
Orange
Rio Grande cutthroat trout
O. c. virginalis
Not disputed
Red
none
none
San Juan River fish,
presumed extinct, likely
requires taxonomic
revision and new
subspecies name
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Figure 1. Previous hypothesis about interior cutthroat trout distributions
(courtesy Krieger presentation at Workshop).
Figure 2. Revised hypothesis about interior cutthroat trout distributions
(courtesy Metcalf et al. 2012).
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4.0 Summary of Expert Panel Responses
The expert panel considered and responded to the Discussion Questions (Appendix C) provided
during the Workshop. The following section summarizes their responses, with their full
responses provided in Appendix D. Responses from the Recovery Team, agency
representatives and/or authors are provided in Appendix E. Table 1 below provides a summary
of whether a reviewer provided a response to a question and the total pages provided by the
reviewer. Answers with „No Response‟ indicate the reviewer did not feel themselves qualified to
respond to that particular question. Expert Panel members are summarized separately from
other attendees of the Workshop (i.e., Recovery Team Members, Agency Representatives and
Authors).
After the table, summaries of the answers for each question are provided. These summaries
focus on the expert panel responses (Panelists #1-8), while including highlights and relevant
points from other attendees (Panelists #9-16).
Table 1: Reviewer Response to Each Question
Expert
Panel
Panelist #1
Panelist #2
Panelist #3
Panelist #4
Panelist #5
Panelist #6
Panelist #7
Panelist #8
Evaluation of the
Science
1
2
3
4
5
Biodiversity Implications
Management Implications
6
7
12
8
9
10
11
13
14
15
16
10
-
-
12
-
7
-
5
5
-
17
Total
Pages
4
10
10
5
Other Attendees
Panelist #9
Panelist #10
Panelist #11
Panelist #12
Panelist #13
Panelist #14
Panelist #15
Panelist #16
-
-
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6
5
4
4
7
4
3
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4.1 Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct
cutthroat trout lineages and inferences based on historical stocking, logical and supported
by the evidence provided in this study? Are there alternative interpretations?
< Panelist 1: The conclusions are plausible, but it should still be considered a working
hypothesis and needs to be supplemented with additional research. Evidence supports blue
lineage fish being stocked into the Arkansas and South Platte River basins and the yellowfin
cutthroat trout association with the Arkansas River basin. The history of the green lineage in
the Arkansas River basin is unclear with several possible explanations.
< Panelist 2: The conclusions reached by the Metcalf studies were not supported by the study.
The gene flow analyses were not done to the best science available and their conclusions
are only one set of many possible alternatives.
< Panelist 3: The Metcalf study does answer many questions, but does not completely answer
questions pertinent to the green lineage fish. The study does support six lineages, mostly
separated by major river basins (Also Panelist 6, 7, 8, 12, 14, 16). With respect to the green
lineage fish, there are alternative explanations for the distribution of these fish on both the
East and West Slopes.
< Panelist 4: The protocols to generate molecular data are sound, with caveats of low sample
size and short sequences (Also Panelist 3, 6, 8, 10, 14). The historical research collection
sites, curatorial practices, and record gaps provide some uncertainty. The study disregards
the possibility of ancestral polymorphism and defaults to the stocking scenario to explain the
distribution of green and blue lineage fish, when the scenario could be more complex.
< Panelist 5: The inferences were more plausible than other scenarios.
< Panelist 6: The study was careful regarding contamination and the validity of using DNA for
historical references.
< Panelist 7: The study is the best available science on the historic and current distribution of
cutthroat trout in the headwaters of the South Platte River. The unlikely alternative
explanation of Metcalf et al. 2012 data would be that all the matching mtDNA museum
samples represent the range-wide organized movement and introduction of a lineage of fish
prior to 1871.
< Panelist 8: Further study is needed to test the six lineage hypothesis (using appropriate
nuclear markers) and refine the geographic range of the lineages (examine more historical
samples). There are alternative explanations for the origin of the Bear Creek population.
Other Panelists
< Panelist 9: The paper explains the patterns in the most parsimonious way, but other
hypotheses cannot be ruled out. From museum specimens, it seems the South Platte River
basin contained its own lineage of cutthroat trout consistent with those found in Bear Creek.
However, few museum specimens were available for the Arkansas River basin to
comfortably determine that the yellowfin were the native cutthroat trout there. Perhaps, it is
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possible these fish were not founded from a stocking event, as suggested in the paper, but
from an invasion from west of the Continental Divide in the late Pleistocene.
< Panelist 10: It is reasonable that Bear Creek fish were stocked from the South Platte River
drainage based on the historical evidence. The native fishes of the Arkansas River drainage
are not as transparent. The conclusions of the 2012 paper, that green lineage fish were not
native to the Arkansas River basin, is somewhat uncertain. See Panelist 4.
< Panelist 14: The conclusion that Bear Creek is native to the South Platte River and not
native to the Arkansas River is supported by the data presented but could be disputed. Bear
Creek fish may have been historically present in the Arkansas River drainage and simply not
represented in the museum samples. The conclusion that the blue lineage fish were
historically restricted to drainage basins on the western slope is supported but the inference
that the blue lineage was historically restricted to the Yampa and Green River drainages is
not supported. The full historic distribution of blue lineage fish remains uncertain. I disagree
with the interpretation that it is unlikely that green lineage was native to the Arkansas River.
< Overall
Panelists generally agreed:
o
the study was sound (1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16), within the
limitations of low sample sizes, short sequences and available museum specimens
(1, 3, 4, 6, 7, 8, 9, 10, 14)
o
the study made a strong case for six lineages in Colorado, with two of them extinct
(3, 5, 6, 7, 8, 11, 12, 14)
o
the study did not provide a clear answer about the relationship between East Slope
and West Slope green lineage fish (1, 2, 3, 4, 6, 10, 14)
o
further analysis is necessary to confirm the conclusions (1, 2, 3, 4, 6, 14)
Other responses worth noting (most of these are elaborated on under other questions):
o
the study supported that the Bear Creek lineage represented fish from the South
Platte River drainage (5, 6, 10, 11, 14)
o
the San Juan River (red lineage) and yellowfin (yellow lineage in Arkansas River
basin) cutthroat trout are likely extinct (3, 6, 12)
o
the Rio Grande cutthroat trout is a distinct lineage (3, 4, 6)
o
the blue lineage ancestral watersheds were the Yampa and White Rivers (3, 6)
o
the blue lineage fish were stocked on the East Slope (1, 5, 6, 14)
o
the green lineage ancestral watersheds were the Colorado, Gunnison and Dolores
Rivers (3, 6)
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2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics
study show a difference in phenotypic characteristics between blue lineage, green lineage,
Bear Cr, and Rio Grande)?
< Panelist 1: They generally do correlate and show difference among the lineages. In
particular, the Bear Creek, Rio Grande, and blue lineages separate consistently in both
studies (Panelist 6, 7, 10, 14, 16).
< Panelist 2: Yes, based on other genetic studies and at a wider scale, the morphological
studies provide a clearer picture of the diversity.
< Panelist 3: The molecular hypothesis explains more variation than the geographical
hypothesis, which is consistent with the results of the genetics study (Panelist 5). There was
evidence that the meristic variation was at the scale of geographic management units
(GMUs). Additional samples are needed to clarify some of the variation, in particular East
Slope green lineage fish.
< Panelist 4: The studies both find there are four extant lineages (green, blue, Bear Creek, Rio
Grande) (Panelist 5, 6, 9, 11, 12, 13). The meristics study provided a more nuanced
perspective, demonstrating difference amongst GMUs.
< Panelist 5: See Panelist 3 and 4.
< Panelist 6: See Panelist 1 and 5.
< Panelist 7: The meristics study supports all six historical lineages and generally agrees with
the genetics study.
< Panelist 8: See Panelist 3.
Other Panelists
< Panelist 10: The green lineage fish had the greatest trait variation. Either the East Slope
green lineage fish represent native trout diversity from a West Slope to East Slope invasion
or the geographical model is correct in supporting differentiation between extant green and
blue fish on the West Slope. Also, see Panelist 1.
< Panelist 11: The populations of green lineage fish on the East Slope are best explained by
either being out of place and originating from the West Slope or they are an admixture of the
green and blue lineages (based on genetic and historical stocking data). It is possible
founder effects caused the unique patterns found in small populations. An analysis of South
Platte River lineage museum samples would help with understanding if Bear Creek is native
to the South Platte River. Also, see Panelist 4.
< Panelist 14: The meristics study revealed more fine-scale differences in green lineage fish
than the genetics study. The West Slope green lineage is intermediate between the blue
lineage and Rio Grande cutthroat trout, whereas the East Slope green lineage had traits that
were intermediary between the West Slope green lineage and Bear Creek fish. Also, see
Panelist 8.
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< Overall
Panelists generally agreed:
o
the meristic study does correlate with the genetic study and supports the four extant
lineages of cutthroat trout in Colorado (All panelists)
o
Bear Creek, Rio Grande and blue lineages consistently separate from other lineages
(1, 3, 6, 7, 10, 11, 14, 16)
3. To what extent are historical spatial distributions of green and blue lineages known?
< Panelist 1: The Colorado River basin is actually subdivided into two basins: the Upper
Colorado River basin and the Lower Colorado River basin. It is presumed the blue lineage
fish originate in the entire Upper Colorado River basin and its three subbasins (Panelist 9).
Green lineage fish have been identified in the South Platte and Arkansas River basins (East
Slope) and Lower Colorado River basin (West Slope). The distribution of the green lineage
on both sides of the Continental Divide and in both the Arkansas and South Platte River
basins is not typical for natural dispersal unless the event occurred recently (Holocene).
< Panelist 2: The historical distributions of the green and blue lineages are not well known.
< Panelist 3: Green lineage fish occurred historically in the Colorado, Gunnison, Dolores
drainages on the West Slope and potentially in the Arkansas basin on the East Slope
(Panelist 11, 13, 14). The blue lineage fish occur in the White, Yampa, and Colorado River
drainages, but are likely in the Arkansas River from stocking (Panelist 8, 11, 12, 13, 14).
< Panelist 4: The complexity of the trout phylogeny and stocking history make it nearly
impossible to infer with certainty, historical distributions. The actual process was likely much
more complicated than we can predict. With the small sample size of specimens, we cannot
say they are “proof” of historical populations.
< Panelist 5: They are not known with certainty (Panelist 15). One hypothesis is that much of
the current overlap in blue-green distribution is the result of stocking. This hypothesis seems
plausible given the available information but this issue has not been resolved conclusively.
< Panelist 6: Data suggesting the distinct blue lineage fish were historically confined to the
Yampa/White drainage (Panelist 10) and East Slope blue lineage fish were a result of
stocking are convincing (Panelists 12, 13). Green lineage fish are presumed to historically
reside in the Colorado/Gunnison/Dolores drainages (Panelist 10, 11, 12, 14). The origin of
East Slope green lineage fish can be explained in a few ways, but more research must be
done to make a firm conclusion (Panelist 11, 14). There are some issues with the data used
to evaluate green lineage fish; notably the mtDNA and nuclear DNA did not agree the
assignment of individual fish to blue or green lineages in some cases.
< Panelist 7: There appears to be good evidence for a blue lineage in the Yampa River basin,
with David Starr Jordan‟s 1889 description of Trappers Lake fish consistent with modern day
pure Trappers Lake fish. David Starr Jordan‟s physical descriptions and figures indicate an
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abundant East Slope green lineage as of 1889. Jordan‟s descriptions of West Slope fish are
not consistent, but tend to support a West Slope green lineage as of 1889.
< Panelist 8: The evidence is at least as strong that the green lineage existed historically on
the East Slope and more analysis will be needed to resolve the question of the origin the
East Slope green lineage fish. As stated in my reply to question 1, this can best be resolved
by additional study including examining more historical samples (if they exist for the area of
interest) and applying appropriate nuclear markers. See Panelist 3 also.
Other Panelists
< Panelist 10: The idea that green lineage fish are not native to the East Slope is plausible
and I would accept it as the best explanation until/if other information comes to light. If Bear
Creek fish were actually native to the Arkansas River basin, then it is likely it would have
been represented in the 1889 samples. Also, see Panelist 6.
< Panelist 13: Data are limited to clarify the origin and status of East Slope blue and green
lineages. We need to proceed with caution when managing the fish on the East Slope, but
neither the blue or green East Slope populations warrant protection under ESA. Also, see
Panelists 3 and 6.
< Panelist 14: The Bear Creek haplotype matches five haplotypes in the South Platte River,
which provides evidence that the purple lineage was native to the South Platte River. Also,
see Panelists 3 and 6.
< Panelist 15: It may be more important to agree on the current “boundaries” of the lineages
and move forward to restore robust populations. Also see Panelist 5.
< Panelist 16: The historical stocking records are remarkably intact and represent the best
information we have to delineate historical distributions. We have a fairly strong concept of
where these fish originated.
< Overall
Generally panelists agreed:
o
blue lineage fish are from the Upper Colorado Basin (White, Yampa Rivers)
historically (1, 3, 6, 7, 8, 9, 10, 11, 12, 16), with Lower Colorado Basin (Gunnison,
Dolores Rivers) and East Slope populations a result of stocking (3, 6, 7, 8, 10)
o
green lineage fish are from the Lower Colorado Basin (Colorado, Gunnison, Dolores
Rivers) on the West Slope, with the reason for their occurrence on the East Slope
unclear (1, 3, 6, 8, 10, 11, 16)
But there was a clear dissenting conclusion:
o
the historical spatial distributions of green and blue lineages are unclear (2, 4, 5, 13,
14, 15)
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4. How does genetic and meristic variation identified in the studies compare with variation in
other cutthroat trout studies? Are levels of variation consistent with differences observed
across species, subspecies or evolutionary significant units (ESUs) in other cutthroat trout?
< Panelist 1: The relationship between genetic and meristic variation and subspecies
designation in cutthroat trout is complex. The separation of both the green lineage and the
Bear Creek population is significant and both populations are likely eligible for subspecies or
ESU-level recognition. There is some complexity associated with the green lineage due to
possible admixturing with the blue lineage.
< Panelist 2: This cannot be answered as comparable studies do not exist for other cutthroat
trout.
< Panelist 3: Blue, green, orange and purple (Bear Creek) lineage fish are demonstrably
monophyletic and exhibit significant divergence in meristic traits across lineages. Molecular
and morphological evidence for diversification of lineages is comparable to, and in most
cases, much better than evidence available for other named subspecies of cutthroat trout.
< Panelist 4: Comparing levels of divergence among studies is difficult, due to differences in
methodologies, sample sizes, analytical protocols, scope, and focus of studies. Rather than
comparing results of studies that focus on single groups, a better approach is to examine
levels of divergence in broad-scale studies.
< Panelist 5: This is challenging to answer because genetic lineages within Colorado often do
not follow geography, but in general, the levels of genetic variation found within populations
of Colorado cutthroat trout seem comparable to those found in other areas. We were not
shown enough data for other subspecies to comment on a comparison. Divergence between
green, blue, Bear Creek, and Rio Grande constitute ESUs or subspecies. Divergence
between East and West Slope populations within the green lineage equate to Management
Units (MUs)
< Panelist 6: The divergence of Colorado cutthroat trout species seems relatively recent
compared to other subspecies of cutthroat trout. An analysis of outbreeding depression
among southern Rocky Mountain cutthroat trout would be highly useful.
< Panelist 7: The lineages appear to qualify as ESUs.
< Panelist 8: There is not enough published information to answer this question. Any
comparison should be based on studies that ideally use the same markers (or marker types,
e.g., mtDNA, microsatellites, SNPs). A study of cutthroat trout thought out the range is
needed and factors such as effective population size, gene flow, and mutation rate, should
all additionally be considered when analyzing diversity differences.
Other Panelists
< Panelist 9: Within species of cutthroat trout, other designated subspecies show similar
amounts of molecular variation. Some strains of Pacific salmon currently managed as ESUs
might show less differentiation in genotype and perhaps meristic characters than discussed
in this situation.
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< Panelist 10: Shiozawa‟s work on cutthroat trout phylogenies which concluded that the Bear
Creek lineage is distinct from Colorado River and Rio Grande cutthroat trout is important.
< Panelist 11: The differences between the different lineages are similar in magnitude to
differences between other trout species. Cutthroat trout are anomalous in that they are
recognized at the subspecies level. Bear Creek should be assigned O.c.stomias along with
the South Platte River fish. Green lineage should be recognized as a distinct subspecies.
The native distribution of O.c.pleuriticus should be revised so it is not historically being
recognized as being present in the Colorado, Gunnison, or Delores River basins. The San
Juan lineage should be described as a new subspecies.
< Panelist 14: Multiple efforts indicate that green, blue, Bear Creek, and Rio Grande are
separate from one another.
< Overall
There was conflicting conclusions among the panelists:
o
genetic and meristic variation is similar to or greater than that seen between other
cutthroat trout lineages (1, 3, 9, 11, 14)
o
comparisons cannot be made with other cutthroat trout lineages (2, 4, 8)
o
at least two lineages qualify for subspecies or ESU designation (1, 3, 5, 7, 11)
5. Did the genetic and meristic studies include all the necessary and pertinent literature to
support their assumptions/arguments/conclusions?
< Panelist 1: Yes, although further testing will be needed to support the hypothesis.
< Panelist 2: No, the genetic studies should have included data from other studies in larger
scale evaluations. The morphology study suffered from not examining historic specimens
from the South Platte River.
< Panelist 3: Both studies cite and include all pertinent literature. There are areas in both
studies where more data and study are warranted.
< Panelists 4 - 7: See Panelist 3
< Panelist 8: Yes, although further study is warranted to address historical distribution of the
green lineage, particularly evidence of the East Slope populations, and testing the molecular
hypothesis using appropriate nuclear markers must be conducted.
< Overall
The majority agreed that the studies included the relevant literature (1, 3-9, 11-15)
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4.2 Biodiversity Implications
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
(a. different subspecies? b. distinct population segments (DPSs)? c. other?)
< Panelist 1: The blue and green lineages on the West Slope should be managed as two
distinct entities and should be considered, at a minimum, two DPSs. To understand the
status of the West Slope green populations, more research is needed of their origin through
use of phylogenetic data to identify nuclear haplotypes. Once this is done, the abundance of
“pure” green lineage populations in the West Slope should be identified, which could result
in East Slope green lineage fish becoming important if it is determined they were the result
of stocking since they would be candidate sources for reintroduction to the West Slope.
< Panelist 2: The lineages constitute different species when their differentiation is compared to
other trout species not in North America.
< Panelist 3: The subspecies, O.c.pleuriticus should be more narrowly defined to the
drainages historically occupied by the blue lineage (Yampa, White). The subspecies
O.c.virginalis refers to fishes in the upper Rio Grande drainage, and should maintain
management on the GMU level. O.c.stomias is not as clear and may require a newly
elevated green lineage and a stricter definition of stomias will require taxonomic revision. It
may be most defensible to propose a new lineage that encompasses green lineage that
identifies East and West Slope lineages as „DPSs‟ with the East Slope population having
more protection than the West Slope.
< Panelist 4: Green, blue, Bear Creek, and Rio Grande approximate differences between
ESUs and divergence between East and West Slope green lineage can be equated to MUs.
O.c.stomias may be categorized as either the green or Bear Creek lineage (see comments
under Questions 7 and 8). This situation has been encountered in other species groups,
particularly the Boreal Toad.
< Panelist 5: Rio Grande populations are O.c.virginalis (Panelist 10). Blue lineage represents
the contemporary distribution of O.c.pleuriticus and should continue to be treated as a
subspecies (Panelist 10) with a revised distribution. Blue lineage presence on the East
Slope is likely due to stocking. The green lineage is a second lineage that seems to be
widely distributed in what was historically the range of O.c.pleuriticus. There are several
scenarios for how to list the green lineage depending on what conclusions are drawn about
the history of the species and what we define as a subspecies. Bear Creek is a distinctive
population that can be listed under ESA. The taxonomy of the greenback trout and whether
or not Bear Creek should be given the name O.c.stomias needs to be resolved by
taxonomists. Bear Creek should either be given the designation of stomias solely for listing
purposes under ESA or declared as a DPS of the species O.clarkii and be listed as such.
< Panelist 6: Addressing subspecies designations will require taxonomic revision and this lies
outside of the purview of the review panel. The Bear Creek (Panelist 16), West Slope green,
East Slope green, and West Slope blue lineages all warrant protection as separate DPSs.
< Panelist 7: Using Mayr and Ashlock (1991), all the lineages appear to be good subspecies
defined within major river drainages, with limits to natural movement of genetic materials
between river drainages.
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< Panelist 8: It is unclear what actually constitutes a subspecies. Data suggests the four
distinct lineages (blue, green, Rio Grande, Bear Creek) are listable DPSs or ESUs.
Other Panelists
< Panelist 9: Since the question posed simply asks whether the lineages are potentially
listable, we are looking to address the first two criteria for a DPS: Discreteness and
Significance. Regardless of how the USFWS decides to rule, both molecular and meristic
data suggest these lineages should be managed as discrete entities even at the GMU level.
< Panelist 11: Bear Creek should be recognized as O.c.stomias and listed under ESA as
endangered. The green and blue lineages do not satisfy the criterion for listing at this time.
< Panelist 14: Blue, green, Rio Grande, and Bear Creek should be listed as subspecies
(Panelist 16). The East Slope green lineage should be considered for a listing as a DPS.
< Overall
Panelists generally agreed:
o
Six lineages constitute separate, distinct lines (1, 3-12, 14-16) and taxonomic
revision of Colorado cutthroat trout is likely warranted (3, 5, 6, 11, 15)
o
O.c.virginalis is limited to the Rio Grande populations (3, 4, 5, 10, 11)
o
O.c.pleuriticus should be more narrowly defined to the drainages historically
occupied by the blue lineage (Yampa, White) (1, 3, 5, 10, 11)
o
Green lineage may be distinct, and the West Slope and East Slope populations may
constitute DPSs or at least MUs (assuming East Slope is not stocked) (1, 3, 4, 6, 10,
14)
7. Is the Bear Creek population considered to be greenback cutthroat trout?
< Panelist 1: The term “greenback” has a varied history, so it is difficult to make a conclusion.
The name for the Bear Creek fish will depend on a decision on 1) whether or not to retain
the common name greenback for the fish in Bear Creek, 2) the result of a petition to the
International Commission on Zoological Nomenclature to change the type specimen for
stomias and to retain the Arkansas River basin, 3) a decision on whether or not to separate
the green lineage fish on the West Slope from those on the East Slope, and/or 4) a decision
as to the relation of the Bear Creek fish to other interior cutthroat trout taxa. The common
name, greenback, can be moved to the Bear Creek fish with less difficulty than the scientific
name, O.c.stomias. Additionally, it is important to show independent support that the Bear
Creek fish are the true original South Platte greenback.
< Panelist 2: This is unsure since the samples from the South Platte River basin were never
examined for morphology.
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< Panelist 3: This is difficult to answer because doing so, would potentially remove protection
from green lineage fish previously classified as greenback cutthroat trout. O.c.stomias could
continue to be defined how they are and all green lineages and Bear Creek can be named in
the recovery plan as lineages that warrant special management and protection.
< Panelist 4: It may be a prudent solution to equate Bear Creek lineage with the taxon
O.c.stomias to maintain a listing for the species. Bear Creek is a distinct genetic and
morphological lineage and represents a distinct evolutionary lineage.
< Panelist 5: See answer to Question 6.
< Panelist 6: The common name seems to be meant for the cutthroat trout in the South Platte
River and it would therefore seem appropriate to give the common name greenback
cutthroat trout to Bear Creek fish (Panelist 7, 8, 10-13).
< Panelist 7: See Panelist 6. Additional work to review and document the phenotypes of the
museum specimens in relationship to modern day Bear Creek and other lineages may help
resolve questions and inconsistencies (Panelist 12).
< Panelist 8: Regardless of the name, it seems the cutthroat trout in Bear Creek are the only
existing representatives of the South Platte River lineage (Panelist 15). Also see Panelist 6.
Other Panelists
< Panelist 9: If the yellowfin was the aboriginal fish of the entire Arkansas River basin, then
the name greenback should default to those found in the South Platte River basin. This is
not necessarily the case for the scientific name stomias since those were assigned to type
specimens that appear to be Rio Grande cutthroat trout. Since the name virginalis predates
stomias, the latter then technically becomes a synonym for Rio Grande cutthroat trout.
< Panelist 16: No. Dr. Shiozawa‟s data show separation between Bear Creek and
“greenbacks” 1 million years ago. Greenback cutthroat trout are the fish from the South
Platte River but maybe due to founder effects, Bear Creek fish, while the ancestor to the
South Platte River, are no longer “greenback” cutthroat trout.
< Overall
Panelists generally agreed:
o
the Bear Creek population should/could retain the common name, greenback
cutthroat trout (1, 4, 6-10, 11-13, 15)
o
the Bear Creek population is likely the only remaining population that was originally
in the South Platte River, but this requires confirmation (1, 6, 7, 8, 10, 12, 14, 15)
Other responses worth noting:
o
the Bear Creek population probably should not retain the scientific name
(O.c.stomias) (3, 9), although others felt it should (11)
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o
confusion has been caused by the type specimen likely belonging to another
subspecies (1, 9, 10, 11, 12)
o
modifying the name could remove protection from the Bear Creek fish and they
definitely warrant protection (3, 5)
8. How do we describe the East Slope green lineage?
< Panelist 1: The East Slope green lineage is a group that clades out within the West Slope
green lineage. The East Slope lineage is not monophyletic with West Slope haplotypes, and
the lack of this indicates the fish entered the region recently from a genetically diverse
population or they were introduced by man from a population that no longer exists on the
West Slope. The meristics study suggests that East Slope and West Slope green lineage
fish are different.
< Panelist 2: The East Slope Green lineage is a distinct lineage (Panelist 6).
< Panelist 3: This will depend on the outcome of studies designed to ascertain the origin of
East Slope haplotypes (Panelist 9). See answers to previous questions.
< Panelist 4: Whether the green lineage is equated with O. c. stomias or a new subspecies
name, the West Slope and East Slope populations should be regarded as two seperate
DPSs or MUs.
< Panelist 5: There are two hypotheses that must be resolved before being able to make a
decision (Panelist 15). One is whether or not the green lineage is native to the East Slope
(Panelist 9, 15). The second is whether the green lineage haplotypes in some East Slope
populations are the result of stocking from West Slope sources (Panelist 15).
< Panelist 6: See Panelist 2. However, the divergence between East and West Slope green
populations warrants further research (Panelist 9).
< Panelist 7: The East Slope green lineage is a group of four existing populations that
physically and genetically assign to the West Slope green lineage. However, they have
unique haplotypes not found within West Slope green lineages. There was originally only
one known South Platte East Slope green lineage population (Como Creek), with the other
South Platte East Slope green lineage population (Fern Lake) being a transplant of Como
Creek stock.
< Panelist 8: The East Slope green lineage fish should be considered from an unknown origin
until more research can clarify their relationship to West Slope fish.
Other Panelists
< Panelist 10: The relationship between the East and West Slope green lineage populations
needs to be resolved further (Panelist 16). Until further research can be conducted, we
should consider affording higher protection to the West Slope green lineage (within range)
and some protection for the East Slope green lineage fish.
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< Panelist 11: The green lineage is a distinct subspecies native to the Colorado, Gunnison,
and Dolores basins. The whole species complex should be revised so the main lineages are
considered species and the minor lineages are considered subspecies.
< Panelist 12 and 13: The East Slope green lineage fish is comprised of green lineage fish
native to the West Slope that have been stocked east of the Continental Divide. It does not
seem the East Slope lineage fish should be considered a separate listable entity; they
should be considered the same as green lineage fish on the West Slope. East Slope green
fish should not be eliminated, but do not warrant protection under the ESA.
< Panelist 14: The current research indicates that East Slope green lineage populations have
unique haplotypes present only on the East Slope and geographic separation from other
green lineage populations. In addition, meristically they appear a bit different than the West
Slope green lineage. Although they are still clearly green lineage fish both genetically and
meristically, they should be managed separately at this time.
< Overall
Panelists generally agreed:
o
the East Slope green lineage is distinct from the West Slope green lineage (1, 2, 4,
6)
o
additional studies are needed to determine the relationship between the East Slope
and West Slope green lineage, including whether the East Slope fish were stocked
from the West Slope (1, 3, 5, 6, 8, 9, 10, 15, 16)
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish
suggest in terms of subspecies or ESU distinctions?
< Panelist 1: This depends on whether the East Slope green lineage originated from stocking
or from a recent natural invasion. If the East Slope green lineage trout can be shown to have
originated from stocking from the West Slope, then their distinctness in morphology
(especially spotting), is not of much importance. The populations then may be of importance
for rehabilitation of West Slope populations. If the East Slope green lineage fish are shown
to be native, the fact that they are imbedded in the West Slope green lineage with mtDNA
should be verified with nuclear genes. Corroborating findings would suggest that they are a
part of the West Slope green lineage. At that point I would manage them as DPSs or ESUs.
< Panelist 2: They suggest they are distinct.
< Panelist 3: East Slope green lineages that are not found in West Slope populations may
comprise a DPS of the green lineage and GMU level management is most appropriate
(Panelist 14).
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< Panelist 4: The entire green lineage should be recognized as a distinct ESU or subspecies
(Panelist 12), with several GMUs recognized as geographically isolated entities within this
ESU/subspecies.
< Panelist 5: I see little basis from existing data to consider the East Slope green lineage
populations a separate subspecies. Under some scenarios, these populations might meet
the criteria to be considered a DPS, if it were concluded that their presence east of the
divide was not the result of stocking.
< Panelist 6: East Slope green lineage should be considered a distinct ESU or DPS.
< Panelist 7: The existence of unique East Slope green haplotypes is not supported by the
limited museum samples, but their uniqueness is not refuted by genetic markers from nonnative populations.
< Panelist 8: This question cannot be answered without further research (Panelist 15). There
is not enough information to characterize East Slope green lineage fish (Panelist 9).
Other Panelists
< Panelist 9: Examination of meristic characters in the museum specimens and characterizing
all green lineage population haplotypes would help inform this decision (Panelist 14).
< Panelist 10: The entire green lineage should be designated a DPS, with greater protection
afforded to the West Slope populations.
< Panelist 14: An investigation of East and West Slope green lineage fish must be done to
analyze the amount of admixture between green lineage fish and blue, rainbow or
Yellowstone, and identify a “pure” population of green lineage fish. Also, additional
exploration of all East and West Slope green lineage haplotypes is needed to see if they
share haplotypes with those on the West Slope. Also, see Panelists 3 and 9.
< Overall
Panelists agreed that the data suggest they are distinct lineages at the DPS or ESU level (1,
2, 3, 5, 6, 10, 14)
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for
green, blue, greenback and Rio Grande cutthroat trout?
< Panelist 1: No, these studies do not resolve the phylogenies enough to conclude probable
routes of colonization (Panelist 4, 7, 8, 9). They do show strong support for geographically
defined subspecies with the addition of Bear Creek. Additional sequence data for
mitochondrial DNA and developing primer sets for nuclear DNA will help to clarify routes of
colonization. The meristics study suggests overlap of West Slope green lineage fish with the
Rio Grande cutthroat trout, but I believe it is too difficult for meristics studies to generate
phylogeographic associations.
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< Panelist 2: This question cannot be answered until more studies are done (Panelist 8).
< Panelist 3: Shiozawa‟s work provides the most likely scenario for colonization/evolution of
interior cutthroat trout, with the ancestor coming from the northwest and diversifying on the
West Slope (blue lineage). Then there was dispersal to the East Slope with subsequent
evolution of the green/yellowfin/Bear Creek/Rio Grande lineages (Panelist 10, 13, 16). It is
unclear whether or not East Slope green lineage fish are native to the East Slope or recently
introduced. Blue lineage fish on the East Slope are likely there from stocking activities.
< Panelist 4: No, the two studies do not give probable routes of colonization for the lineages.
Contradicting evidence from the two studies could be accommodated by a scenario that
invokes an initial dispersal of O. clarkii into drainages on both sides of the Continental
Divide, followed by divergence of lineages in subdrainages. Subsequent dispersal would
have allowed spread of lineages into other drainages.
< Panelist 5: There are two hypotheses and currently available analyses do not allow one to
distinguish between these hypotheses.
< Panelist 6: It is difficult to objectively test routes of colonization. It is not necessary to
objectively weigh evidence of genetic and phenotypic divergence of extant lineages to make
decisions about separate conservation designations such as ESUs or DPSs.
< Panelist 7: See Panelist 5.
< Panelist 8: See Panelist 1.
Other Panelists
< Panelist 11: The fact that the meristic study revealed the East Slope green lineage fish fall
between the two main green and blue clusters and three out of four show evidence of
genetic admixture supports the hypothesis that they are of hybrid descent.
< Panelist 14: It seems fairly accepted in the published phylogenies that all four lineages (Rio
Grande, blue, green and Bear Creek) came from a common ancestral line. There are two
potential routes of colonization. The first is that cutthroat trout entered Colorado from the
NW and then the Rio Grande, green and Bear lineage moved south and eventually East
over the Continental Divide diversifying along the way. The second route is two separate
events, one from the NW establishing the blue lineage and one from the West/Southwest
which moved East establishing the Rio Grande, green and bear lineages. In either case, the
more established historical view that the green lineage descended directly from blue lineage
has less current support than green lineage descending from Rio Grande.
< Overall
Panelists generally agreed that these studies do not provide enough data to identify routes
of colonization (1, 2-10, 14, 16). Almost all panelists refer to other research than these
genetics and meristics studies to answer this question, in particular Dr. Shiozawa‟s
research.
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11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What
could lead to those differences and are there any taxonomic implications?
< Panelist 1: The blue lineage fish are the Colorado River cutthroat trout that originated in the
West Slope and were most likely stocked to the East Slope (Panelist 14). This is supported
by the East Slope blue lineage fish matching a subset of haplotypes in Trapper‟s Lake
(Panelist 14). The lack of genetic diversity in East Slope blue lineage fish could be due to
stocking by man or a small founder population or bottlenecks (Panelist 8, 10). The green
lineage fish can be interpreted as a single lineage polytomy containing all interior cutthroat
trout except the Yellowstone cutthroat trout line. The Bear Creek lineage is then an
independent line in the polytomy or the entire green lineage can be divided into two clades
with the Bear Creek fish being one line branching off basally from the predominant green
lineage. Morphological data separating the Bear Creek lineage from green lineage is less
informative because Bear Creek is so highly inbred. Examination of South Platte River
museum specimens will help to answer how much inbreeding influences their morphology.
< Panelist 2: The variation is significant and should be considered distinct lineages until they
are tested and proven otherwise.
< Panelist 3: Addressed under questions 6, 9, 10.
< Panelist 4: The morphological and genetic patterns correspond with subdrainages and are
consistent with variation among populations (MUs) within lineages (ESUs).
< Panelist 5: Addressed under questions 6 and 8.
< Panelist 6: Addressed under questions 1, 6, and 8 for the green lineage. Evidence suggests
East Slope blue lineage fish are of recent hatchery origin from the West Slope (Panelist 8,
13).
< Panelist 7: Addressed under question 9 for the green lineage. Many East Slope and West
Slope (outside of the Yampa River drainage) blue lineage populations were established from
a unique lake population of Colorado River cutthroat trout within the blue lineage (Panelist 9,
14).
< Panelist 8: Green lineage fish likely historically existed on the East Slope, but more analysis
will be needed to resolve the question of the origin of East Slope green lineage fish.
Other Panelists
< Panelist 9: See Panelist 7 for blue lineage fish. Green lineage fish show variation between
East/West Slopes in both phenotype and genotype, which could be a result of natural
invasions or from stocking west to east (Panelist 14).
< Panelist 11: The East Slope green lineage is likely a result of stocking and are an admixture
between the green and blue lineages.
< Panelist 12 and 13: The East Slope green lineage is the result of small founding populations
of stocked fish.
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< Overall
The answers under question 6, 8 and 9 generally apply here. Panelists generally agreed:
o
the blue lineage on the East Slope were stocked from Trapper‟s Lake (1, 3, 6, 7, 8, 9,
12, 13, 14)
o
the green lineage has several possible relationships between East and West Slope
populations (1, 3, 5, 6, 7, 9, 10, 11, 14, 15), as well as the Bear Creek population (1,
3)
o
there is not enough evidence to separate East Slope and West Slope populations of
both blue and green lineages within their respective lineage (1, 3, 6, 8, 15), although
they may merit protection as DPSs or MUs for the green lineage (3, 4, 5, 6)
4.3 Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited
genetic and meristic variability compared to green and blue lineages? What approaches,
if any, should be considered to manage genetic variability in this lineage to ameliorate
potential or actual inbreeding effects?
< Panelist 1: Bear Creek fish show less variability than the green lineage fish (Panelist 16).
However, Bear Creek fish are a single, inbred population, subject to drift and founder effect,
so it is difficult to say how representative of the morphology historically. The Harvard
collection of fish should be examined. The population must be duplicated in the South Platte
River basin, immediately. It may be useful to try genetic rescue (Panelist 6, 8, 9) with other
green lineage fish in those replicated populations. The risk of population loss is too high with
one small population.
< Panelist 2: The genetic variability in the Bear Creek lineage should not be altered by
introducing other alleles from other lineages. The population should be maintained and
protected in Bear Creek, habitat restoration should be done in the area. There is justification
to relocate them to fishless streams in the South Platte River basin.
< Panelist 3: An unpublished MS thesis from Andrew Martin‟s lab suggested very limited
genetic variability in the Bear Creek population exists (Panelist 14). There is also evidence
of developmental abnormalities in the hatchery, which could be from environmental factors
and selection pressures (Panelist 6, 16). The recovery of the Bear Creek population requires
it to be replicated in South Platte River basin streams (Panelist 6, 12), in Bear Creek itself,
and in the hatchery (Panelist 14).
< Panelist 4: Bear Creek only exhibits one mtDNA haplotype (Metcalf et al. 2012). Details on
nuclear genetic data are not published. Morphological analyses (Bestgen and Rogers 2013)
show a contracted morpho-space, although this lineage exists as a single population, and
thus among-population variation is not available. Maintaining a large population in the wild
(possible replicated in suitable habitats as outlined below) should be a priority.
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< Panelist 5: There is not a consistent trend with Bear Creek meristic variability based on the
meristic study. The most important issue for this population is whether it shows inbreeding
depression. The experiment currently being conducted on Bear Creek fish should shed light
on whether the abnormalities in hatchery-raised fish are because of inbreeding depression
and/or environmental conditions associated with culture (Panelist 10). In addition,
comparisons with other lineages to determine if Bear Creek has higher than average
abnormalities would informative.
< Panelist 6: Metcalf et al. (2007) reports low genetic diversity for the four East Slope
populations, including Bear Creek. Phenotypically, Bear Creek fish are divergent from other
lineages but have maintained variation comparable to other lineages. Inbreeding effects
should be examined. Duplicating the population within the South Platte River basin should
be undertaken and if issues arise, genetic rescue of those populations may be merited. The
Bear Creek population should not be impacted by these activities. See Panelist 1 and 3.
< Panelist 7: High levels of hatchery deformities may not limit the establishment of new wild
Bear Creek lineage populations, but is assumed to reflect the lineages‟ overall fitness.
Caution should be used with any outcrossing activities.
< Panelist 8: The immediate priority is to replicate the Bear Creek population (Panelist 14).
Individuals should be transferred to a large enough location that can support a population
size which minimizes loss of diversity due to a bottleneck. See Panelist 1.
Other Panelists
< Panelist 9: Studies should be conducted to determine if there are any actual inbreeding
effects in the wild and, if there are, genetic rescue should be performed on a small number
of individuals. Bear Creek and several replicate populations should be maintained.
< Panelist 10: Bear Creek fish were clearly different from other lineages but the there was no
opportunity to compare Bear Creek fish to museum specimens. This is an investigation with
broad support that would be important to our understanding of potential inbreeding that the
Bear Creek fish might have experienced over the past 130 years. To ameliorate possible
inbreeding in hatcheries, maximize the size of any replicated populations to include as many
mature individuals in future spawning efforts. Also, see Panelist 5.
< Panelist 16: I do not advocate for introducing additional genetic material or “forcing
hybridization” but instead translocating Bear Creek fish to a range of different habitats
(gradient, temperature, aspect, etc) and letting genetic selection exert pressure on each of
these populations. Mixing them then at a later period could then help preserve the extant
genetics left in this population. Also, see Panelists 1 and 3.
< Overall
All panelists agreed this is an important and small population worthy of protection and that is
currently at-risk.
There is no agreement on whether the Bear Creek population shows reduced variability.
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o
the Bear Creek population shows reduced variability compared to the green lineage
fish, with respect to meristics (1, 4, 10, 16) and genetics (3, 4, 11, 14, 16)
o
the Bear Creek population does not show reduced variability compared to other
lineages (5, 6, 9, 15)
There are conflicting opinions about management actions:
o
replicate Bear Creek fish into multiple populations, usually within the South Platte
River basin (1, 2, 4, 6, 8, 10, 11, 12, 14, 16)
o
undertake genetic rescue of the replicated populations along with extensive
monitoring (1, 6, 8)
o
do not interfere with the genetics, there is still too little information (2, 6, 7, 15, 16)
o
evaluate hatchery stocks, inbreeding depression and outbreeding depression prior to
any genetic rescue or population replication (3, 5, 6, 8, 9, 10, 15)
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat
trout for the Arkansas River basin?
< Panelist 1: The likely native Arkansas River cutthroat trout is the extinct yellowfin (Panelist 3,
5, 7, 11, 12, 16). However if a recent natural invasion of the green lineage into the Arkansas
River basin has occurred, then the green lineage in the Arkansas River basin would likely
also contain genetic material from the Yellowfin. A series of good nuclear gene phylogenies
would allow identification of those haplotypes.
< Panelist 2: The East Slope green lineage with its unique haplotype and distinctive
morphology.
< Panelist 3: Yellowfin are presumed extinct, so the East Slope green lineage fish are the best
candidates for reintroduction to the Arkansas River basin. It appears that there is less
urgency to restocking the Arkansas River drainage at this time, so it will be best to await
results of definitive studies to identify whether East Slope green lineage fish are native, and
whether suitable (low to no introgression) populations exist as donors (Panelist 12).
< Panelist 4: Bear Creek is a poor candidate because of its small population size, low genetic
variability, and propagation problems and may not be native to the Arkansas River basin.
The best candidate for re-establishing native cutthroat trout across the Arkansas River basin
is the green lineage from the East Slope (Panelist 6).
< Panelist 5: Green lineage fish are from an uncertain origin and other trout introduced could
not be considered “native cutthroat trout of the Arkansas basin.” The basin could be used to
further conservation goals by expanding Bear Creek and/or Rio Grande populations there.
< Panelist 6: See Panelist 4. Subsequent data and analyses may find that East Slope green
lineage fish are introduced from the West Slope.
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< Panelist 7: No reintroductions of “native Arkansas” fish should be conducted until more data
is available to confirm what fish are native to the basin (Panelist 9, 10). However, Bear
Creek fish could be reared in controlled reservoir sites within the Arkansas River basin for
reintroduction to the South Platte River basin.
< Panelist 8: There is not enough information to determine what population to reintroduce in
the Arkansas River basin. However, if sufficient habitat exists to replicate the Bear Creek
population within the Arkansas River basin, this should be done to stabilize the Bear Creek
population with the understanding Bear Creek may not be the native species of the basin.
Other Panelists
< Panelist 11: It makes sense to stock Bear Creek (Panelist 13) fish since the native cutthroat
trout species to the Arkansas River have gone extinct. Alternatively, it is possible that South
Fork Hayden Creek may represent a native Arkansas River drainage population, suggesting
that decisions about whether to replace current populations of cutthroat trout inhabiting
Arkansas River basin streams should be made on a case-by-case basis and populations
without strong evidence of admixture or stocking should remain.
< Panelist 12: See Panelist 3. If it becomes apparent the East Slope green lineage fish in the
Arkansas River basin are a result of stocking, then it may be appropriate to reintroduce Bear
Creek cutthroat trout into the Arkansas River basin (Panelist 14).
< Panelist 14: Both the green lineage and the Bear Creek lineage could be native to the
Arkansas River, although Bear Creek are more likely. If East Slope green lineage fish are
found to be native through more research, they should be stocked. See Panelist 12.
< Panelist 15: I would be more concerned with disease introductions and/or potential human
movement into the wrong drainages by the public. Most of our limited funding should be
used for the study and introduction of the lineages for which we are confident.
< Overall
Panelists generally agreed:
o
the likely native Arkansas River cutthroat trout is the extinct yellowfin (yellow lineage)
(1, 3, 5, 7, 11, 12, 16)
o
East Slope green lineage fish are the best candidate for reintroduction in the
Arkansas River basin (2, 3, 4, 6)
o
additional studies (genetic and field) should be performed before reintroductions are
done (1, 3, 5-12, 14)
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14. How should next-generation DNA sequencing (NGS) approaches be used in Colorado
River, Bear Creek, and Rio Grande cutthroat trout management?
< Panelist 1: First, nuclear markers should be identified and verified (Panelist 12). Also,
additional independent loci should be examined. Second, it could be used to generate
longer sequence data (Panelist 9). Third, both SNP development and phylogenetic data
generation can be accomplished with less cost per base pair of data than is currently
achieved with Sanger sequencing. Finally, this technique can be used to obtain significantly
more data from degraded DNA found in museum specimens.
< Panelist 2: They should be done at a larger scale to identify relationships and evidence of
ancestral polymorphisms in genes that are not interpreted as originating from interbreeding.
< Panelist 3: Further development of nuclear DNA markers (Panelist 4) and a large suite of
microsatellite DNA loci to fully characterize genetic diversity, relatedness, and levels of
introgression is necessary. Also, further study of East Slope green lineage fish is warranted.
< Panelist 4: NGS can be used to assay a larger proportion of the genome and develop
diagnostic markers. Despite suggestions, there is limited use of NGS for historic samples.
Also, see Panelist 3.
< Panelist 5: NGS could be used to screen markers and identify genes associated with
adaptations, identify nuclear data that would help to resolve the hypotheses surrounding
East Slope populations with green lineage haplotypes, and provide more information about
the distribution of genetic diversity across the Bear Creek genome.
< Panelist 6: Target single nucleotide polymorphisms (SNPs) only within the blue, green, Bear
Creek, and Rio Grande lineages which would help to distinguish among lineages (Panelist
11). Another option would be to obtain a much larger set of SNPs for individuals from the
four lineages in question (Panelist 13). This would provide more data and a greater
resolution of genetic relationships than in the first option. Also, NGS could be used to
reanalyze the museum fish from Metcalf et al. (2012) (Panelist 11).
< Panelist 7: Apply next-generation DNA sequencing on the cross section of known cutthroat
trout lineages. Use NGS DNA to assist with identifying source populations for genetic rescue
of Bear Creek and for monitoring recovery goals.
< Panelist 8: NGS should be used to address questions concerning the range of the green
lineage fish (specifically, the origin of East Slope green lineage fish) and test the six lineage
hypothesis generated from the mtDNA data. NGS should be applied to both museum and
contemporary samples (although the application to museum specimens will likely be difficult
due to lower quality of the DNA) (Panelist 11).
< Overall
Panelists generally agreed that next generation DNA sequencing could be used:
o
to examine additional independent loci to develop better phylogenetic relationships
(1, 2, 3, 5, 6, 8)
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o
to identify and verify nuclear markers and nuclear sequences that can be used for a
variety of purposes, including documenting genetic exchanges and during monitoring
of populations/broodstock (1, 2-7, 9, 12, 16)
Other responses worth noting:
o
costs can be prohibitive when used at a broad scale (4, 6, 8)
o
NGS could be used with museum specimens (1, 6, 8)
15. What are other prudent and reasonable management and research priorities for the species
given the outcome of these studies?
< Panelist 1: It is critical to continue to search the West Slope green lineage for mitochondrial
DNA haplotypes matching the East Slope green lineage (Panelist 14). Non-conservation
populations should be examined. SNPs should receive less emphasis until good nuclear
DNA phylogenies are developed for numerous genes (Panelist 3). Nuclear DNA phylogenies
must also be generated to strengthen the assessment of mitochondrial signals (Panelist 3).
The status of populations must be determined as accurately as possible now.
< Panelist 2: A full scale morphological study with finer level of evaluation of differentiation
within drainages should be conducted. Also, broader and more complete sampling of genes
for all of the lineages of cutthroat trout with finer level of evaluation of differentiation within
drainages.
< Panelist 3: Establish new populations of Bear Creek lineage in the South Platte River
drainage as soon as possible and protect Bear Creek from human encroachment (Panelist
6). Sustain a viable fish hatchery program for Bear Creek lineage fish. Evaluate pure and
experimental crosses of Bear Creek fish for inbreeding and outbreeding depression.
Evaluate the genetic and meristic status of East Slope green lineage fish once nuclear
markers are developed (Panelist 14). After identifying the status of East Slope green lineage
fish, identify the appropriateness of stocking Arkansas River drainages. Initiate taxonomic
revision of cutthroat trout in Colorado. Survey the San Juan GMUs for presence of red
lineage fish (Panelist 12). Scope a program to produce red lineage fish through
backcrossing. Assess threats to green lineage fish on the West Slope and maintain federal
listing as necessary. Assess the population status of blue lineage fish in the West Slope
drainages, continue demographic and genetic assessment, and prevent habitat degradation
and hybridization. Also see Panelist 1.
< Panelist 4: A comprehensive morphological study of historic collections should be conducted
including West Slope specimens (Panelist 7, 14).
< Panelist 5: See responses to other questions.
< Panelist 6: NGS analysis of museum specimens from Metcalf et al. (2012) should be a
priority. Develop a panel of SNPs from Dr. Shiozawa‟s NGS data or from additional RADsequence data. Resolve the West Slope versus East Slope and natural colonization versus
anthropogenic introduction theories surrounding green lineage fish. Quantify the inbreeding
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of Bear Creek lineage fish (Panelist 7). Perform genetic rescue of Bear Creek fish if
necessary. Increase the understanding of connectivity among populations of both blue and
green lineages. Test the likelihood of outbreeding depression in crosses among lineages.
< Panelist 7: Apply NGS DNA sequencing on the cross section of known cutthroat trout
lineages. Determine what existing cutthroat trout populations could be considered for mixing
with Bear Creek to increase genetic diversity and reduce deformities, while maintaining the
maximum Bear Creek genetic signature and meristics, based on DNA and physical
characteristics. Determine the level of DNA and meristics deviation that could be allowed by
the ESA under a beneficial Bear Creek hybridization program. See Panelist 4.
< Panelist 8: A broad phylogeographic look at cutthroat trout is needed. It should also be a
priority to survey the San Juan lineage.
Other Panelists
< Panelist 9: We should continue to manage these lineages at the GMU level while protecting
at least East Slope green fish until taxonomic uncertainty can be resolved. Research
priorities should include examining museum specimens to further assess meristic traits
among Bear Creek fish, green lineage fish and yellowfin cutthroat trout. More importantly,
fitness studies should be conducted to evaluate what the consequences (if any) might result
from limited genetic diversity in the Bear Creek population, and whether they are suitable for
large-scale reintroduction efforts. These studies are critical to inform whether genetic rescue
efforts are warranted.
< Panelist 11: The top priority is to establish some natural populations of Bear Creek fish in
either the Arkansas or South Platte River basins. The second priority is to assess the
degree of inbreeding depression in Bear Creek fish.
< Panelist 12: Meristic and morphometric studies of the San Juan and South Platte River
museum specimens would provide insight into which of the current lineages they are most
similar to and if they still exist (Panelist 14). Intensive inventories in the San Juan drainage
should continue in an effort to find an extant population of the presumed extinct San Juan
cutthroat lineage. Projects that eliminate non-native populations and replace them with pure
lineages should continue. See Panelists 3 and 9.
< Panelist 13: Extend genetic and meristics analyses to Colorado River cutthroat trout in the
rest of their historic range outside of Colorado. Also, use NGS with all intermountain
cutthroat trout at a finer scale (6 digit HUC).
< Panelist 14: Analyzing more East Slope green populations to see if the meristic differences
continue to consistently show the East Slope green populations as “different” will provide
evidence for whether DPS or another listing is warranted. In addition, further study on the
West Slope of both green and blue lineages is needed to inform their historic distribution,
especially for the Colorado River drainage. Also, see Panelists 1, 4, 9, and 12.
< Panelist 15: Reintroducing fish into the South Platte River drainage may be difficult because
of extreme population growth and past and current drought-related fire conditions. In order
to reintroduce Bear Creek fish into this area, a very thorough knowledge of land use,
productivity, and availability are needed. Criteria to identify recovery sites must be created
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also. One prudent research topic that should be pursued is to better understand the
phylogenetic relationships among different lineages. Also, given the variability in the Bear
Creek fish, we should look at the effects of placing fish in new habitats.
< Panelist 16: Resolve the West Slope and East Slope green lineage confusion. Test the
survival of different Bear Creek stocks overtime and differences in recruitment strength.
Evaluate the success of Bear Creek fish translocation into different habitats.
16. Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while
fish from eggs collected in the wild and reared in a hatchery often have noticeable
abnormalities; similar to, but potentially greater than some other stream and lake spawning
attempts east of the Continental Divide in Colorado. What conclusions can you make from
these findings and what inference to future management of the lineage can you predict?
What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
< Panelist 1: The Bear Creek population is expressing a higher proportion of deformed fish
that usually observed. It is possible that the deleterious genes causing deformities are in
such high frequency that it is not rapidly removing defective genes from the population. It
would be helpful to have the hatchery raised deformities quantified by conducting an
experiment with other green lineages or interior cutthroat trout populations (Panelist 9).
< Panelist 2: You cannot make conclusions about this from hatchery fish because there are
too many variables that cannot be controlled for.
< Panelist 3: The underlying causes of abnormalities warrant further study. Recovery of the
Bear Creek lineage requires it to be replicated into South Platte streams (with renovation
and barriers as needed) and existing fish in Bear Creek itself and in the hatchery program
are the only possible sources.
< Panelist 4: Potential issues could arise due to low genetic diversity and high-relatedness
(Panelist 16). Widespread propagation and stocking of Bear Creek should not occur.
Instead, a few isolated habitats should be conserved and replicated and a monitoring plan
should be put into place for population parameters and morphological characteristics.
< Panelist 5: Experiments to understand the deformities are warranted and important. If the
studies underway provide evidence for significant inbreeding depression, then some sort of
genetic rescue should be attempted, that involves controlled introductions over time.
< Panelist 6: Addressed under question 12. Further research into the deformities is warranted.
< Panelist 7: This was experienced in other cutthroat trout populations and was alleviated by
establishing broodstocks and then fertilizing hatchery-reared eggs with milt from wild
populations. Since Bear Creek fish are able to survive in current habitat limitations, they may
be successful in reestablishing new stream and lake locations.
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< Panelist 8: Inferences of the findings cannot be made because there has been no study that
quantifies the abnormalities and relates them to the environment. To better understand how
to produce viable populations, look for locations that share similar habitat features with the
Bear Creek drainage, such as water temperature. Given the need (in my opinion) to
replicate the population soon, it would be preferable to integrate the research into habit
needs with the replication effort. Researchers should monitor closely the relationship
between habitat features and the performance of the replicate populations.
Other Panelists
< Panelist 10: We should use caution when using this population for future production and
restoration. We can use techniques to maximize genetic diversity and further fitness-related
studies. Also, progeny of Bear Creek hatchery fish will be ready for stocking in the wild in
2014, and monitoring of the released fish will provide insight as to their survival in the wild.
< Panelist 11: This should be revisited after populations have been established to assess the
success rate and fitness. It is important for all manipulations of Bear Creek fish to be studied
so we can learn as much as possible about population establishment and gene pool
changes over time.
< Panelist 13: Bottleneck events likely played a role in the Bear Creek population and reduced
the genetic diversity of the population. Managers may also consider PIT tagging fish and
taking a “stud book” approach to spawning, check the motility of sperm from males, or track
the hatching success of each pairing.
< Panelist 14: It is still important to keep and replicate the Bear Creek population in several
locations with its current genetic make-up to safeguard this population. The long–term
management of this species likely cannot rest on the Bear Creek population alone but will
need to include a plan to systematically diversify targeted replicate populations by adding
one or more closely related individuals. The ongoing fitness study in the hatchery crossing
Bear Creek and green lineage fish should be replicated in a field. In addition, a study to add
diversity at a much lower introgression level, can be implemented and closely monitored.
< Panelist 16: These fish originated in a small founder population and future movements and
management will be very difficult. Future research may include introducing them into
different habitats to see where they survive best.
< Overall
Panelists generally agreed that it would valuable to quantify hatchery raised deformities
relative to other lineages or interior cutthroat trout populations and under a variety of
environmental conditions (1, 3, 5, 6, 8, 9, 11, 15).
17. Please provide other relevant comments not addressed in the above questions.
< Panelist 1: Geographic isolation is likely the primary evolutionary force in speciation of North
American obligate aquatic organisms. The Arkansas and South Platte River basin lineages
are confusing because they are similar but downstream connections were too far apart. This
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suggests a recent, possibly Holocene, transfer across a low order stream system. Similar
patterns are seen with other populations of cutthroat trout and other fishes in the west.
< Panelist 2: Overall, more data must be collected on all lineages in order to make sound,
scientific conclusions. Without the necessary data, a decision should not be rushed or else
the natural signature of the complex could be lost forever.
< Panelist 3: Several alternatives are available. First, nothing could be done and the Bear
Creek and East and West Slope green lineages would be protected. Second, the East Slope
green lineage could be designated as a DPS and could be managed as a separate
population from the West Slope. Finally, the Service could await a taxonomic revision, and
list the purple lineage as endangered under the ESA. Assuming the green lineage becomes
a listed subspecies, the East Slope could be a DPS under the ESA.
< Panelist 4: An overarching conservation goal should be to identify entities that encapsulate
biodiversity across the landscape. Many freshwater fishes of the northern hemisphere
represent recently evolved, sympatric lineages of uncertain taxonomic status, with
unrecognized taxonomic diversity perhaps greatest in salmonids.
Other Panelists
< Panelist 12: The current status of West Slope green lineage populations as “threatened”
requires federal agencies to engage in formal Section 7 consultation on all actions that may
affect one of these populations. The time and funding spent on consultation is a cause for
concern for federal agencies. Re-examination of the number of green lineage populations
may reveal that threatened status is no longer warranted. We need to generate a nontechnical summary of the workshop findings that can be shared with the public and with
managers in the various management agencies (state and federal). Agency managers who
are charged with making land management decisions need to understand the basic findings
from the workshop in simple terms. Specialists within each agency can then work with
managers to provide technical details as needed.
< Panelist 13: Precaution should be taken, but action should not be paralyzed by uncertainty.
We must act to conserve the Bear Creek population and replicate it in other watersheds. Rio
Grande cutthroat trout management should continue as it has been.
< Panelist 15: Maintaining current lineages and improving rare lineages is of more concern to
me than definitely understanding the historic connections.
4.4 Public Comments
A member of the OHV group attended the Workshop public session and expressed a general
interest in the research and potential management implications to the recreational users along
Bear Creek in El Paso County, Colorado. Written public comments were received from Trout
Unlimited and are included in Appendix F.
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5.0 Overall Summary
Unless otherwise stated, each conclusion was accepted by every panelist that mentioned this
item (there are several items that were not mentioned by one or more panelists).
< Rio Grande cutthroat trout are a distinct lineage and there are no revisions to historic or
current range, taxonomy or nomenclature.
< San Juan River drainage had a distinct lineage that is currently unnamed/unrecognized
and is likely extinct. There seemed to be general agreement that some field effort should
go toward confirming the lack of native (red lineage) cutthroat trout there now.
< Yellowfin cutthroat trout were the native trout to the Arkansas River and is now extinct.
There are no revisions to historic range, taxonomy or nomenclature. Most panelists felt
there were no other native trout to the Arkansas River drainage, but that was not a
strong consensus.
< Colorado River cutthroat trout (blue lineage) historic range was on the West Slope and
included the Yampa and White Rivers. The blue lineage fish on the East Slope were
stocked from the West Slope (Trapper‟s Lake). There was less agreement about how far
south the blue lineage fish occurred historically on the West Slope (i.e., Colorado River).
Generally, panelists also did not feel the blue lineage merited any special protection.
< Bear Creek trout are a distinct lineage and merit protection and significant efforts to
preserve the population. The majority of panelists did agree that the Bear Creek trout
were the remnant population representing the original South Platte River basin cutthroat
trout. There was not agreement about the priority management needs for this species,
although most panelists agreed for the need for experiments to determine if the
deformity rate is unusual for cutthroat trout generally and/or if they are result of hatchery
conditions. There was also general agreement for stocking Bear Creek fish into more
locations (with most agreeing that should be within the South Platte River basin).
< There was little consensus regarding the green lineage on any topic. All panelists agreed
that Gunnison, Dolores and the Colorado River on the West Slope included the historic
range of the green lineage. There was obvious disagreement about the green lineage on
the East Slope. Some panelists viewed the data as supporting stocking on the East
Slope; other panelists felt it supported complex evolutionary history, which may or may
not include stocking. Some panelists suggested the green lineage could be native to the
East Slope, most did not. All panelists agreed further study was needed to resolve this
issue with larger sample sizes and better understanding of the separation between the
blue and green lineages on the East Slope.
< There was not agreement on whether Bear Creek lineage or green lineage should be
considered greenback cutthroat trout and/or O.c.stomias. Ultimately, this issue for both
lineages cannot be resolved until pending taxonomic issues are resolved and a
taxonomic revision undertaken, as pointed out by several panelists.
< Panelists generally felt that both studies were high quality research and the data was
informative, but that the low sample sizes of the genetic study hampered drawing firm
conclusions about specific issues.
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6.0 Management and Research Recommendations
The panelists suggested a number of relevant research projects and management activities.
The following include a short of list of suggested research and management that were
suggested by multiple people and/or were suggested as priorities.
Suggested Priority Research Projects
< Taxonomic efforts to resolve common and scientific names including:
<
o
Revision of the historic range of O.c.pleuriticus
o
Establish common and scientific names for both the green lineage and the Bear
Creek population (purple lineage), with one of them retaining the common name
“greenback cutthroat trout”. This would be in conjunction with clarifying the status
of the scientific name O.c.stomias.
o
Establish common and scientific names for the San Juan river native cutthroat
trout (red lineage)
All panelists suggested additional research into the East Slope green lineage:
o
Additional assessment of current genetic status with larger sample sizes to
determine level of introgression with the blue lineage and whether there was any
introgression with yellowfin cutthroat trout prior to their extinction.
o
Additional sampling from West Slope green lineage fish to determine if there are
matching haplotypes
< Nuclear DNA research relating to:
o
Developing phylogenies among these lineages
o
Develop additional genetic information to provide better resolution among interior
cutthroat trout lineages
o
Develop nuclear DNA markers that can further clarify the relationship between
East and West Slope green lineage fish
< Many panelists suggested research regarding Bear Creek (purple) lineage:
o
Assess hatchery deformity rate relative to other interior cutthroat trout
o
Assess hatchery deformity rate under a range of hatchery conditions
o
Assess fitness of hatchery stock in a range of field conditions
o
Assess inbreeding and outbreeding depression
< Conduct additional field efforts to identify any remnant San Juan cutthroat trout (red
lineage) populations
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Suggested Priority Management Activities
< Protect and replicate the Bear Creek population. There were several ways proposed for
doing this but establishing additional populations within the South Platte River basin was
the most frequent suggestion after understanding and protecting the hatchery stock.
< Coordinate protection with the taxonomic efforts so that the Bear Creek population, in
particular, does not end up without protection.
< Coordinate ESA protection (via DPS or ESU designations) with the taxonomic revisions.
< Evaluate status of green lineage in particular after additional genetic research to
determine merit for protection under ESA.
(Courtesy Krieger Presentation at Workshop)
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�APPENDIX A
Agenda, Attendees and Suggested Reading for the
Greenback Cutthroat Trout Genetics and Meristics
Expert Panel Workshop
30 July – 1 August 2013
Lakewood, Colorado
��Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Dates: July 30, 31, August 1, 2013
Location:
U.S. Fish and Wildlife Service Office
134 Union Blvd.
Lakewood, Colorado 80228
Workshop Goals
1) Evaluate science of recent genetics and meristics studies. Reach consensus about
implications for management
2) Recommendations for future efforts
a. Additional research
b. Management activities
Workshop Agenda
Day 1 (July 30, 2013)
8:15
Welcome and introductions
8:30
Overview of the workshop objectives, agenda, and process
9:00
Presentation by Greenback Recovery Team – Context of Genetics and Meristic
Studies
9:30
Break
9:45
Presentation of Genetics Study (Metcalfe et al. 2012)
10:45
Recitation of Genetics Study discussion questions
11:00
Discussion of Genetics Study
12:00
Lunch
1:00
Presentation of Meristics Study
2:00
Recitation of Meristics Study discussion questions
2:15
Discussion of Meristics Study
3:15
Break
3:45
(Continued) Discussion of Meristics Study
4:30
Compilation of notes, comments, and recommendations by Workshop Panelists
4:45
Review of Day 1 findings
5:00
End of Day 1
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Day 2 (July 31, 2013)
8:15
Brief review of objectives and agenda for Day 2
8:30
Presentation by Dr. Shiozawa on his recent genomic analysis work
9:30
Discussion on Dr. Shiozawa’s presentation
10:00
Break
10:15
Overview and discussion of other relevant studies
11:30
Lunch
12:30
Sharing of comments from Dr. Behnke (Kevin Bestgen – presenting)
1:30
Discussion of Dr. Behnkes’s comments
2:30
Discussion of questions regarding areas of agreement/disagreement between
studies
3:30
Session Compilation of notes, comments, and recommendations by Workshop
Panelists
3:45
Break
4:00
Public Input
6:00
Review of Day 2 findings
6:15
End of Day 2
Day 3 (August 1, 2013)
8:15
Brief review of objectives and agenda for Day 3
8:30
Discussion of questions regarding taxonomic and management implications of
studies
10:00
Break
10:30
(Continued) Discussion on taxonomic and management implications of studies
11:30
Lunch
12:30
Discussion Questions
3:00
Break
3:15
(Continues) Discussion Questions
3:45
Compile notes, comments, and recommendations of Workshop Panelists
4:00
Review of Day 3 findings
4:15
Review of Workshop findings
4:30
Next Steps – Preparation of Individual Reports and Workshop Summary Report
5:00
End of Day 3 and Workshop
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Discussion Questions for Panelists
To discuss during workshop and to which each panelist will respond in writing after the
workshop. The responses will then be compiled into a summary report.
1. Does the meristic study correlate with findings in the genetics study (i.e, does the
meristics study show a difference in physical characteristics between blue lineage, green
lineage, Bear Cr, and Rio Grande)? To what extent are current spatial distributions of
GB, CR lineages known?
2. Do the lineages identified in the genetics and meristics studies rise to the level of a
listable entity
a. different subspecies?
b. distinct population segments (DPS)?
3. Are the conclusions reached in the genetics study (Metcalf et al. 2012), including the
identification of distinct cutthroat lineages and inferences based on historical stocking,
logical and supported by the evidence provided in this study?
4. How does genetic and meristic variation identified in the Studies compare with variation
in other cutthroat trout studies? Are levels of variation consistent with differences
observed across species, subspecies or ESUs in other cutthroat trout? Did the genetic and
meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
5. How should next-generation DNA sequencing approaches be used in Colorado River,
Bear Creek, Rio Grande cutthroat trout management?
6. The Bear Creek lineage exists as a single small population. What is the evidence for
limited genetic and meristic variability compared to GB, CR lineages? What are the
research priorities for the species given the outcome of these studies?
7. Do our genetic and meristic studies provide any resolution to probable routes of
colonization for green, blue, greenback and Rio Grande cutthroats?
8. Are the east slope - west slope variation seen for green and blue lineages significant?
What could lead to those differences and is there any taxonomic implications?
9. What do the rare haplotypes and morphological consistencies of east-green fish suggest
in terms of subspecies or ECU distinctions?
10. How should we address the nomenclature for O. stomias?
11. Is the Bear Creek population considered to be greenback?
12. How do we describe the east slope green lineage?
13. Could the “unusual” east slope green populations be a factor of native populations plus
stocked fish from Grand Mesa?
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Management Discussion Topics
14. What approaches, if any, should be considered to manage genetic variability in the Bear
Creek lineage to ameliorate potential or actual inbreeding effects?
15. What guidelines should be used to manage populations that show signs of introgression?
-
With non-native species, native species
16. Can existing blue or green restoration projects be converted to good representatives of
Bear Creek by stocking over blue or green populations?
17. Which cutthroat lineage or subspecies should be considered for reintroduction in the
Arkansas basin and for the San Juan basin?
18. In terms of population biology, what the implications of managing green and blue
lineages that are not in their native drainages.
19. Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while
fish from eggs collected in the wild and reared in a hatchery often have noticeable
abnormalities; similar to, but potentially greater than some other stream and lake
spawning attempts east of the Continental Divide in Colorado.
- What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
- What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the S. Platte
drainage?
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Documents for Distribution Prior to Workshop
Essential reading:
BESTGEN ET AL. In Prep. Meristics paper (draft available to Workshop members)
Brunelli, J.P., J.M. Mallatt, R.F. Leary, M. Alfaqih, R.B. Phillips, G.H. Thorgaard. 2013. Y chromosome
phylogeny for cutthroat trout (Oncorhynchus clarkii) subspecies is generally concordant with
those of other markers. Molecular Phylogenetics and Evolution 66:592-602.
HOUSTON. D. D., D. B. ELZINGA, P. J. MAUGHAN, S. M. SMITH, J. S. KAUWE, R. P. EVANS, R. B.
STINGER, AND D. K. SHIOZAWA. 2012. Single nucleotide polymorphism discovery in cutthroat
trout subspecies using genome reduction, barcoding, and 454 pyro-sequencing. BMC Genomics
13:724- 740.
LOXTERMAN, J. L., AND E. R. KEELEY. 2012. Watershed boundaries and geographic isolation: patterns of
diversification in cutthroat trout from western North America. BMC Evolutionary Biology 12:38.
METCALF, J. L., V. L. PRITCHARD, S. M. SILVESTRI, J. B. JENKINS, J. S. WOOD, D. E. COWLEY, R. P.
EVANS, D. K. SHIOZAWA, AND A. P. MARTIN. 2007. Across the great divide: genetic forensics
reveals misidentification of endangered cutthroat trout populations. Molecular Ecology 16:44454454.
METCALF J. L., S. L. STOWELL, C. M. KENNEDY, K. B. ROGERS, D. MCDONALD, J. EPP, K. KEEPERS, A.
COOPER, J. J. AUSTIN, AND A. P. MARTIN. 2012. Historical stocking data and 19th century DNA
reveal human-induced changes to native diversity and distribution of cutthroat trout. Molecular
Ecology 21:5194-5207.
PRITCHARD, V. L., J. L. METCALF, K. JONES, A. P. MARTIN, AND D. E. COWLEY. 2008. Population
structure and genetic management of Rio Grande cutthroat trout (Oncorhynchus clarkii
virginalis). Conservation Genetics.
ROGERS, K. B. 2010. Cutthroat trout taxonomy: exploring the heritage of Colorado’s state fish. Pages
152-157 in R. F. Carline and C. LoSapio, editors. Wild Trout X: Sustaining wild trout in a
changing world. Wild Trout Symposium, Bozeman, Montana. Available online at
http://www.wildtroutsymposium.com/proceedings.php
SHIOZAWA, D. K., R. P. EVANS, P. UMACK, A. JOHNSON, AND J. MATHIS. 2010. Cutthroat trout
phylogenetic relationships with an assessment of associations among several subspecies. Pages
158-166 in R. F. Carline and C. LoSapio, editors. Wild Trout X: Sustaining wild trout in a
changing world. Wild Trout Symposium, Bozeman, Montana. Available online at
http://www.wildtroutsymposium.com/proceedings.php
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Short summaries:
FWS. 2012. FWS Position Paper on ESA consultations on greenback cutthroat trout, including the
cutthroat referred to as Linage GB. Updated October 4, 2012.
ROGERS, K. B. 2012. Characterizing genetic diversity in Colorado River cutthroat trout: identifying
Lineage GB populations. Colorado Division of Wildlife, Fort Collins.
ROGERS, K. B. 2013. Recent developments in cutthroat trout taxonomy: implications for Colorado River
cutthroat trout. Colorado Parks and Wildlife, Fort Collins.
Historical perspective:
BEHNKE, R. J. 1992. Native trout of western North America. American Fisheries Society Monograph 6.
(no PDF).
BEHNKE, R. J. 2002. Trout and salmon of North America. The Free Press. (no PDF).
YOUNG, M.K. 2009. Greenback cutthroat trout (Oncorhynchus clarkii stomias): a technical conservation
assessment. [Online]. USDA Forest Service, Rocky Mountain Region. Available:
http://www.fs.fed.us/r2/projects/scp/assessments/greenbackcutthroattrout.pdf
Other species, similar issues:
CONNOR, M. M., AND T. M. SHENK. 2003. Distinguishing Zapus hudsonius preblei from Zapus princeps
princeps by using repeated cranial measurements. Journal of Mammalogy 84:1456-1463.
GOEBEL, A. M., T. A. RANKER, P. S. CORN, AND R. G. OLMSTEAD. 2009. Mitochondrial DNA evolution
in the Anaxyrus boreas species group – this is instructive because these toads were taken off the
“warranted but precluded list” after this came out.
Other interesting relevant bits:
BROSI, B. J., AND E. G. BIBER. 2009. Statistical inference, Type II error, and decision making under the
US Endangered Species Act. Frontiers in Ecology and the Environment 7:487-494.
DESALLE, R., M. G. EGAN, AND M. SIDDALL. 2005. The unholy trinity: taxonomy, species delimitation
and DNA barcoding. Philosophical Transactions of the Royal Society 360:1905-1916.
PENNOCK, D. S., AND W. W. DIMMICK. 1997. Critique of the Evolutionarily Significant Unit as a
Definition for “Distinct Population Segments” under the U.S. Endangered Species Act.
Conservation Biology 11:611-619.
WAPLES, R. S. 1998. Evolutionarily significant units, distinct population segments, and the Endangered
Species Act: Reply to Pennock and Dimmick. Conservation Biology 12:718-721
Other trout genetics papers to consider
ALLENDORF, F. W., AND R. F. LEARY. 1988. Conservation and distribution of genetic variation in a
polytypic species, the cutthroat trout. Conservation Biology 2:170-184.
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
BERNATCHEZ, L., AND A. OSINOV. 1995. Genetic diversity of trout (genus Salmo) from its most eastern
native range based on mitochondrial DNA and nuclear gene variation. Molecular Ecology 4:285297.
CRETE-LAFRENIERE, A. L. K. WEIR, AND L. BERNATCHEZ. 2012. Framing the Salmonidae family
phylogenetic portrait: a more complete picture from increased taxon sampling. PlosOne 7:xxxxxx.
HOHENLOHE P.A., S.A. AMISH, J.M. CATCHEN, F.W. ALLENDORF, AND G. LUIKART. 2011. Nextgeneration RAD sequencing identifies thousands of SNPs for assessing hybridization between
rainbow and westslope cutthroat trout. Molecular Ecology Resources 11:117-122.
HUBERT, N., R. HANNER, E. HOLM, N. E. MANDRAK, E. TAYLOR ET AL. 2008. Identifying Canadian
Freshwater Fishes through DNA Barcodes. PLoS ONE 3(6): e2490.
doi:10.1371/journal.pone.0002490
LARA, A., J. L. PONCE DE LEON, R. RODRIGUEZ, D. CASANE, G. COTE, L. BARNATCHEZ, AND ERIK
GARCIA – MACHADO. 2010. DNA barcoding of Cuban freshwater fishes: evidence for cryptic
species and taxonomic conflicts. Molecular Ecology Resources 10:421-430.
UTTER, F. M., AND F. W. ALLENDORF. 1994. Phylogenetic relationships among species of Oncorhynchus:
a consensus view. Conservation Biology 8:864-867.
WILSON, W.D. AND T.F. TURNER. 2009. Phylogenetic analysis of the Pacific cutthroat trout
(Oncorhynchus clarki ssp.: Salmonidae) based on partial mtDNA ND4 sequences: A closer look
at the highly fragmented inland species. Moleculat Phylogenetics and Evolution 50:406-415.
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Greenback Cutthroat Trout Scientific Review Workshop – List of Attendees
Facilitators
Dr. Tom Turner – University of New Mexico
Ms. Melissa Greulich – AMEC
Panel Members
Dr. Marlis Douglas – University of Illinois
Dr. Richard Mayden - St. Louis University
Dr. Jeffrey Olsen - FWS Conservation Genetics Program
Mr. Bruce Rosenlund - retired, FWS fisheries
Dr. Dennis Shiozawa – Brigham Young University
Dr. Robin Waples – Northwest Fisheries Science Center, NOAA Fisheries
Dr. Andrew Whiteley – University of Massachusetts Amherst
Agency Representatives
Mr. Dirk Miller - Representative Colorado River Cutthroat Trout Conservation Team
Dr. Kevin Rogers – Aquatic Research Scientist, Colorado Parks and Wildlife
Ms. Pam Sponholtz - Representative FWS Fisheries Program
Ms. Leslie Ellwood – Greenback Cutthroat Trout Recovery Team, FWS
Mr. Doug Krieger - Greenback Cutthroat Trout Recovery Team, Colorado Parks and Wildlife
Mr. Jay Thompson - Greenback Cutthroat Trout Recovery Team, BLM
Ms. Mary Kay Watry - Greenback Cutthroat Trout Recovery Team, NPS
Mr. David Winters - Greenback Cutthroat Trout Recovery Team, USFS
Dr. Andrew Martin – University of Colorado, Boulder
Dr. Jessica Metcalf – University of Colorado, Boulder
Dr. Kevin Bestgen – Colorado State University, Ft. Collins
Mr. Chris Kennedy – Fishery Biologist, FWS, Estes Park, Colorado
�APPENDIX B
Meeting Notes from the
Greenback Cutthroat Trout Genetics and Meristics
Expert Panel Workshop
30 July – 1 August 2013
Lakewood, Colorado
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
US Fish and Wildlife Service
Denver, CO
July 30, 2013
8:15 Introductions
8:20- 9:25 Doug Krieger: Presentation on the Purpose and Background of the Workshop
o Greenback Trout
Extinct in 1937
Rediscovered in 1973 and then listed as endangered
Threatened in 1978: Arkansas drainage discovered, rendered downlisting
o Greenback recovery team is comprised of:
USFWS
BLM
CDOW, now CPW
NPS
USFS
o Original distribution of trout species in the state of Colorado:
West slope: Colorado River
East slope: Greenback
South: Rio Grande
o Restoration of native cutthroat trout species:
Is difficult because many non-native species exist.
Involves restocking native species and then reevaluating progress.
Requires the sorting out non-native and native species. Yellowstone, Snake
River, and rainbow trout are the main species that hybridized with native
cutthroat species. Many techniques used to distinguish between different
species – shown in PowerPoint but not discussed in detail.
o Metcalf et al 2007: Molecular ecology discovered that native species were not
necessarily isolated to their original locations.
Results found that out of 9 east slope populations only 4 were actually of GB
lineage and 1 population in the west slope was of GB lineage.
The next step was to find out where populations were located pre-settlement.
o CU Genetic Study
Museum specimens were studied to see how historic populations now line up
with current population locations.
o Meristics Study – Kevin Bestgen at CSU
Genetics may not be the only way to distinguish what species are present;
meristics may also assist with distinguishing populations.
o Current understanding:
Colorado cutthroat is now NW part of state
Greenback is now west slop in Colorado river, Gunnison, and Dolores
South Platte is in the Central North part of the state
***Look at slides for before and after
It is important to figure out where to restock certain species in the correct places, which
should incorporate both historical data and current population locations.
Comments and Questions:
o Bruce Rosenlund speaks about the history of the program at US FWS. Historically,
fish that represented distinct populations were collected, including invasive species,
and then scientists blindly tested specimens and identified them. GB, Rio, and
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Colorado River all formed a large cluster and were hard to distinguish while others,
non-natives, were easily distinguished.
Question: What does the science say, and what should we do? Are these both
objectives of the workshop?
Response: The aim of the workshop is to come to a consensus of what the
science says and how we should apply the results. Another important
component of the workshop is to also identify the threats to cutthroat trout:
hybridization, land use, etc.
Comment: The question of what we should do does not really have a scientific
response.
Response: Individual opinions and consensus of what we should do should
be discussed. In the end it is up to FWS to make the final decisions about
what species to list. What entities out there should the FWS look at while
making that decision? That is the purpose of the workshop. Do any of these
threats qualify the subpopulations to be listed under ESA? Is the FWS being
overly protective? The aim is not to figure out what should be listed, but to
provide information to make the decision.
Comment: A participant attended a similar workshop before and panelists created a
single, cohesive report so that attendees’ responses to identified questions were not
tied to them. This was a concern because they were worried about their jobs.
Comment: Doing the cohesive, single report is not a good approach for this
workshop mostly because it is a violation of a law. We also would like to show
the diversity in responses from the array of attendees that have been brought
together to evaluate such a complex issue.
Question: What parts of these outcomes are parts of the public record?
The meristics study is not complete and Dr. Bestgen would not like it to be
distributed to the public until it is completely ready.
Comment: In previous reviews, a draft study has never been used, so this is
unfamiliar territory for the FWS with regard of what to do with panelist
responses to questions that could change when the draft meristics paper
changes.
Question: When we make the final report, will it be available to the public?
Response: Yes. There has been discussion of holding onto the summary
report until the meristics study is complete.
Concern was expressed about when the report comes out. The answers and
comments need to match the meristics study. What if the study changes and
then does not match the comments?
Question: Can panelists be listed as #1, #2, etc?
Comment: We should write a prelude to each section that describes the background
of each panelist that writes a response to assist readers with understanding where a
panelist is coming from in their interpretation and perspective.
Comment: We chose the variety of people here today because we wanted a
variety of perspectives.
Comment: We have enough scientific integrity to make educated statements
about the questions and that is why we were chosen. We do not need to state
our qualifications before each question.
Comment: Each person should evaluate whether or not they have enough
background to make educated comments on the questions. Don’t make a
comment if you do not feel comfortable with the subject matter.
Comment: It is important to remember that most of all, the workshop was created to
provide scientific expertise and disregard any politics of the situation.
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Question: Has the prohibition of any other groups from the discussion part of the
workshop been legally approved?
Response: Yes. The public interest groups understood the need for scientific
stakeholders to be the only ones present during discussions in order to make
the most progress.
o Question: Who is the public that will be invited?
Response: Some local advocacy groups, Trout Unlimited, etc.
Question: Aren’t there more stakeholders that should be involved other than
Trout Unlimited?
Response: Yes, there will be oil and gas and water groups that are
interested once the listing process starts.
Response: The listing process is completely separate and the public
will be included in that process as well. It will probably stimulate more
involvement.
Comment: Abbreviations and acronyms of different species should be cleared up before
discussions begin:
o Blue = CR, Colorado River
o Green = GB, Greenback
o Bear Creek = South Platte native GB, BC
Question: In the Houston et al. paper, some of the graphs have “GR”, should that be “GB”?
o Response: Yes, it should be GB
Comment: The discussion questions came together rather quickly because the meristics
report came out close to the workshop. They were created prior to discussions and therefore
may evolve with the process. The group organizers are open to additional questions and
edits to existing questions.
Comment: The definition of subspecies is very nebulous. Species complexes could also be
discussed and considered for the GB trout situation.
o Comment: Species complexes: hybrid species – 2 different species as parents. The
FWS discussed looking at this as a species complex. Zuni blue sucker example was
given.
o Comment: There is no time on the agenda to discuss exactly what a subspecies is,
and this is important for the topic. It is difficult to say if we could come to a decision
without discussing what a subspecies is, however this could take days.
o Question: Why doesn’t the group discuss lineage, which can be identified, rather
than species or subspecies?
Yes, the topic of lineage will be brought up many times
o Comment: From the FWS perspective, the agency often talks about what lineage is.
It doesn’t have to be 100% of one population, if it is mostly 1 type, then the agency
considers it that species. However, representatives of FWS would still like to hear
what the group thinks about what a lineage is.
Comment: If local populations are reviewed, there is much variation. The
concept of a lineage makes sense and most of the studies do discuss
lineage.
9:45 History of Cutthroat Trout Stocking in Colorado – Chris Kennedy
o Review of the Metcalf studies, but focused more on the 2012 paper.
o The 2007 paper found that the distribution changes in the east and west slope
primarily was from fish stocking.
o Conducted research on fish stocking records from the State Fish Commissioner
reports – 1889 & 1890
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1899 – 1943 Colorado state archives
1942-1972 CDPW kardex files
Ends up producing complete state archive of files
Federal files more difficult to find.
Overall, about 1.2 billion fish that were stocked in a 100+ period
About 245 million cutthroat trout, about 2.5 million/year
Peak of stocking in mid 1900, in the 1930s
This coincided with state agencies acquiring cutthroat trout eggs.
State cutthroat trout egg retrieval occurred between 1914-1940
Twin lakes – state had a hatchery, most of what was taken was put back into
the Arkansas River drainage
Most important Areas:
Trappers and Marvine Lakes – White-Yampa
Grand Mesa Lakes – Colorado and Gunnison
Emerald lakes - Upper San Juan
Federal – Leadville national fish hatchery 1899-1930
Most insignificant except for Grand Mesa Lakes, and Yellowstone
Grand Mesa Lakes
Gunnison river drainage, had cutthroat trout historically
Operated by Leadville national fish hatchery 1899-1909
State also collected eggs
Over 50 million eggs collected. 29 million restocked.
5 lakes primarily used for egg retrieval. Stocked rainbow trout into Ward lake.
Island
Ward
Eggleston
Barron lake
Alexander lake
Also stocked brook trout eggs to another lake – see ppt.
The private landowner, Radcliffe, gained control of the area to stock and
maintain fish in the area that contained all 5 lakes.
State took control of operations in 1913 and stocked Alexander, Barren, and
Island lake with rainbow trout.
Stocked trappers and Marvine lakes with cutthroat species later on.
Fish from Grand Mesa lakes area was stocked in almost every major
drainage in Colorado at some point by the federal government. The state also
stocked many of the drainages in the state with Grand Mesa eggs.
Also sold eggs to other states and countries.
Trapper’s Lake
White river drainage
Historically contained cutthroat trout
Eggs collected by the state in 1903.
26 million eggs collected from 1914-1925
Late 1930s stocked Yellowstone cutthroats
Marvine Lakes
White river drainage
Historically contained cutthroat trout
Egges collected 1907 to 1936
Eggs from Marvin and Trapper’s lakes
Almost every major drainage in CO received eggs.
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Emerald Lakes
San Juan River drainage
Historically fishless
Rainbow trout introduced before 1900, most fish suspect from these lakes.
Not a significant source of native cutthroat
CPW looked at fish and none showed similarities with San Juan
lineage.
Collected eggs 1898-1924
Records of Emerald Lakes egg distribution very vague and do not allow for
anyone to make conclusions.
In the hatchery, eggs are not fertilized. Fertilized on site, then taken and
distributed by the hatchery.
New Mexico vs. Colorado stocking
CO started stocking about 20 years before.
CO had 14 hatcheries operating while NM only had 1.
A lot less stocking occurring in NM. NM had more of an appreciation for their
native cutthroat trout species.
Read letter from game warden to fisheries resource operator at NPS
(Yellowstone).
o Letter from NM biologist stated they would only stock the
native, indigenous species to the NM water ways that are
more adapted to their waters and land.
Bear Creek Greenback Population
Every taxonomist has stated this population is different.
Bear Creek near Pike’s peak and CO Springs
In 1889, a scientist wrote that Bear Creek was fishless except for brook trout
1882, writing indicates that a man named Jones had a fish hatchery.
Beaver Creek, De la Verge Hatchery, and Bell Hatchery were nearby and
contained trout. Jones could have obtained his fish from these sites.
De la Verge Hatchery – had cutthroat trout. Newspaper article said
the man who operated the hatchery personally went to the mountains
to collect his trout.
Chris’s opinion is that Jones got eggs from De la Verge Hatchery.
Comment – peaks to Beaver Creek and De la Verge hatchery very
low and accessible by people, even in early 1900’s.
Summary:
CO leader in trout propagation.
See slides….
Question: How much did you miss? There was a lot of data to go through.
Response: There was a lot of private hatchery work prior to State and
Federal government work with fish distribution. However, these people were
out to make money from the trout. Now most of the native cutthroat species
exist at higher elevations, which indicates that they had to be stocked later
when roads and accessibility existed by the government and not by private
landowners.
Question: Are there any waters in CO that have not been influenced by stocking?
Response: There may be some smaller, individual waters. CO stocking was
massive. At one point, CO was the leading producing of the non-native
species brook trout.
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Comment: Stocking of eggs is so easy. Bestgen received bull trout eggs from
Montana in the mail.
Comment: Even back then, people would send eggs abroad on steam ships
and the eggs would survive.
Comment: It is nice to gain the historical opinion. New Mexico saw that native
species did much better than non-native species. Maybe this is also why
some of the southern CO pops are still native. Specifically, the native GB
population and Rio Grande population.
Question: Have you found anything about attempts to choose certain eggs from fish
hatcheries before dispersing them?
Response: No, they took whatever they could find.
Question: Is it safe to say there was a genetic bottleneck effect in the case of the
BC?
Question: What is the average fecundity of a female?
About 500-600/female back in those days
Comment: The mindset of the late 1800’s was more agriculturally focused. It is
important to remember this when analyzing the history of why they stocked the way
they did. There also weren’t regulations, fishing licenses, etc.
Jessica Metcalf – The Journey of Cutthroat Trout Genes in CO
o Conservation genetics
Issues arise when a population is extirpated before genetic analysis is
completed.
DNA analysis was conducted on museum specimens that predate events to
help establish baselines.
Ancient DNA is from post-mortem specimens. DNA molecules often decayed:
highly fragmented, scarce, chemically modified/mutated. Also easily
contaminated with modern DNA.
o Methods involve using DNA extraction and PCR in a facility that prohibits introduction
of other DNA samples.
o Purpose of the 2012 study:
Conducted a genetics survey of cutthroat trout species across CO to find a
genetic pattern that represents the subspecies.
Found support for 2 separate types of subspecies. Mitochondrial DNA used
to make 2 groups.
Question: Where is the Bear Creek population? Did you use K = 3?
o Response: We did, but ended up at K = 2. Can’t remember the
data. There is data that shows K = 3 is divergent
Question: How high up did you go up for K = analysis.
o Response: K = 10
Comment: If you do look at K = 3, the PDR could be a completely
different population.
Comment: At K=2, the result is more robust than the K=3, which was
much more variable between the 2 datasets (DNA).
Found 1 population with the green haplotype on the west slope.
Concluded that the locations are not likely due from natural
movements, but from historical stocking.
Blue was CR and Green was GB from this study.
New hypothesis started to be questioned. Chris began to research to see if
the natural locations could indeed be completely mixed up.
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Started to look for museum samples that predated stocking and found some.
2012 study
Sampling
Samples were from the CO and NM between 1857 and 1889.
Attempted to extract DNA from 44 individuals and successfully
extracted it from 30 samples.
Samples were fixed in ethanol, which allowed for easier extraction
than if specimens were in formalin.
Samples were from 5 geographically different areas of the S. Platte
River Drainage.
Sequence data
Only sampled mitochondrial data
DNA highly fragmented
o Subset of the modern DNA
o Question: Were they contiguous?
Response: Somewhat contiguous. They were looking
at areas where there was some variation between
subspecies and also where primers would adhere
easiest.
o Sequenced 6 mtDNA fragments
o Question: were you able to compare nucleotide sequences
from individuals?
Yes. Answer to question later on
o 430 base pairs analyzed
Replication
Many cases, multiple fish were sampled
For an individual specimen, multiple DNA samples were taken
For an individual specimen, multiple labs sampled the same DNA
For each sequence, multiple PCRs and sequencing were repeated.
Nine out of 14 samples from the S. Platte specimens had DNA that was
amplifiable.
Two samples were able to obtain 4 DNA extractions – example
An additional way to confirm amplification and DNA validity.
Degraded DNA bps quantity maxes out at about 200 bps.
Amplification of smaller bp segments easier than the large segments
for fragmented bps.
Results:
Most sequenced from S. Platte and Arkansas River Drainage.
Statistical parsimony network, 430 bps explanation
Eight fish from the S. Platte were the same
Question: Were the jars containing the specimens separate?
o Response: The jars were actually separated by project site.
Question: Of the 5 jars, how many haplotypes came from the same
jars?
o Response: S. Platte – 4 jars. There is a chance the DNA could
have contaminated other samples from the same jar. San
Juan drainage specimens – 2 haplotypes and from the same
jar.
Question: The network is not rooted, correct? How did the orange
become its own lineage? Andy will discuss.
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Results indicate that lineage can be explained by drainage.
S. Platte river drainage
Only 1 lineage found in the drainage
Represented as the “Bear Creek” lineage
Arkansas river drainage
Yellowfin and Greenback
Arkansas river – yellow, not found today, extinct
Green specimens in this area explanation:
o Green lineage could have crossed the continental divide
naturally OR
o Could be a result of a stocking event even though Chris did
not find evidence of this.
Underlying assumption of the research: historical specimens are from where
they actually say they are from.
Question: how high is the continental divide by the S. Platte and Arkansas
River drainage?
Response: Very high. Water diversions were also considered and
evaluated. No diversion in the area until 1932.
o Modern data as sampled the same amount of times as the historic data and
performed AMOVA. Conclusion was that there has been a significant decrease in
variation by drainage.
Only computed the unique permutations for the modern dataset.
o Question: Could you get the same result if the historic sample was not a random
sample? You focused the samples on certain places?
Response: No, we sampled everything that we could, but there could be a
bias with the collection sites from the original collectors of the samples.
o Question: Could it be that if more samples were taken from the historic specimens,
that lineages are actually more similar than divergent? Relating to the network
image, most of the black dots are much closer together than divergent with the
exception of the San Juan.
Andrew Martin – Addressed questions that are related to studies
o Structure plot for the number of K values assessed.
o K=3
BC clusters closer to Como
Severy may be a combination
Lack of variation or complete genetic divergence could explain the east slope
populations.
o Data for phylogeny on cutthroat trouts
Loxtermand and Keeley
Metcalf et al. 2012 – The relationships between the putative subspecies are
unsure. The larger triangles show the variation amongst a subspecies and
area spanned by the subspecies spatially.
o Uncertainty
The mitochondrial data from the 2012 dataset – mitochondrial DNA is
maternally passed down and cannot reveal admixed ancestry.
o Widespread stocking
It is possible that every population has been influenced by stocking, including
the Bear Creek population.
If Bear Creek is from admixed ancestry, you would expect it shares ancestry
with others
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�Some allele networks show that BC is fairly divergent from other pops.
Preliminary data shows that BC is not an admixture of other pops. Still
doing more research on this.
Bear Creek alleles are not strikingly different from other populations,
but there are alleles that exist in the BC pop that do not exist in any
other pop.
How many microsatellite data per locus
BC < 2
Stock populations < 1 allele
On average about 1.5 per locus
o Taxonomic revision
What is a species and a subspecies?
Is there separation in morphological space?
Can they reproduce?
Genetic/developmental cohesion
Comment: The relationship and overlap between mtDNA and nuclear DNA is very beneficial
for this study. If there is any more nuclear DNA that can supplement the mtDNA 2012, it
would be helpful.
Comment: Brunelli et al. paper – it would be good to talk about this paper and discuss how
the Y chromosome research is related.
Was ND2 used for a certain reason?
o Yes, used in Yellowstone studies before
1:00 Kevin Bestgen – Phenotype predicts genotype for lineages of native cutthroat trout in
the southern Rocky Mountains
o Metcalf et al 2007 and the antelope creek GB population created confusion.
o Revisited Metcalf research and results about population locations and distribution
o Purpose of Study:
Do the morphological characteristics support the genetic patterns found in
Metcalf?
US law supports using morphological distinction of species to identify and
subsequently protect species.
Can the three lineages be distinguished based on morphological
characteristics?
Compare the Geographic Model and Molecular Model to explain lineage
distributions.
o Methods:
Stream selection protocol:
Picked 3 populations from each geographical pop. Unit
24 or 12 fish per stream
Restricted to streams to reduce lake population influences that may
affect morphology
Picked streams that had some molecular data available
Also made sure that streams sampled had >150 fish/mile to eliminate
the possibility of reducing populations with low numbers
Conservation stream are those that have a certain percentage of trout
purity and therefore do not have many non-native species.
o No stocking history, etc.
o Some conservation streams were found they shouldn’t be
included in the database following the molecular analysis.
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Collection
Strict guidelines for protocols and samples taken (size limits)
839 specimens from 49 streams
Sample preparation
Transferred from formalin to ethanol
Data collection
Many morphological traits analyzed, only important will be discussed
Spot patterns: divided into 6 zones and counted spots by zone
Analyses
Variation of GMU’s could point out how the morphological traits are
associated with the landscape.
Population means used frequently in the past
Morphological analyses
DFA classify individuals or populationss by geographic or molecular models
and GMUs
DFA assumes groupings are equal prior to study
Molecular analyses
ND2 gene sequence used to assign pops to lineages
AFLP markers used for Yellowstone and rainbow
These used as screening tools to understand lineages and remove admixed
species.
Question: What about mixing green and blue?
Response: There wasn’t much contamination, but Kevin will look into
this more.
Response: Putative admixed GB and CR fish were not excluded from
the study, but unsure of how many pops.
Response: Some of the individuals were classified using the ND2 and
some with the AFLP markers were used.
Question: Do the colors fade after preserving the fish?
Response: Yes, but the blacks stay and are very distinguishable even
after preservation.
Results
Random selection was important – picking out the oddities to sample would
have skewed the data and resulted in a bad sample
Geographic coverage was good and spatially spread out
Blind protocol ensured no bias – when assessing the fish, was not sure
where the fish were from.
Replicated counts for the difficult traits
From the genetic information:
Only one blue lineage in the San Juan and Dolores
2 green lineages in the Arkansas
Censored populations
36 Bear Creek Fish
Irish Canyon Creek was eliminated – found to be all Yellowstone
cutthroat
Abrams Creek (25) changed from blue to green
AFLP censored individuals, >0.5% admixture
Molecular model
Blue : 24 streams
Green 14 streams
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RG 12 streams
BC 36 fish
Geographic
West 25 streams
East 10 streams
RG 12 streams
BC 36 fish
Variation for the sampled species extremely variable. Showed example of Rio
Grande cutthroat, which is one of the least variable of the 4 species. Variation
within species and between species.
Fin counts, spots are features that were found to be variable.
Trait comparisons
Lateral Series Scale Counts
o Bear creek and Rio Grande have lower lateral series scale
counts whereas Blue and Green have higher counts
o Between east and west slope species, not much difference of
lateral scale
Basibranchial tooth counts
o 61% of Bear Creek do not have them at all.
o Close behind, Rio Grande
o Green and Blue typically have more
o Still much variation within species, specifically in the Rio
Grande
Pyloric ceaca counts
Posterior gill raker counts
o Bear Creek – few
o Blue lineage- relatively more than others
Trunk Spots
o Green lineage and Rio Grande had lower numbers
o Bear Creek had higher number of spots
East and West trunk spots
o Relatively equal
Fore-caudal spots
o Rio Grande and green low
o Bear creek higher
Mid-caudal spots
o Green and rio grande low
o Blue high
Caudal peduncle spot size
% with spots on head
o Rio grande few
o Bear creek many
Multivariate data analysis
Geographical
Green and blue lineages very similar overall
Rio grande very different
Molecular model
Green lineage very broadly distributed and overlaps with the blue
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4 outliers of the green lineage populations are those that lie on the
east slope, which indicates they are much different from the other
pops on the west slope.
BC is very different, Blue different, Green and RG overlap
Question: For the PCA, in Table 3, even spot number and spot size are
correlated with length in every population. Does this have something to do
with size? It may have something to do with shape and size and would be
worthy of consideration.
Response: With the Bear Creek pop being smaller with less spots,
would mean that the BC pop would pull away more. There is
something else going on in PC1. The traits are not necessarily
attributed to size, which are fairly stable once measured on an adult
fish.
Comment: Size should not have an impact on PC1. A covariance was
run, but a correlation may be useful to run.
Question: Were the BC populations stunted at all?
Response: No they were just small, but not visibly stunted or skinny.
Hatchery fish were also in good condition, those that were not in good
condition were not used.
Evaluated the 4 east slope populations and compared to the west slope fish
Lateral series scale counts and trunk spots very different
Question: Meristics can be sensitive to temperature when developing. Is
there a consistent temperature difference between east and west that would
influence meristics?
Response: No climate data was taken.
Comment: A lot of the streams sampled are instrumented, so it is
possible to take data on such environmental factors.
Comment: Could use temperature and a regression model. It would
also be useful to integrate elevation too.
Comment: There have been studies that show temperature can alter
morphology when genetics may match up. Larval studies also have
shown that temperature can be an influence.
Question: Are there any morphological characteristics that are more impacted
by microhabitats, inbreeding, etc. Could you expect a broader phenotypic
variation than in others?
All GB populations on the east slope have 2 haplotypes, all GBs on
west side are different.
All the CR on east side have common trapper’s lake haplotype, but
the Blue in the west slope have another.
Multidimensional scaling could be used to assess environmental
influences on phenotype. Would be a powerful tool to analyze data
more.
Comment: In Mexican trout species, there is no correlation between the
amount molecular and morphological variation. Most species can be
distinguished more often with genetic analyses, but is often supplemented
with morphological data if available.
Geographic model
Bear creek and Rio Grande classify well
West slope classified poorly
Discriminant function analysis (DFA) - geographic
Workshop Meeting Notes – Day 1
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100% of east slope fish classified correctly
About 56% of west slope classified correctly, which indicates there
likely is another species that exists on the west slope.
Question: Why wasn’t the Bear Creek population included in the East slope
population?
They would not have classified as an east slope population because
they are so different. They would have been excluded because they
would have been seen as an admixed population. They would have
never been tested.
Molecular Model
Green lineage had the most individuals being misclassified
Bear Creek classified correctly most
Discriminant function analysis – molecular
Green again misclassified most
DFA completed within a lineage- how did a lineage classify within their GMU?
There are unique attributes of the populations within the GMUs.
Discussion
Bear creek are the most distinct populations.
It is difficult to compare BC populations to historical specimens to find any
differences and similarities.
The Rio Grande population is very distinct.
Morphologically closest to Green lineage fish
Populations are very structured around 3 major drainages
E and W slope populations:
Geographic models moderately support
East slope lineages, distinct between east and west slope pops
West slope – indicates there are at least 2
Blue lineage had the lowest variation among all traits and was also classified
correctly the most.
There was a high classification rate among blue, green and RG pops within GMUs.
Recommendations
Assess museum specimens
Additional samples – blue and green especially.
Front range Green populations need more research
Phenotype structuring present at watershed/ GMUs
Comment: Nanita fish picture from the US National Museum from Trapper’s Lake is
very similar to a presumed blue lineage fish.
Comment: In the paper, ¾ of the strange east slope fish don’t match up mtDNA. The
best explanation for those is that they have some type of mixed ancestry. It may end
up not giving any explicit answer of what type they are.
Question: Wouldn’t you expect this for blue also?
Response: Not necessarily, because the stocking in those areas
happened more recently, this would show more strongly in the genetic
analysis.
Comment: The unique east slope haplotype is not seen in the historic S. Platte
samples. Also, in the 1800’s FWS, train car service moved east to west via train,
including moving fish. Some correlation with the train lines and stocked waters close
in proximity to the trains has been noted.
Question: Why is the story for the greens not as straightforward?
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Comment: When doing a geographical model – greens and blues are combining on
each slope.
3:45 Continued Discussion of Meristics Study
o Question: Is there anything in the morphological data that shows BC data is
variable?
You would expect a bottleneck to reduce variation in a population, but the
data does not show the BC population is any less variable than other
populations.
Sometimes, asymmetry may be evaluated to see if there is any evidence of
inbreeding. Could this be done for the BC population?
You could do this for a small population; it is not out of the question.
o Question: How do the meristics and the genetics data correlate with one another?
In order to understand that, the group needs a better understanding of why
the genetics studies are showing different patterns?
The mtDNA and FLPs are showing different patterns
The biggest question is why the east slope shows so much variation. It
comes back to the historical stocking data and the realization that stocking
had a large influence on what we are seeing today. The mtDNA and nuclear
DNA comparisons show that the current species are of an admix ancestry.
The east and west slope GB are different especially when the blue
type are the same. Shouldn’t there be some sort variation in the blue
because they were also stocked?
Overall there is a lot more variation in the green lineage, in the
trapper’s haplotype, so this may be the reason why GB diverged.
An issue with the genetics study: we need to analyze alleles from the
outgroups and delete those alleles from the group being analyzed –
plesiomorphics traits.
o Question: Are we talking about a phylogenetic unit that diverged but never connected
again geographically? Or are we talking about a phylogenetic unit that is connected
and related but are just different from each other? Would most populations be
connected geographically or are there certain barriers that would completely inhibit
their transport to areas?
There are three basins that have confluences that would allow connections,
and unsurprisingly they have similar lineages.
QUESTION: When was the last time they could have crossed the continental
divide?
There are some scenarios where they could have crossed with recent
glaciation.
General consensus is that the events happened within the last 3 million
years. The possibility of incestral polymorphism is there. The other issue is
human induced changes. Gene flow amongst trout is not common. Could the
key question really be whether or not we need todistinguish natural from
man-made events?
There has also been a lot of tectonic movement that literally moved rivers. It
is difficult to say when these events took place and how to separate this from
human-induced change.
o Question: Another issue is how do we explain what alleles have been selected for?
Discussion of supergenes.
Workshop Meeting Notes – Day 1
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�o
Question: There is a strong geographical signal related to the GMUs. This is a good
indication that it is a natural signal. With there being so much similarity within GMUs,
this is a signal that the environment is playing a larger role. Although humans did
play a role, the environment prevails. Now that we have this diversity in the state, it is
what is present and is what we should manage for now. The question should be, how
do we manage what we have?
o Question: From the services’ perspective, how important is a geographically
confined entity for listing?
The ESA hierarchy is species, then subspecies.
Distinct populations segments also are looked at for ESA listings. Specifically,
discrete populations and ecological significance (up to interpretation).
It depends on the scientific community to determine subspecies/species and
the contribution of the population to the community as a whole – i.e. the BC
population is unique when compared to all other populations and would afford
a listing because it has scientifically been shown there are no other
populations like it.
o Question: If the BC population is distinct morphologically, but you do not have any
historical range data and it is up for protection, where do you conserve?
Metcalfe et al 2012 found that S. Platte is its historic range.
From the ESA perspective, you must not just show it is a unique population,
but also that there is a threat to its existence.
o Question: Why do we only see a few mitochondrial haplotypes within the S.Platte?
o Comment: The BC population has been used in hatcheries and individuals have
shown extreme incestral traits and are very difficult to cultivate. Many deformities,
etc.
o Question: When talking about such abnormalities, it suggests the population is
inbred and bottlenecked, which suggests it comes from a fairly large population. In a
small population, you would not see such abnormalities. It suggests Jones’ fish came
from the S. Platte.
o Question: Isn’t there some structure in the BC population? Lower and upper?
There are some very large waterfalls. Most of work has been done with the
lower population. Fish are capable of moving downstream but not upstream.
o Question: How do the abnormalities in Como creek compare to the ones seen in BC
hatchery raised fish?
In nanita and como fish, about 5% are abnormal in hatcheries, whereas the
majority of BC fish are abnormal when raised in a fish hatchery.
Environmental conditions can produce impacts in fish morphology and could
be to blame.
o Question: Are we following the BC progeny in the hatchery to see if they are dying
off?
Some of the fish are not making it due to deformities, but majority are doing
alright.
The group decides there is a general consensus that the BC lineage is something different
and actions need to be made to at least conserve this species.
Where we are now and what do we need to discuss in order to address the GB issue?
o Dennis Shiozawa: The difference between GB lineage between east and west slope
needs more research.
o Bruce Rosenlund: It was surprising how well the meristics study separated out the
blues, rio grandes, and BC.
o Doug Krieger: The quality of the studies is outstanding. It is interesting how we are
back to meristics after 30 years.
Workshop Meeting Notes – Day 1
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Leslie Ellwood: The meristics study is interesting. Looking forward to more
discussions on the green and blue lineages on greenback.
How many of the GB populations are linked to the Como broodstock?
It would be worthwhile to consider restoring genetic diversity within the existing BC
population to ensure stability and then distribute the population. We also have not
even brought up the issue of climate change.
The next question should be focused on what do we do about the science we
discussed today?
If BC is unique, are we coming to the consensus that it is the new GB cutthroat trout?
We spent a lot of time on discussing the green lineage, is that what we truly need to
discuss or should we redirect discussion towards the BC population?
Keep the big picture in mind.
Workshop Meeting Notes – Day 1
Page 16
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
US Fish and Wildlife Service
Denver, CO
July 31, 2013
8:30 Dennis Shiozawa: Cutthroat genetics – mtDNA, nuclear markers, and marker
development
o Cutthroat made of 8 major species and 12-15 subspecies. Subspecies are thought to
have started to diverge 12-15 million yrs. ago.
o Review of studies:
Behnke ’s hypothesis (2002). His view was developed by looking at
drainages in order to classify species.
Smith et al. (2002) phylogeny study. Developed through an older DNA-based
RFLP method. Shiozawa does not believe the O.c. clarki, O.c. utah are
placed correctly.
Wilson and Turner (2009). Used ND4. Dr. Shiozawa agrees more with the
phylogeny of this study.
Loxterman and Keeley (2012). Used ND2. Found “great basin” which is
actually Bonneville. Also distinguished Bonneville – Yellowstone, which is
actually Yellowstone.
Metcalf et al. (2012). Used ND2 and COI. More realistic with what the genes
are able to tell us.
o Compared mtDNA genes for O. clarkii vs O. mykiss and found differences in bps.
o Created a phylogeny based whole mitochondrial genome. O. mykiss and O. clarkii
were placed next to each other.
o Shiozawa’s study
3649 bp of mtDNA at 1000 reps
ND1, ND2, ATPase, Cytb
Issues with some “bootstrap” values, so reran with more bps.
Found the 8 cutthroat trout subspecies form well supported clades
Bear River form of the Bonneville cutthroat trout is a sister taxon to the
Yellowstone
Bonneville, CR, GB, and Rio Grande are sister taxa with strong separation
Two major cutthroat trout lines show strong separation
Two major polytomy
Can be explained in Benhke’s phylogeny tree
O. c. utah location in Benhke’s work is not supported by Shiozawa’s.
BC lineage was found to break off near the GB lineage rather than the
Rio Grande population.
o Timing of the splits – Molecular clocks
Project divergence times with 0.5% per million years
2.2 million Lahontan and west slope separate from each other
1.94 million RG, GB separate from Yellowstone and Bear River
o Hydrography history:
Lahontan and west slope were separated when Lake Idaho dried up
subsequently creating two sister taxa. Lahontan ended up being concentrated
near the Humboldt River and the West slope moved from the Snake River to
the Bear River.
o Split of Bear River from the Yellowstone taxa
Workshop Meeting Notes – Day 2
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2400 bps of mtDNA genes ND1 and ND2
Some Bear River haplotypes are found in Snake River drainage
Bear River population was found to be much more divergent earlier than the
estimated time period from the phylogenetic analysis.
GB species separation at around 1.15 million years ago, which means there should
be more diversity since the divergence occurred longer ago than the Bear River and
Yellowstone.
Good “bootstrap” values in phylogenetic tree ~ 92. Found GB and BC
lineages diverged from each other
Question: Did you explore other modes of max likelihood assessments?
Response: Yes, I did maximum likelihood and neighbor joining.
Question: What did you use to calibrate the clock?
Response: The calibration was mainly going through and speaking with Jerry
Smith. Before we publish this, we will go through and compare with fossil
dates. Really, right now there is no calibration so I compared with the CreteLafreniere paper as calibration.
Question: Where did you get the 0.5% per million years?
Response: It was more of a visual measurement based on values.
Question: What are you using as your mechanism for the split between Bear River
and Lahontan? Barriers?
Response: When you look at whitefish, they diverge much more slowly than
others. Behavior could play a role, migration specifically. Whitefish migrate
and move much more which limits the diversification and explains a lower %
divergence time/year. Trout/Salmonids, however, move, but then remain in a
location which would allow for more diversification. In the Bear River
situation, once the population reached the Snake River they remained
sedentary for a bit and diversified.
Question: There was a lot of diversification about a million years ago. What was
happening geographically that would cause GB populations to diverge?
Response: There was a glaciation event around 600,000 years ago. It is not
known exactly what was going on around that area. In the Great Basin area,
there were a lot of headwater stream captures that allowed fish to come in,
but not to leave. However, it is not known of what exactly happened in the
Rocky Mountain region at that time.
Shiozawa believes the CR is not of concern – distinct population. The GB lineage is
however not as straightforward.
Image of trout movement in the west.
Colored polygons represent species range.
Ribosomal DNA discussion
So specific to the organism, that one can almost identify the exact individual
by looking at it.
Currently they are doing work on creating ribosomal markers to better use
this method for identifying trout species.
Can Metcalf be tested independently?
Arkansas and S. Platte basins should have nuclear and mtDNA identical to
some of the source CO river basin populations
The contemporary GB basin of origin should have a greater diversity of
haplotypes.
Should look at CO River basin for haplotype diversity
Residual DNA from original lineages may exist in introgressed populations of
cutthroat trout.
Workshop Meeting Notes – Day 2
Page 2
�Can still look for this by doing quick scans with AFLPs. Then those
populations with residual DNA can be used to generate sequences.
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Tools
Analyzed 8057 bp of CO River and Arkansas River basin
Co River basin divergent from Arkansas River except for South Prong,
Hayden Creek population.
o Is this a product of invasion or stocking?
o This should be looked into, to see if anything does truly
represent Arkansas River drainage fish.
Question: You are saying that there were 2 invasions of the Arkansas
River Drainage?
o Response: Shiozawa’s sequences should be looked at to see
if more sequences can be replicated in the preserved fish.
Jessica should do this.
o Comment: You are a suggesting that there were multiple
invasions of different haplotypes?
Limitations
Study based on mtDNA, which is technically a single marker. This may not
reflect the entire history because the marker is only from one parent
(females). Nuclear markers are needed.
Development of New Markers
Next Generation DNA sequencing platforms used for a few methods:
Single nucleotide polymorphisms (SNPs)
o Aimed to obtain more markers that could be used to classify
trout.
o Method looks at several taxa and a single nucleotide, then
DNA is amplified and the nucleotide sequence is looked for.
o Recent studies did not completely cover cutthroat trout, so
Shiozawa lab decided to tackle this.
Transcriptomes using Illumina HiSeq 2000
Shiozawa SNP study
9 lineages of cutthroat and rainbow trout were reviewed.
Methods:
36 individuals sampled
Used EcoR1 enzymes from bacterial cells to cut DNA at restriction
sites, then removed smaller DNA segments by spinning DNA
samples, then ligated at sticky ends back together. Separated DNA
sequences according to MID barcodes.
Fluidigm – conducted over 9,000 reactions for 1 tray
o Allowed for classification of homozygous and heterozygous
individuals for a certain allele.
Results:
A total of about 29,000 SNPs were identified and 228 primers were
developed and run on Fluidigm chips. About 100 SNPs were
validated.
Separation of taxa
o West slope, coastal, Lahontan, and Bonneville separated out
easily
o GB not as clean of a separation
o Bear Creek fall in the same area as GB populations
Workshop Meeting Notes – Day 2
Page 3
�o A few GB populations fall in the CR populations
Question: What percentage of SNPs were variable within a subspecies,
compared to percentage of variability within a group?
Unsure, will have to look into this.
Question: Can you track which individual produced a data point on the
Fluidigm graphs?
Yes. Each point can be traced back to an individual.
Conclusions
This study has added diagnostic markers that can be used to
determine levels of hybridization and introgression. The process used
will be very helpful for management of natural resources when it is
necessary to distinguish between species and subspecies.
Future Studies
Markers have often been chosen because of their availability rather
than their ability to provide phylogenetic information.
Widely used genes have been developed using organisms that are
hard to adapt to non-model organisms.
Whole genome studies would be helpful, but are extremely expensive
and do not provide enough information to make management
decisions.
Comment: S. Prong Hayden population looks as if it lines up more with the
Rio Grande populations more than the GB population. How much of the data
is dependent on the choice of SNPs?
Response: It could change the data, and is an interesting point. We
chose SNPs that showed differences between the different groups.
This issue goes back to us needing to screen more SNPs or do more
research on the segments we chose. Additionally, we put in GB
populations that were actually intergressed populations, so it is
deceiving to look at them as pure GB populations.
Alternatives to SNPs study
Transcriptome: all of the RNA in a group of cells, i.e. muscle tissue.
Depends on the timing also because certain mRNA will be active at
different times of the year.
mRNA degrades very quickly once an organism dies.
o There are ways to counteract this process.
Results for the 3 cutthroat trout (Bear River, Bonneville, and Lahontan). A
total of 288 genes are promising for higher level of phylogenetic relationships
among Salmonids. 421 genes exhibit variation among cutthroat trout
subspecies. Can use this data to develop more SNPs that are more
promising for the previous methodology.
If the same species and populations are sampled at another time of
the year, additional SNPs could be identified because other mRNA
will be active.
Comment: The next generation sequencing is an extremely new method and the
work being conducted in present day will really help to shape future hypotheses.
Comment: Obtaining as many bps from 96 samples with the next gen
sequencing methodology ends up costing much less.
Comment: BC falls in between Rio Grande and Greenback, is this correct based on
your results?
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Workshop Meeting Notes – Day 2
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Response: Yes, that is what we concluded, but we would like to go back and
reevaluate.
Comment: It does not contradict the genetic or the meristics studies.
Comment: It is important to remember with the nuclear DNA, that there is natural
selection occurring, which does not occur with mtDNA. With the SNPs we have to
remember that selection may be a part of the equation.
Question: Jessica, what is the possibility of using next gen sequencing with museum
specimens?
Response: The genome is very fragmented, so the methods would have to
be a little different. Contaminants in the preserved specimens could impact
the results. It would be something that we would really have to plan and think
about. We would have to identify what modern data we would need, etc.
Comment: The SNPs have much lower mutation rate, which could be useful. If you
want fine scale structure within Colorado, then using 100 SNPs is providing less
information than fewer microsatellites.
Question: Does anyone know how far along the rainbow trout genome is? Around
80% complete as of now?
Question: Dennis, what is your thought on why these 100 stamps did not distinguish
coastal and rainbow?
Response: They may have been undersampled compared to the other
groups. It would be nice in future studies to get a much more robust range of
variation within groups.
1:20 Discussion of Dr. Behnke ’s work (statements attributed to him were compiled from
various sources for discussion)
o Discuss how the molecular model fits with the geographical model.
o Behnke : Reliance on ND-2 mtDNA unreliable and unstable, CO1 should be used.
Response: Unsure of why ND2 is not a valid tool for the GB trout purposes.
Comment: The rate of evolution for the time frame involved did not occur
quickly, therefore using the ND2 segment should not be an issue.
Comment: Maybe, by more unstable he means it changes more rapidly,
which would actually be more useful for our purposes.
Comment: General consensus that ND2 is fine to use in our issue.
o Behnke : Examine all hypotheses
o Behnke : Science is about confronting uncertainty with alternative hypotheses
o Behnke : We have to be careful with the use of mtDNA because all the confusion
with the DNA studies is bad PR for conservation of biodiversity. What does he mean
by this?
Comment: He is speaking of the 2 Metcalf studies that have differing results
and that the public perception of science may be tarnished because the
science has changed. However, that is how science works, but it does look
different to those who are not familiar with the process.
Comment: We should not rely solely on the newest data as the current truth;
we should look at all the research as a whole.
Comment: We also have to consider that Behnke ’s audience for decades
was Trout Magazine, and he was responsible for relaying the scientific
message to a huge audience. He also felt that the constant debate was
holding up conservation efforts; something could have been done for
conserving the species the whole time the debate has been going on.
o Is there a serious public relations problem with science?
Workshop Meeting Notes – Day 2
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We must use the best science and management at the time. Mistakes have
been made in the past, but it was the right decision at the time.
In ESA it states the best available knowledge must be used to make
decisions.
On the ESA protection side of the issue, patience is wearing thin. GB on the east
slope and GB west slope are being protected still temporarily until we come to a
conclusion.
Which units of Cutthroat are listed?
Greenback listed
Rio Grande candidate
Colorado River, not warranted for protection
Lahontan listed
There has been talk of doing some research on the existing populations while they
are still listed.
Practical management implications would be good to address tomorrow.
Behnke : We should shift from a typological species concept to a polytypic species
concept. This does somewhat regress thinking.
Typological concept is the thought that a species was created and exists for a
reason.
Discussion of the origin of subspecies and the complexity involved in identifying
subspecies (Rick Mayden).
Comment: Behnke has been right so many times that it would be unwise to
disregard his insight that has been developed from years of experience.
Comment: Bestgen’s study did disprove some of Behnke ’s results, and it is
completely understandable that Behnke missed the distinctions from
Bestgen’s.
Question: What were some of Behnke ’s comments with Metcalf 2007? Similar to
2012?
Yes, he stated molecular information isn’t the entire story and that there was
a lack of information.
He argued that with some population loss and ancestral diversity leads to the
mosaic we see across Colorado.
Also, we have lost a lot of populations and diversity that is is difficult to
determine what we are seeing today is not just an artifact of what was here
previously.
When Behnke first diagnosed a GB, which populations did he originally use? What
characteristics did he use to make this conclusion?
It isn’t totally clear what specimens he used to draw his conclusions.
2:15 Review and Comparison of Hypotheses summarized by Tom
o Geographic Hypothesis
Add: it is not just cutthroat trout that we can apply these hypotheses to, but
also across taxa. Drainage divides have often been used to explain fish
biodiversity in many species and regions.
This hypothesis also defines human impacts to the historical populations.
o Molecular-Historical Hypothesis
Metcalf et al 2007 – cannot discern stocking and natural events through
ancestral polymorphism.
The Bear Creek lineage is thought to only occur in the S. Platte and currently
exists outside of its natural range.
Workshop Meeting Notes – Day 2
Page 6
�How do we know that the Bear Creek lineage did not extend into the
Arkansas River drainage from the S. Platte drainage?
If so, this would put 3 potential lineages in the Arkansas.
We are fairly confident that the green lineage originally was a west slope
species, but whether or not it moved naturally or through stocking is the
question.
Green on west slope have the same haplotypes as the east slope, but
are a few bps different – Fact.
1889 sample had the same haplotype as two lakes in the east slope. They
could have naturally moved or could have been stocked. However, they are
not found on the west slope, and never were, which gives weight to them
being native to the east slope. Hayden is in the Arkansas drainage and is one
of the areas these fish were found, which is in the same drainage as the BC
population.
Green lineage on east slope discussion.
Despite admixture, these species have somehow have maintained
their integrity.
Bestgen et al. Molecular data was stronger than the geographic
range. However, the geographic distinctions still dictate the
populations.
o Geographic Management Units (GMUs) – Hierarchal Analysis of Variance
These hypotheses gradually are divided into smaller pieces (Geographic to
Historical/molecular to GMUs).
Can we put together a list that summarized findings?
o Facts that no one can dispute.
o Generally accepted scientific findings that are not (yet) disputed.
o What are the disputed scientific findings?
Interpretations of data that do not match
Findings that do not coincide between studies
4:35 Public Comment period/Richard Mayden : Species Concepts
o Classes:
Artificial classes do not participate in natural processes
Natural classes participate in natural processes
o Individuals vs. Classes
Individuals can only be described but not defined like classes. Classes have
characteristics that define them.
o Natural vs. Artificial classes
Natural classes have many definitions because they participate in natural
processes that regularly alter their state.
o Species: Individuals vs. Classes
Species category of monophyletic trees change with time because species
evolve. Kingdom through Genus do not follow the same changes
o If you treat species as a class, they do not change over time. If treated as individuals,
they will show change with time.
o Concepts: Evolutionary Species Concept is a theoretical concept that maintains
lineage over time.
o In order classify, multiple species concepts must be used to catch all biodiversity.
Each concept individually misses species.
o Question: What is the utility of lineage vs subspecies vs species?
Workshop Meeting Notes – Day 2
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Response: Under this paradigm, subspecies just do not exist. Lineages exist
and are species. The suckers and trout are classified differently even though
they have completely the same distribution. Suckers are species, trout are
subspecies.
o Question: A lot of management occurs at the population level, but the ESA
addresses species. Distinct populations are more flexible than classifying entities as
species. Working together and relaying correct information to the management
agencies from the scientists in key. A lack of this communication has led to many
mistakes in management history.
o In ESU guidance:
Based on best scientific information
Sparingly use distinct population segments
DPS should add up to a species
Collectively, each one is a piece of diversity and if one is lost, the
species is lost.
Aldo Leopold – if biodiversity is going to be altered, the pieces that
make up the whole must be preserved.
However, how small do you go? What constitutes a DPS?
Conserving genetic diversity
Final Discussion
o Break management and scientific questions up.
o Are there pressing management questions that are not on the list?
o Any additional questions that need to be addressed should be sent to Leslie.
Workshop Meeting Notes – Day 2
Page 8
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
US Fish and Wildlife Service
Denver, CO
August 1, 2013
Revision of ―Factsheet‖
o Facts
Subspecies of cutthroat trout historically have been defined largely by
geography—major drainage basins.
Extensive transfer of cutthroat trout through stocking occurred for more than a
century.
o Transfers primarily occurred from West to East. Primary sources were
centered around the White River at Trapper’s/Marvine Lakes (blue
lineage) and on the Grand Mesa (green lineage) at the headwaters of the
Gunnison.
Como creek, Hutcheson Lake and Como creek/Hunter’s/South Fork Poudre
crosses were historically used to stock recovery populations in the S. Platte
drainage to establish new pops of presumed greenback.
Cascade creek was used to stock recovery populations in the Arkansas River
drainage.
Yellowfin declared extinct by 1904.
Greenback declared extinct in 1937. From the 1950’s to the 1980’s, populations
thought to be greenback cutthroat trout were found. Listed as endangered in
1973. Downlisted to threatened in 1978.
Bear Creek haplotype matches the museum specimens from 5 locations within
the S. Platte drainage.
As the first reviser, Jordan coined the term ―greenback‖ for native trout in the S.
Platte and the Arkansas drainages.
Historic reference materials were collected from 1856-1889 and are available to
past and current researchers.
Morphological variation of historical specimens is largely unknown.
All lineages on the east slope are currently listed as threatened, green lineage on
the west slope are threatened, and blue lineage populations on the west slope
are not protected under ESA.
Rio Grande cutthroat trout are a candidate species for listing under ESA.
o
Generally accepted (or at least not yet disputed) findings
Habitat quality at Bear Creek has been compromised by sedimentation.
Bear Creek and Como Creek fish appear normal in the wild, but exhibit serious
deformities in the hatchery.
Current data supports at least 4 extant lineages of cutthroat trout in Colorado.
o mtDNA and meristics/morphometric studies are congruent in supporting
this.
Bear Creek is upstream what appears to be a one-way barrier to upstream
migration of cutthroat and was presumed to historically be fishless.
In samples analyzed so far, green lineage mtDNA haplotypes are found on both
sides of continental divide. The two most common east slope haplotypes are not
found on the west slope.
Blue lineage mtDNA haplotypes are found on both sides of the continental divide.
East slope haplotypes are a subset of what is found on the West slope and are
limited to haplotypes currently found in Trapper’s Lake.
Workshop Meeting Notes – Day 3
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�o
o
Most green and blue lineages are separated by barriers. Most barriers are
natural, but some are man-made. Populations above natural barriers are
likely present from stocking.
o Green lineage fish are not found in the Yampa or the Green River drainage.
The type specimens for O. c. stomias have a haplotype found in Rio Grande
lineage.
o Hammon’s collection notes suggest that the type specimens were likely
collected from the Rio Grande drainage.
Geological and other evidence indicates stream-capture events across the
continental divide occurred during the Pleistocene.
Meristic/morphometric analyses show consistent differences between groups
defined by mtDNA haplotypes. Patterns were stronger when individuals were
grouped according to genetic lineage than when grouped according to
geographical hypothesis. Meristic differences were also apparent at the level of
GMUs.
The green lineage East slope fish show meristic/morphometric differences from
the West slope green lineage fish.
The blue lineage fish on the East slope show meristic/morphometric differences
from the West slope blue lineage fish.
The blue lineage fish currently present on the west slope are presumed to have
originated on the west slope.
Some conservation populations show evidence of introgression from Yellowstone
cutthroat trout and rainbow trout. Conservation populations are populations that
count towards recovery.
Key Questions to Resolve:
Can ancestral polymorphism be distinguished from historic stocking influences
on populations with our existing analyses? If so, how? IMA, other programs, or
evaluation of nuclear genes?
The appropriateness of using ND2 and CO1.
Are the green lineage fish on the East side of the divide are a result of stocking
or natural processes?
What is the level of inbreeding in the Bear Creek population?
Is Bear Creek representative of historic populations in the S. Platte drainage?
o See point in the Facts section.
o Use of next generation sequencing of museum samples and the meristics
study would help to verify this.
The green lineage fish currently present on the west slope are presumed to have
originated on the west slope.
What is the phylogenetic relationship among cutthroat trout lineages?
o Additional character information should be obtained.
Review of Questions:
o Management Question 14:
K. Rogers: Costs of the bottleneck were assessed. 4 female BC and 4 green
lineage eggs were fertilized. Offspring were evaluated for survivorship,
morphology, movement patterns, etc. Lab data are still being collected and
evaluated. This should help to determine if there is a problem with the
bottleneck and will help to guide what actions are taken to manage the BC
population. It will help determine if we should disperse BC individuals in the
S. Platte and risk possible inbreeding with green lineage fish.
Workshop Meeting Notes – Day 3
Page 2
�
Comment: Cannot answer this until we know what the level of inbreeding is in
the population. It is premature to try and answer this until we know if there is
indeed inbreeding depression in the BC population.
Comment: Currently, data suggests that this population
Question: So is this the O.c.stomias population then? What is the ―green‖
lineage population?
Yes, BC=stomias, green population is unnamed.
Answer: Whitely: If the BC is indeed the last and there is no sign of
inbreeding, I propose that we replicate the population over the landscape.
Tom agrees.
Comment: Another thing to consider is that the hatchery fish are very
different from the wild population: hatchery population had different avg.
spots and had basalbrachio teeth, whereas the natural populations had no
teeth. We could use wild, hatchery, or a combination of the two to create wild
populations. The hatchery fish are F1 generation, so they are not too
removed from the wild populations.
Question: Are the temperatures in the hatchery comparable to the wild
populations?
Yes, they are almost identical.
So there must be some other factor affecting the BC hatchery fish.
Question: Is the BC wild population suitable on its own to propagate with the
populations low genetic diversity?
Response: Given that BC only represents a small fraction of what was
actually present historically, do we want to use the current population
or try and back up the genetic clock to try and diverse the population.
Question: Do we want to keep the wild BC population ―pure‖?
It would be smart to replicate the existing population in several
streams and other waterways to have it present, but also create a
population that is more robust and diverse, then compare.
Question: are there candidate streams?
Yes.
The FS is working on quantifying suitable habitat for the BC pop.
Question: Is there concern with putting a stream fish in a lake? Selection
issues?
Yes, in the long term, but with our current situation it wouldn’t really
affect the population other than the size of fish. A priority is to
replicate the populations soon, and the use of a lake would allow for
this; potentially use of Zimmerman Lake.
Monitoring of inbreeding impacts in new wild populations would be a
priority. Comparison of any signs of inbreeding in both wild and
hatchery populations would be very valuable lesson.
Comment: The morphology of the BC are so different that it would not take
long to compare samples to historic samples in order to conclude whether or
not BC was the historic cutthroat trout in the S. Platte.
Question: Is a recovery plan in place?
No, the taxonomic classification must happen first, but there will
definitely be a recovery plan.
Question: Should there be some consideration of artificial connectivity to help
disperse the BC populations? I’m not a fan of anthropogenic/unnatural
connections, but it is a consideration.
Workshop Meeting Notes – Day 3
Page 3
�
Question: Concerning climate change, are you more concerned with
waterways being altered in the north?
Yes, it is a big concern with Rio Grandes because they are so high up
and waterways at higher elevations are expected to decrease the
most.
Management Question: What guidelines should be used to manage populations that
show signs of introgression?
o
o
o
o
o
With non-native species, native species
Changed question to ask about populations rather than lineages.
Added question about introgression with non-native and native species introgression
with the native species.
Question: How many populations are left that are considered to have introgression
with non-native species (rainbow and Yellowstone)?
A lot. More on the west slope, east slope has less.
Comment: A lot of populations reflect the history of people affecting the landscape.
Managing species for the historical stocking history is an interesting concept and I
would not completely wipe out what was created from stocking.
Would you completely wipe out the Yellowstone and rainbow then?
We should not wipe out admixed populations until we know whether or not
they were indeed created by stocking or natural processes.
Question: What is known about the historic life history of these species?
Yellowstone have an extensive life history
If we look at the populations we have now, we have relatively sedentary
populations and that is why you see some gene flow between populations
that are mobile.
Management Question 16: Can existing blue or green restoration projects be
converted to good representatives of Bear Creek by stocking over blue or green
populations?
o Does anyone have a proposed hypothesis to explain the blue and green distribution
the west slope (Figure 2 from Rogers 2013)?
The upper Colorado basin is a place where both the blue and the green
lineages could have both naturally have been present.
This hypothesis is consistent with saying blue and green lineages were split
between southern (green) and northern (blue) in the west slope, with a
separate population in the San Juan drainage and possible admixing in
between in the Colorado drainage.
o Another option would be to stock upstream and let individuals trickle downstream
and naturally let mixtures occur, but maintain natural populations upstream.
o A few ESA deliberations:
Should the BC be listed as endangered?
If the blue and green lineages are separate entities, should they be listed?
Must look at threats to the smaller green lineage group.
o How much does the ESA stick to taxonomy? This will determine how specific we are
with management and listing of a species.
The blue and the green are more different than the blue and the west slope
greens are alike. It would make more sense to list the east and west slope
Workshop Meeting Notes – Day 3
Page 4
�greens as a package and the blue separately rather than separate the greens
and blues by east and west slopes.
Management Question: Which cutthroat lineage or subspecies should be
considered for reintroduction in the Arkansas basin and for the San Juan basin?
o
o
Arkansas River drainage:
Currently, BC are present, but thought to originate in the S. Platte and there
is no evidence showing that BC were historically present in the Arkansas.
It is much harder to remove cutthroat and replace with other cutthroat down
the road than to replace brook with cutthroat. We should be absolutely sure
that the Arkansas is BC range before we restore it, otherwise down the road
we will be in the same predicament we are in today.
Green lineage should be considered for the Arkansas because there are
historic populations that were present. This could however be a result of
stocking because they were found at Twin lakes, which was heavily stocked
in 1889.
Our priority should maybe turn immediately be turned to the S. Platte, where
we know what populations should be there – BC. Maybe we should hold off
on the Arkansas drainage until we find more information before we make any
decisions about the Arkansas. Be cautious.
Could this impact the green lineage populations in the S. Platte if we
find out later that they are unique?
San Juan drainage:
How confident are we that we have sampled enough to determine that the
San Juan lineage is not present?
Not confident.
Then, the plausible solution to this would be to sample first to see
what is there and then determine what should be there.
Are reintroductions being occurred in the San Juan?
Yes, by Durango there is a blue reclamation that is occurring and has
been going on for a few years. It has halted now until further
developments are made.
Does the upper San Juan near the Lower Colorado basin, have suitable
habitat?
Yes, there is a lot of suitable habitat.
It was suggested that the area should be extensively sampled to be
sure there is not a population that drifted up there.
Action Item: It would be helpful to have a 1-2 page document that can be understood by
managers to explain what was discussed and the decided conclusions. For the USFS and
BLM. This would maybe be completed by the US FWS.
Meristics Study and Workshop Summary Report Issue:
o Kevin and Kevin will talk and estimate how long it will take to finish their study and
report.
o The summary report should not be shared with anyone outside of the working group
until it is finalized and published.
Trout Unlimited may push the report and the listing.
Workshop Meeting Notes – Day 3
Page 5
�o
We are certain the BC population needs to be listed, but unsure about the green and
blue lineages. TU needs to be talked to and told a better ―package‖ will be developed
if given enough time.
o There is interim protection for the green lineages and many oil and gas projects are
underway and consulting with FWS currently. There is some urgency because of this
issue.
Biodiversity Implications: Listable Entities?
o Do lineages identified in the Genetics and Meristics studies rise to the level of a
listable entity? Different subspecies, distinct population segments, other?
Currently, all listings are to the level of subspecies. We did not hear anything
new at this workshop regarding listing subspecies. Now, all we can do is
compare subspecies.
For DPS, the framework is very similar. We could go through the framework
and discuss in this context, but currently, cutthroat trout are discussed by
subspecies.
Significance to the taxa, range, must occur in a unique ecological
setting, differs markedly in genetic characteristics.
The blue and green lineage distinction is validated by both studies, can they
be thought of as two separate species?
How different are the green and blue from other cutthroat species?
o If they are different lineages, they are different lineages.
Listing the east and west slope green lineages could be listed as two
separate DPS – suggested by Susan Linner.
West slope blue is a monophyletic individual entity, strongly defined
by meristic and genetic data.
The difference with the blue and green issue is that the green needs
taxonomic revision because it is not pleuriticus.
In the end, does it really matter that we call BC stomias? The point is not
what we call it, but that we protect it.
o Where we currently stand is 3 distinct lineages: BC, Blue, and Rio Grande.
Is the BC population considered to be the Greenback cutthroat trout?
o Jordan originally named stomias as ―greenback‖, which means large spots. It seems
to reference the Rio Grande lineage, however the museum specimens of stomias
and virginalis were mixed up. Although he may have been naming a lineage that did
not originate in the area, the name should stay with the lineage that it was associated
with by the first reviewer, which is Jordan.
How do we describe the East Slope Green lineage?
o It at least should be a DPS.
What do rare haplotypes and morphological consistencies of east-green fish suggest in
terms of subspecies or ESU distinctions?
o There is sufficient evidence to say that a DPS that can represent the east green fish.
o There are 2 haplotypes on the east slope that are not found on the west slope,
although only a few bps off. The meristics study suggested they were much more
different.
From an ESA perspective, Steve Chambers suggested it is easier to list more, then delist,
rather than try to additionally list something later.
o Susan Linner responded that it is not easier from a work load perspective.
Common name reference that should be used for populations:
o Green
o Blue
Workshop Meeting Notes – Day 3
Page 6
�o Rio Grande
o Bear Creek
In responses to the questions, panelists will create a small glossary of the terminology used.
Evaluation of the Science questions
o Are the conclusions reached by Metcalf et al. (2012), including the identification of
distinct cutthroat lineages and inferences based on historical stocking, logical and
supported by the evidence provided in the study? Are there other alternative
interpretations?
What are the historical distributions?
What is the stocking history?
What do people think of the ―fishless‖ inference of Bear Cr?
o How does genetic and meristic variation identified in the studies compare with
variation in other cutthroat trout studies? Are levels of variation consistent with
differences observed across species, subspecies or ESUs in other cutthroat trout?
Additional questions or topics
o Could post on the Greenback cutthroat trout recovery page that the panel was held
and is finished. Also post an estimated timeline. Same goes for the CR cutthroat
recovery team.
Workshop Meeting Notes – Day 3
Page 7
�APPENDIX C
Greenback Cutthroat Trout Genetics and Meristics
Expert Panel Review
Discussion Questions and Fact Sheet
��Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Discussion Questions for Panelists
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct
cutthroat lineages and inferences based on historical stocking, logical and supported by the
evidence provided in this study? Are there alternative interpretations?
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics
study show a difference in phenotypic characteristics between blue lineage, green lineage, Bear
Cr, and Rio Grande)?
3. To what extent are historical spatial distributions of green, blue lineages known?
4. How does genetic and meristic variation identified in the studies compare with variation in
other cutthroat trout studies? Are levels of variation consistent with differences observed across
species, subspecies or ESUs in other cutthroat trout?
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support
their assumptions/arguments/conclusions?
BiodiversityImplications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
b. distinct population segments (DPS)?
c. Other?
7. Is the Bear Creek population considered to be greenback cutthroat trout?
8. How do we describe the East Slope green lineage?
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish
suggest in terms of subspecies or ESU distinctions?
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for
green, blue, greenback and Rio Grande cutthroats?
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What
could lead to those differences and are there any taxonomic implications?
Panelist
Page 1
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited
genetic and meristic variability compared to green, blue lineages? What approaches,
if any, should be considered to manage genetic variability in this lineage to ameliorate potential
or actual inbreeding effects?
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat
for the Arkansas River basin?
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear
Creek, and Rio Grande cutthroat trout management?
15. What are other prudent and reasonable management and research priorities for the species
given the outcome of these studies?
16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while
fish from eggs collected in the wild and reared in a hatchery often have noticeable abnormalities;
similar to, but potentially greater than some other stream and lake spawning attempts east of the
Continental Divide in Colorado.
-What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
-What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
17. Please provide other relevant comments not addressed in the above questions.
Panelist
Page 2
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Fact Sheet (for use with Discussion Questions)
Historical Summary
Subspecies of cutthroat trout historically have been defined largely by geography—major
drainage basins.
Extensive transfer of cutthroat trout through stocking occurred for more than a century.
o Transfers primarily occurred from West to East. Primary sources were centered around
the White River at Trapper’s/Marvine Lakes (blue lineage) and on the Grand Mesa (green
lineage) at the headwaters of the Gunnison.
Como Creek, Hutcheson Lake and Como Creek/Hunter’s/South Fork Poudre crosses were
historically used to stock recovery populations in the S. Platte drainage to establish new
populations of presumed greenback cutthroat trout.
Cascade Creek was used to stock recovery populations in the Arkansas River drainage.
Yellowfin cutthroat trout declared extinct by 1904.
Greenback cutthroat trout declared extinct in 1937. From the 1950’s to the 1980’s, populations
thought to be greenback cutthroat trout were found. Listed as endangered in 1973. Downlisted to
threatened in 1978.
Bear Creek haplotype matches the museum specimens from 5 locations within the S. Platte
drainage.
As the first reviser, Jordan coined the term “greenback” for native trout in the S. Platte and the
Arkansas drainages.
Historic reference materials were collected from 1856-1889 and are available to past and current
researchers.
Morphological variation of historical specimens is largely unknown.
All lineages on the east slope are currently listed as threatened, green lineage on the west slope
are threatened, and blue lineage populations on the west slope are not protected under ESA.
Rio Grande cutthroat trout are a candidate species for listing under ESA.
Generally Accepted Findings (not currently in dispute)
Habitat quality at Bear Creek has been compromised by sedimentation.
Bear Creek and Como Creek fish appear normal in the wild, but exhibit serious deformities in the
hatchery.
Current data supports at least 4 extant lineages of cutthroat trout in Colorado.
o mtDNA and meristics/morphometric studies are congruent in supporting this.
Bear Creek is upstream what appears to be a one-way barrier to upstream migration of cutthroat
and was presumed to historically be fishless.
In samples analyzed so far, green lineage mtDNA haplotypes are found on both sides of
continental divide. The two most common east slope haplotypes are not found on the west slope.
Blue lineage mtDNA haplotypes are found on both sides of the continental divide. East slope
haplotypes are a subset of what is found on the West slope and are limited to haplotypes currently
found in Trapper’s Lake.
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
o
Most green and blue lineages are separated by barriers. Most barriers are natural, but
some are man-made. Populations above natural barriers are likely present from stocking.
o Green lineage fish are not found in the Yampa or Green River drainages.
The type specimens for O. c. stomias have a haplotype found in Rio Grande lineage.
o Hammon’s collection notes suggest that the type specimens were likely collected from
the Rio Grande drainage.
Geological and other evidence indicates stream-capture events across the continental divide
occurred during the Pleistocene.
Meristic/morphometric analyses show consistent differences between groups defined by mtDNA
haplotypes. Patterns were stronger when individuals were grouped according to genetic lineage
than when grouped according to geographical hypothesis. Meristic differences were also
apparent at the level of GMUs.
The green lineage East slope fish show meristic/morphometric differences from the West slope
green lineage fish.
The blue lineage fish on the East slope show meristic/morphometric differences from the West
slope blue lineage fish.
The blue lineage fish currently present on the west slope are presumed to have originated on the
west slope.
Some conservation populations show evidence of introgression from Yellowstone cutthroat trout
and rainbow trout. Conservation populations are populations that count towards recovery.
Key Questions to Resolve:
Can ancestral polymorphism be distinguished from historic stocking influences on populations
with our existing analyses? If so, how? IMA, other programs, or evaluation of nuclear genes?
The appropriateness of using ND2 and CO1.
Are the green lineage fish on the East side of the divide are a result of stocking or natural
processes?
Is Bear Creek representative of historic populations in the S. Platte drainage?
o See point in the Facts section.
o Use of next generation sequencing of museum samples and the meristics study would
help to verify this.
The green lineage fish currently present on the west slope are presumed to have originated on the
west slope.
What is the phylogenetic relationship among cutthroat trout lineages?
o Additional character information should be obtained.
What is the level of inbreeding in the Bear Creek population?
�APPENDIX D
Expert Panel Reviewer’s Responses
to the
Greenback Cutthroat Trout Genetics and Meristics
Discussion Questions
��Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
Panelist #1 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study?Are there alternative interpretations?
They appear to be generally supportable, especially the identification of the linkage between Bear Creek
and the South Platte River Basin. But this is still to be viewed as a strong working hypothesis, not an
absolute proof. Additional corroborating evidence should be sought. For example the matching of
identical blue lineage cutthroat trout haplotypes from the Yampa River Basin with haplotypes in the
Arkansas and South Platte river basins is strong secondary evidence that those fish were stocked from the
Green River Basin into the Arkansas and South Platte river basins.
The association of the Yellowfin cutthroat trout with the Arkansas River Basin is also plausible. These
data make sense relative to what one would expect for a fish lineage that naturally invaded a separate
basin – they should show divergence from their ancestral source because of the isolation provided by the
basins.
But two other factors should also be considered. First the existence of museum specimens from the late
1800s in the Arkansas River Basin which are part of the ‘green lineage’ raises some question as to the
nature of the trout lineages originally present in the Arkansas River Basin. Clearly the museum specimens
could have been stocked. But these and modern green lineage haplotypes in the Arkansas River Basin do
not match known haplotypes from the green lineage in the Colorado River Basin. As with the blue lineage
fish, you would expect to see very similar or identical haplotypes in the Arkansas River Basin if the fish
were stocked from a Colorado River Basin source. It is important to note that: 1) the full diversity of the
Colorado River Basin green lineage is not yet known 2) several green lineage haplotypes in the South
Platte River Basin match those in the Arkansas River Basin 3) green lineage haplotypes in the Colorado
River Basin and the Arkansas River Basin do not show clear separation into two discrete groups within
TCS networks, which would be expected if sufficient time had passed for lineage extinctions and
subsequent diversification. The mismatch of the green lineage haplotypes in the Colorado River Basin
and the green lineages in the Arkansas River Basin means we cannot rule out a second natural invasion
into the Arkansas River Basin occurring more recently in geological time. The matching of the green
lineage fish in the Arkansas and South Platte River Basins suggest a common origin, potentially stocking,
for one or both basins.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Creek, and Rio
Grande)?
They generally do, especially with the principal components analysis where multiple data sets are
combined. The Bear Creek population consistently separates from the other populations sampled. The Rio
Grande and blue lineages also tend to separate relatively consistently. Addition of spotting measures
generates better separation of the blue and green lineages. Yet the separation is not so distinct that it can
be used in place of molecular data. In fact you would expect that morphological data would be the result
of multiple factors – multiple genes, environmental influences, potentially even epigenetic processes. So
the lack of distinct separation is not surprising.
Panelist #1
Page 1
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
3. To what extent are historical spatial distributions of green, blue lineages known?
To discuss the regions in which these two lineages are found it is useful to also clarify their presumed
basins of focus. Use of the term upper Colorado River may work for our workshop, but on a broader scale
it could lead to some confusion.
For water management purposes the Colorado River Basin is divided at Lee’s Ferry, located just below
Glen Canyon Dam, into the Upper Colorado River Basin (upstream of Lee’s Ferry) and the (Lower
Colorado River Basin) downstream of Lee’s Ferry. All waters of the Colorado River Basin considered in
this discussion are in the Upper Colorado River Basin. Within the Upper Colorado River Basin are three
major subdivisions, the Green River Basin (including the Yampa and White Rivers), the Colorado River
Headwaters (including the Colorado River upstream of Moab, Utah, which thus includes the Gunnison
River and the Dolores River basins), and the San Juan River Basin.
The entire Upper Colorado River Basin has traditionally been assumed to contain the Colorado River
cutthroat trout. The type specimen for Colorado River cutthroat trout was collected in Wyoming in the
Green River Basin. The mitochondrial haplotypes that correspond to the cutthroat trout in the type locality
region (Green River Basin) are the blue lineage. By default the definition of the entire Upper Colorado
River Basin as the native range of the Colorado River cutthroat trout implies that the blue lineage is
expected to be found throughout the three subbasins of the Upper Colorado River Basin. From broader
studies of the Colorado River Basin cutthroat trout, the blue lineage is well established in the Green River
Basin and is also found in the Colorado River Headwaters and the San Juan River Basin. This distribution
was assumed to reflect the ancestral distribution of the blue lineage fish.
The South Platte River Basin and the Arkansas River Basin on the east slope of the Rocky Mountains
have traditionally been considered the native range of the greenback cutthroat trout. Robert Behnke
identified populations of cutthroat trout in the two basins as remnant greenback populations.
Mitochondrial DNA studies conducted for Colorado Parks and Wildlife included these populations and
identified a separate mitochondrial lineage that appeared to belong to the greenback cutthroat trout. This
mitochondrial lineage was found in scattered populations in the Arkansas and South Platte River
drainages. This is the green lineage.
Green lineage fish have also been identified in the Colorado River Basin and these have been confined to
the Colorado River Headwaters as defined above. The distribution of the green lineage fish on both sides
of the continental divide and in both the Arkansas and South Platte River basins is not what would be
expected under natural dispersal hypotheses unless the dispersal event was very recent (Holocene). The
Bear Creek population which appears to either form a polytomy with the other interior cutthroat trout
(Bonneville, Colorado River, Rio Grande and green lineage greenback cutthroat trout), or to be basal to
the greenback (green lineage) cutthroat trout is more concordant with patterns expected from ancient
dispersal events, especially if it is representing the South Platte greenback which would have had to
invade from an Arkansas Basin ancestor which in turn had to invade from the Colorado River Headwaters
(West Slope) or Rio Grande basins.
The dilemma that exists is while the difference between the Bear Creek population and the other green
lineage fish is real, we cannot yet rule out a recent natural invasion for the origin of the green lineages in
the Arkansas River Basin. Since the greenback was traditionally designated as the native trout of the
Arkansas and South Platte River Basins, this implies that the native trout should be inclusive of a broader
range of genetic lineages.
Panelist #1
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�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
The designation of subspecies is generally based on geography and that is backed by clear genetic
separation. But notably the Paiute cutthroat trout (O. c. seleniris; federally listed as endangered) was
described based on the lack of spots on the body. This subspecies is only found in a single stream system
in the Lahontan Basin on the east slope of the Sierra Nevada. Morphological and genetic studies have not
shown significant separation from the Lahontan cutthroat trout (federally listed as threatened). Likewise
the Snake River finespot (tentatively O. c. behnkei) has very distinct spotting differences from the
‘sympatric’ Yellowstone cutthroat trout, but again genetic markers have not been able to distinguish any
differences. Behavioral and spotting differences between finespot and Yellowstone cutthroat trout has
resulted in their being managed as separate entities. Essentially they are treated as separate subspecies.
Conversely, the Bonneville cutthroat trout in the Bear River of the Bonneville Basin are genetically
significantly closely linked to the Yellowstone cutthroat trout, not the Bonneville cutthroat trout in the
main Bonneville Basin. Their morphological difference with Bonneville cutthroat trout in Snake Valley of
the western Bonneville Basin was felt to be due to divergence induced by isolation of the Snake Valley
region following dessication of Lake Bonneville.
So the degree of genetic separation of both the green lineage and the Bear Creek population is quite
significant. Both entities are likely eligible for either subspecies or ESU-level recognition. What is not yet
clear relative to the green lineage on the West Slope is how much of the admixture with the blue lineage
is due to stocking and how much may be due to fish from the Green River Basin naturally infusing genes
into the population through infrequent or rare dispersal events. Given that they are in the same major river
basin, some exchange is likely to have occurred naturally. That may be decipherable by studying blue
lineage haplotype diversity in the Colorado River headwaters since the work on the Arkansas and South
Platte River Basins show Trappers Lake haplotypes being the stocked lineage.
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
Generally I think they did. I did not extensively examine the literature cited by the authors. However in
publications the authors are limited by editors in the number of citations they can include. So it is not
possible to evaluate the literature they cited relative to the total number of papers they considered. I did
get the feeling that at least one of the authors wanted their paper to be the final answer to the problem. I
agree that their interpretation does appear to follow the logical pattern I would expect to find with these
fish. However if it does, then it should stand up to additional tests of their hypothesis. That is how science
works. Once a hypothesis is posed others should be able to test it and either refute or support it. By
multiple testing of the hypothesis we get closer to the true answer.
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Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
b. distinct population segments (DPS)?
c. other?
The blue and green lineages on the West Slope should be managed as two distinct entities. The blue
lineage is probably in good condition given the populations in both Utah and Wyoming as well as those in
northwestern Colorado. The green lineage may suffer from introgression with stocked blue lineage fish,
and the first step to understanding its status will be to evaluate the nature of the nuclear genomes in the
West Slope green populations, especially relative to that from the blue lineage Trappers Lake fish. This
means that it will be important to generate phylogenetic data with multiple nuclear genes, and the nuclear
genes need to have sufficient variability to generate a good phylogenetic signal isolating Trappers Lake
trout from other blue lineage haplotypes. The general prediction is that if the blue lineage nuclear
haplotypes in the Colorado River headwaters region (the green lineage drainages) match those in the
Trappers Lake fish, then the likelihood of introgression with introduced Trappers Lake fish is high. This
does require phylogenetic datasets and not AFLPs, microsatellites, or SNPs because lines of descent need
to be known. It is possible that the green lineage has historically had some introgression induced by
natural movement of blue lineage fish from the Green River Basin. Again phylogenetic data should help
identify the region of origin of those nuclear haplotypes.
If the green lineage is found to have little or no blue lineage influence other than that attributed to
stocking, then the challenge will be to assess the abundance of relatively ‘pure’ green lineage populations
in the West Slope drainages. This situation could raise the green lineage to listable status. This could also
make the East Slope green lineage fish important if it is determined that those were the result of stocking
since they would be candidate sources for reintroduction to the West Slope.
At minimum the blue and green lineages should be considered distinct population segments.
7. Is the Bear Creek population considered to be greenback cutthroat trout?
This is a difficult question because the greenback cutthroat trout has such a varied history. The incorrect
designation of a type specimen begins the problem – were the characters used to define the type specimen
significantly different than the actual characters in the South Platte River cutthroat trout? Was Behnke’s
decision to resurrect an assumed extinct species based on characters gleaned from introgressed
populations? The DNA markers were initially developed based on populations designated as pure by
Behnke. Many of the markers developed were informative, not diagnostic, and other than mtDNA, no
markers were used to generate phylogenetic information relative to other cutthroat trout subspecies and
rainbow trout. Most markers in widespread use in the state of Colorado are based on AFLPs and
microsatellite data analyzed in Structure, where lineages are determined by their assignment into set
groups. This does not generate lineage of descent data.
So the history of misidentification in greenback cutthroat trout has significantly confounded the issue.
Technically the subspecific epitaph, O. c. stomias, is invalid, if the search of the historical records is
correct. Further Behnke’s morphological and meristic work will be incorrect since his populations were
likely introgressed with multiple lineages of cutthroat trout. Thus the name of the Bear Creek fish will
depend on 1) a decision on whether or not to retain the common name greenback for the fish found in
Bear Creek, 2) the result of a petition to the International Commission on Zoological Nomenclature to
change the type specimen for O. c. stomias and to retain the Arkansas River drainage designation (and of
course it will require the designation of a new type specimen which should either be from a historic
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collection – i.e., Harvard University’s specimens or a Bear Creek specimen), 3) a decision on whether or
not to separate the green lineage fish from the Colorado River Basin from the green lineage in the
Arkansas and South Platte River basins, and 4) a decision as to the actual phylogenetic association of the
Bear Creek fish with other interior cutthroat trout taxa. The common name, greenback, can be moved to
the Bear Creek fish with less difficulty than can the scientific name, O. c. stomias. However given the
significance of this subspecies a solid case for an exception does exist.
It will be very important to show independent support for classifying the Bear Creek cutthroat trout as a
true remnant of the original South Platte River greenback cutthroat trout. This should be possible with
next generation sequencing.
8. How do we describe the East Slope green lineage?
The East Slope green lineage fish are a group that, based on mtDNA, clades out within the West Slope
green lineage. From data generated to date, the green lineage on the East Slope is imbedded within that
West Slope clade. The East Slope lineage is not monophyletic within the West Slope haplotypes. The lack
of monophyly indicates that either the fish entered the region recently or from a major transfer event of a
genetically diverse population (and lineage extinction has not taken place but potentially haplotype
divergence has) or that they were introduced by man from multiple sources which no longer exist (or have
not yet been sampled) on the West Slope. As noted elsewhere the East Slope haplotypes, while clearly
imbedded in the West Slope clade, are neither identical to nor nearly identical to known West Slope
haplotypes. This should be further investigated.
The morphological/spotting data suggest that the East Slope green lineage fish are different from the West
Slope green lineage. This could be due to a founder effect, drift, environmental differences, or
introgression with a pre-existing cutthroat trout. It would be very useful to have similar morphological
data for the museum fish from the green lineage in the Arkansas River Basin, the yellowfin cutthroat
trout, and the South Platte greenback collection from Harvard’s Museum of Comparative Zoology.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
This depends on whether the East Slope green lineage originated from stocking or from a recent natural
invasion. If the East Slope green lineage trout can be shown to have originated from stocking from the
West Slope, then their distinctness in morphology (especially spotting), is not of much importance. The
populations then may be of importance for rehabilitation of West Slope populations.
If the East Slope green lineage fish are shown to be native, the fact that they are imbedded in the West
Slope green lineage with mtDNA should be verified with nuclear genes. Corroborating findings would
suggest that they are a part of the West Slope green lineage. At that point I would manage them as distinct
population segments or ESUs.
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10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
Currently published papers on cutthroat trout genetics do not resolve the phylogenies of the interior
cutthroat trout well enough to answer this question since they all generate polytomies or weakly
supported nodes separating the Bonneville, Colorado River, greenback, Bear Creek, and Rio Grande
lineages. It is important to note that while these analyses fail to show resolution in line of descent, they do
show strong support for each ‘geographically defined’ subspecies with the addition of the Bear Creek
lineage as a separate branch on the polytomy.
Additional sequence data from the mitochondrial genome will generate more strongly supported clades,
which will help answer that question. In addition the development of primer sets for nuclear genes will
allow the establishment of multiple gene phylogenies, which can be examined both individually and as a
concatenated data set. These will generate a consensus phylogeny which should establish the most likely
pathways of colonization of the interior west by cutthroat trout.
The meristic data suggest an overlap of the West Slope green lineage with the Rio Grande cutthroat, but I
do not put much weight in the ability of meristics to generate phylogeographic associations because the
range of variability is too great with any individual character to separate founder effects from
pleisiomorphic states.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
Blue lineage – the wide distribution of the blue lineage in the Green River Basin indicates that it is an
endemic lineage of cutthroat trout and, given that the type specimen is from Wyoming, it is the subspecies
currently identified/recognized as the Colorado River cutthroat trout. The blue lineage populations on the
East Slope appear to be introduced from stocking activities in the late 1800s and early 1900s. This is
strongly supported by the east slope blue haplotypes being identical to several found in the Trapper’s
Lake region of the White River Drainage. Genetically the blue lineage fish also appear to be less variable
in the East Slope basins. This could be interpreted as supporting their originating from stocking activities
by man, although a small founder population or bottlenecks could also be invoked to generate low
haplotype diversity. The most likely cause is stocking.
Green lineage – this lineage is found in the Colorado River Headwaters (defined in question 3 above), the
Arkansas River Basin, and the South Platte River Basin. It appears to be absent from the Green River
Basin. Depending on the analysis, the green lineage fish can be interpreted to be a single lineage in a
polytomy containing all of the recognized interior cutthroat trout except the Yellowstone cutthroat trout
line. The Bear Creek lineage, in this case, is an independent lineage in the polytomy. Or the green lineage
can be divided into two clades, with the Bear Creek fish being one line branching off basally from the
main (predominant) green lineage.
Depending on how one designates the basic relationships of the Bear Creek fish (unresolved member of a
polytomy or a resolved clade branching from within the green lineage), the Bear Creek trout would be
treated as either a separate but equal entity to the green lineage (thus both definitely appear to deserve
subspecies status), or the Bear Creek population would be a highly unique offshoot of the green lineage,
making the Bear Creek population’s status as an independent subspecies less clear. This needs to be
answered, but published data do not have the resolution to give a definitive (high bootstrap support)
picture of the relationships. The use of the early museum specimens resulted in 430 base pairs of
sequence data, too few to generate a robust phylogenetic signal. Even as many as 3600 bp of mtDNA data
fail to give much additional resolution (Shiozawa et al 2010). Yet this question is basal to the
determination of the degree of uniqueness in the Bear Creek population relative to the green lineage
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populations being examined across the various drainages. The Bear Creek population is clearly unique,
but if it is a member of a true irresolvable polytomy, showing equivalent separation from the other interior
cutthroat trout subspecies, management decisions are easier to make than if it is an offshoot of the green
lineage, or any other interior lineage.
The separation of the Bear Creek fish from the green lineage – the difference between the Bear Creek and
other green lineage fish is significant. The morphological data are less informative simply because the
Bear Creek population is so highly inbred. It is not clear what effect that will have on the morphological
differences. The examination of the South Platte museum specimens will help answer that question.
Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
The meristics report shows that the Bear Creek fish have less variability than the green lineage fish for
many measured characters. However since this is a single inbred population which has clearly been
subject to drift and founder effect, it is not clear how strongly this represents what these characters might
have been in the Arkansas River Basin. The fish in Harvard’s collection should be examined.
It is imperative that the population be duplicated in multiple isolated streams, in the South Platte River
Basin, as quickly as possible. While this is being done, it would be useful to attempt genetic rescue in
additional duplicated populations with limited, say 2-5%, introgression with other green lineage fish. Of
concern is the possibility that current inbreeding is so high that some deleterious genes are approaching
fixation. It is much better to continue with both population rescue and population duplication while other
concerns such as genetic status, fry deformities, etc. are being assessed because the risk of population loss
is too high with just the one small population that is known to exist.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
At this point the most likely native Arkansas River cutthroat trout is the extinct Yellowfin. However if a
recent natural invasion of the green lineage into the Arkansas River Basin has occurred, then the green
lineage in the Arkansas River Basin would likely also contain genetic material from the Yellowfin. These
hidden haplotypes should be seen in trout from within the basin in either mitochondrial or, most likely,
nuclear DNA sequences. The information could be retained in fish from highly introgressed populations.
A series of good nuclear gene phylogenies would allow identification of those haplotypes.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
A number of possibilities exist with next generation sequencing. The first priority with this procedure
should include development and verification of nuclear markers capable of producing phylogenetic
signals. While it is highly likely that mtDNA studies underway will help resolve questions of lineage of
descent, mtDNA is a single locus. Additional independent loci should be examined so that the
phylogenies are robust.
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Second, this technology can be used to generate sequence data (skipping Sanger sequencing altogether).
Such procedures will shift the processing of data into the bioinformatics realm and is the logical next step
to generating large nuclear DNA sequence data sets.
Third, both SNP development and phylogenetic data generation can be accomplished with less cost per
base pair of data than is currently achieved with Sanger sequencing.
Finally, next generation sequencing provides a way to obtain significantly more information from
museum specimens. Given that some of the next gen sequencers are optimized for fragment sizes found in
degraded DNA, it is possible to generate significantly more genomic information from the museum fish
DNA.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
Most of the priorities are scattered throughout my responses.
It is critical to continue searching the West Slope green lineage for mitochondrial DNA haplotypes
matching the East Slope green lineage. This can be aided by using the proper nuclear DNA markers that
have a phylogenetic signal.
Non-conservation populations should be examined as well, since residual genetic information should
remain in introgressed populations. This can be sorted out with phylogenetic approaches.
SNPs suffer from the same limitations as AFLPs and microsatellites and probably should receive less
emphasis until good nuclear DNA phylogenies are developed for many genes (from which diagnostic
SNP loci can be obtained).
It is critical to generate nuclear DNA phylogenies so that the strength of the mitochondrial signal can be
assessed and so that additional genes are available for forensic investigations of the drainage associations
of the various trout populations.
It is important that the status of the populations be determined as accurately as possible. The technology
that is rapidly developing with next generation sequencing will provide answers to many of the questions
about this complex group which could not be breached just a few years ago.
One factor to keep in mind with all of the turmoil associated with the current state of the greenback
cutthroat trout is that, had preservation not begun until we had the genetic tools in use today, we would
likely have lost many of the populations that can now potentially serve as source populations for recovery
of fish on both slopes of the Rocky Mountains. The effort to this point has not been in vain.
16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish
from eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than some other stream and lake spawning attempts east of the Continental Divide
in Colorado.
-
What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
-
What steps or research could you take to better understand how these trout could successfully
produce viable populations if replicated in streams in the South Platte River drainage?
Anecdotally it appears that the Bear Creek fish are expressing a higher proportion of deformed fish than is
usually observed. Highly inbred populations risk problems with deleterious genes that are expressed in
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the homozygous state. In small inbred populations these problem genes may increase in frequency by
genetic drift enhanced by low population size. That could be the case in this population. The process of
domestication involves continued breeding to eliminate (purge) such genes from the population. The lack
of expression of these traits in the adult fish is likely due to a failure of deformed fry to survive. Yet,
whether this is due to a series of single genes, each causing different deformities, or a number of
polygenic complexes causing such deformities, it is likely that the deleterious genes are in high enough
frequency within the population that the mortality of deformed fish is not rapidly removing the defective
genes from the population.
It is not clear what the frequency is for similar deformities in other small, isolated populations of trout.
Hatchery rearing is not attempted on most of those populations because they are often not critical enough
to management that hatchery rearing is needed. It would be useful to have this quantified as # of
deformities /1000 swim-up fry (or other easily quantified age class), in replicates, and with multiple other
green lineage (or interior cutthroat trout) populations including both large meta-populations and isolated,
potentially bottlenecked populations. The experiment would need to be done under fixed temperature and
chemical conditions. This would establish baseline data for understanding the significance of this level of
inbreeding and the apparent normal appearance of the adult fish. Further, fluctuating asymmetry can be
examined in the fish used for the meristic study to determine if greater asymmetry exists in the Bear
Creek population than is seen in other populations. Parallel genetic studies could be conducted to
determine overall heterozygosity of the population, especially in comparison with other potentially
bottlenecked populations as well as populations in streams with robust metapopulation structure.
Such studies, comparing multiple populations with the Bear Creek population, would allow a better
understanding of the degree of concern that one should have with the fry deformities. If other populations
show similar deformity frequencies when reared in a hatchery environment, then the deformities would be
less of a concern, even if the Bear Creek fish show higher homozygosity and asymmetry than other
populations.
17. Please provide other relevant comments not addressed in the above questions.
In reality, geographic isolation is likely the primary evolutionary force driving speciation processes within
western North American obligate aquatic organisms. So with cutthroat trout the general hypotheses put
forth by Behnke are rational. What he did not anticipate is the potential for reticulation (re-coalescing of
populations) during repeated Pleistocene climate oscillations and the ability of phylogenetic approaches to
tease these events apart. It is becoming more apparent that even within basins, large subbasins can have
their own evolutionary trajectory especially if the connections between the subbasins include sections
with less favorable habitat which can act as partial barriers to gene flow.
In the case of the trout in the Arkansas and South Platte River systems, one recurring question to me
relative to data I had seen prior to the 2012 paper was why were the fish in both basins so similar to one
another when their downstream connections were obviously too far apart to be likely paths of
colonization. This coupled with the lack of native trout in the North Platte River Basin suggested that a
very recent, possibly Holocene age, transfer event across a low order stream system must have occurred.
Behnke had hypothesized such a recent transfer of Colorado River cutthroat trout as being the origin of
the greenback cutthroat trout. But that did not explain the similarity between the two East Slope basins. A
recent event could have happened but would be unlikely. Two recent events, one from the West Slope of
the Rocky Mountains to the Arkansas River Basin and one from the Arkansas River Basin to the South
Platte River Basin would be even less likely. The findings of Metcalf et al. 2012 do fit better with what is
known for trout dispersal and isolation patterns.
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Similar patterns are seen with other populations of cutthroat trout as well as other fishes in the west. An
example occurs in the Bonneville Basin where fish in the Bear River Basin appear to have entered that
Basin at a different time than the existing fish (cutthroat trout - Loudenslager and Gull 1980, Martin et al
1985; redside shiner - Houston et al.2010; leatherside chub - Johnson et al 2004; Utah chub - Johnson
2002; speckled dace – Billman et al 2010 ). Two points can be seen in this transfer event – first species
were transferred and then isolated from the basin of origin and second they had contact with resident fish
in the receiving basin. The populations retained relatively high separation between the invading taxa and
the resident taxa – generating a relatively narrow hybrid zone. Thus in Utah, streams of the Bear River
contain the Northern leatherside chub, a recognized species while those streams from approximately Utah
Lake south contain the Southern leatherside chub. Utah chub show a similar pattern as does the redside
shiner.
Billman, E. J., J. B. Lee, D. O. Young, M. D. McKell, R. P. Evans, and D. K. Shiozawa. 2010.
Phylogenetic divergence in a desert fish: differentiation of speckled dace within the Bonneville,
Lahontan, and Upper Snake River Basins. Western North American Naturalist 70:39-47.
Houston, D. D., D. K. Shiozawa, and B. R. Riddle. 2010. Phylogenetic relationships of the western North
American cyprinid genus Richardsonius, with an overview of phylogeographic structure.
Molecular Phylogenetics and Evolution 55:259-273
Johnson, J. B., 2002. Evolution after the flood: phylogeography of the desert fish Utah chub (Gila
atraria). Evolution 56: 948-960.
Johnson, J. B., Dowling, T. E., Belk, M. C., 2004. Neglected taxonomy of rare desert fished: congruent
evidence for two species of leatherside chub. Syst. Biol. 53: 841-855.
Loudenslager, E. J. and G. A. E. Gall. 1980. Geographic patterns of protein variation and subspeciation in
cutthroat trout, Salmo clarki. Syst. Zool. 29:27-42.
Martin, M. A., D. K. Shiozawa, E. J. Loudenslager and J. N. Jensen. 1985. Electrophoretic study of
cutthroat trout populations in Utah. Great Basin Nat. 45:677-687.
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Panelist #2 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
This reviewer is not convinced by the conclusions presented in either Metcalf et al. (2007) or Metcalf et
al. (2012). The analyses regarding gene flow via introductions were not done to the best science available
and as a result cannot distinguish between ancestral polymorphisms of alleles (falsely interpreted as
introductions and breeding of stocks or introgression). Their conclusions are only one of a few others.
2. Does the meristic study correlate with findings in the genetics study (i.e, does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
Yes, based on other genetic studies and at a wider scale by others than Metcalf et al. the morphological
studies provide a much clearer picture of the diversity. Studies of this nature should be continued and
funded to resolve the taxonomy of the cutthroat lineage. These studies should not be done by anyone that
does strictly genetics or morphology of any other organisms. They should be done by a professional
taxonomist and systematist for proper data collection and interpretation of analyses.
3. To what extent are historical spatial distributions of green, blue lineages known?
Not very well, frankly.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
This cannot be answered as comparable studies do not exist for other cutthroat trout.
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
No, the genetic studies should have included data from other studies in larger scale evaluations. The
morphology study suffered from not examining historic specimens from the South Platte River.
Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies? At least.
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b. distinct population segments (DPS)?
c. other?
Frankly these lineages constitute different species when one compares the differentiation of these lineages
with that of other trout species not in North America (those that have been historically studied by the
same people in the US and have conservative views). If the diversity of characters were to be interpreted
for Eurasian trout species the cutthroat lineages would be called different species.
7. Is the Bear Creek population considered to be greenback cutthroat trout?
I cannot say as the samples from the South Platte River were never examined for the morphology.
8. How do we describe the East Slope green lineage?
It is a distinct lineage.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
They are distinct.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
This question can in no way be answered as there has not been enough detail done in any studies thus far.
Anything proposed otherwise is simply guesswork and not science.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
Yes, they are significant. They have unique morphologies and genetics. There are many reasons for
historic transfer and differentiation that do not include human activities. Taxonomically they should be
considered distinct lineages until such time they are tested to interpret otherwise.
Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
Yes, there may be limited variability in this population but this may be natural and should not be changed
through the introductions of other alleles from other trout. This species should be maintained and
protected in Bear Creek and there should be habitat restoration done in this system. Otherwise, there
could be justification to relocate individuals to some known fishless streams in the South Platte River
Basin with good habitat to see if there is increase in genetic variability.
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Don’t mess with the genetics of this species. We do not know enough about it morphologically or
genetically to justify any management changes that involves introductions of alleles from other trout. This
will only make the matters worst in the future.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
The current lineage there with the unique haplotype and distinctive morphology.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
These data provide good information on the phylogenetic relationships of these trout lineages and should
be done at a broader scale to identify close relationships to determine evidence of ancestral
polymorphisms in genes that are not interpreted as originating from interbreeding. Otherwise the data
gathered from this will provide a large library of genes that can be monitored to examine historical and
recent exchanges and relationships.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
Full scale morphological study with finer level of evaluation of differentiation within drainages
Broader and more complete sampling of genes for all of the lineages of cutthroat with finer level of
evaluation of differentiation within drainages
Once these are done by consortium of researchers for best available science interpretation then a sound
basis will be available to make management decisions but only then.
16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish
from eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than some other stream and lake spawning attempts east of the Continental Divide
in Colorado.
-
What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
You cannot make any general conclusions from this from hatchery materials. There are too many
variables that cannot be controlled for. This lineage may simply be unique relative to others and
in an evolutionary and developmental transition.
-
What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the S. Platte drainage?
See above about comments for South Platte River.
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17. Please provide other relevant comments not addressed in the above questions.
There needs to be significantly more data collected on these fishes across the cutthroat lineages and at a
finer scale than what has been done to date in order to make sound scientific conclusions. The data that
exists today, much of it unpublished or not in complete focus on the questions at hand, do not provide a
sound basis for making significant management decisions at this time. Until such time that the science
exists, and funding should be provided to do this, the best available science to address these questions is
just not there at this time. Too much rushed and preliminary findings can further complicate the picture–
possibly to the point that the natural signature of the complex will be lost forever. Some researchers
involved in this seem to be too rushed and have done very incomplete analyses and interpretations to be
considered sound.
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Panelist #3 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
I will begin my answer by stating that the Metcalf et al. 2012 paper, published in the high-quality
scientific journal Molecular Ecology, was a carefully conducted piece of work that was enormously
helpful in identifying and understanding historical distributions of cutthroat trout lineages in Colorado.
These researchers obtained considerable historical material and used state-of-the-art ancient DNA
techniques and practices to avoid problems with DNA sample contamination. The resulting data set is
well analyzed and conclusions appropriate. That said, there were few samples available for analysis
(roughly 30 were successfully isolated and amplified) and only short DNA fragments from the mtDNA
could be analyzed. In my view, small sample sizes limit some inferences that can be conclusively drawn
from the data, and the study does not definitively rule out alternative hypotheses. Some alternatives are
more important than others from a management perspective, and I will follow up on those below.
A major finding of the paper was that six distinct (i.e., demonstrably monophyletic) mitochondrial DNA
(combined ND2 and COI gene sequences) lineages were identified from historical samples – three distinct
lineages occurred on the East Slope of the Rocky Mountains including purple (South Platte drainage –
represented only in Bear Creek in modern samples), orange (Rio Grande drainage), and yellow (Arkansas
River, now presumed extinct); and three lineages on the West Slope including blue (Yampa and Colorado
Rivers), green (Colorado, Gunnison, and Dolores Rivers), and red lineage (San Juan River – presumed
extinct). The green lineage also occurred in the Arkansas River Basin in historical samples, and as such,
was the only lineage that occurred on both sides of the continental divide. Metcalf et al. hypothesized that
purple lineage fish were O. c. stomias (sensu stricto – limited to the South Platte River and introduced
into Bear Creek), yellow lineage fish were O. c. macdonaldi, orange lineage fish were O. c. virginalis,
blue lineage fish were O. c. pleuriticus, and that green and red lineage fishes were unnamed lineages. Of
unnamed lineages, extant green lineage fish could meet criteria to be named a distinct subspecies
(geographic isolation, distinctive meristic features).
At this time, it is unknown whether red lineage fish is nameable or a listable entity, and the issue may be
moot unless one or more native population of fishes is found in the San Juan River drainage. It is possible
that introgressed individuals will be identified that have the red lineage mtDNA haplotype or something
closely related to that haplotype. In this case, it may be possible to „resurrect‟ a relatively genetically pure
strain through careful brood stock management and genetic-marker assisted backcrossing, if deemed
important from a conservation standpoint. A successful marker-assisted program necessitates further
development of co-dominant nuclear DNA markers (i.e., microsatellites or SNPs) to fully characterize the
degree of introgression of each individual in the brood stock. It appears likely that yellow lineage fish (O.
c. macdonaldi) are extinct. Population surveys along with genetic analysis of Arkansas River drainage
populations may identify some fishes that bear yellow lineage haplotypes, but this seems unlikely.
A second important finding was that four of six historical lineages were distributed solely in single major
river drainages. A number of researchers, dating back to some of the first ichthyologists to describe
cutthroat trout subspecies (e.g., David Starr Jordan), have hypothesized that major drainage divides are
important geographic features that isolate distinct cutthroat trout lineages (a more recent example is
Loxterman and Keely 2012), although gene flow across drainage divides can and does occur (through
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stream capture). Metcalf et al. 2012 present historical data that are consistent with the interpretation that
major drainage divides are the predominant structuring feature for cutthroat trout diversity in Colorado.
Two important and notable exceptions to this finding were observed for the green lineage that occurred on
both sides of the continental divide and in the Colorado, Gunnison and Dolores R. drainages on the West
Slope, and the blue lineage that occurred in both the Yampa and Colorado R. drainages on the West
Slope. Modern samples analyzed in Metcalf et al. 2007 also indicated that blue lineage fish were present
in large numbers in East Slope drainages. In cases where lineages occur in multiple drainages, Metcalf et
al. hypothesized that historical stocking is predominately the cause. Chris Kennedy, a co-author of the
paper and a presenter at the Greenback Cutthroat Trout (GBCT) workshop, offered compelling analysis of
historical stocking records that indicated that stocking was conducted on a massive scale (hundreds of
millions of fish), stocked predominately from West Slope to East Slope drainages. This would serve to
mix lineages and obscure historical patterns of isolation that corresponded with distinct watersheds. Most
compelling was the evidence that blue lineage fish were stocked into the S. Platte and Arkansas River
drainages and subsequently were established in previously fishless habitats, or introgressed with existing
fishes (Metcalf et al. 2007, 2012, Kennedy presentation). This was supported by the presence of identical
haplotypes (e.g., common alleles found at Trapper‟s and Marvine Lakes that served as a source for
stocked fish) on both sides of the divide.
The origin of green lineage fish on the East Slope is less certain. There are several alternative hypotheses
based on the data in hand:
1) The green lineage is native to the West Slope and was introduced into East slope drainages by
stocking.
2) The green lineage is native both to the West and East Slopes.
3) The green lineage is native to the East Slope and was subsequently reintroduced to the West slope
either by natural events (i.e., stream capture) or by stocking.
Hypothesis 1 is favored by Metcalf et al. 2012, and although these authors raise the possibility that
Hypothesis 2 is correct in the paper, they do not discuss it further. The strongest support for Hypothesis 1
would be if all East Slope green lineage populations contained haplotypes that were identical to West
Slope haplotypes (i.e., East Slope haplotypes are a nested subset of West Slope). This is not observed
with the samples in hand, but it is possible that more extensive geographic sampling may reveal this
outcome. Hypothesis 3 seems least likely and is not supported by the data in hand as stocking rates from
East to West Slope drainages were much lower than from West to East.
With regards to Hypothesis 2, a gene tree based on ~8000 bp mtDNA sequence data (presented by D.
Shiozawa at the workshop) suggested the following relationships with good levels of bootstrap support: a)
monophyly of a clade that contains all green lineage and Bear Creek haplotypes (96% support) b)
monophyly of Taylor Creek, Como Creek, and Severy Creek haplotypes (100% support), and c) a sister
relationship of Rio Grande (orange lineage) plus green lineage (with 98% bootstrap support). One green
lineage haplotype found in the S. Prong of Hayden Creek, Arkansas River drainage did not fall within the
monophyletic lineage in item (b) above. This tree suggests that Hypothesis 2 cannot be rejected at this
time and that the East Slope contained individuals with a divergent green lineage haplotype(s).
A potentially complicating factor is that Hypotheses 1 and 2 are not necessarily mutually exclusive, and it
is possible that they are both correct. In other words, it is possible that West Slope green lineage fish were
stocked into populations that already contained genetically distinct native East Slope green lineage fish
and then subsequently introgressed. It is also possible that West Slope fish were stocked into fishless
creeks to create a mosaic pattern of West and East Slope haplotypes in the Arkansas (and perhaps S.
Platte) River drainages. The gene tree presented by Shiozawa suggests that S. Prong of Hayden Creek
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may be one such population where West Slope green lineage fish have introgressed, because haplotypes
there do not share most recent common ancestry with other East Slope green lineage fishes in Taylor,
Como and Severy Creeks. Another complication is that incomplete lineage sorting (i.e., haplotypes have
not achieved monophyly) have caused this result. Incomplete lineage sorting occurs when insufficient
time has passed to „sort‟ ancestral haplotypes (through genetic drift, mutation, and possibly local
selection) into monophyletic lineages, even though the two gene pools have been isolated for several
thousand years or more.
It should be noted here that Shiozawa‟s work is unpublished and has not been peer-reviewed. However,
the methods appear to be sound and the dataset is impressive with respect to the number of base pairs
examined, but few individuals were sequenced. I should also note that the Metcalf et al. 2012 gene tree
was unresolved at key nodes that would have indicated the relative timing of certain events with regard to
the evolution of green lineage haplotypes. Without larger and more geographically widely distributed
sampling, it may not be possible to assess alternative hypotheses. More research on this topic is necessary
and warranted.
In summary, the Metcalf et al. 2012 paper, while an excellent piece of work, leaves some unanswered
questions that pertain mostly to green lineage fish. Among these are: 1) What is the most probable origin
and process that gave rise to green lineage haplotypes on the East Slope? 2) Are East Slope green lineage
fish „native‟ to the Arkansas River or were they recently introduced? 3) Are East Slope green lineage
haplotypes a nested subset of West Slope haplotypes? 4) What are the effects of incomplete geographic
sampling and/or incomplete lineage sorting as it pertains to reconstructing the origin of East Slope/West
Slope green lineage fish? 5) Are there genomic remnants of yellow lineage fish or native East Slope green
lineage fish in present-day populations of the Arkansas River drainage? These questions are germane to
what should lineage(s) should be restored to the Arkansas River drainage.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
The meristic study by Bestgen et al. examined ten meristic traits (plus standard length) in 744 fish
distributed in 49 distinct localities and 14 Geographic Management Units (GMUs) across relevant
drainages. Meristic traits matched four that were traditionally used by ichthyologists and added six more,
including a quantitative analysis of spotting patterns. It was one of the tasks of this workshop to critically
evaluate this work, but it has not been subject to peer review otherwise. Fin clips were obtained from each
individual for genotyping to link mtDNA lineage to individual meristic counts explicitly. A strict blind
protocol was employed to minimize bias due to investigator pre-conceptions about a particular collecting
locality. In the final study design, it was possible to evaluate variation in meristic traits attributable to
major drainage divides, ND2 haplotype, and Geographic Management Units. Two hypotheses were
examined: (1) the Geographical Hypothesis states that the majority of variation in meristic traits across
individuals and populations could be explained by grouping individuals into West Slope, East Slope, and
Rio Grande categories, and (2) the Molecular Hypothesis states that most variation could be explained by
grouping individuals and populations by mtDNA-ND2 lineage. Principal Components Analysis (PCA)
and Discriminant Function Analysis (DFA) indicated that the Molecular Hypothesis explained more
variation than the Geographical Hypothesis – consistent with the results of Metcalf et al. 2012. Thus, the
answer to the question posed above “are meristics and genetics correlated?” is yes. Moreover, the
Molecular Hypothesis provided a better fit to the meristic data than the Geographical Hypothesis (based
on multivariate analyses), although it should be noted that these hypotheses are related -- the Molecular
Hypothesis essentially partitions the Geographical Hypothesis into more drainages. However, a critical
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difference between the two hypotheses is that the Molecular Hypothesis allows for cross-drainage
stocking (because individuals are assigned to lineage based on ND2 haplotype, independent of collection
locality), but the geographical hypothesis does not.
Univariate and multivariate analyses of meristic data based on mtDNA-ND2 lineage demonstrated that
blue and green lineage fish could be separated primarily on the basis of the number of trunk spots and
fore- and mid-trunk spotting ratios. There was strong support for historical stocking as a factor that
explained the distribution of blue lineage fish on the East Slope. Other strongly supported findings were
that Bear Creek was significantly distinguishable from all other cutthroat trout examined and did not
overlap with any other species in PC space. The number of basibranchial teeth, number of anterior gill
rakers, and mean spot size were important traits that distinguished Bear Creek from other lineages. Rio
Grande cutthroat trout were also significantly distinct, but some characters were shared across different
lineages (usually green and Bear Creek lineages, although different subsets of characters overlapped
between lineages). Similarities for subsets of characters among green, purple (Bear Creek), and orange
(Rio Grande) lineage fish is not surprising given that they share recent most common ancestry compared
to the blue lineage fish that are more distantly related (based on ND2 tree in Bestgen‟s presentation and
Shiozawa‟s mtDNA gene [~8000 bp] trees).
There was evidence that a substantial portion of meristic variation could be explained at a geographic
level that is finer than implied by either the Geographic or Molecular Hypotheses. This is the Geographic
Management Unit scale (there are 14 GMUs throughout the region). Variation attributable to GMU was
especially evident for Rio Grande cutthroat trout and green lineage when classification via DFA was
conducted at the population level. This is the de facto level that management activities are currently being
conducted.
Another important finding was that East Slope green lineage fish were distinguishable from West Slope
green lineage fish based on lateral line scale counts, basibranchial tooth counts, and trunk spot counts.
This is consistent with the idea raised above (in Question 1) that East Slope green lineage fish may have
deeper and more complicated origins on the East Slope than would be predicted if they were introduced
more recently by stocking. Inter-lineage variation probably contributed to relatively high misclassification
rates in the green lineage. However, some differences between East and West Slope blue lineage fish
were also identified, for example, lateral line scale counts and fewer spots. This result may also suggest
complex introgression histories and local environmental conditions that may account for at least some of
the East Slope/West Slope differences in the green lineage. At the very least, examination of meristics in
historical material (if possible) and extant populations, and more genetic study of East Slope green
lineage fish is warranted.
With regards to quality, the Bestgen et al. study is among the most comprehensive meristic datasets ever
compiled for cutthroat trout. Sample and data collection was sufficiently geographically dense to address
all hypotheses laid out in the objectives of the study. Any limitations in sample size were imposed by the
lineage examined, for example, Bear Creek had only two “populations” one in the wild and the other from
the hatchery. There are also relatively few East Slope green lineage populations. The analyses are
appropriate and well executed. It should be publishable in a peer-reviewed scientific journal after peerreview and some revision. Future research should focus on extensive surveys of cutthroat trout
populations throughout Colorado, with collection of sufficient specimens (where possible) to conduct
additional meristic and molecular analyses. Specimens and tissues should be carefully archived in a wellcurated natural history collection to create a resource base for future conservation efforts.
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3. To what extent are historical spatial distributions of green, blue lineages known?
The preponderance of evidence suggests that green lineage fish occurred historically in the Colorado,
Gunnison, Dolores River drainages on the West Slope, and potentially in the Arkansas River Basin on the
East Slope (Metcalf et al. 2012). Interestingly, the green lineage does not fit the “single drainage – single
lineage” paradigm that appears to be the general observation in cutthroat trout. Likewise, blue lineage fish
occur in the White, Yampa, and Colorado River drainages. It appears clearer that blue lineage fish were
introduced into the Arkansas River by stocking and historically were limited to the White and Yampa
River drainages. Geological and/or climatic events can facilitate headwater capture across major divides –
detailed study across drainage divides is warranted to evaluate the presence of major lineages across
numerous drainages.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
Blue, green, orange and purple lineage fish are demonstrably monophyletic and exhibit significant
divergence in meristic traits across lineages. Molecular and morphological evidence for diversification of
lineages is comparable to, and in most cases, much better than evidence available for other named
subspecies of cutthroat trout.
5. Did genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
I have commented on the high quality of both the Metcalf et al. 2012 and Bestgen et al. (unpublished)
studies in my responses to Questions 1 and 2, respectively. These are well researched, well executed, and
clearly written studies that, to my knowledge, cite and include all pertinent literature including a lot of
unpublished stocking records and other literature that is difficult to access. I have identified areas in both
studies where additional data and study are warranted, but both stand alone as seminal contributions to
understanding the processes responsible for variation in present-day cutthroat trout lineages in Colorado.
Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
The Metcalf et al. 2012 study identified, and Shiozawa‟s mtDNA and the Bestgen et al. meristic studies
confirmed, that there is previously unrecognized biodiversity within currently named subspecies of
cutthroat trout in Colorado. Taxonomic revision of cutthroat trout in Colorado is warranted and justified
based on the new understanding of diversity afforded by molecular and meristic studies. There is some
subjectivity about subspecific designation (the classic “lumpers” vs. “splitters” debate among
taxonomists), but the evidence for additional biodiversity in this complex is clearly demonstrated by the
data. However, any taxonomic revision will take considerable time.
The preponderance of molecular and meristic data indicates the following:
The subspecies name O. c. pleuriticus currently refers to fishes in the White, Yampa, Colorado,
Gunnison, Dolores (and San Juan?) River drainages. Metcalf et al. 2012 suggested that the name
pleuriticus should be more narrowly defined to the drainages historically occupied by the blue
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lineage (Yampa, White) – a stricter definition than is currently recognized. Molecular and
meristic data suggest that this is appropriate, and indicate that the previous definition was too
broad and did not recognize biodiversity contained in green lineage fish. This change would leave
open the taxonomic status of the green lineage to revision.
The subspecies name O. c. virginalis currently refers to fishes in the upper Rio Grande drainage
(Rio Grande, Pecos, Canadian Rivers) and this designation is well supported by molecular and
meristic data. There is also considerable molecular and meristic variation across GMUs, which
suggests that management should continue at the GMU level.
The subspecies name O. c. stomias currently refers to all cutthroat trout on the East Slope
excluding fish in the Rio Grande drainage. Metcalf et al. 2012 suggested that the name stomias be
restricted to purple lineage fish. The purple lineage is demonstrably monophyletic and exhibits
large differences in meristic traits from all other East Slope fish, and so this is justifiable.
However, one important question is distinctiveness of East Slope green lineage fish – whether
they should be “lumped” into O. c. stomias or not? Jordan clearly intended fishes in the South
Platte and the Arkansas River to be included in stomias. According to Shiozawa‟s tree, purple
and green lineage fish (East and West slope inclusive) share most recent common ancestry with
respect to other named subspecies. This situation will require additional careful study, and a
newly elevated green lineage (perhaps to a new subspecies) and a stricter definition of stomias
will require taxonomic revision.
In the long run, it may be most defensible to propose a new entity that encompasses green lineage
fish (perhaps as a new subspecies) with East and West Slope lineages identified as „distinct
population segments‟. The East Slope DPS would probably require protection and intensive
management. The West Slope DPS is probably much more secure.
b. distinct population segments (DPS)?
See my reponse in the 3rd bullet above.
c. Other?
7. Is the Bear Creek population considered to be greenback cutthroat trout?
This is a difficult question to answer, and it depends on the evolutionary origins and taxonomic status of
East Slope green lineage fish. From a pragmatic standpoint, restricting the name O. c. stomias to Bear
Creek would remove protection from green lineage fish on the East Slope (and the West Slope). In the
short run, it may afford more protection to keep the current taxonomic status in place, and adopt a model
currently employed for Gila Trout, that is, to name relict lineages in the recovery plan and then manage
those separately. Thus, if O. c. stomias is retained as it is currently defined, and Bear Creek, East Slope,
and West Slope green lineages are named in the recovery plan as lineages that warrant special
management and protection. This would allow intensive management that circumvents the need for
immediate taxonomic revision as a precursor to conserve green lineage fish on the East Slope. Recovery
goals can be written in a way that emphasizes the critical status of Bear Creek fish, while not removing
protection from the East Slope green lineage until its origin can be ascertained.
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8. How do we describe the East Slope green lineage?
This will depend on the outcome of studies designed to ascertain the origin of East Slope haplotypes – see
my comments above.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
Haplotypes that are (thus far) unique to the East Slope green lineage (i.e., not found in West Slope
populations) appear to be relatively common in Como, Severy, and Taylor Creeks, and possibly in the S.
Prong of Hayden Creek. This observation, along with unique meristic variation suggests that certain East
Slope populations may comprise a distinct population segment (DPS) of the green lineage, given that they
are discrete from other populations and significant in relation to the green lineage. It may be difficult to
manage green lineage populations on the East Slope because they may have different introgression
histories and repeated backcrossing events to green lineage fish more recently introduced via stocking –
perhaps the GMU level of management is most appropriate for this purpose.
A few caveats are that mixed ancestry in these populations may complicate ESU designation. Likewise,
the green lineage may need to be elevated to a subspecies to allow for DPS status to be assigned under the
endangered species act (ESA).
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
The most likely scenario for the historical route of colonization comes from Shiozawa‟s work, because
trees are nearly fully resolved with regards to the relative timing of ancestry of cutthroat trout lineages in
Colorado. This work suggests that colonization occurred from the northwest, with the common ancestor
of blue and green/purple/orange/yellow/red lineage fish diversifying on the West Slope. An ancient
colonization event occurred via an ancestor of green/purple/orange/yellow/red lineage to the East slope.
The earliest divergence among extant lineages (yellow/red excluded) in this group was Rio Grande
cutthroat trout, and then purple and green. What is not clear is if East Slope green lineage fish are native
to the East Slope or recently introduced. This is a critical issue to be addressed by future research. Blue
lineage fish on the East Slope almost certainly occur there via stocking activities.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
I have addressed this question in my responses to questions 6, 8, 9 and 10.
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Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
The Bear Creek (purple) lineage is critically endangered, given that it resides only in a single creek with
probably fewer than 500 fish. Andrew Martin presented research from an unpublished MS thesis that
suggested limited genetic variability in this lineage compared to other cutthroat trout lineages in
Colorado. There is evidence of developmental abnormalities in the hatchery, which may arise in high
frequencies in a controlled environment because of relaxed natural selection pressures in captivity. It is
also possible that abnormalities occur for environmental reasons such as water quality issues, lack of
essential minerals or nutrients, and others. The underlying causes of abnormalities warrant further study.
Recovery of the Bear Creek lineage requires it to be replicated into South Platte streams (with renovation
and barriers as needed) and existing fish in Bear Creek itself and in the hatchery program are the only
possible sources. This leads to the possibility of inbreeding or an unintentional founder event that could
influence local genetic diversity. Under ideal conditions, it is most prudent to stock fish directly from a
donor stream into a recipient stream to avoid hatchery-induced “domestication” selection. However, given
low numbers in Bear Creek and the possibility for demographic fluctuations due to sedimentation and
other environmental changes, it will be critical to use hatchery fish as founders to new populations. Thus,
careful evaluation of hatchery stocks for genetic diversity and evidence of viability loss due to inbreeding
is essential. It may be prudent to develop a brood stock management plan that stipulates mating designs,
refreshment and retirement rates of brood stock, and steps to reduce domestication selection (e.g.,
supplying wild feed, and naturalized conditions in captivity). A monitoring program for newly established
populations should be implemented immediately following restocking.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
The Metcalf et al. 2012 study showed that Bear Creek (purple lineage) fish were found only in the South
Platte River, and that yellow lineage fish (presumably native to the Arkansas River) are probably extinct.
In my estimation, that leaves East Slope green lineage fish (Como, Severy, Taylor, and perhaps Hayden
Creek) as candidates for donor populations for reintroduction into the Arkansas River drainage. It is
essential to identify suitable streams and assess what trout populations exist there. Judicious stream
renovation, barriers, and stocking from donor populations may be the best approach to repopulation
Arkansas River streams. It appears that there is less urgency to restocking the Arkansas River drainage at
this time, so it will be best to await results of definitive studies to identify whether East Slope green
lineage fish are native, and whether suitable (low to no introgression) populations exist as donors.
Otherwise, a carefully designed and genetic marker assisted breeding program could be established to
„restore‟ genetic purity through backcrossing. This would necessitate a large suite of nuclear DNA
markers that could be assessed non-destructively and careful tagging and recording of mating schemes in
the hatchery. A general guideline should be to use wild populations as donors when possible. Once new
populations are established, a monitoring program should be implemented to assess stocking success and
demography of stocked fish.
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14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
Successful marker-assisted breeding programs necessitate further development of co-dominant nuclear
DNA markers (i.e., preferably a large number of single nucleotide polymorphic markers [SNPs]) and
perhaps a large suite of microsatellite DNA loci to fully characterize genetic diversity, relatedness, and
levels of introgression. High-throughput characterization of nuclear DNA markers will be absolutely
essential as all fishes in the Bear Creek lineage should be genotyped to assist with setting goals for
genetic diversity, assessing new populations for founder effects, and designing brood stock management
plans. Further study of East Slope green lineage fish is also warranted, with similar goals and objectives
as indicated for Bear Creek.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
Management, Highest Priority:
a. Establish new populations of Bear Creek lineage fish in the South Platte River drainage as soon
as possible.
b. Protect Bear Creek from human encroachment.
c. Continue and sustain efforts to establish a viable hatchery program for Bear Creek lineage.
d. Carefully evaluate pure and experimental crosses of Bear Creek fish for inbreeding and possible
outbreeding depression.
e. Establish a large set of co-dominant nuclear DNA markers that are set up for high-throughput
analysis. I suggest SNPs should be developed from the cutthroat trout transcriptome (using East
Slope and West Slope green, blue, and purple lineage fish as sequencing templates with
barcoding) and mapped to the rainbow trout genome to identify genes that are potential targets of
natural and hatchery-induced selection, as well as neutral variation. AFLPs are dominant markers
and are not as well suited to exploring backcrosses and variation linked to known genes.
f. Once item e. is complete, evaluate the genetic and meristic status of East Slope green lineage fish.
g. Based on the outcome of item f., identify appropriateness of stocking Arkansas River drainages.
h. Initiate taxonomic revision of cutthroat trout in Colorado. This is desperately needed to recognize
biodiversity that was revealed by molecular and meristic study, and to pave the way for protection
of East Slope green lineage fish if warranted by further molecular study, and for increased
protection of Bear Creek fish.
i. Survey San Juan GMUs for presence of red lineage, conduct simultaneous demographic surveys.
j. Depending on the outcome of item i., scope a program to produce „red lineage‟ fish through
backcrossing.
Continuing Activities:
k. Assess threats to green lineage on the West Slope. Explore (or maintain) federal protection as
necessary and warranted. Continued management at the GMU level is appropriate.
l. Assess population status of blue lineage fish in West Slope drainages, continue demographic and
genetic assessment, prevent habitat degradation and opportunities for hybridization with nonnative species. Management at the GMU level is appropriate.
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16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish
from eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than some other stream and lake spawning attempts east of the Continental Divide
in Colorado.
-
What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
I answered this question above (see response to Question 12).
17. Please provide other relevant comments not addressed in the above questions.
There seems to me to be several alternatives with regards to listing and federal protection. There is a
possibility that the discovery of new biodiversity within cutthroat trout in Colorado could lead to reduced
protection of some new biodiversity. The options as they appear to me are to:
1) Do nothing. In this case, Bear Creek and East and West Slope green lineages are protected. The
disadvantage will be challenges to protection of West Slope green lineage fish based on Metcalf
et al. 2012.
2) As an alternative to the „do nothing‟ scenario, it may be possible to designate East slope green
lineage as a DPS under the current scenario and manage it separately (and more intensively) from
West Slope. However, the Service should monitor impacts to West Slope green lineage
populations closely to assess impacts to West Slope green lineage fish.
3) The Service could await much need taxonomic revision, list the purple lineage as the only
remaining greenback cutthroat and uplist it to Endangered under ESA. Assuming that the green
lineage becomes a listed subspecies, the East Slope could be a DPS under ESA.
There will almost certainly be challenges to scenarios 1 and 2, but they could be employed as a stopgap
until taxonomic revision is complete.
Unresolved question:
1) How did Rio Grande cutthroat trout maintain distinctiveness as a lineage despite historical
stocking? The record indicates that New Mexico favored native fish over stocked fish, and that
stocking was much less than occurred in Colorado, but some stocking did occur. Given the
importance and emphasis on massive stocking in Colorado, why weren‟t more blue and green
lineage fishes stocked into the Upper Rio Grande basin in Colorado? Was there evidence of
massive stocking there, and if so, why is there no evidence of introgression in Rio Grande
cutthroat trout? This question speaks to expected outcomes of stocking in the South Platte River –
it may be that stocking could be relatively ineffective as an agent of gene flow in some
circumstances. This could be because stocked fish fail to thrive in a novel environment, or
hybrids are selected against and backcrosses are favored. It may be most appropriate to address
this question if Rio Grande cutthroat trout is listed in the near future.
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Panelist #4 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
A major limitation is the small number (N=30) of historic specimens used in Metcalf et al. (2012:
Table 1). Obtaining and analyzing DNA for museum specimens is no easy accomplishment and the data
the study generated contribute to our understanding of mtDNA diversity in historic populations of O.
clarkii. However, the small sample size that represents historic diversity warrants special caution in
interpretation of the data.
Uncertainty surrounds collection localities, and thus, basin/drainage of origin of the historic specimens
used in Metcalf et al. (2012). Historic records appear ambiguous and some information is based on
inferences made from anecdotal information (as summarized in Kennedy 2010). Contributing to this
uncertainty are historic acquisition of museum specimens (i.e., actual routes of surveys or expeditions),
curatorial practices (i.e., re-packaging/ shipping of fishes post-collection) and likely gaps in stocking
records (i.e., undocumented moving of fishes prior to the collection of historic specimens).
Generally, methodologies and analytical protocols employed to generate the molecular data in Metcalf et
al. (2012) are technically sound, with caveats of low sample size (as above) and short sequences (partial
ND2 gene), limiting statistical power of analysis and inferences that can be made (e.g., AMOVA Fig. 6).
One shortcoming of the Metcalf et al. (2007) paper was that stocking history was considered the only
likely scenario explaining the pattern, while an evolutionary scenario explaining these patterns as
retention of ancestral polymorphism was disregarded. This led to the conclusions that ―the wrong fish
were stocked in the wrong places.‖ Rogers (2010) showed that green and blue lineage populations were
genetically distinct and native to West Slope drainages, underscoring that evolutionary patterns are often
complex and not easily explained with simplistic scenarios. The subsequent study by Metcalf et al. (2012)
considered the green lineage native to the West Slope, but still favored stocking as likely scenario for
occurrence of green lineage populations on the East Slope.
I disagree with stocking as the best explanation for occurrence of green-lineage fishes on both sides of
the Continental Divide. An alternative scenario that assumes the green lineage to be native to both
East and West Slope drainages is likely, because (a) green-lineage haplotypes unique to East Slope
drainages are not replicated among natural populations on the West Slope (data unpublished); and (b)
morphological distinctness of East versus West Slope green lineage populations (Bestgen and Rogers
2013).
Two additional reservations: (1) Data (sample sizes) are insufficient to make the assertion that the
Bear Creek population was native to South Platte River only, but not the Arkansas River basin (Metcalf
et al. 2012). (2) Alternative biogeographic scenarios, most notably hypotheses by Behnke (1992, 2002)
are inaccurately presented; Behnke (1992) noted close similarity between Colorado River, greenback
and Rio Grande Trout and invoked derivation of Rio Grande from greenback cutthroat trout as one among
several alternative biogeographical scenarios.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
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The morphological (Bestgen and Rogers 2013) and genetic (Metcalf et al. 2007, 2012) data agree
that there are four distinct extant lineages (blue, green, Bear Creek and Rio Grande). Other studies
with a broader focus also identified the same lineages [e.g., Loxterman and Keely 2012, Housten et al.
2012 and Wilson and Turner (although the latter study did not include a sample representing the green
lineage)].
Morphological analyses by Bestgen and Rogers (2013) further provided a more nuanced perspective,
demonstrating differences among populations in subdrainages (referred to as GMUs: Geographic
Management Units). Methodologies of this study are sound and include: a broad geographic coverage,
random population selection, blind protocols and replicate counts for difficult traits.
Results show frequency differences across meristic and qualitative (spotting pattern) traits, which
translated in a multivariate framework (ordination and cluster analyses) into distinct groups with some
overlap in multidimensional morphospace. However, complete separation based on morphological
diversity, particular in meristic characters, is unlikely for closely related lineages as the ones examined;
traits were selected in part on what was historically used in cutthroat trout taxonomic studies (e.g.,
Behnke 1992), so as to facilitate comparisons with published data. Classification rates in Discriminant
Function Analysis (DFA), both of individuals and populations to GMU of origin, were surprisingly high
for intra-specific variation, underscoring morphological distinctness of the blue and green lineages.
3. To what extent are historical spatial distributions of green, blue lineages known?
The complexity of phylogeographic (evolutionary) patterns in combination with an extensive stocking
history makes it impossible to infer with certainty historical distributions. However, available
morphological and genetic data are likely a good approximation of phylogeographic patterns as long
as alternative hypotheses are fully considered. The ―truth‖ is likely more complex than what we
anticipate (or would like). Natural populations exist as dynamic entities over space and time, distributed
across a heterogeneous landscape and subjected to a multitude of processes (e.g., climate fluctuations,
stochastic events) that influence their genetic and morphological diversity in unexpected ways (Douglas
et al. 2003).
Genetic analyses of historic museum samples (Metcalf et al. 2012) documented the blue lineage in West
Slope drainages and the green lineage in West and East Slope drainages. Failure to detect lineages in
specific subdrainages cannot be taken as ―proof‖ that they indeed did not occur there historically; sample
size was simply insufficient to encapsulate historic diversity.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
Comparing levels of divergence among studies is difficult, due to differences in methodologies,
sample sizes, analytical protocols, scope and focus of studies. Even a simple measure, such as percent
sequence divergence, is dependent on the evolutionary rate of the marker examined (e.g., ND2 in vs
ND4). Rather than comparing results of studies that focus on single groups, a better approach is to
examine levels of divergence in broad-scale studies (i.e., those including more taxa and/or a larger
geographic area).
For example, results in Wilson and Turner (2009) indicate genetic differences derived from mtDNA
sequence analysis among O. clarkii subspecies are similar to differences among O. gilae subspecies. A
caveat of broad-scale studies is that each taxon is only represented by a few individuals. Within-group
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diversity is thus difficult to evaluate, and some groups may not be represented (e.g., green lineage is
missing in Wilson and Turner 2009).
Studies of O. clarkii involving nuclear genetic data (e.g., microsatellite loci, AFLP) have mostly aimed at
evaluating levels of introgression by introduced subspecies, and analyses focus on clustering, rather than
genetic divergence (Metcalf et al. 2007, Pritchard et al. 2008, Rogers 2010, 2012, 2013). Furthermore,
due to the uncertainty of homology of AFLP fragments (a particular band is present or absent, different
character states unknown), distance estimates are not meaningful.
As stated above, morphological characters commonly used in cutthroat trout studies were selected by
Bestgen and Rogers (2013) to facilitate comparison among studies and details on congruence between
their study and earlier works are summarized therein.
Without a detailed assessment (which goes beyond this review), I would offer as a general observation:
level of divergence between the four lineages (green, blue, Bear Creek and Rio Grande) approximate
differences between ESUs or subspecies, respectively; divergence between East and West Slope
populations within the green lineage can be equated with Management Units (MUs).
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
Pertinent literature appears to be included. See comments under (1) re: conclusions in Metcalf et al.
(2012).
Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
b. distinct population segments (DPS)?
c. Other?
Based on my review of the available data, levels of divergence between the four lineages (green, blue,
Bear Creek and Rio Grande) approximate differences between ESUs; divergence between East and
West Slope populations within the green lineage can be equated to Management Units (MUs). It is
important to note that divergence among the four lineages is quite similar (also discussed under 10).
The existing taxonomy recognizes three distinct subspecies, creating a dilemma how to partition four
lineages among three taxa. Based on geography, the blue lineage could be equated with O. c. pleuriticus,
and the Rio Grande lineage with O. c. virginalis, leaving O. c. stomias as available category for either the
green or Bear Creek lineage with the remaining one having to be described as a new subspecies (see
comments under questions 7 and 8).
Taxonomic re-arrangement would influence conservation of subspecies/lineages similar to the Anaxyrus
boreas species group (Goebel et al. 2009). Interestingly, the Boreal Toad has a similar distribution to O.
clarkii subspecies and it also exhibits ―many highly divergent and isolated lineages at the southern edge
of its distribution‖ (Goebel et al. 2009: 223), a reflection of shared biogeographic histories. As
recommended by Goebel et al. (2009) resource agencies should be encouraged to consider
phylogeographic patterns in their management of aquatic and terrestrial species in the region (see also
comments under question 10).
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7. Is the Bear Creek population considered to be greenback cutthroat trout?
As Behnke points out (2002:195) there is much confusion regarding what represents a greenback
cutthroat trout, mainly due to inadequate and erroneous early descriptions (as summarized in Behnke
1992). Behnke (2002) recognized the distinct phenotype of Bear Lake (Bear Creek) lineage; it is
prominently depicted (page 195) in addition to a stream resident form (page 197).
As outlined under (1) the available data are inconclusive regarding Bear Creek population as the ―true‖
representative of the taxon O. c. stomias. However, since the Bear Creek population represents a distinct
mtDNA lineage, exhibits morphological distinctness, and exists as a small isolated population on one
hand, whereas the taxon O. c. stomias is a listed entity on the other hand, it may be a prudent solution
for management to equate the Bear Creek lineage with the taxon O. c. stomias. The Bear Creek
population is genetically and morphologically unique and represents a distinct evolutionary lineage
(ESU). Due to its rarity, extensive management focus will be needed to prevent it from becoming
extinct. Listing under the ESA would provide this level of attention and protection.
8. How do we describe the East Slope green lineage?
Molecular genetic markers have aided tremendously in detecting cryptic biodiversity, or alternatively,
reducing inflated taxonomic diversity (Douglas et al. 2006). Since species are still described
morphologically, once new molecular clades (evolutionary lineages) are discovered, a sound
morphological evaluation is necessary to guarantee taxonomic recognition of evolutionary diversity (as
per Douglas et al. 2007).
If the Bear Creek lineage is equated with the taxon O. c. stomias, a new subspecies would have to be
described (morphologically) to accommodate the green lineage (including both West and East Sope
populations), with the East Slope populations being regarded as a distinct population segment (DPS) or
management unit (MU) within this new O. clarkii subspecies. Similarly, if the green lineage is equated
with O. c. stomias, the East Slope lineage would also have be designated as an MU or DPS within O. c.
stomias to accommodate its genetic and morphological distinctness from West Slope populations of the
green lineage.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
The four lineages (green, blue, Bear Creek and Rio Grande) are separated by several nucleotide
differences from each other (Metcalf et al. 2012:Fig. 4); there is some additional minor variation within
lineages (Metcalf et al. 2012:Fig. 2) but a detailed overview of haplotype distribution by
drainages/populations is lacking. If my recollection of presented/discussed data is correct, these minor
variations correspond to geographic patterns and consequently represent additional variation among
drainages. This is consistent with the morphological data (Bestgen and Rogers 2013) that showed a
subtle, but clear signal of geographic variation among different qualitative and meristic characters,
leading the authors to distinction of GMUs (Geographic Management Units).
The entire green lineage should be recognized as a distinct ESU or subspecies, with several GMUs/
recognized as geographically isolated entities (MUs) within this ESU/subspecies; the East Slope green
lineage populations would represent one such MU. Genetic and morphological differences between East
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and West Slope populations of the green lineage are not sufficient to warrant recognition of each as a
distinct ESU.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
Evolution of cutthroat trout in the West likely occurred as a series of reticulate events, rather that a
single-non-reversible event. While headwater transfers/stream captures are rare, climate oscillations (and
precipitation) during Pliocene/Pleistocene were driving forces in shaping diversity in the arid
Southwest (see Douglas et al. 2006, Hopken et al. 2013).
Pleistocene climate was characterized by increasing variability (oscillations) providing potential
biogeographic hypotheses for diversification in cutthroat trout in spite of apparent geographic
barriers (as summarized in Minckley et al. 1986). Pleistocene climate fluctuations have been shown to
correspond with intra-specific diversification (Douglas et al. 2009).
The range-wide study of O. clarkii by Loxterman and Keely (2012) showed that genetic diversity largely
correspond with basins; smaller drainage connections added complexity to the overall generalized
patterns. Similarily, Shiozawa et al. (2010) provided a detailed analysis of mtDNA divergence across O.
clarkii and associated major splits with vicariant events; drainage divides were likely major barriers to
gene flow. In addition, biogeographic hypotheses have generally broad support across diverse taxa (e.g.,
Boreal Toad as mentioned under question 6).
Metcalf et al. (2007) rejected an interbasin transfer of fishes in the Rockies of Colorado ―because it has
not been recorded,‖ although it is unclear what this statement referred to (I agree – nobody was there to
observe it and lived to tell about it). Several studies (Loxterman and Keely 2012, Turner and Wilson
2009, Shiozawa et al. 2010, Metcalf et al. 2012) have shown that relationships among the four lineages
are unresolved. This reflects recent divergence of these lineages, and stands in contrast to the assertion by
Love Stowell (2011, unpublished) that the O. c. pleuriticus/O.c. stomias split is much older than
proposed. However, mid-Pleistocene fossils document presence of potential ancestors of O. clarkii in the
Rio Grande basin, suggesting a deeper split between cutthroat trout in East and West Slope drainages.
Behnke (1992) regarded this scenario as less plausible, because given the high morphological similarity
between West and East Slope populations, he assumed a more recent split between Colorado River and
greenback cutthroat trout. The morphological analyses by Bestgen and Rogers (2013) showed cooccurrence of two morphologically distinct forms in these basins, once genetic data were used to
distinguish between populations representing each lineage.
Contradicting evidence could be accommodated by a scenario that invokes an initial dispersal of O.
clarkii into drainages on both sides of the Continental Divide, followed by divergence of lineages in
subdrainages. Subsequent dispersal would have allowed spread of lineages into other drainages.
When and where basin-transfers occur is way beyond the scope of this review.
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11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
The morphological (and to some extent genetic) patterns correspond with subdrainages and are
consistent with variation among populations (MUs) within lineages (ESU).
Genetic data have been primarily generated and analyzed to distinguish lineages or detect hybridization
among distinct subspecies (Metcalf et al. 2007, 2012, Rogers 2010, 2012, 2013). Detailed information on
variation within each lineage was not presented.
The morphological study by Bestgen and Rogers (2013) specifically examined variation within and
among populations in both lineages. Results demonstrate variation by subdrainage within each lineage,
leading the authors to identify GMUs.
Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
Bear Creek only exhibits one mtDNA haplotype (Metcalf et al. 2012). Details on nuclear genetic data are
not published. Morphological analyses (Bestgen and Rogers 2013) show a contracted morpho-space,
although this lineage exists as a single population, and thus among-population variation is not available.
In small populations, genetic diversity is lost due to genetic drift. Maintaining a large population in the
wild (possible replicated in suitable habitats as outlined below) should be a high priority.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
The Bear Creek lineage, albeit currently in the Arkansas River drainage, is a poor candidate due to
its small population size, low genetic variability and apparent problems in propagation environments. It is
also questionable if indeed it is or ever was indigenous to the Arkansas River basin (but see comments
above under questions 1, 6 and 7).
If the goal is to re-establish native cutthroat trout across Arkansas River drainages, green lineage fishes
would be the best candidates. It is a likely scenario that the green lineage is native to both East and West
Slope based on: (a) morphological data by Bestgen and Rogers (2013), and (b) unpublished information
provided during the workshop [specifically, distribution of distinct green-lineage haplotypes unique to
East Slope drainages, and patterns in nuclear DNA (albeit the latter data was sparse and presentation
lacked context)].
Green lineage population as many replicated populations (Rogers 2010, 2012, 2013); preferably, green
lineage fish from the East Slope localities should be selected for establishment of additional
populations in the Arkansas River basin, since they form a distinct MU (see comments under questions
9, 10, 11)
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14. How should next-generation DNA sequencing (NGS) approaches be used in Colorado River, Bear
Creek, and Rio Grande cutthroat trout management?
NGS approaches can be powerful tools to assay a larger proportion of the genome, and consequently of
the genetic variation within an individual, population or species. However, costs are prohibitive to
generate genome-scale data for studies at the population level with conservation implications (i.e., assay
variation within and among populations in various drainages). Furthermore, NGS approaches can be
employed to develop diagnostic markers, such as SNPs (Single Nucleotide Polymorphisms as per
Houston et al. 2012) that distinguish different species, subspecies, lineages or even populations and will
make screening methodologies (e.g., introgression, purity assessment) more reliable and cost-effective.
Caution is warranted. NGS appears to be the panacea for all the limitations of previous genetic methods
(as the next technology ―on the PCR block‖ always has) but we are only starting to understand the
bioinformatics tools that will be needed to mine the massive amounts of data generated by these
approaches, the best practices to generate, manage and archive such enormous data sets, and how to
assure data are accurate and reflecting biological diversity and not methodological artifacts (e.g.,
RG90712, RG90714 and RG90732 in Houston et al. 2012).
Despite suggestions during the workshop, I see limited use of NGS approaches for historic samples.
The limitations and uncertainties listed under (question 1) will not magically disappear, simply because
fancier technologies are used. Poor quality of DNA in historic samples, combined with low DNA
concentration (yield) will amplify genotyping errors common in some NGS technologies (i.e., they are
very efficient, but also very ―sloppy‖ methods compared to more traditional approaches with much lower
accuracy). Before agencies step forward to provide funding for NGS studies, they should make sure that
the results are not just of academic interest, but will be applicable in managing natural resources.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
A comprehensive morphological study of historic collections would be informative and insightful.
Questions that could be addressed are:
(1) How widespread (or restricted) were the morphological patterns characteristic for the extant Bear
Creek population?
(2) Which extant green and blue lineage populations are morphologically most similar to historic
specimens found in Colorado, Arkansas and South Platte River drainages?
The morphological study by Bestgen and Rogers (2013) detected fine-grained variation that corresponds
to sub-drainages and reflects a natural pattern either induced by slight differences in habitat among the
different basins/drainages (i.e., ecophenotypic variation) or due to evolutionary differences (ecotypic
differences).
Because they first used molecular diagnosis for separating green versus blue lineage individuals, they
then were successful in using ordination and clustering algorithms to detect subtle morphological
variation that exhibits large overlap in character trait distribution and thus was puzzling to Behnke (1972)
who unfortunately did not have advanced molecular tools available at the time of his seminal studies. The
morphological study by Bestgen and Rogers (2013) forms a very solid foundation against which
future population changes can be gauged; thus, future monitoring should continue collection of
morphological data.
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16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish
from eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than some other stream and lake spawning attempts east of the Continental Divide
in Colorado.
- What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
- What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
Evolutionary and conservation concepts suggest potential issues due to low genetic diversity and highrelatedness (genetic similarity) in breeding parents. Perhaps fishes in the wild can recognize related
individuals and avoid becoming ―kissing cousins;‖ more technically expressed: mate choice might reduce
inbreeding.
The observed problems do not bode well for ―Bringing back O. c. stomias‖ by extensive
propagation/widespread stocking of progeny of the Bear Creek population as eluded to in Metcalf et al.
(2012). The genetic and morphological distinctness exhibited by Bear Creek individuals should be
conserved and replicating the existing population in a few natural, isolated habitats would serve as an
assurance against extinction of this lineage should the population crash or be lost due to stochastic events.
A monitoring plan should accompany these replication efforts, with standard population parameters being
recorded to assure life history characteristics remain similar to those of the original population and also as
a gauge for population well-being. In addition, morphological characteristics should be monitored, since
they will be good indicators if the population experiences evolutionary changes (due to drift/small
population size or environmental forces). Genetic monitoring on a 3-5-year interval would be informative,
too, to detect any introgression/admixture by accidentally introduced cutthroat trout individuals.
17. Please provide other relevant comments not addressed in the above questions.
Our overarching conservation goal should be to identify entities that encapsulate biodiversity across the
landscape. To manage biodiversity, groups with independent evolutionary histories must first be
identified (Mayden and Wood 1995), and these may be categorized traditionally in taxonomic categories
such as ‗‗species‘‘ and ‗‗subspecies‘‘, or, alternatively, as ‗‗evolutionary significant units‘‘ and
―management units‖ (summarized in Douglas et al. 2005, Hopken et al. 2013). The latter categories
provide efficient means of characterizing intra-specific diversity and have been particularly applicable to
conservation of salmoniform fishes (e.g., Waples 1995).
Many freshwater fishes of the northern hemisphere represent recently evolved (often sympatric) lineages
of uncertain taxonomic status (Douglas et al. 1999), with unrecognized taxonomic diversity perhaps being
greatest in salmonids (Behnke 1972).
Systematists make taxonomic decisions on the basis of quantitative and qualitative traits (Douglas et al.
1989). The former are measurable and can thus be subjected to statistical analysis with repeatable
outcomes. Other important traits that distinguish biological entities, such as pattern and extent of spotting
patterns and shape or configuration of body parts, are intentionally or intuitively scored qualitatively.
Visual recognition of subtle similarities and differences in appearance is a major component of "seeing
well, or of noticing and distinguishing with accuracy the objects which we perceive" (Rafinesque 1820).
No doubt, subtle differences exist and have been used to identify different evolutionary entities in
cutthroat trout (Behnke 2002).
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The ‗art of seeing well,‘ was defined by Rafinesque (1820) as ‗‗the art . . . of noticing and
distinguishing with accuracy the objects which we perceive . . . [It] is a high faculty of the mind,
unfolded in a few individuals, and despised by those who can neither acquire it nor appreciate its
results.‘‘ (Doulas et al. 1998)
REFERENCES CITED:
BEHNKE, R. J. 1972. The systematics of salmonid fishes of recently glaciated lakes. Journal of the
Fisheries Research Board of Canada 29:639–671.
BEHNKE, R. J. 1981. Systematic and zoogeographical interpretation of Great Basin trouts. Pages 95-124.
In: R. J. Naiman and D. L. Solz, editors. Fishes in North American desert. Wiley, New York.
BEHNKE, R. J. 1992. Native trout of western North America. American Fisheries Society Monograph 6.
BEHNKE, R. J. 2002. Trout and salmon of North America. The Free Press.
DOUGLAS, M. E., W. L. MINCKLEY, AND H. M. TYUS. 1989. Qualitative characters, identification of
Colorado River chubs (Cyprinidae: genus Gila) and the ‗‗art of seeing well.‘‘ Copeia 1989:653–
662.
DOUGLAS, M. E., R. R. MILLER AND W. L. MINCKLEY. 1998. Multivariate discrimination of Colorado
plateau Gila spp.: the ‗‗art of seeing well‘‘ revisited. Transactions of the American Fisheries
Society 127:163–173.
DOUGLAS, M.E., M.R. DOUGLAS, G.W. SCHUETT, AND L.W. PORRAS. 2006. Evolution of Rattlesnakes
(Viperidae: Crotalus) in the warm deserts of western North America shaped by Neogene
vicariance and Quaternary climate change. Molecular Ecology 15:3353-3374.
DOUGLAS, M. E., M. R. DOUGLAS, G. W. SCHUETT, L. W. PORRAS, AND BLAKE L. THOMASON. 2007.
Genealogical Concordance between Mitochondrial and Nuclear DNAs Supports Species
Recognition of the Panamint Rattlesnake (Crotalus mitchellii stephensi Klauber). Copeia
2007(4): 920-932.
DOUGLAS, M.R., P.C. BRUNNER, AND L. BERNATCHEZ. 1999. Do assemblages of Coregonus (Teleostei,
Salmoniformes) in the Central Alpine region of Europe represent species flocks? Molecular
Ecology 8:589—603.
DOUGLAS, M. R., AND P. C. BRUNNER. 2002. Biodiversity of Central Alpine Coregonus (Salmoniformes):
Impact of one-hundred years management. Ecological Applications 12(1):154-172.
DOUGLAS, M. R., M. E. DOUGLAS, AND P. C. BRUNNER. 2003. Drought in an evolutionary context:
Molecular variability in Flannelmouth Sucker (Catostomus latipinnis) from the Colorado River
Basin of Western North America. Freshwater Biology 48:1254-1273.
DOUGLAS, M. R., P. C. BRUNNER, AND M. E. DOUGLAS. 2005. Evolutionary Homoplasy among Species
Flocks of Central Alpine Coregonus (Teleostei: Salmoniformes) and implications for taxonomy.
Copeia 2005(2):347-358.
DOUGLAS, M. E., M. R. DOUGLAS, G. W. SCHUETT, AND L. W. PORRAS. 2009. Climate change and
evolution of the New World pitviper genus Agkistrodon (Viperidae). Journal of Biogeography
36: 1164—1180.
HOPKEN, M.A., M.R. DOUGLAS, AND M.E. DOUGLAS. 2013. Stream hierarchy defines riverscape genetics
of a North American desert fish. Molecular Ecology 22:956—971.
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LOXTERMAN, J. L., AND E. R. KEELEY. 2012. Watershed boundaries and geographic isolation: patterns of
diversification in cutthroat trout from western North America. BMC Evolutionary Biology 12:38
PRITCHARD, V. L., J. L. METCALF, K. JONES, A. P. MARTIN, AND D. E. COWLEY. 2008. Population
structure and genetic management of Rio Grande cutthroat trout (Oncorhynchus clarkii
virginalis). Conservation Genetics.
MAYDEN, R. L., AND R. M. WOOD. 1995. Systematics, species concepts, and evolutionary significant unit
in biodiversity and conservation biology. American Fishery Society Symposium 17:58–113.
METCALF, J. L., V. L. PRITCHARD, S. M. SILVESTRI, J. B. JENKINS, J. S. WOOD, D. E. COWLEY, R. P.
EVANS, D. K. SHIOZAWA, AND A. P. MARTIN. 2007. Across the great divide: genetic forensics
reveals misidentification of endangered cutthroat trout populations. Molecular Ecology 16:44454454.
METCALF J. L., S. L. STOWELL, C. M. KENNEDY, K. B. ROGERS, D. MCDONALD, J. EPP, K. KEEPERS, A.
COOPER, J. J. AUSTIN, AND A. P. MARTIN. 2012. Historical stocking data and 19th century DNA
reveal human-induced changes to native diversity and distribution of cutthroat trout. Molecular
Ecology 21:5194-5207.
MINCKLEY, W. L., D. L. HENDRICKSON, AND C. E. BOND. 1986. Geography of western North American
freshwater fishes: description and relationships to intracontinental tectonism. In: Zoogeography of
North American Freshwater Fishes (Eds Hocutt CH, Wiley EO), pp 519–613. John Wiley &
Sons, New York, NY.
RAFINESQUE, C. S. 1820. Ichthyologia Ohioensis, or natural history of the fishes inhabiting the river and
its tributary streams, preceded by a physical description of the Ohio and its branches. W. G. Hunt,
Lexington, Kentucky. (Reprint of Call 1889.)
ROGERS, K. B. 2010. Cutthroat trout taxonomy: exploring the heritage of Colorado‘s state fish. Pages
152-157 in R. F. Carline and C. LoSapio, editors. Wild Trout X: Sustaining wild trout in a
changing world. Wild Trout Symposium, Bozeman, Montana. Available online at
http://www.wildtroutsymposium.com/proceedings.php
ROGERS, K. B. 2012. Characterizing genetic diversity in Colorado River cutthroat trout: identifying
Lineage GB populations. Colorado Division of Wildlife, Fort Collins.
ROGERS, K. B. 2013. Recent developments in cutthroat trout taxonomy: implications for Colorado River
cutthroat trout. Colorado Parks and Wildlife, Fort Collins
SHIOZAWA, D. K., R. P. EVANS, P. UMACK, A. JOHNSON, AND J. MATHIS. 2010. Cutthroat trout
phylogenetic relationships with an assessment of associations among several subspecies. Pages
158-166 in R. F. Carline and C. LoSapio, editors. Wild Trout X: Sustaining wild trout in a
changing world. Wild Trout Symposium, Bozeman, Montana. Available online at
http://www.wildtroutsymposium.com/proceedings.php
WAPLES, R. S. 1995. Evolutionary significant units and the conservation of biological diversity under the
Endangered Species Act. Pages 8–27 in J. L. Nielsen and D. A. Powers, editors. Evolution and
the aquatic ecosystem: defining unique units in population conservation. Symposium 17.
American Fisheries Society, Bethesda, Maryland, USA.
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Panelist #5 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
The identification of six different lineages, two of which have no contemporary representatives (identified
so far, at least) seems to be robust. Great care was taken in preparing the historical DNA samples, so
identification of museum specimens should be reliable. In general, the inferences about stocking seem
more plausible than alternative hypotheses. Conclusions regarding nomenclature of O.c.stomias are
speculative, although not necessarily implausible.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
The meristic study generally supports the conclusions of Metcalf et al. (2012) regarding the major
lineages of cutthroat trout in Colorado. Statistically significant differences in several morphometric/
meristic traits were found between groups of samples, and these differences were stronger when the
groups were based on mtDNA lineage than when they were based on geography.
3. To what extent are historical spatial distributions of green, blue lineages known?
They are not known with certainty. The historical study of Metcalf et al. (2012) focused on East Slope
collections. Figure 2 in Rogers (2013) shows that the green and blue lineages currently have broad
overlap in many West Slope drainages. One hypothesis is that much of the current overlap in blue-green
distribution is the result of stocking. This hypothesis seems plausible given the available information but
this issue has not been resolved conclusively.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
This is challenging to assess because previous studies have been based on the geographic subspecies
hypothesis, and genetic lineages within Colorado often do not follow geography. However, in general the
levels of genetic variation found within populations Colorado cutthroat trout seem comparable to those
found in other areas. Some previous studies have shown that the geographically defined subspecies in
Colorado are distinctive as a group but not as strongly differentiated among themselves as some of the
other named subspecies.
I am not an expert in cutthroat trout morphometrics/meristics, and we were not shown enough
comparative data for other subspecies to comment on this comparison. Given the recent demonstration
that genetic lineages of O. clarkii within Colorado do not always follow geography, it would be important
to revisit old meristic/morphometric studies that might have evaluated collections of mixed lineages and
hence obscured underlying differences.
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
Both studies appropriately cited the published literature.
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Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
b. distinct population segments (DPS)?
c. Other?
Four extant lineages were identified in these studies and they are considered separately
Rio Grande: Populations in this lineage are genetically and morphologically distinct and occur
within the nominal historic range for O.c.virginalis. Therefore, it seems reasonable to retain that
subspecies designation for these populations. Ideally, this would be tested by genotyping the type
specimen(s).
Blue lineage: This appears to represent the contemporary distribution of O.c.pleuriticus. The
most plausible explanation for appearance of some blue lineage haplotypes east of the continental divide
is stock transfers from the west. Co-occurrence of many green lineage populations west of the divide
indicates that the historical distribution of the blue lineage is not as broad as originally thought. However,
this lineage appears to be the best representation of O.c.pleuriticus so it could continue to be treated as a
subspecies with revised distribution, at least until a formal taxonomic revision is conducted. However, it
would be important to confirm whether the type specimen(s) of O.c.pleuriticus actually does carry a blue
lineage haplotype.
Green lineage: This is a second lineage that appears to be broadly distributed within what was
historically considered to be the range of O.c.pleuriticus. Complications related to green-lineage
haplotypes east of the divide are discussed below under Question 8. Several possibilities might be
considered for placing this lineage within the ESA concept of ‘species.’ 1) If the blue lineage remains a
subspecies and retains the name pleuriticus, the green lineage might be considered another (new)
subspecies, with the two subspecies having largely non-overlapping distributions (after accounting for
stock transfers) within the historical range of Colorado River cutthroat trout. Whether this is reasonable or
not depends on one’s concept of subspecies; because this issue was not discussed at any length in the
workshop, it is difficult to draw any conclusions in that regard. 2) The blue and green lineages might both
be considered to be DPSs within the subspecies O.c.pleuriticus. Genetic and morphological (and perhaps
ecological) differences could be used to support such a designation under the joint DPS policy. However,
at least some genetic analyses suggest that the green and blue lineages are not sister taxa. That argues
against this approach, unless perhaps the other taxa were also included as DPSs of a larger, more
inclusive species or subspecies. 3) The green lineage might be considered a DPS of another taxonomic
unit (species or subspecies). It is not clear what this larger unit might be unless it is the entire species O.
clarkii. Under this scenario, the species cutthroat trout would include a number of subspecies and one or
more DPSs that are not nested within the subspecies. This might be reasonable, reflecting the reality that a
species could be composed of various subspecific units that have achieved different degrees of isolation
and divergence (some distinctive enough to be considered subspecies, others only DPSs). However, I
can’t think of a species for which this type of arrangement has been formally proposed.
Bear Creek: It seems clear that this population is distinctive enough to be a listable entity under
the ESA. Others have made the argument that this population should get the name O.c.stomias and be
considered to be true descendants of greenback cutthroat trout. I don’t necessarily disagree but think that
is an issue that taxonomists need to resolve. In the meantime, two options seem feasible: 1) declare that
BC will be considered to be stomias and greenback for purposes of the ESA, at least until the
nomenclature is formally resolved. This would provide for the most continuity in ESA listing status. 2)
declare that, at a minimum, BC qualifies as a DPS of the species O. clarkii and can be listed as such. This
would presumably require some legal maneuvering to accomplish.
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7. Is the Bear Creek population considered to be greenback cutthroat trout?
See answer to previous question.
8. How do we describe the East Slope green lineage?
I am not sure that currently available information allows us to reliably distinguish between two competing
hypotheses:
1) The green lineage is native to the East Slope.
2) Green lineage haplotypes in some East Slope populations are the result of stocking from West
Slope sources.
My hunch is that the second hypothesis is more likely to be true, but I could be wrong. This is a situation
where policy makers have to determine how precautionary one wants to be. Conserving these East Slope
green lineage populations would help preserve future options, but would come at some cost to society.
Under the assumption that #1 is true, FWS could consider these East Slope populations to be a DPS of the
larger green lineage (if it becomes a new subspecies). If instead the green lineage is considered a DPS of
O. clarkii, it is not clear how the East Slope population could have a separate listing status.
With more nuclear data it might be possible to distinguish between these hypotheses. Programs like Jody
Hey’s computer program IMa can potentially distinguish between hypotheses that involve long-term
isolation and those that involve more recent gene flow. Collecting enough nuclear data to adequately test
this should be a priority.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
Although (as noted above) the concept of subspecies is fuzzy and was not discussed much at the
workshop, I see little basis from existing data to consider the East Slope green lineage populations a
separate subspecies, under any subspecies definitions one can find in the literature. Per Question 8, under
some scenarios these populations might meet the criteria to be considered a DPS, if it were concluded that
their presence east of the divide was not the result of stocking.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
The two competing hypotheses are laid out in the MS thesis by Love Stowell (2011): Behnke’s
hypothesis of multiple, relatively recent stream-capture events across the continental divide, or Metcalf’s
hypothesis of an older and one-time crossing of the divide, followed by diversification among subbasins. I
don’t believe that currently available analyses allow one to distinguish between these hypotheses.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
See responses to Questions 6-9.
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Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
Based on Table 12 in the draft Bestgen report, Bear Creek fish have higher than average levels of
morphometric/meristic variability at some traits and lower than average at others—no really consistent
trend. Some of the variation could be influenced by environmental differences between hatchery and wild
fish from Bear Creek.
For Bear Creek, the most important issue is not the level of (presumably neutral) genetic variation at
traditional markers, but whether the population shows evidence of inbreeding depression. Reports of high
frequencies of major abnormalities in hatchery Bear Creek fish are alarming in this regard, but they could
be due partially or entirely to environmental conditions associated with culture. The common-garden
experiment currently being conducted should shed light on this issue. This experiment should also
provide an opportunity to evaluate the basis for the small size of Bear Creek fish. If it is genetically based
it provides additional support for distinctiveness of this lineage; if it turns out to be largely environmental,
the meristic/morphometric results should be re-evaluated with this in mind, because several of the
characters used were positively correlated with size. It would also be useful to expand the meristics work
to assess fluctuating asymmetry in Bear Creek and see how it compares with levels in putatively healthy
populations.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
By all accounts, yellowfin are extinct. The two East Slope populations with green-lineage haplotypes are
of uncertain origin; I would not recommend spreading them unless it can be conclusively demonstrated
that they are indigenous to the basin. Therefore, native cutthroat from the Arkansas River basin could well
be extinct. Trout introduced from other areas could not be considered ‘native cutthroat of the Arkansas
River Basin.’ However, such introductions might serve general conservation goals by expanding the
range of current lineages of Bear Creek and/or Rio Grande populations.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
Next generation sequencing (NGS) is a broad range of approaches that already are providing vast
amounts of new genetic data for non-model species. This is not a silver bullet that will solve all of the
challenging questions about cutthroat trout in Colorado. Nevertheless, these approaches might be useful
in several regards:
Screening large numbers of markers might identify outliers that are linked to genes associated
with adaptations.
More nuclear data might help resolve competing hypotheses regarding East Slope populations
with green lineage haplotypes (see Q 8).
NGS data could provide more detailed information about the distribution of genetic diversity
across the Bear Creek genome.
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15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
See responses to other questions
16. Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish from
eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than, some other stream and lake spawning attempts east of the Continental
Divide in Colorado.
- What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
- What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
See response to Question 12. If the studies underway provide evidence for significant inbreeding
depression, then some sort of genetic rescue should be attempted. As was the case for the Florida panther,
this could involve controlled introductions of a small number of individuals over time with careful
monitoring of founder contributions. This could be done in several new, experimental populations without
affecting the base population. The most plausible sources for immigrants might be contemporary
populations in the Rio Grande drainage or green lineage populations.
17. Please provide other relevant comments not addressed in the above questions.
A few minor suggestions to consider in finalizing the meristics report:
Table 5-8: include sample size under the name of the collection
Table 9 and elsewhere: show results for at least one more principal component, since the first 2
only capture a bit over 50% of the total variation.
It would be good to see a more rigorous evaluation of the effects of size, since Bear Creek fish are
very small and several traits are positively correlated with size.
Table 10: exactly which groups of samples are compared here?
Discriminant function analyses: clarify that jackknife/leave-one-out procedures were used in
assessing classification accuracy.
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Panelist #6 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
In my opinion, the Metcalf et al. (2012) study was very well performed. The data themselves were
difficult to collect, given the degraded nature of the DNA and small quantities they were able to obtain.
The measures they took, in collaboration with the Australian Center for Ancient DNA (ACAD), satisfy
doubts about contamination and the validity of using DNA for historical inferences.
Metcalf et al. (2012) provides evidence for six, and possibly seven, distinct lineages of cutthroat trout in
Colorado waters historically. I will start with discussing inferences that are more supported from the
evidence and then progress towards inferences that have less support.
First, the historical presence of a distinct cutthroat trout lineage (I will use the term lineages as it has been
used in Metcalf et al. (2012) and as we decided to focus on this term during our panel meeting) in the
South Platte River (purple lineage) is supported by the data. The presence of two haplotypes in the nine
individuals sequenced and the divergence of these haplotypes from other cutthroat trout historical and
modern haplotypes makes a convincing case. The modern samples make a convincing case that this
historical South Platte River lineage now is known only to occur in Bear Cr (Arkansas drainage; I will use
the term drainages as it has been used in Metcalf et al. (2012) and other papers related to this issue,
though it was also used interchangeable with „basin‟). The Bear Cr. lineage is genetically divergent from
other southern Rocky Mountain cutthroat trout lineages (Love Stowell 2011; Metcalf et al. 2012).
Second, the presence of a distinct lineage in the Rio Grande drainage is clear and does not seem to need
further discussion for this report.
Third, the existence of distinct blue lineage is well supported by the evidence presented in Metcalf et al.
(2012). It needs to be recognized that only one individual was sequenced from the White/Yampa by
Metcalf et al. (2012). When combined with modern data from the White/Yampa presented in Metcalf et
al. (2012) but also in conjunction with the much broader survey summarized by Rogers (2013; Recent
developments in trout taxonomy) a convincing case is made for the distinction of this lineage from others.
Further, the combination of these studies makes a convincing case that the blue lineage is native to the
White/Yampa drainage. Metcalf et al. (2012) found evidence of the blue lineage in the Colorado drainage.
The data on historical stocking presented by Metcalf et al. (2012), Rogers (2013), and the presentation by
Chris Kennedy that we saw during the panel meeting suggest that the presence of this blue lineage in the
Colorado is due to historical stocking from nearby operations in the Yampa/White drainage.
Fourth, the existence of a distinct green lineage is well supported by the evidence presented in Metcalf et
al. (2012). Again, it should be acknowledged that a limited number of historical samples were examined
(six individuals from four locations in the Colorado and Gunnison drainages) but combined with the
modern data from Metcalf et al. (2012) and in conjunction with broader geographic surveys (Rogers
2010; Rogers 2013), a convincing case is made that the green lineage is native to the
Colorado/Gunnison/Dolores drainages.
Fifth, the historical presence of a distinct cutthroat trout lineage in the San Juan drainage is supported by
the data. Two distinct haplotypes were observed. However, the use of one locus and limited historical
samples dictate that care is used regarding this particular conclusion. Additional historical samples would
help to substantiate this observation, as would fortuitous sampling of possible extant populations of this
apparently distinct lineage.
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Sixth, the distinct yellow lineage in the Arkansas drainage is well supported. The eight individuals
sequenced from four locations make a good case that this represents the extinct O. c. macdonaldi.
Seventh, green lineage fish on the East Slope present the greatest challenge and harbor the most
uncertainty. Two individuals from Twin Lakes (collected in 1889) in the Arkansas River drainage had
green lineage haplotypes based on historical samples. This can be explained by two hypotheses. First,
undocumented historical stocking could have moved green lineage fish from west to east of the divide.
Second, green lineage fish may have naturally colonized the Arkansas River drainage at an earlier point
(likely earlier than they would have been anthropogenically moved). Modern data, summarized by Rogers
(Rogers 2010; Rogers 2013) reveal green lineage haplotypes in additional Arkansas River drainage sites.
Further, the most common East Slope haplotypes are not found west of the Divide (see „Facts‟ sheet). As
discussed below, there is evidence of morphological divergence of green lineage fish on opposite sides of
the Divide (Bestgen et al. 2013). Thus, the most contentious finding in Metcalf et al. (2012) relates to the
East Slope green lineage fish.
Additional considerations: all historical inferences from Metcalf et al. (2012) are based on 30 individuals
and one maternally inherited locus (a fact fully acknowledged by these authors). As was discussed during
the panel meeting, next-generation sequencing (NGS) approaches may be useful to reveal patterns at
many loci in the nuclear genome and/or a larger portion of the mitochondrial genome. NGS can work for
small fragments of DNA so it may be very useful in this regard. More genetic data could help resolve the
relationships in question and I recommend that this step occur. However, it should also be kept in mind
that, unless additional museum specimens are found (from which usable DNA can be obtained), historical
inferences will be limited by sample size. Caution should therefore be exercised and over-interpretation of
historical data should be guarded against.
2. Does the meristic study correlate with findings in the genetics study (i.e, does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
The meristic/morphometric study performed and report written by Bestgen, Rogers, and Granger was
very well done (Bestgen et al. 2013). Molecular and morphological data were generally concordant. The
molecular and phenotypic data sets provide independent sources of information for the evaluation of
taxonomic hypotheses. That these two sources agree in this case allows us to greatly strengthen the
inferences we can make. The meristics/morphometrics report finds morphological differences among the
blue, green, Bear Cr., and Rio Grande lineages. The Bear Cr. (purple) lineage was particularly divergent.
The blue and green lineages were generally divergent once spotting pattern data were included. However,
green lineage fish from the East Slope were more similar to blue lineage fish along PC1 than they were to
West Slope green lineage fish.
The general concordance between molecular and phenotypic data sets provides highly valuable
information for Colorado cutthroat trout. Phenotypic variation like that examined, which likely has a
highly polygenic basis, can be influence by natural selection, gene flow, and genetic drift, and mutation
(likely to a lesser extent over the time periods considered). Environmental factors could also influence the
phenotypic data. However, the traits examined are likely to have low environmental sensitivity relative to
many other traits. Further, the report found consistent differences between rainbow trout and cutthroat
trout from the same location. Environmental induction would not be consistent with this observation.
Thus, the potentially confounding effect of similar environments leading to similar phenotypes in highly
divergent lineages seems to be minimized in this data set.
3. To what extent are historical spatial distributions of green, blue lineages known?
I review the evidence regarding historical spatial distribution of the green and blue lineages above
(Rogers 2010; Metcalf et al. 2012; Bestgen et al. 2013; Rogers 2013). The data that indicate that the
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genetically and morphologically distinct blue lineage was historically confined to the Yampa/White
drainage are convincing. The data that suggest that blue lineage fish east of the Divide are due to past
stocking are convincing (based on the distribution of blue lineage haplotypes and the phenotypic
similarity of east slope blue lineage fish with the most likely hatchery west slope blue lineage hatchery
source). The combined data that suggest the green lineage was historically present in the
Colorado/Gunnison/Dolores drainages are also convincing. The lack of detection to date of the green
lineage haplotypes in the Yampa/White drainage is particularly compelling. The case for the presence of
blue lineage haplotypes throughout the Colorado/Gunnison/Dolores due to hatchery stocking is also
convincing.
The most difficult pattern to explain remains the green lineage individuals/populations east of the Divide.
Morphological as well as genetic divergence suggests that hatchery stocking alone may not explain these
patterns. Further, of the four east slope blue lineage populations examined in the morphological study
(Bestgen et al. 2013), three were green lineage for mtDNA haplotypes but their nuclear genome assigned
largely to the blue lineage. I suspect that this may be due to the AFLP data used and the way the program
STRUCTURE was implemented. AFLPs are dominant markers; band presence indicates that an
individual has either two copies of the allele at a locus (homozygote) or one (heterozygote). Band absence
indicates that an individual is homozygous recessive. STRUCTURE was used with the data to assign
individuals from test populations to either the blue or green baseline data sets (K. Rogers pers. comm.).
When forced to assign the individuals in question (from the east slope green mtDNA lineage), it did not
assign to the green lineages in terms of their nuclear DNA. Instead they assigned largely to the blue
lineage. However, their assignment to the blue lineage could also indicate that these populations are
divergent in their nuclear allele frequencies from other west slope green linage populations. If a third
choice had been present, that is, if east slope green lineage nuclear allele frequencies were well
characterized and represented a third baseline group, assignment of the populations in question may have
been made to this third group. It is difficult to distinguish between these alternatives with the data in
hand. However, use of STRUCTURE with no location prior may provide some insight. Further, as I will
elaborate upon in question 14, use of additional SNP data may help.
Further complicating this issue is the possibility that the East Slope green lineage could be native to the
East Slope (that is, it naturally colonized the Arkansas River drainage at some point prior to human
stocking activities) and subsequent hatchery stocking of west slope green and or blue lineage fish may
have obscured the historical signal. It will be difficult to tease apart the historical versus anthropogenic
hypotheses if both have occurred.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
It seems most likely that the radiation of cutthroat trout in Colorado (defined as the six or seven lineages
defined in question 1 above) has been relatively recent compared to divergence of other subspecies of
cutthroat trout. This radiation appears to have occurred on the order of 200,000 to 1 million years ago,
though it is possible it was slightly longer (Love Stowell 2011). Other cutthroat trout lineages,
particularly West Slope cutthroat trout (O. c. lewisi) and Yellowstone cutthroat trout (O. c. bouvieri) are
more evolutionarily divergent (Allendorf and Leary 1988; Metcalf et al. 2012).
It should be noted that an analysis of outbreeding depression among southern Rocky Mountain cutthroat
trout would be highly useful. Hybrid offspring between rainbow trout and other cutthroat trout lineages
such as the West Slope cutthroat trout (O. c. lewisi) have been shown to have reduced fitness in the wild
(Muhlfeld et al. 2009). The Rocky Mountain cutthroat trout lineages discussed in this report have
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diverged more recently than rainbow trout and West Slope cutthroat trout. It is possible that hybridization
among these southern Rocky Mountain lineages exhibit little to no outbreeding depression, but this needs
to be tested. Crosses have been intentionally or unintentionally performed in hatcheries and in the wild.
However, without performing these crosses in a controlled manner or quantification of their fitness
effects, conclusions regarding outbreeding depression cannot be drawn. I recommend that experimental
quantification of outbreeding depression be performed, as is already underway for the Bear Cr. lineage
(Kevin Rogers pers. comm).
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions
Yes, Metcalf et al. (2012) and the Bestgen et al report (Bestgen et al. 2013) were both well written and
draw from pertinent literature well.
BiodiversityImplications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
I agree with the argument made by one of the panelists that subspecies designation lies outside of
the purview of the review panel. Addressing subspecies designations will require taxonomic
revision. This does not preclude the need to determine whether distinct lineages warrant
protection as DPS‟s.
b. distinct population segments (DPS)?
In my opinion, the purple lineage (Bear Cr.), West Slope green lineage, West Slope blue lineage,
and East Slope green lineage could warrant protection as separate DPSs.
c. Other?
7. Is the Bear Creek population considered to be greenback cutthroat trout?
A great deal of discussion occurred regarding what should be called greenback cutthroat trout. This
common name appears to have been meant for cutthroat trout in the South Platte River, according to
David Starr Jordan. Outside of the controversy about type specimens and what should receive the name
stomias, it seems appropriate to give the common name greenback cutthroat trout to the Bear Cr. purple
lineage.
The origin of fish in Bear Cr. remains uncertain. Kennedy (2010) provides a detailed report about Bear
Cr. and how cutthroat trout may have gotten there. He makes a convincing case that a) Bear Cr. was
historically fishless and b) the fish likely came from a private hatchery either near Colorado Springs (De
La Vergne hatchery) or in Manitou Park (Bell Hatchery). For the historically fishless point (a), there is a
substantial barrier downstream of the extant Bear Cr. population and Kennedy (2010) uses some historical
references to support a lack of fish in Bear Cr. The historically fishless Bear Cr. inference seems valid to
me. For the point about the origin of Bear Cr. fish (b), fish at these two hatcheries at that time (roughly
1882) apparently came from either Trout Cr. (South Platte Drainage) or Beaver Cr. (Arkansas Drainage).
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Kennedy (2010) and in his presentation at the panel meeting argues that Trout Cr. would have been the
more likely source, based on geographic distance and ease of travel. While it appears that uncertainty will
always remain regarding this issue, the analysis of historical records provides support for the current
hypothesis, based on genetic data, that a cross-basin transfer occurred and that Bear Cr. is the last known
remnant of the South Platte River-native purple lineage
8. How do we describe the East Slope green lineage?
The East Slope green lineage should be considered a distinct lineage until further information is available.
The mtDNA and morphological data are concordant. I also describe above (question 3) how there may be
nuclear genomic divergence of the East Slope green lineage from the West Slope green lineage. Together,
the data in hand indicate that separate consideration is the more conservative conservation action.
It should be distinctly recognized that the divergence between East and West Slope green populations
warrants further research. If historical divergence (separate invasion of West Slope green lineage into the
Arkansas River drainage prior to human fish movement) has been followed by more recent
anthropogenically induced hybridization with West Slope green lineage fish (through stocking) then it
should be considered whether the East Slope green linages are a hybrid taxon worthy of protection (see
Allendorf et al. 2001; Trends in Ecology and Evolution 16 (11): 613-622).
It is possible that future data and analyses will reveal that East Slope green lineage populations are solely
of hatchery origin (founded from West Slope green lineage fish from hatcheries). Then the decision will
have to be made regarding the continued conservation of a hatchery-origin lineage. It could be argued that
divergence over approximately 100 years could be ecologically and evolutionarily significant and that
continued conservation at that point is warranted. However, this would be a much more tenuous argument
to make than the one outlined in the paragraph immediately above.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
As mentioned above, I believe the current evidence in hand suggests that the East Slope green lineage
should be considered a distinct ESU or DPS.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroats?
It is very difficult to objectively test possible routes of colonization. Many routes are consistent with the
data currently in hand. A scenario that involves separate invasion of the Colorado and White/Yampa
rivers to form the green and blue lineages respectively seems possible. Further cross-Divide movement is
necessary to explain the purple lineage and the East Slope green lineage. How these historical movements
occurred and whether they occurred one or multiple times is beyond my expertise and current knowledge
of this geographic region. Further, it is not necessary to fully understand colonization routes to objectively
weigh evidence of genetic and phenotypic divergence of extant lineages and make decisions about
separate conservation designations such as ESUs or DPS‟s.
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11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could
lead to those differences and are there any taxonomic implications?
Please see my answers above (Questions 1, 6, and 8) for the green lineage. Regarding the blue lineage, I
find the argument that blue lineage fish found east of the divide are of recent hatchery origin convincing.
The East Slope blue lineage fish have the common mtDNA haplotypes found in the West Slope blue
lineage hatchery source. Further, there was no evidence for morphological divergence of East Slope blue
lineage populations from the West Slope blue lineage hatchery source.
Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be
considered to manage genetic variability in this lineage to ameliorate potential or actual inbreeding
effects?
Metcalf et al. (2007) report low genetic diversity for the four East Slope populations (green lineage and
Bear Cr. included). They report a mean observed heterozygosity of 0.23 (sd = 0.11) for these four sites.
However, data for Bear Cr. alone are not available in that paper. Metcalf et al. (2012) report that „the
population (Bear Cr.) harbours [sic] little genetic variation for loci that are typically variable in cutthroat
trout populations‟ and cite Metcalf et al. (2007). Thus, I am not able to report heterozygosity or allelic
diversity metrics for the Bear Cr. population relative to other populations. We have been told that Bear
Cr. has low genetic diversity from the Martin group. It would be helpful to see a table of genetic diversity
metrics for populations that have been analyzed to date at both microsatellites and AFLPs (would have to
assume Hardy-Weinberg proportions for AFLPs to estimate expected heterozygosity).
Phenotypically, Bear Cr. fish were divergent from other lineages but have maintained variation in the
traits examined (Bestgen et al. 2013). Fish from the blue lineage had consistently lower variation in traits
examined, in terms of the reported coefficient of variation (CV; Table 12 Bestgen et al. 2013). If Bear Cr.
went through a population bottleneck in the recent past (upon founding or later), we might expect less
phenotypic variation in this population than in other populations. However, it is difficult to compare
phenotypic variation among populations. Many factors influence phenotypic variation. If we assume there
are many loci underlying the variation at each trait, then we are dealing with quantitative genetic
variation. This variation will be influenced by variation at underlying loci as well as environmental
variation. If we assume the traits examine have relatively low environmental sensitivity, then we are
assuming the observed phenotypic variation is largely due to underlying genetic variation. In general, we
might expect a close relationship between molecular genetic variation (as determined by nuclear markers
such as microsatellites, AFLPs, or SNPs) and quantitative genetic variation, more specifically, with the
additive genetic variation for the traits in question. When the effects of alleles are additive, they influence
the phenotype in the same way regardless of what other alleles are present. The alleles act independently
of each other and therefore, as a result, differences in phenotype resulting from additive effects of alleles
get transmitted from parents to offspring. Dominance and epistatic effects are not transmitted in the same
way. It is additive effects of alleles that contribute to evolutionary responses to selection. Further, when
we speak of a relationship between molecular genetic variation and quantitative genetic variation, we are
speaking of relationships between measures of heterozygosity at neutral markers and estimates of additive
genetic variation of the phenotypic traits examined.
Importantly, bottlenecks can cause dominance genetic variation to be converted to additive genetic
variation. If this occurs, the relationship between neutral genetic variation at molecular genetic markers
and additive genetic variation is weak. With respect to Bear Cr., additive genetic variation for the traits
measured may have been exposed during a bottleneck. This could explain the relatively large estimates of
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phenotypic variation in this population we suspect went through a bottleneck. Importantly for the
persistence of the Bear Cr. population, this population could still carry many recessive deleterious genes
that may have drifted to high frequency or fixation during a bottleneck. Therefore, this population may
still have a high genetic load. Thus, while it is promising that individuals from Bear Cr. have as much
phenotypic variation as they do, we cannot make any conclusions about genetic variation underlying this
phenotypic variation without controlled crosses and the implementation of a quantitative genetic study
design. We also cannot draw conclusions about the likelihood of inbreeding effects on fitness (inbreeding
depression) from the phenotypic data.
Inbreeding effects should be quantified in the Bear Cr. population. This could involve quantification of
abnormalities in hatchery reared fish and estimates of fluctuating asymmetry (Roff and Reale 2004). An
even more thorough assessment could be accomplished through controlled laboratory crosses. For
example, a series of inbred crosses could be used to compare inbred and outbred offspring. If full-siblings
were mated once, followed by the mating of a first-generation female offspring with her first-generation
male brother, all second-generation offspring would be highly inbred (inbreeding coefficient (F) = 0.375).
The same female could be mated to an unrelated male to obtain offspring with an inbreeding coefficient
(F) of zero. Inbred and outbred offspring from replicate crosses could then be compared. Traits such as
length, weight, growth rate, early survival, and fluctuating asymmetry would all be useful to examine.
Beyond quantification of inbreeding, I believe genetic rescue should be considered as a management
option for the Bear Cr. population. Genetic rescue is an increase in mean fitness in a population owing to
immigration of new alleles (Tallmon et al. 2004). A genetic rescue effect, if observed, indicates that
inbreeding has negatively affected fitness in the focal isolated population. This is a major issue in
conservation genetics. There is a wide variety of data that indicate that inbreeding depression (inbreeding
with subsequent negative effects on fitness) can have major effects on population persistence, through
extinction vortex dynamics. However, inbreeding effects are environmentally sensitive, conditionspecific, and likely to be species-specific (Thrower and Hard 2009). Small population can become purged
of deleterious recessive alleles by natural selection (Crnokrak and Barrett 2002). However, a vast amount
of empirical data now make it clear that purging is not an effective mechanism to reduce inbreeding
depression in most plants and animals (Leberg and Firmin 2008; Allendorf et al. 2013). On the other
hand, many small headwater trout populations seem to persist for potentially long periods of time despite
very small effective population sizes. Greater efficacy of purging over long time periods (hundreds to
thousands of generations) under continuous inbreeding might help explain the persistence of naturally
isolated trout populations.
Experimental data for a genetic rescue effect come from various taxa. The idea seems simple: introduce
genetic variation through translocation of individuals and restore fitness. The likely mechanism is through
masking (making heterozygous) deleterious alleles that negatively effect fitness when homozygous.
Examples include prairie chickens (Westemeier et al. 1998), Swedish adders (Madsen et al. 1999),
Scandinavian wolves (Vila et al. 2003), among others. However, theoretically, we may expect a fitness
decline in the F2 generation and beyond (outbreeding depression). The likelihood of outbreeding
depression is a function of genetic similarity of introduced and extant individuals: we expect increased
outbreeding depression with increased genetic distance (Frankham et al. 2011). Few studies look beyond
the F1, so this has not been well explored. Further, few studies to date have replicated their results or
controlled for environmental conditions (Tallmon et al. 2004).
We have reason to be worried about inbreeding effects for the Bear Cr. population. In addition to the
apparent effects on hatchery-reared individuals, this population also appears to have been introduced
relatively recently. Therefore, purging of deleterious recessive alleles is unlikely to have occurred in this
population.
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I recommend the following with respect to the Bear Cr. population: I believe this population itself should
not have individuals introduced to it. As the last remnant of the South Platte River lineage (to the best of
current knowledge), it should be monitored closely and for now, not have attempts made to introduce
individuals. However, the Bear Cr. population needs to be replicated across the landscape. One extreme
event such as a fire or flood could cause extinction. Therefore, I recommend that Bear Cr. individuals, as
the last remnant of the South Platte River lineage, should be introduced to a number of sites in the South
Platte River drainage. Once established, these populations should be monitored closely, under the
rationale explained by Schwartz et al. (2007). At a minimum, population growth rate should be
monitored. It would be preferred if genetic metrics such as mean expected heterozygosity, mean number
of alleles, and mean allelic richness were monitored yearly. Further, I recommend that the effective
number of breeders that give rise to each cohort (Nb) be estimated yearly (Whiteley et al. 2012). Nb is
estimated when single sample effective population size estimators (e.g. LDNe; Waples and Do 2008) are
applied to a single cohort (young-of-the-year). Nb is an indicator of the number of families produced by
the parents of that cohort, the variance in reproductive success among those parents, and early familydependent survival of the offspring produced (Waples and Do 2010; Christie et al. 2012).
If multiple metrics in any of these replicated populations point towards population decline, loss of genetic
diversity, or reduced numbers of effective breeders (as a surrogate for reproductive success and output),
genetic rescue should be considered. This would entail the introduction of a small number of individuals
to the replicated populations. The source of those individuals will need to be carefully considered. It is
possible that East Slope green lineage individuals would be most appropriate. I would hope that more
resolution about East Slope green lineage fish is available by the time this transfer may be necessary.
Careful consideration should be used to decide the number and sex of introduced fish. Population genetics
theory dictates one-migrant-per-generation among populations equally linked by gene flow is enough to
keep the same neutral alleles segregating in the populations and that the relative strength of gene flow and
selection would determine the fate of non-neutral alleles (Wright 1931; Wright 1940). Whitlock and
colleagues (Ingvarsson and Whitlock 2000; Whitlock et al. 2000) have shown that the “effective
immigration rate” of new alleles in small isolated populations should be elevated over that expected under
the neutral theory because immigrant alleles can increase rapidly in frequency due to selection. The
Florida panther could be used as an important case study for South Platte cutthroat trout. In this example,
Hedrick (1995) used population genetic models to show that a brief period of high gene flow followed by
subsequent generations of low gene flow should reduce the frequency of deleterious alleles without
substantially reducing the frequency of locally adaptive alleles.
It is important to recognize that genetic rescue comes with risks. F2 individuals may have reduced fitness
due to outbreeding depression (Edmands 2007). I recommend close monitoring to determine if genetic
rescue is having a positive effect in this particular circumstance. This would allow an assessment of
whether genetic rescue is a good option for additional populations. This monitoring would need to include
an estimation of the fitness of individuals in the rescued populations. This can be done through genetic
identification of fish to cross type (resident x resident, resident x transplant, or transplant x transplant) and
estimation of fitness as a function of cross type via capture-mark-recapture (CMR) experimentation. Fish
could be individually identified via genetics or with passive integrated transponder (PIT) tags.
A final note for this question, it came up during the panel meeting whether addition of fish from Bear Cr.
to an existing population of blue and or green lineage fish in the South Platte River was a viable option. In
my opinion, this is far less preferable than the type of controlled genetic rescue experiment I outline
above. This alternative would be highly uncontrolled and it would be difficult to understand if there was a
positive or negative effect of the introduction. It is much more likely that this would result in swamping
the genome of Bear Cr. fish, compared to rescue where a small amount of gene flow is meant to alleviate
inbreeding without swamping the genome.
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13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
This question is directly related to the extant genetic data with the greatest uncertainty (East Slope vs.
West Slope green lineage). Above, I describe the alternative explanations for the extant genetic data for
the East Slope green lineage. Given that I conclude that these data suggest that the most prudent
alternative is to consider the East Slope green lineage as a distinct entity worthy of separate conservation
(an ESU or DPS), and given the data that the East Slope green lineage was present in Twin Lakes in the
Arkansas River drainage in 1889 (Metcalf et al. 2012), then it follows that the East Slope green lineage
should be considered for reintroduction as the native cutthroat trout of the Arkansas River drainage.
However, I reiterate, subsequent data and analyses may find that East Slope green lineage fish are
introduced from the west slope.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
Single Nucleotide Polymorphism (SNP) markers obtained from next generation sequencing (NGS)
approaches could be highly useful for cutthroat trout from the blue, green, and Bear Cr. lineages. I see
two possible options, which echo the comments made by one of the panel members during our meeting.
The first option would be to use the data generated by Dr. Shiozawa‟s group but to target SNPs only
within the blue, green, Bear Cr., Rio Grande lineages. This could provide a moderate (on the order of
100‟s) amount of SNPs that are highly informative for distinguishing among the lineages in questions.
This relatively small set of SNPs could be efficiently run on future samples with the use of a platform
such as the Fluidigm system, which can assay 96 SNPs in 96 individuals in a short amount of time.
The second option is to obtain a much larger set of SNPs. For example, the RAD-seq (Hohenlohe et al.
2011) approach could be used to obtain on the order of 10,000 SNPs for individuals from each of the four
lineages in questions. This would provide more data and even greater resolution of genetic relationships
than described in first option. A limitation is that RAD-seq remains relatively expensive and would be
more difficult to perform on subsequent fish than the Fluidigm approach described above. Thus, the
RAD-seq approach does not provide an efficient diagnostic tool moving forward. Given the need to
screen large numbers of individuals from many populations, I recommend the first option.
AFLPs are useful and have provided valuable information regarding cutthroat trout in Colorado. They
have greatly helped in unraveling the story as we understand it currently. However, due to issues related
to the one I describe above (related to the East and West Slope green lineage; question 3), AFLPs will
continue to provide results with multiple interpretations and that are less clear than those that could be
obtained with an informative set of SNPs.
During the meeting, the utility of the application of NGS to museum-obtained DNA was discussed. NGS
could be used to re-analyze the museum fish from Metcalf et al. (2012) at many loci in the nuclear
genome and/or a larger portion of the mitochondrial genome. NGS can work for small fragments of DNA
so it may be very useful in this regard. I reiterate my point, however, about the limitation of inferences
based on 30 fish, no matter how much data per fish are ultimately obtained.
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15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
I will summarize points I have made regarding future research in my answers above
1) NGS analysis of museum specimens from Metcalf et al. (2012)
2) Development of panel SNPs from Dr. Shiozawa‟s NGS data or from additional RAD-seq
obtained data. This panel of SNPs should be used to help further resolve the relationship among
lineages and patterns of hybridization.
3) Resolve the green lineage issue (West Slope vs. East Slope; natural colonization vs. more recent
anthropogenic introduction)
4) Quantify inbreeding in the Bear Cr. lineage
5) Replicate the Bear Cr. lineage across the landscape, perform genetic rescue if necessary (as
determined based on genetic monitoring)
6) Increase understanding of connectivity among populations of both the blue lineage
(Yampa/White drainage) and green lineage (Colorado, Gunnison, Dolores drainages) west of the
Divide. Quantify risk of extinction for isolated populations.
7) Test likelihood of outbreeding depression in crosses among these various lineages
16. Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish from
eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than some other stream and lake spawning attempts east of the Continental
Divide in Colorado.
-
What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the S. Platte drainage?
Please see my answer to question 12. The initial observation of high rates of physical abnormalities in
Bear Cr. fish raised in captivity warrants further research on the potential effects of inbreeding in this
small, isolated, and valuable population.
17. Please provide other relevant comments not addressed in the above questions.
All comments are contained within my answers to questions 1 – 16.
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Literature Cited
Allendorf, F. W., and R. F. Leary. 1988. Conservation and distribution of genetic variation in a polytypic
species: the cutthroat trout. Conservation Biology 2:170-184.
Allendorf, F. W., G. Luikart, and S. N. Aitken. 2013. Conservation and the Genetics of Populations. John
Wiley & Sons, West Sussex, UK.
Bestgen, K. R., K. B. Rogers, and R. Granger. 2013. Phenotype predicts genotype for lineages of native
cutthroat tout in the southern Rocky Mountains. US Fish and Wildlife Service Draft Technical
Report.
Christie, M. R., M. L. Marine, R. A. French, R. S. Waples, and M. S. Blouin. 2012. Effective size of a
wild salmonid population is greatly reduced by hatchery supplementation. Heredity 109:254-260.
Crnokrak, P., and S. C. H. Barrett. 2002. Perspective: Purging the genetic load: A review of the
experimental evidence. Evolution 56:2347-2358.
Edmands, S. 2007. Between a rock and a hard place: evaluating the relative risks of inbreeding and
outbreeding for conservation and management. Molecular Ecology 16:463-475.
Frankham, R., J. D. Ballou, M. D. B. Eldridge, R. C. Lacy, K. Ralls, M. R. Dudash, and C. B. Fenster.
2011. Predicting the probability of outbreeding depression. Conservation Biology 25:465-475.
Hedrick, P. W. 1995. Gene flow and genetic restoration: The Florida panther as a case study.
Conservation Biology 9:996-1007.
Hohenlohe, P. A., S. J. Amish, J. M. Catchen, F. W. Allendorf, and G. Luikart. 2011. Next-generation
RAD sequencing identifies thousands of SNPs for assessing hybridization between rainbow and
westslope cutthroat trout. Molecular Ecology Resources 11:117-122.
Ingvarsson, P. K., and M. C. Whitlock. 2000. Heterosis increases effective migration rate. Proceedings of
the Royal Society of London Series B - Biological Sciences 267:1321-1326.
Kennedy, C. M. 2010. Weird Bear Creek: A history of a unique cutthroat trout population. Technical
Report USFWS:1-9.
Leberg, P. L., and B. D. Firmin. 2008. Role of inbreeding depression and purging in captive breeding and
restoration programmes. Molecular Ecology 17:334-343.
Love Stowell, S. M. 2011. Evolution and conservation of cutthroat trout (Oncorhynchus clarkii spp.) in
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Madsen, T., R. Shine, M. Olsson, and H. Wittzell. 1999. Restoration of an inbred adder population.
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Metcalf, J. L., V. L. Pritchard, S. M. Silvestri, J. B. Jenkins, J. S. Wood, D. E. Cowley, R. P. Evans, D. K.
Shiozawa, and A. P. Martin. 2007. Across the great divide: genetic forensics reveals
misidentification of endangered cutthroat trout populations. Molecular Ecology 16:4445-4454.
Metcalf, J. L., S. L. Stowell, C. M. Kennedy, K. B. Rogers, D. McDonald, J. Epp, K. Keepers, A. Cooper,
J. J. Austin, and A. P. Martin. 2012. Historical stocking data and 19th century DNA reveal
human-induced changes to native diversity and distribution of cutthroat trout. Molecular Ecology
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Muhlfeld, C. C., S. T. Kalinowski, T. E. McMahon, M. L. Taper, S. Painter, R. F. Leary, and F. W.
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Letters 5:328-331.
Roff, D., and D. Reale. 2004. The quantitative genetics of fluctuating asymmetry: A comparison of two
models. Evolution 58:47-58.
Rogers, K. B. 2010. Cutthroat trout taxonomy: exploring the heritage of Colorado's state fish. Wild Trout
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Rogers, K. B. 2013. Recent developments in cutthroat trout taxonomy: implications for the Colorado
River cutthroat trout. Colorado Parks and Wildlife Technical Report.
Schwartz, M. K., G. Luikart, and R. S. Waples. 2007. Genetic monitoring as a promising tool for
conservation and management. Trends in Ecology & Evolution 22:25-33.
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Tallmon, D. A., G. Luikart, and R. S. Waples. 2004. The alluring simplicity and complex reality of
genetic rescue. Trends in Ecology & Evolution 19:489-496.
Thrower, F. P., and J. J. Hard. 2009. Effects of a single event of close inbreeding on growth and survival
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Wabakken, and H. Ellegren. 2003. Rescue of a severely bottlenecked wolf (Canis lupus)
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linkage disequilibrium. Molecular Ecology Resources 8:753-756.
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Panelist #7 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
The ancient mtDNA work suggests the existence of six geographic lineages based upon the limits of
museum samples available and the smaller number of museum samples that mtDNA could be recovered
from. However, additional support for the existence of geographic based lineages is also supported by the
Dr. Rogers AFLP data in Table S3, resulting in a correlation between museum samples, modern DNA
samples and their locations within geographic locations.
Although limited, the small 430-bp subset of mtDNA data ties the mtDNA sequence of the existing Bear
Creek (Colorado Springs) to nine mtDNA museum samples collected within the South Platte River
drainage between 1871-1889. It is the best available science on the historic and current distribution of
cutthroat trout native to the headwaters of the South Platte River drainage. The nine mtDNA museum
samples, representing five separate populations, are reasonably well distributed and represent two
collections separated by 18 years.
The unlikely alternative interpretation to the Metcalf (2012) data would be that all the matching mtDNA
museum samples represent the range-wide organized movement and introduction of a lineage of fish prior
by 1871. Although brook trout were present at the site of the 1889 Jordan collection in Bear Creek
(Denver area), and documents the movement of fish from thousands of miles away by 1889, the ability to
move a uniform population of fish into four separate sites within the South Platte River drainage would
appear to be limited by 1871. However, ranching and mining were present with the South Platte River
drainage by the 1860s (SPNHA), and Metcalf et al. (2012) indicates fish propagation and movement by
the early 1870s. As indicated by the Jordan collections, the railroad made the wide spread movement of
any fish species a possibility. The Denver, South Park and Pacific Railroad reached into the headwaters of
the South Platte River (Como) by 1879 (SPNHA), and the headwaters of the Arkansas River (Leadville)
by 1880 (Clark). As an indication of how fast the widespread movement of non-native fish became, the
first fish distributed from the Leadville National Fish Hatchery were brook trout to Colorado, South
Dakota and Nebraska in 1890 (Rosenlund, 1989).
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
Based upon a random selection of AFLP assigned lineage fish populations and blind passes of meristic
and genetic materials, the Bestgen and Rogers study supports physical and genetic differences between
major river drainages. As stated in the study, “individual traits and discriminant function analysis also
showed substantial structuring within lineages, organized by drainage basin (GMU’s).” Overall, the
meristic study supports the assignment of the blue lineage within the Yampa River drainage, green
lineage within the Dolores, Gunnison, Upper Colorado River drainages, and Rio Grande cutthroats within
the Rio Grande River drainage. Metcalf (2012) and Bestgen (2013), and the Arkansas River collections of
Jordan (1889) provide some indication of a green lineage within the Arkansas River, and possibly the
South Platte River drainage. However, movement of non-native fish into Twin Lakes is documented by
1889, and may explain the existence of green lineage fish collected in 1889. However, the existence of the
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unique East Slope green haplotypes is not supported by the limited museum samples, but not refuted by
known genetic markers from non-native populations.
The meristic study also supports the evidence that the yellowfin and San Juan lineages are extinct, or
currently at population levels below detection, based upon the AFLP screening of conservation
populations of Colorado River cutthroat trout.
3. To what extent are historical spatial distributions of green, blue lineages known?
Although limited to less than 30 pages within the Bulletin of the United States Fish Commission, Vol. IX,
for 1889, the work of David Starr Jordan appears to provide limited formal (for the time) documentation
of the presence and distribution of native fish species within Colorado. Plus, some interesting insights into
politics and loss of aquatic habitats. Jordan also documented the presence of non-native fish across the
landscape by 1889, with brook trout, rainbow trout and Atlantic salmon present in Twin Lakes
(headwaters Arkansas River drainage) by 1889 (page 6 of 1889 report). Although the documentation of
non-native fish makes any speculation on the distribution of native fish difficult by 1889, some
information may be inferred:
Blue lineage. Jordan describes fish from Trappers Lake, and states that several fine examples were
obtained from anglers. Although it is not clear if he visited Trappers Lake, his description of the Trappers
Lake fish appears consistent with known modern day specimens (page 29). Based upon Jordan’s historic
information, museum samples, Metcalf et al. (2012) and Bestgen (2013), there appears to be good
evidence for a blue lineage in the Yampa River basin.
Green Lineage East. Jordan states that “stomias” is a “small trout with very large spots and small scales”.
“The black spots are larger than in any other of our trout.”
GREEN-BACK Trout, Jordan 1889
Jordan also states that stomias is “very common in all the upper tributaries of the Arkansas River and
Twin lakes.” For the Platte basin, Jordan states that stomias is “abundant in the Park Range and in
mountain streams generally.” He also states that “the trout taken by us in the tributaries of the Platte
seems to be identical with the “green-back trout” of the Arkansas.” Thus, the observation of Jordan,
suggests a common/abundant large spotted trout existing within the South Platte and Arkansas River
drainages that Jordan visited, or had gained knowledge of by 1889. Although Metcalf obtained DNA from
the 1800s collection, there is no reference to the physical appearance of the 1871-1889 museum
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collections. Without impacting the museum samples, a limited meristic review of the 1871-1889 museum
collections should be conducted.
Green Lineage West. Jordan states that “trout are very abundant in all the headwaters of the Colorado and
its tributaries, wherever the waters are clear and cold”. He also states “As a whole, the trout from the
Colorado approach most nearly to those from the Rio Grande.” And on page 22, he states that the “Rio
Grande trout have the dark spots rather large and more or less confined to the dorsal and caudal fins and
the region between them.” However, the Jordan illustrations of Rio Grande cutthroat (Plate III, Fig. 7-8)
show a posterior fine spotted adult fish, and a larger spotted “young” fish. Interestingly, Jordan states that
the Eagle River is “very well stocked with trout” and the “Eagle River show more resemblance to the
yellow-fin of Twin Lakes in the small size of the spots and the plain coloration.” Apparently, based upon
his Eagle River observations, he concludes that “the nearest relative of the yellow-finned trout is
“pleuriticus, from which I think it is descended.”
Thus, Jordan’s physical descriptions and figures appear to support a large spotted cutthroat trout
throughout the Arkansas and South Platte Rivers that would support a green lineage east in 1889. His
Eagle River observations of fine spotted fish would not support a green lineage west. But, his written
description of a Rio Grande cutthroat and his statement that, as a whole, trout from the Colorado resemble
Rio Grande cutthroats, would support a green lineage west in 1889. Overall, Jordan’s 1889 observations
for Colorado were limited from 19 July when he arrived in Pueblo, to 2 August when he appears to depart
Delta for Utah.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
I am unable to address with any degree of expertise the differences that have been published for other
studies to either support or refute the degree of differences needed to support lineages, races, subspecies
or species.
However, Metcalf et al. (2012) and Bestgen (2013) document landscape level genetic and meristic
variation with the data and conclusions based upon blind passes of materials and protocols to limit
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variation due to human error. The final report clearly shows that landscape boundaries have shaped
physical and genotypic differences to where individuals and populations can be assigned to landscape
boundaries within a known level of accuracy. Although Metcalf et al. (2012) and Bestgen (2013) have
documented the exchangeability of lineages between major river drainages, Crandall (2000) would seem
to support the Metcalf lineages as ESU’s, since both genetic and physical differences can be demonstrated
between the original physically isolated populations.
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
In my experience as a management biologist, both studies reference a wide range of published and agency
reports that support their conclusions.
Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
b. distinct population segments (DPS)?
c. Other?
This is an area where I feel that I have limited abilities to address the question. However, based upon
Mayr and Ashlock (1991), who defined subspecies as “a collection of populations occupying a distinct
breeding range and diagnosably distinct from other such populations” all the lineages appear to be good
subspecies defined within major river drainages, with limits to natural movement of genetic materials
between river drainages. In addition, Bestgen and Rogers demonstrate that the lineages can be
“diagnosed” to geographic sites by both physical and genetic methods.
7. Is the Bear Creek population considered to be greenback cutthroat trout?
Based upon the limited genetic data, it is reasonable that Bear Creek (Colorado Springs) represents the
best known existing population of native trout that occurred within the South Platte River drainage
between 1871-1889. If it is appropriate to continue to use “greenback” to describe the salmonid native to
the South Platte and Arkansas River drainages, Bear Creek should be considered to be greenback
cutthroat trout. However, there appears to be much confusion between the large spotted and small spotted
forms of cutthroat trout collected and described within the South Platte, Arkansas, and Colorado River
drainages. Additional work to review and document the phenotypes of the museum collections, in
relationship to modern day Bear Creek (Colorado Springs) and other described lineages (Metcalf,
Bestgen), may help resolve questions and inconsistencies within historic accounts.
8. How do we describe the East Slope green lineage?
The East Slope green lineage is a group of four existing populations found within the South Platte (2) and
Arkansas (2) Rivers that physically and genetically assign to the West Slope green lineage. However, they
have unique haplotypes not found within West Slope green lineages, and I assume, within no other known
fish populations. Please note that there was originally only one known South Platte East Slope green
lineage population (Como Creek), with the other South Platte East Slope green lineage population (Fern
Lake) being a transplant of Como Creek stock.
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9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
There may have been a large spotted form of cutthroat trout native to the South Platte and Arkansas River
drainages that are now represented or partially represented by up to four existing populations. As
previously stated, the existence of unique East Slope green haplotypes is not supported by the limited
museum samples, but their uniqueness is not refuted by genetic markers from non-native populations.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
As of this time, no.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
My understanding is that there is no difference between the East and non-Yampa West Slope populations
of Trappers Lake (blue lineages) which supports the fact that many East Slope and West Slope blue
populations were established from a unique lake population of Colorado River cutthroat trout within the
blue lineage. My position on the variation of east/west green populations is stated in question 9.
Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
Hatchery reared fish founded from small adult cutthroat populations, such as Bear Creek and other
“greenbacks” (Como Creek), exhibit high percentages of bi-lateral asymmetry and other obvious physical
deformities. Although the wild Bear and Como Creek populations do not exhibit the high deformity rates
observed in their hatchery off spring, it is assumed that it is a reflection of the overall fitness of the wild
populations.
Milt from other “greenback” wild populations was used in past broodstock programs to increase genetic
diversity and reduce deformities with some success. Since there appears to be no other living population
that conforms to the genetics of the South Platte museum samples, past examples of mixing populations is
not available. Hopefully, other panelists can provide recommendations on how to increase genetic
diversity and reduce deformities (Florida panther example), but limit the dilution of what is unique within
the remaining Bear Creek (Colorado Springs) population.
Based upon past experience with mixing populations to improve diversity, caution should be used for
selecting candidates for out-crosses. Future science may not support the purity of the populations used for
out-crosses.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
Based upon previous work, Metcalf (2012), and Bestgen (2013), there are no remaining yellowfin
cutthroat trout known within the Arkansas River drainage. Although there may be a relationship between
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green lineage large spotted greenbacks and the Arkansas River drainage, it is not well defined at this time.
No reintroductions of “native Arkansas” basin fish should be conducted until more supporting data is
available. However, controlled reservoir sites within the Arkansas River drainage may be well suited for
the rearing of Bear Creek fish for reintroductions within the South Platte River drainage.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
Please see Question 15 for research issues.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
Apply next-generation DNA sequencing on the cross section of known cutthroat trout lineages.
Conduct experiments on the fitness of the existing Bear Creek fish.
Based upon DNA and physical characteristics, what existing cutthroat trout populations could be
considered for mixing with Bear Creek to increase genetic diversity and reduce deformities, while
maintaining the maximum Bear Creek genetic signature and meristics?
Determine the level of DNA and meristics deviation that could be allowed by the ESA under a
beneficial Bear Creek hybridization program.
Continue to search for museum specimens and conduct additional research to review and
document the genetics and meristics of applicable museum collections in order to help resolve
questions and inconsistencies within historic accounts.
16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish
from eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than some other stream and lake spawning attempts east of the Continental Divide
in Colorado.
-
What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
This issue has been experienced in other cutthroat populations/broodstocks. In the early part of the
greenback recovery program, the genetic limits of the remaining pure fish were uncertain, but direct
transfers of approximately 60 adult Como Creek fish did result in new reproducing populations. Later in
the greenback recovery program, broodstocks were established, and milt from other wild pure populations
was used to fertilize hatchery reared eggs and reduce deformities. Both methods of re-establishing wild
populations were successful in establishing new lake and stream populations from a subset of a small
stream population(s). To some extent, the same can be said for the Trappers Lake strain of fish currently
found in Lake Nanita, and the use of these fish for management purposes by Colorado Parks and Wildlife.
Since Bear Creek fish are able to survive within their current habitat limitations, I would think they would
be as successful in re-establishing new stream and lake reproducing populations as the Como Creek stock
was. However, research into the fitness and performance of these fish in the wild could improve the longterm chances for recovery success over a wide range of habitats, and possibly their performance within
the presence of other native fish species. Please see Question 15 for suggested research topics.
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-What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
Please see Question 15 for suggested research topics.
17. Please provide other relevant comments not addressed in the above questions.
No response
References
Bestgen K.R., Roger KB, Phenotype predicts genotype for lineages of native cutthroat trout in
the southern Rock Mountains, un-published report, July 2012, 87 pages.
Clark J. The Ted Kierscey Collection, Leadville Colorado a Capsule History
Crandall, KA. Considering evolutionary process in conservation biology 2000.
Metcalf J. L., S. L. Stowell, C. M. Kennedy, K. B. Rogers, D. McDonald, J. Epp, K.Keepers, A.
Cooper, J. J. Austin, and A. P. Martin. 2012. Historical stocking data and 19th century
DNA reveal human-induced changes to native diversity and distribution of cutthroat
trout. Molecular Ecology 21:5194-5207.
Rosenlund BD, T.R. Rosenlund (1989) Leadville National Fish Hatchery 1889-1989. Fisheries
May-June 1989, pp 18-20.
SPNHA. South Park National Heritage Area, southparkheritage.org
Bulletin of the United States Fish Commission, Vol. IX, for 1889. Pages 1-29
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Panelist #8 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
The Metcalf et al. (2012) study is well designed and provides evidence for a new hypothesis regarding the
spatial distribution of genetic diversity of cutthroat trout in Colorado prior to large scale transfers. The
results supporting six lineages (4 extant) are compelling. In my opinion, however, there are two caveats
regarding the data set that should be considered when interpreting the results (the authors acknowledge
these caveats). First, the inferred spatial distribution of each lineage (historically in Colorado) is derived
from a relatively small sample (n=30). This small sample size makes it challenging to define the
geographic range of each lineage and leads to some uncertainty regarding the origin of some
contemporary populations, notably Bear Creek and some green lineage fish on the East Slope. The
authors contend Bear Creek cutthroat trout represent O. c. stomias and are outside of their native range
(South Platte River drainage) due to an early 20th century transfer. This is a reasonable hypothesis but it
also possible (perhaps not as likely) that stomias could have existed in the Arkansas River drainage and
the Bear Creek area prior to stocking. Additional historical samples from the Arkansas River (if they
exist) would be needed to examine this alternative explanation. Second, the mitochondrial DNA sequence
data is effectively a single gene and thus represents one possible genetic outcome of the combined forces
(e.g., gene flow, genetic drift, mutation, assuming no selection) that influence intra-specific genetic
diversity. Mitochondrial DNA has advantages for this type of analysis but support for the new
“molecular” hypothesis would be strengthened if similar results were found using appropriate nuclear
markers.
Bottom line: I feel the conclusions by Metcalf et al. (2012) are consistent with the data in the study,
supporting a hypothesis of six mitochondrial lineages in Colorado cutthroat trout (4 extant and 2 extinct).
Further study is needed to test the six lineage hypothesis (using appropriate nuclear markers) and refine
the geographic range of the lineages (examine more historical samples).
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
Yes, the meristic study does show that meristic variation is consistent with the molecular hypothesis. On
the other hand, the meristic variation is also consistent with the geographic hypothesis, although the
correlation does not appear to be as strong as for the molecular hypothesis. I found the combination of the
meristic study (Bestgen et al. unpublished) and molecular study (Metcalf et al. 2012) showed that major
diversity (lineages) in Colorado cutthroat trout is/was strongly influenced by major drainage basins as
well as continental divide.
3. To what extent are historical spatial distributions of green, blue lineages known?
The results from Metcalf et al. (2012) and Bestgen et al. (unpublished) suggest the blue lineage was
historically confined to the West Slope of the continental divide and limited mostly to the Yampa River
drainage. This data includes contemporary samples (Bestgen et al. unpublished) that show blue lineage
fish on the East Slope have lower genetic diversity and a subset of the haplotypes compare to blue lineage
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fish on the West Slope – as would be expected from transfers that occurred in the late nineteenth and
early twentieth centuries.
The historical distribution of the green lineage fish is less clear from the available data. The results from
Metcalf et al. (2012) suggest the green lineage occurred on the West Slope south of the blue lineage in the
Colorado and Gunnison River drainages. However, the historical collection also included two green
lineage samples from the East Slope. The authors suggest these samples may have been influenced by
transfers (that occurred prior to 1889) of West Slope green lineage fish. However, the East Slope
collections contain unique haplotypes not found on the West Slope which is inconsistent with a west-toeast transfer. In my opinion, the evidence is at least as strong that the green lineage existed historically on
the East Slope and more analysis will be needed to resolve the question of the origin the East Slope green
lineage fish. As stated in my reply to question 1, this can best be resolved by additional study including
examining more historical samples (if they exist for the area of interest) and applying appropriate nuclear
markers.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
As a geneticist I’ll focus my response mostly on the genetic variation. This is not an easy question to
answer and I don’t feel I have adequately considered the literature to address the question. First of all, any
comparative assessment would have to account for the impacts of transfers and hybridization such as was
done in the two studies above. Second, any comparison should be based on studies that ideally use the
same markers (or marker types, e.g., mtDNA, microsatellites, SNPs). I am not aware of published studies
of cutthroat trout that would allow this type of comparison. Ideally, what is needed is a single study of
cutthroat trout throughout the range. A couple examples were presented during the workshop; however to
my knowledge most of the information is unpublished. Finally, differences in diversity can be influenced
by a number of factors (e.g., effective population size, gene flow, mutation rate) that should be considered
when comparing and interpreting levels of genetic variation.
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
Both studies contained adequate literature support. What is needed, in my opinion, is further study to 1)
address the historical distribution of the green lineage, particularly the evidence of east slope populations,
2) test the molecular hypothesis (based on mtDNA) using appropriate nuclear markers. Also, it is not
clear if the molecular hypothesis describes the meristic variation significantly better than the geographic
hypothesis. Perhaps this could be tested statistically.
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Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
It is not clear to me what a subspecies is and therefore I have trouble evaluating the study
conclusions in this context.
b. distinct population segments (DPS)?
I think the combination of the meristic and genetic studies suggest the four extant lineages are
potentially listable entities as DPSs or evolutionarily significant units. Additional information
concerning life history variation and ecological differences, if they exist among the lineages,
would further support defining the lineages as the listable entities.
c. Other?
7. Is the Bear Creek population considered to be greenback cutthroat trout?
This make sense and is supported by the fact that the Bear Creek ND2 haplotype matches the museum
specimens from the South Platte River drainage and the fact that the term “greenback” was assigned to
native fish in the South Platte and Arkansas River drainages. Regardless of the name, it appears that the
cutthroat trout in Bear Creek are the only existing representatives of the purple (South Platte) lineage.
8. How do we describe the East Slope green lineage?
Given that the East Slope populations possess haplotypes not found on the West Slope it is harder to
argue that the East Slope fish are the result of transfers. They could represent part of the natural range of
the lineage. In my opinion, the East Slope green lineage fish should be considered as of unknown origin
until further study can clarify their relationship to the West Slope fish. Clarifying the distribution of the
green lineage should be a top priority for future research
9. What do rare haplotypes and morphological consistencies of east-green lineage fish suggest in terms of
subspecies or ESU distinctions?
In my opinion, this question cannot be resolved without further research. There is not enough information
in the present studies to characterize the East Slope green lineage fish. Here is where additional genetic
markers, preferably nuclear loci, could provide some insight.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
In my opinion they do not. The genetics and meristic (Bestgen et al. unpublished) studies I’ve seen were
not designed to answer this question. The question should be addressed by evaluating alternative
hypotheses and examining a broader geographic scale like some of the ideas presented by Dennis
Shiozawa in the workshop.
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11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
This question relates to question 3. With respect to the blue lineage, the East Slope fish appear to be nonnative; the result of transfers in the late 1800’s and early 1900’s. The East Slope fish have less diversity
and possess a subset of the haplotypes of the West Slope fish, consistent with transfers. This East Slope –
West Slope variation most likely reflects founder events / bottle necks that occurred during and after the
period of transfers.
Regarding the green lineage, the evidence is at least as strong that fish existed historically on the East
Slope. That is, the East Slope fish possess haplotypes not found on the West Slope. This East Slope –
West Slope variation could have taxonomic implications but more analysis will be needed to resolve the
question of the origin the East Slope green lineage fish. See also the answers to questions #3, 8, and 9.
Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
The greatest concern regarding this lineage is that only a single population, Bear Creek, exists. The
immediate priority must be to replicate the population to reduce the risk of loss of the lineage due to any
catastrophic event in Bear Creek. Sufficient individuals should be used to transfer the extant genetic
diversity to other locations sufficiently large to support a population size that minimizes loss of diversity
due to a bottleneck. The replicate populations should be closely monitored and evaluated to assess
changes in diversity.
Genetic rescue (where gametes from one or more other lineages are mixed with Bear Creek lineage to
increase genetic diversity in Bear Creek) should be considered but only after a more detailed evaluation of
the risk of inbreeding and loss of extant diversity.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
I don’t believe the present studies provide sufficient information to fully answer this question. More study
is needed, including a more detailed evaluation of the origin the East Slope green lineage fish using
additional genetic markers and evaluation of more museum specimens from the Arkansas River Drainage
(if they exist) to establish if it contained purple lineage (Bear Creek) populations. Having said that, if a
high quality location for a replicate Bear Creek population exists in the Arkansas River drainage, then the
Bear Creek lineage should be considered as one source for reintroducing native cutthroat trout in the
Arkansas River drainage. Such an approach would have to weigh the risks associated with losing the Bear
Creek population against potentially occupying non-native territory.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
This approach is not cheap. In my opinion, NGS should be used judicially to address questions
concerning the range of the green lineage fish (specifically, the origin of East Slope green lineage fish)
and test the six lineage hypothesis generated from the mtDNA data. NGS should be applied to both
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museum and contemporary samples (although the application to museum specimens will likely be
difficult due to lower quality of the DNA).
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
I think a broad phylogeographic look at cutthroat trout is needed. It should also be a priority to survey the
San Juan drainage for existing populations that may represent the presumed extinct San Juan lineage.
Beyond that, further research needs should be determined once the next study results are complete (e.g.,
question 14).
16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish
from eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than some other stream and lake spawning attempts east of the Continental Divide
in Colorado.
-
What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
I hesitate to draw any conclusions from this information because as far as I know there has been no study
to quantify the abnormalities and relate them to the environment (hatchery vs wild). Therefore, I would
first conduct a study to assess the extent and type of abnormalities in different environments using proper
controls.
-
What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
I would suggest looking for locations that as much as possible share similar habitat features to the Bear
Creek drainage. Specifically, consider factors such as water temperature that influence development and
growth rate. It will be important to know what habitat features constrain population growth and influence
survival. However, I would not wait on studies to replicate the population if the information is not easily
acquired. Given the need (in my opinion) to replicate the population soon, it would be preferable to
integrate the research into habitat needs with the replication effort. Researchers should monitor closely
the relationship between habitat features and the performance of the replicate populations.
17. Please provide other relevant comments not addressed in the above questions.
No response.
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Other Attendee’s Responses
to the
Greenback Cutthroat Trout Genetics and Meristics
Discussion Questions
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Panelist #9 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
In general, the paper describes the most parsimonious explanation for the patterns seen given the data.
Some conclusions are better supported by the limited data than others. However, some alternative
hypotheses cannot be ruled out. For example – with five widespread museum collections from the South
Platte River basin, it certainly appears that it harbored its own native cutthroat lineage consistent with
those currently found in Bear Creek. Unfortunately, few museum collections were available from the
Arkansas River Basin to comfortably determine that the yellowfin was the native trout there – particularly
since the collections were restricted to the headwaters of the Arkansas River basin, and that two
specimens collected in 1889 from Twin Lakes showed mitochondrial signatures consistent with green
lineage fish. Though perhaps unlikely, it is possible that these fish were not founded by a stocking event
as suggested in Metcalf et al. 2012 but rather by a natural invasion from west of the Continental Divide
perhaps in the late Pleistocene.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
The meristics study correlates surprisingly well with the genetic work – a finding not at all anticipated at
the outset of the study.
3. To what extent are historical spatial distributions of green, blue lineages known?
Collections of blue and green lineage fish are unfortunately sparse in the museum study, making it
difficult to nail down the distribution of these fish. However, when combined with information on extant
populations, confidence in the ranges provided in the Metcalf study becomes more compelling. For
example, not only have green lineage fish not been detected in the White and Yampa River basins despite
intensive sampling, but the Green River basin in Utah and Wyoming also harbor blue lineage fish. It
would be difficult to make the case that the Yampa and Green River basins were not part of the aboriginal
range of blue lineage cutthroat trout.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
Within the species cutthroat trout, other designated subspecies show similar amounts of molecular
variation (see Loxterman and Keeley 2012, Houston et al. 2012). I am not aware of ESU designations in
cutthroat trout, but my impression is that some strains of Pacific salmon currently managed as ESUs
might show less differentiation in genotype and perhaps meristic characters than we are discussing here.
Homing to discrete natal streams has justifiably led them to be protected as ESUs.
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5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
Not sure about all, but certainly adequate to support their conclusions
Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
b. distinct population segments (DPS)?
c. Other?
Although different species concepts will yield different interpretations for these questions, I think it is
instructive to consider the position released by the USFWS in 1996 (USFWS 1996) since that will
ultimately form the foundation for any listing decision. That document states that the “authority to list a
species…extends to subspecies, and for vertebrate taxa, to distinct population segments” but that the
authority to list DPS should be implemented sparingly. Conservation efforts under the Act should be
taken to avoid important losses of genetic diversity (particularly those in which a population segment
whose loss would produce a gap in the native range of a species). The National Marine Fisheries Service
instituted a policy in 1991 for Pacific salmonids that suggests a stock should be considered an ESU if it is
substantially reproductively isolated from other conspecific population units and represents an important
component in the evolutionary legacy of the species – and it was the spirit of the ESU that was used to
develop the USFWS policy on DPS. In that document, three elements are considered in a decision
regarding the status of a possible DPS as threatened or endangered under the Act: 1) Discreteness of the
population segment in relation to the remainder of the species to which it belongs; 2) The significance of
the population segment to the species to which it belongs; and 3) The population segment’s conservation
status in relation to the Act’s standard for listing. Since the question posed simply asks whether the
lineages are potentially listable, we are really just looking to address the first two criteria:
Discreteness – the policy maintains a population segment may be considered discrete if it “is markedly
separated from other populations of the same taxon as a consequence of physical, physiological,
ecological, or behavioral factors. Quantitative measures of genetic or morphological discontinuity may
provide evidence of this separation”. Given the historically isolated nature of the various drainage basins
(for fish) and the results of both the molecular and meristic work, it would be hard to argue that the extant
lineages are not discrete. While the yellowfin cutthroat specimens also appear to be discrete, additional
work should be conducted on the San Juan lineage to determine if they meet the above criteria.
Significance – three of the four criteria outlined in the policy under significance are relevant for the extant
lineages of cutthroat trout. Loss of these lineages would result in a significant gap in the range of the
taxon. In the case of the South Platte native, it appears that the Bear Creek fish represent the only
surviving natural occurrence of that lineage, and there is evidence that the lineages differ markedly from
each other in their “genetic characteristics” (as well as phenotypic traits). Again, it is hard to argue that
the extant lineages are not significant.
Regardless of how the USFWS decides to rule, both molecular and meristic data suggest these lineages
should be managed as discrete entities even at the GMU (4 digit HUC) level. That is presently the current
practice for Colorado Parks and Wildlife, and should continue to be the case.
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7. Should the Bear Creek population considered to be greenback cutthroat trout?
It is clear from David Starr Jordan’s writings that he intended the name “greenback” to be applied to the
fish of the Arkansas and South Platte River basins excluding the large yellowfin cutthroat trout found in
Twin Lakes. If Metcalf et al. (2012) are correct in assuming that the yellowfin was the aboriginal fish of
the entire Arkansas River basin, then the name greenback should default to those found in the South Platte
River basin. This is not necessarily the case for the scientific name stomias since those were assigned to
type specimens that now appear to be Rio Grande cutthroat trout. Since the name virginalis predates
stomias, the latter then technically becomes a synonym for Rio Grande cutthroat trout.
8. How do we describe the East Slope green lineage?
It depends – I think more research is necessary to try and elucidate if they indeed are aboriginal to the
East Slope, or if they merely display uncommon haplotypes and meristic characters by virtue of
anthropogenic activities that may have subjected them to extreme genetic bottlenecks that could fix rare
genotypic and phenotypic characters in their populations
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
Again, confirmation of whether these traits are an artifact of their past or represent real native diversity
needs to occur. Examination of meristic characters in the museum specimens and characterizing all green
lineage population haplotypes would help inform this decision.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
They certainly provide some compelling evidence for probable invasion routes, but not much resolution at
this point.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
Blue lineage – there is no east/west variation in either the phenotype or genotype in these specimens when
the relevant comparisons are made. Blue lineage fish on the East Slope are mildly different
phenotypically from blue lineage west of the Divide only if the entire range is considered (includes fish
from Utah and Wyoming) – but that is not the relevant comparison. Since the current paradigm suggests
that all blue lineage fish on the East Slope were derived from spawn operations conducted at Trappers and
Marvine Lakes, they should be the ones to compare to. There are no phenotypic differences between East
Slope blue fish and fish derived from Trappers Lake. In addition, all East Slope blue populations share the
common haplotypes found in Trappers Lake fish.
Green lineage – there is east/west variation in both phenotype and genotype in these fish, and compelling
arguments can be made for how those differences could have arisen either through natural invasions from
west to east across the Divide some 10,000 years ago or by stocking from west slope sources that
harbored rare haplotypes that were easily fixed in the population through genetic bottlenecks that could
have certainly manifested themselves through small founding populations in marginal habitats. Additional
research is necessary to evaluate the significance of these differences and what the taxonomic
implications should be.
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Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
Although molecular evidence suggests limited genetic variability, studies should first be conducted to
determine if there are any actual inbreeding effects in the wild. If there are indeed fitness consequences,
then genetic rescue should be considered – but only with a small number of individuals. In addition, Bear
Creek and several replicate populations should be maintained even in their inbred state. Repatriated
populations could be used to manage genetic diversity. Meristic variability did not appear to be much
different than what was seen in blue and green lineages.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
We need to resolve the status of East Slope green fish before that can be answered. If indeed the yellowfin
is the only native of the Arkansas River basin, then additional flexibility could be considered in Arkansas
River basin repatriation efforts.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
Much longer sequence reads in both the nuclear and mitochondrial genomes will greatly improve our
confidence in results and will likely reveal additional structure that will assist in addressing some of the
questions above such as native routes of invasion and similarities between East and West Slope fish.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
We should continue to manage these lineages at the GMU level while protecting at least East Slope green
fish until taxonomic uncertainty can be resolved. Research priorities should include examining museum
specimens to determine if Bear Creek fish represent the meristic diversity present in the museum
specimens well, and if the green lineage fish and yellowfins labeled as “greenbacks” in the museum
collections show different meristic traits, and whether those meristic traits are also different from West
Slope green lineage fish. More importantly, fitness studies should be conducted to evaluate what the
consequences (if any) might result from limited genetic diversity in the Bear Creek population, and
whether they are suitable for large-scale reintroduction efforts. These studies are critical to inform
whether genetic rescue efforts are warranted.
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16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish
from eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than some other stream and lake spawning attempts east of the Continental Divide
in Colorado.
-
What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
The potential for fitness consequences may exist in this population that appears to have gone
through a substantial bottleneck. Controlled studies should be implemented to evaluate the
potential fitness consequences to inform future management
-
What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
Studies evaluating the general fitness of these fish compared to others and their hybrids should be
considered in both lab and field settings.
17. Please provide other relevant comments not addressed in the above questions.
No response
Literature cited
Houston, D. D., D. B. Elzinga, P. J. Maughan, S. M. Smith, J. S. Kauwe, R. Paul Evans, R. B Stinger, and
D. K. Shiozawa. 2012. Single nucleotide polymorphism discovery in cutthroat trout subspecies
using genome reduction, barcoding, and 454 pyro-sequencing. BMC Genomics 13:724-740.
Loxterman, J. L., AND E. R. Keeley. 2012. Watershed boundaries and geographic isolation: patterns of
diversification in cutthroat trout from western North America. BMC Evolutionary Biology 12:38.
Metcalf J. L., S. L. Stowell, C. M. Kennedy, K. B. Rogers, D. McDonald, J. Epp, K. Keepers, A. Cooper,
J. J. Austin, and A. P. Martin. 2012. Historical stocking data and 19th century DNA reveal
human-induced changes to native diversity and distribution of cutthroat trout. Molecular Ecology
21:5194-5207.
USFWS. 1996. Policy regarding the recognition of distinct vertebrate population segments under the
Endangered Species Act. Federal Register 61(26):4722-4725.
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Panelist #10 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
For the most part, I believe that their conclusions are well supported. It is of value to have 5 museum
collections for the South Platte River which provided more specimens than any other drainage on which
to compare modern collection from Bear Creek. The possibility of the Bear Creek populations also being
native to the Arkansas River basin is intriguing, but the preponderance of evidence does not suggest that
that is a likely scenario. Newspaper accounts (all except one), Fish Commission reports, and the Jordan
surveys suggest that Fountain Creek drainage was devoid of trout, and with the amount of fish husbandry
occurring in the Pikes Peak region at the time – stocking of Bear Creek seems to be a reasonable
assumption, and that the trout stocked came from the closest source (Trout Creek?) which is South Platte
River in origin.
Further confusing the issue of what cutthroat was native to the Arkansas River drainage is the unique
haplotype found in two of the fish from the Twin Lakes and Lake Creek 1889 collections that is also only
exhibited in the S. Prong Hayden fish (and nowhere on West Slope). In addition, Jordan is his 1891 report
states that the “green-back trout” was very common in the tributaries of the upper Arkansas River, and
were also identical to those that he collected in the South Platte River.
This adds some uncertainty to the conclusion from the 2012 paper that green fish were likely not native to
the Arkansas River basin. On the other hand, numerous (and consistent) Platte River museum specimens
make it abundantly clear that the green fish (found in two of the upper Arkansas River museum
collections) were not the same as the native trout to the Platte River, as Jordan suggested.
The low number of museum specimens actually evaluated, particularly for the West Slope, has been of
concern. However, that is only based on a “more is better” bias, and I have not heard that this was
considered a study weakness by the reviewers of the 2012 paper, or by our panel.
There was some concerned voiced that STRUCTURE should have been run with K set at more than 2.
Doing so may have provided some better insight and may have altered some of the results in the Metcalf
et al. (2007) paper. Some additional work with STRUCTURE (or SNP) may also be necessary to assist in
sorting out the mixed AFLP vs mtDNA results for the three East Slope green fish populations.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
Using the molecular model, I believe that there is strong inference in support of the meristic work for
Bear, RG, and blue; with less certainty for the green fish. Phenotypic traits, PCA and DFA all suggested
that Bear Creek were substantially different morphologically. But, of course, there was no opportunity to
examine museum specimens and conduct necessary morphological counts.
Blue fish grouped well phenotypically and via DFA, not surprising given their similarity (both
morphologically and genetically) and appearance of “Trappers-like” attributes. Lowest CVs for 8 or 10
traits was indicative of the low variation in appearance.
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Conversely, the green fish had the greatest trait variation and had highest CV values for 4 of 10 traits. The
range of the widely varying characteristics was intermediate between blue and RG, which muddied the
PCA results. The disconnect between mtDNA (basis for molecular model) and AFLP results for three out
of the four unique east slope green populations is also a source of incertitude for the meristic study.
Bestgen suggests a couple of hypotheses that might explain the wide variation and also the distinctive
morphology of the East Slope greens. One of those – that the East Slope greens may represent native trout
diversity from a West Slope to East Slope invasion – was in part derived from Metcalf-identified rare
haplotypes. On the other hand, using the geographic model lent support to differentiation between extant
green and blue fish on the West Slope.
3. To what extent are historical spatial distributions of green, blue lineages known?
Metcalf et al. (2012) found that the later collection dates of the blue and green fish and their occurrence
outside of their putative native range made the picture less clear for those two lineages, however there is
more evidence in support of blue fish representing Colorado River cutthroats restricted to the
White/Yampa drainages. No museum collections or extant populations of green fish in those drainages
are defining.
See above (questions #1 & 2) for discussion about uncertainty in green fish historic range that is
applicable here. Martin sent an email to the group on 7/31 with his views on the two alternatives to the
complex green fish picture. I believe that his points suggesting that green fish are not native to the east
slope (through a second wave colonization) are more plausible, and I would accept that as the best
explanation until/if other information comes to light. S. Hayden and its unique haplotypes (matching two
of the Arkansas River museum specimens, but also haplotypes not found on west slope) present a
particularly untidy picture. But again, the preponderance of evidence suggests that the Fountain drainage
was fishless including Severy Creek.
The possibility of Bear Creek fish being native to Platte AND Arkansas Rivers was suggested at the
workshop, as an alternative to Bear Creek being stocked with South Platte River fish. Admittedly, there is
not a smoking gun in terms of the actual stocking event of Bear Creek. However, it would stand to reason
that if the Bear Creek fish were actually native to the Arkansas River that lineage would have been
represented in the 1889 samples.
Although the East Slope picture is clouded for the green fish, there is more substantive support,
particularly for morphology, to suggest that the green and blue were distinct on the west slope.
Classification rates of these two groups were low under the geographic analysis.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
I do not have a working knowledge of other genetic cutthroat studies. However, I believe that Shiozawa’s
work that he explained in his presentation is of particular importance. Those investigations using over
8000 BP from numerous mtDNA genes (ND1, 2, 4L, 4, 5, 6, CytB) provides powerful resolution on
cutthroat phylogenies. He concluded that Bear Creek lineage is distinct from Colorado River cutthroat
trout and Rio Grande cutthroat trout.
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5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
I can’t offer anything on this question.
Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies? Based on the evidence I have seen so far, I would feel comfortable with
subspecies status for Rio Grande, Colorado River and Bear Creek (greenback).
b. distinct population segments (DPS)? The green lineage is most in question, but mostly likely
should be considered a DPS.
c. other?
7. Is the Bear Creek population considered to be greenback cutthroat trout?
Bear Creek haplotype matches the museum specimens from 5 locations within the South Platte River
drainage and provides strong inference that the Bear Creek lineage represents the native fish of the South
Platte River. Since early taxonomists intended “stomias” to apply to fish from the Platte River (even
though the type specimens are Rio Grande cutthroat trout), it seems reasonable to consider Bear Creek
trout as greenbacks. I believe that this is the salient point. What that cutthroat is actually named, is of less
concern to me and I will yield to those better schooled in deliberations of fish nomenclature.
8. How do we describe the East Slope green lineage?
The group generally accepted that ”Meristic/morphometric analyses show consistent differences between
groups defined by mtDNA haplotypes. Patterns were stronger when individuals were grouped according
to genetic lineage than when grouped according to geographical hypothesis. Meristic differences were
also apparent at the level of GMUs.” This applies to the green lineage as well. Waples stated that the
green lineage fish should not be considered as a portion of pleuriticus, and Martin emphatically stated that
greens were not greenbacks.
But the East Slope green lineage fish issues still remains unresolved from my perspective. The
disagreement between AFLP (blue) and mtDNA (green) for three of the East Slope populations needs to
be resolved to further define the relationship between West Slope and East Slope green fish. As
mentioned in my responses to previous questions, the shared haplotypes between the S. Prong and the
museum specimens (but not West Slope green) may be a need for more investigation (SNPs?).
I did like the suggestion voiced by one of the panel members that until such time as we can further
research the west/east green lineage questions, that we might consider managing the green lineage fish
differently on West and East Slope. I believe that the point of that discussion was to consider affording a
higher level of protection for the West Slope fish (within range), than those on the East Slope – but still
with some overall ESA protection.
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9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
With current knowledge, I favor arguments made by Metcalf that it is most likely that the East Slope
green fish are a result of stocking. But phenotypic differences between east and west do add an element of
uncertainty. Bestgen provides two possible explanations; the first that Grand Mesa derived stocking may
have been replaced or “swamped” with existing or remaining native fish on the West Slope, but the same
may not have occurred on the more sparsely populated (fishless?) East Slope; or second, that the East
Slope green fish represent archetypal native cutthroat trout diversity from reinvasion from the west.
In terms of ESA issues, refer to my answer for questions #6 and 8. Likely that DPS is most appropriate
for the green lineage, but with some greater protection afforded the West Slope (Colorado and Gunnison
native) populations.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
Based on genetics, perhaps Shiozawa’s analysis provides a reasonable hypothesis for phylogeny along
with his “molecular clock”. Generally, his progression supports the morphology of similarities of
yellowfin, greenback and Rio Grande. The main difference between the genetic phylogeny as suggested
by Shiozwa and the morphology is with blue fish (Colorado River cutthroat trout) and Bear Creek, where
the Shiozawa phylogeny tree shows early divergence between Colorado River cutthroat trout and the link
to Bonneville/Bear Creek and the yellowfin/Rio Grande cutthroat trout/greenback branch.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
There are perhaps more implications for taxonomy of the green lineage, rather than the blue, in part
complicated due to the presence of green lineage museum specimens on the East Slope (Arkansas River).
The DFA for the molecular model evaluated within the meristic report indicated all populations of blue
lineage grouped together using phenotypic characteristics. The geographic model by reason of low
classification rates for the west suggests distinction between green and blue, but, since the east fish were
composed of nearly equal number of blue and green lineage, this poses the question of uniqueness for the
East Slope blue fish. Those East Slope blues had physical characteristics intermediate between West
Slope green lineage and blue lineage. Loss of genetic and morphological characteristics due to
bottlenecking within East Slope populations was discussed at the workshop as a possible explanation. But
generally, it is still reasonable to conclude that blue fish are represented by Colorado River cutthroats
with a historic range restricted to the White/Yampa River basin.
Bestgen provides two hypotheses to explain the variation seen between East and West Slope green fish.
As discussed in question #9 above, the uncertainty concerning green lineage makes taxonomic (and
listing) questions more difficult without further research.
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Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
Metcalf concluded that Bear Creek fish exhibited “…little genetic variation for loci that are typically
variable in cutthroat trout populations”. Phenotypically, the Bear Creek trout were clearly different
morphologically compared to other lineages in the meristic study, based on physical traits and PCA and
DFA techniques. But there was no opportunity to compare Bear Creek fish to museum collections used
for DNA studies by Metcalf. This is an investigation with broad support that would be important to our
understanding potential inbreeding that the Bear Creek fish might have experienced over the past 130
years.
Deformities in hatchery produced progeny are common and suggest inbreeding.
One strategy for ameliorating possible inbreeding impacts that was discussed during the workshop was to
maximize the size of any replicated populations and to include as many mature individuals in future
spawning efforts to increase genetic recombination diversity and improve fitness.
The fitness research currently being conducted by Rogers should also provide valuable information to see
if infusing green genetics provides biological benefits that would improve the ability to tolerate and adapt
to other habitats.
A question came up during the workshop if some morphological characteristics are more susceptible to
environmental or inbreeding impacts. It was suggested that multidimensional scaling could be used to
assess environmental influences on phenotype.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
Before that decision could be made, some additional research (using SNPs) to investigate the unique
haplotypes of Arkansas River green fish (S. Hayden and Severy), and the disagreement between mtDNA
and AFLP results for other green populations (besides S. Hayden) should be evaluated.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
I can’t offer anything on this question.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
It was noted during discussion of the Shiozawa SNP study that this line of investigation using next
generation DNA sequencing has added diagnostic markers that can be used to determine levels of
hybridization and introgression. It is hoped that the process used will be very helpful for management of
natural resources when it is necessary to distinguish between species and subspecies. However, I am not
qualified to suggest if that will be a “prudent and reasonable” research direction, nor how those might
affect management.
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16. Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish from
eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to, but
potentially greater than some other stream and lake spawning attempts east of the Continental Divide in
Colorado.
-
What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
Indicates a level of inbreeding that is uncommon, compared to other native cutthroat populations
that have been used in hatchery production. Metcalf et al. (2012) suggested caution when using
this population for future production and restoration, but suggested utilizing techniques to
maximize genetic diversity and further fitness-related studies. I would agree with this approach
and efforts are currently underway to do consider both of these strategies.
-
What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
Spawning efforts at CPW and USFWS hatcheries in 2013 will produce progeny which are
planned for stocking to the wild in 2014. Monitoring and evaluation of those plants will provide
our first assessment of how the Bear Creek trout fitness to survive and function in a new
environment. Hopefully, on a parallel track, we will also be able to evaluate cutthroats that were
purposely hybridized between Bear X green (Carr Ck) trout in both laboratory and field.
17. Please provide other relevant comments not addressed in the above questions.
No response
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Panelist #11 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
Two things are worth pointing out. First, the Metcalf et al (2012) work involved many dedicated scientists
and an immense effort to bring together data about the historical stocking record, modern DNA
assessments of the distribution of lineages across the landscape, and painstakingly difficult and detailed
analysis of museum samples. Each person had a different perspective about trout and biodiversity and we
reached a consensus among the diverse group of scientists on the meaning of the data. Second, the work
was published in a leading journal. Molecular Ecology is widely recognized as the best venue for
publishing original research in the field of conservation genetics (see
http://www.molecularecologist.com/2013/06/2012-impact-factors/). The work was subjected to rigorous
peer-review, a process that improves the veracity of the work and requires absolute transparency and
allows claims only when based on evidence.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
The meristics work has not been subject to peer review and so should be viewed as preliminary;
nonetheless, there is clear evidence for phenotypic differentiation between green and blue lineage trout
and between these two lineages and the trout in Bear Creek. Concordance between the phylogenetic and
meristics results supports recognition of four distinct taxa in Colorado. The four populations of green
lineage fish on the East Slope that are anomalous are best explained by 1) being out of place (the inferred
ancestry of the green lineage traces to the West Slope) and 2) admixture between the green and blue
lineages (based on genetic data and evidence of stocking from the West Slope to the East Slope) (see
Bestgen et al. 2013, Table 2). It is possible that founder effects may have caused some of the unique
patterns in the meristic data found in small populations such as South Prong Hayden and Bear Creek. A
similar analysis of South Platte River lineage museum samples housed at Harvard’s Museum of
Comparative Zoology would help us understand if contemporary Bear Creek is morphologically similar
to historic, native South Platte River cutthroat trout.
3. To what extent are historical spatial distributions of green, blue lineages known?
Given the work of Rogers and others (Martin and Metcalf, Loxterman, Shiozawa), the geographic
distribution of the two lineages is well known and is unlikely to change in any significant way. The
current distribution data coupled with the stocking data support the view that the green lineages' ancestral
range was the Gunnison, Colorado and Dolores River drainages, and the blue lineage was restricted to the
Green, Yampa and White River drainages. Nonetheless, there is some uncertainty surrounding the
presence of the green lineage in the Arkansas River drainage. Although the most likely explanation is that
stocking or mislabeled specimens explains the presence of the green lineage in the Arkansas River
drainage in 1889, genetic and meristic analysis of additional museum specimens will shed more light on
this issue.
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4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
The taxonomy of cutthroat trout is somewhat anomalous because in many other genera, when there are
clear groups based on phenotype, genes and geography, the groups would be recognized as distinct
species. There is precedent for elevating some subspecies to species status. For instance, the divergence
between Oncorhynchus gilae, O. mykiss and O. apache is equivalent to what is observed among the major
subspecies of cutthroat trout, including between the green, blue, Bear Creek and Rio Grande lineages.
At the very least, 1) the Bear Creek fish should be assigned the subspecies name O. c. stomias and a new
holotype designated that is a bona fide South Platte River fish (one from the Harvard collection); 2) the
green lineage should be recognized as a distinct subspecies with an appropriate name; 3) the native
distribution of O. c. pleuriticus should be officially revised so that it is not recognized as being
historically present in the Colorado, Gunnison or Delores River basins; 4) the San Juan lineage should be
described as a new subspecies (to emphasize its extinction).
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
Yes, to our knowledge. Additionally, one aspect of the peer review process is an evaluation of this
criterion; consequently, for the Metcalf et al. (2012) paper we can say that this is true emphatically. Were
the citations exhaustive (meaning all relevant papers were cited): probably not.
Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
b. distinct population segments (DPS)?
c. Other?
There are compelling data supporting recognition of O. c. stomias (Bear Creek) as deserving recognition
as an endangered species because 1) it is rare, 2) its range is only a fraction of what it once was, and 3)
there are significant threats. The green lineage and O. c. pleuriticus do not appear to satisfy the criteria for
listing at this time because they are widespread and locally abundant on the West Slope.
7. Is the Bear Creek population considered to be greenback cutthroat trout?
Type specimen of O. c. stomias is actually O. c. virginalis from the Rio Grande basin. The common name
greenback was first coined by Jordan for fish in the South Platte River, so technically, based on the data
from Metcalf et al. (2012), Bear Creek fish are greenback cutthroat trout. Because greenbacks are referred
to as O. c. stomias, it makes sense to recognize Bear Creek fish as representative of O. c. stomias.
8. How do we describe the East Slope green lineage?
As described earlier, the green lineage should at least be considered a distinct subspecies native to the
Colorado, Gunnison and Dolores River basins. All available information should be included when
formally describing the subspecies. Alternatively, the whole species complex could be revised so that the
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main lineages are recognized as species and minor lineages considered subspecies. In this, we can
imagine a single West Slope species (O. pleuriticus) that consists of three subspecies (O. p. pleuriticus
restricted to the Green, Yampa, and White River basins; O. p. gunnisoni restricted to the Colorado,
Gunnison, and Dolores River basins, and O. p. sanjuani restricted to the San Juan River). If this
taxonomy is adopted, then the East Slope fish should also be correspondingly revised.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
See response to question #8.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
Our best explanation based on the stocking and genetic data is that all green lineages on the East Slope
were stocked and many are likely descendents of admixture between the green and blue lineages. The fact
that the meristic study revealed the East Slope green lineage fish fall between the two main green and
blue clusters and three out of four show evidence of genetic admixture supports the hypothesis that they
are of hybrid descent.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
Before we accept the pattern as real, I'd like to see a randomization test instead of a parameter test of the
data. In other words, for the green lineage, remove the admixed populations and then randomly sample
the population so that the sample sizes per slope are the same as the observed data and generate a nonparametric test. This also needs to be done for the blue lineage. This type of analysis is similar to what
Metcalf et al. (2012) did for the AMOVA analysis. Importantly, when the meristics study is published, all
of the raw data should be published as well, perhaps using the Dryad database as Metcalf et al. (2012) did
for the data associated with the museum-based work.
Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
Although the data were not presented at the meeting, the data are published. Most of the loci show that
Bear Creek has one or sometimes two alleles whereas there are always multiple alleles present in GB or
CR (see example below). Another indication of reduced genetic diversity and inbreeding depression is the
high frequency of phenotypic abnormalities of Bear Creek fish when monitored in hatchery settings (see
Tiira et al. 2006. Evidence for reduced genetic variation in severely deformed juvenile salmon. Can. J.
Aquat. Fish. Sci. 63: 2700-2707).
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Figure 1. Histogram of allele frequencies (% of alleles sampled) for GB, CR and Bear Creek fish. This
result is typical for all loci surveyed to date.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
Given that the native Arkansas River Basin fish appears to have gone extinct (based on Metcalf et al.
2012 and surveys), it makes sense to stock the native South Platte River fish (O. c. stomias, known as
Bear Creek fish) throughout the Arkansas River simply because O. c. stomias is so rare. Both green
lineage and O. c. pleuriticus are widespread and locally abundant on the West Slope (their native range)
so there is no compelling reason to use East Slope habitats for propagation of lineages that are relatively
abundant and native to the West Slope. Alternatively, it is possible that South Fork Hayden may represent
a native Arkansas River drainage population, suggesting that decisions about whether to replace current
populations of cutthroat inhabiting Arkansas River basin streams should be made on a case-by-case basis
and populations without strong evidence of admixture or stocking should remain.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
The question should really not be how should NextGen be used for management, but rather, what are the
most relevant questions for which we need answers? If the question is: What is the closest sister taxon to
O. c. stomias, then NextGen can be used to sequence a large number of independent genes for the purpose
of inferring phylogenetic relationships. If the question is: How much of the historic variation of O. c.
stomias is still present in the modern Bear Creek population, then NextGen approaches can be used to
sequence large fractions of the genomes of museum samples from the South Platte River and modern O.
c. stomias from Bear Creek. Ms. Love-Stowell is currently pursuing study of modern O. c. stomias
genomes at CU Boulder.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
The top priority, at this moment, is to establish some natural populations of O. c. stomias in either the
Arkansas or South Platte River basins. Importantly, when this is done, the stocking and establishment of
the population should be studied. This is a fertile area of research for a graduate student who is interested
in combining field-based studies of ecology and population biology with genetic monitoring.
The second priority is to assess the degree that O. c. stomias suffers from inbreeding depression.
Assessment of inbreeding depression is best accomplished using crosses and measuring the dependence
of individual fitness on F (see Jimenez et al. 1994. An experimental study of inbreeding depression in a
natural habitat. Science 266: 271-273).
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16. Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish from
eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to, but
potentially greater than some other stream and lake spawning attempts east of the Continental Divide in
Colorado.
-What conclusions can you make from these findings and what inference to future management of the
lineage can you predict?
-What steps or research could you take to better understand how these trout could successfully
produce viable populations if replicated in streams in the South Platte River drainage?
This is a question that should be re-visited after several populations have been established to assess
whether establishment is successful or not. In addition, it is important to assess the results of the fitness
experiment. Overall, it will be important for all manipulations of O. c. stomias to be studied so that we
can learn as much as possible about how populations become established and how the gene pool changes
over time. This is another way NextGen sequencing can be applied to answer questions. In this case the
question is: How does the gene pool of O. c. stomias change during establishment?
17. Please provide other relevant comments not addressed in the above questions.
We have been committed to doing the best possible science to aid the management of endangered species.
We hope that we can continue to work productively together so that our efforts lead to the successful
establishment of populations in nature AND provide opportunities for the next generation of scientists,
teachers and ecologically informed citizens to participate in the science that should accompany the
management of trout.
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Panelist #12 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
I found the approach taken and the conclusions reached in Metcalf et al. (2012) to be logical and well
supported by a significant amount of evidence. As a non-geneticist, the existence of six (6) historic
lineages of cutthroat trout in Colorado as well as the current existence of four (4) extant lineages is well
supported by the evidence presented in the study.
It appears that there are other interpretations, but none are as logical and well supported as the
interpretations put forth by Metcalf et al. (2012). As Helen Neville from Trout Unlimited stated in her
review of Metcalf et al. (2012), their conclusions “make sense”.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
The meristics study correlates well with the “Molecular Classification Model” proposed by Metcalf et al.
(2007, 2012). The meristics study showed much less correlation with the traditional “Geographic
Classification Model” that is based on separate sub-species evolving in isolated river basins on different
sides of the Continental Divide.
3. To what extent are historical spatial distributions of green, blue lineages known?
Metcalf et al. (2012) provides strong evidence that the green lineage was historically distributed in the
upper Colorado, Gunnison, and Dolores River basins in southwestern Colorado and east-central Utah.
Green lineage populations found outside of these three basins can be logically traced back to stocking
events.
Metcalf et al. (2012) provides strong evidence that the blue lineage was historically distributed in the
Yampa, White, Green, and lower Colorado River basins in northwestern Colorado, southwestern
Wyoming, and eastern Utah. Blue lineage populations found outside of these four basins can be logically
traced back to stocking events.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
I lack the expertise to answer this question.
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
Both of these studies included all of the pertinent literature that I am aware of.
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Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics & meristics studies rise to the level of a listable entity?
The preponderance of evidence suggests that there are four extant listable cutthroat trout entities in
Colorado: Green, Blue, Rio Grande, and Bear Creek. I do not have the taxonomic knowledge to state
whether these entities are subspecies, DPSs, or something else.
7. Is the Bear Creek population considered to be greenback cutthroat trout?
It appears that the Bear Creek fish are representatives of the native trout of the South Platte River basin. If
the South Platte native trout are considered greenback cutthroat trout, then the Bear Creek population
should be considered greenback cutthroat trout as well. Taxonomists need to sort out the confusion
regarding the type specimen that was collected for greenback and determine which lineage should be
assigned the name “greenback”.
8. How do we describe the East Slope green lineage?
The East Slope Green lineage likely is comprised of green lineage fish native to the West Slope that have
been stocked east of the Continental Divide. The East Slope green lineage fish originated on the West
Slope and appear to have developed slightly different meristics and spotting patterns during their isolation
on the East Slope (perhaps as a result of small population size, genetic inbreeding/ bottlenecking). It
doesn’t appear that the East Slope green lineage fish should be considered a separate listable entity (they
should be considered the same as green lineage on the West Slope).
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
I don’t believe that the East Slope green lineage fish should be considered a separate listable entity under
ESA -- they should be considered the same entity as green lineage on the West Slope. Additional genetic
testing/sequencing of West Slope green lineage fish should help clarify whether the East Slope green
lineage fish possess a unique haplotype.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
I lack the expertise to answer this question.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
Again, I am not a geneticist, but it seems to me that the variation seen in the East Slope and West Slope
fish is a function of genetic isolation of the East Slope fish for the past 100+ years since they were
stocked from West Slope hatcheries. I do not believe that the green and blue lineage fish on the East
Slope should be considered separate listable entities from their West Slope counterparts.
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Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
Not sure about the first part of the question, but logically the main short-term goal for the Bear Creek fish
is to establish several self-sustaining wild populations. As these wild populations become established,
gametes from different year classes and locations can be gathered to improve the genetic variability in
captive reared populations.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
The evidence suggests that yellowfin cutthroat trout were the native cutthroat in the Arkansas River
drainage. Since the yellowfin is extinct, it is unclear which lineage should be reintroduced into the
Arkansas River drainage. Additional genetic studies of green lineage populations on the East Slope might
clarify which lineage should be reintroduced in the Arkansas River basin. Further genetic analysis of the
South Fork Hayden Creek cutthroat trout population might help determine if their unique haplotype is the
appropriate lineage for reintroduction in the Arkansas River basin. If it becomes apparent that the East
Slope green lineage fish currently in the Arkansas River basin were founded by stocking from the West
Slope, then it may be appropriate to reintroduce Bear Creek cutthroat into the Arkansas River and thereby
establish Bear Creek populations in both their native range (South Platte) and the other major drainage
(Arkansas) on the East Slope.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
Though not my area of expertise, it sounds like nuclear DNA testing is needed to clarify the degree of
introgression in many populations.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
--Conducting meristic and morphometric studies of the museum specimens from the South Platte River
drainage in comparison to the Bear Creek fish should help clarify whether the Bear Creek fish are indeed
native to the South Platte River.
--Meristic and morphometric studies of the San Juan museum specimens would provide insight into
which of the current lineages they are most similar to.
--Intensive inventories in the San Juan drainage should continue in an effort to find an extant population
of the presumed extinct San Juan cutthroat lineage.
--Projects that eliminate non-native populations and replace them with pure lineages should continue. The
recent findings also re-emphasize the importance of using extreme caution when renovating/eliminating
populations that include presumably admixed cutthroats – it is important not to lose important genetic
material.
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16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while
fish from eggs collected in the wild and reared in a hatchery often have noticeable
abnormalities; similar to, but potentially greater than some other stream and lake spawning
attempts east of the Continental Divide in Colorado.
-What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
-What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
No response.
17. Please provide other relevant comments not addressed in the above questions.
Hopefully the results from this workshop will allow the FWS to re-evaluate the ESA status of green
lineage populations on the West Slope (and East Slope too). The current status of West Slope green
lineage populations as “threatened” requires federal agencies to engage in formal Section 7 consultation
on all actions that may affect one of these populations. The time and funding spent on consultation is a
cause for concern for federal agencies. Re-examination of the number of green lineage populations may
reveal that threatened status is no longer warranted.
We need to generate a non-technical summary of the workshop findings that can be shared with the public
and with managers in the various management agencies (state and federal). Agency managers who are
charged with making land management decisions need to understand the basic findings from the
workshop in simple terms. Specialists within each agency can then work with managers to provide
technical details as needed.
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Panelist #13 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
I am not a geneticist but I am convinced that the findings of the study are sound and there is sensible and
logical support for the findings.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
The findings of both studies are well correlated. I believe the conclusions of both studies. The data
presented by Bestgen et al. support the Metcalf et al. findings. The results are most ambiguous for the
green lineage but the statistical inferences in the paper are sound.
I also agree with Bestgen et al.’s recommendation that “Preservation of that genetic diversity, regardless
of where it resides on the landscape, should be a guiding principle for future management.”
3. To what extent are historical spatial distributions of green, blue lineages known?
I believe the blue and green lineages were native to the western slope and introduced on the eastern slope.
But the data are limited to clarify the status of the blue and green fish on the eastern slope. We need to
proceed with caution when managing the fish on the eastern slope but I do not think the blue or green
lineages on the eastern slope require protection under ESA.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
I don’t know.
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
Yes, I believe they are robust studies and well supported by the literature.
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Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
I think the Bear Creek fish should be protected as the fish native to the eastern slope. I do not think the
blue and green lineages should be treated differently on the western slope. Additional recognition by
managers to conserve and protect the blue and green lineages within their native GMUs (western slope) is
warranted.
a. different subspecies?
No
b. distinct population segments (DPS)?
Possibly for the blue/green, but I’m not sure the status of those lineages on the western slope is in
sufficient jeopardy to warrant listing.
c. other?
No
7. Is the Bear Creek population considered to be greenback cutthroat trout?
Yes
8. How do we describe the East Slope green lineage?
These are West Slope fish that were introduced to the eastern slope. They should not be eliminated but
given the number of populations in their native range on the western slope the green fish on the eastern
slope do not warrant protection under ESA.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
I’m not sure.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
I think Shiozawa’s presentation is the most plausible.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
It is my opinion that those variations could be explained by small founding populations of stocked fish
that were subsequently moved around on the eastern slope. The variation could have arisen from a
mutation in the founding population that was then replicated.
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Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
The approach that CPW has taken thus far seems appropriate. Introducing some variability is appropriate
but a cautious approach should be taken (which is what CPW has done).
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
I would use the Bear Creek fish.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
It would be valuable to increase the sample size of fish run through that analysis. Adding different
populations from each GMU (perhaps 6 digit HUC) across all subspecies would add greatly to our
understanding of cutthroat phylogeny. That would of course be expensive and I’m not sure where that
money would come from.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
-Extending genetic and meristic analyses to Colorado River cutthroat trout in the rest of their historic
range outside of Colorado.
-Next generation sequencing of all intermountain cutthroat at a finer scale (6 digit HUC was suggested in
response to question #14 above).
16. Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish from
eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to, but
potentially greater than some other stream and lake spawning attempts east of the Continental Divide in
Colorado.
-
What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
There were likely one or more bottleneck events where much of the genetic diversity within the
population was lost. The abnormalities are a concern since the overall fitness of the population is
compromised. It will create a management challenge but there are brook trout populations throughout the
west that were founded with just a few fish and seem to be thriving. So we should not over-react and
tinker too much with the fish that have survived in Bear Creek.
-
What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
The work that CPW is undertaking to introduce some variation has merit. Managers may wish to PIT tag
every fish in the population and then take a “stud book” approach to spawning such that individual
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pairings are known and can be controlled. Perhaps split each batch of eggs and fertilize it with several
individual males. It may also be desirable to check the motility of the sperm from each male and/or use
more than one male with each female/batch so that the risk of failed fertilization is reduced. May also
want to track hatching success of each pairing to see if there are some fish that are not contributing or
have a higher level of success/failure.
17. Please provide other relevant comments not addressed in the above questions.
We need to take a precautionary approach to conservation of diversity on the landscape. But we should
not be paralyzed by uncertainty. We simply must act to conserve and replicate the Bear Creek population.
It needs to be replicated in other watersheds and steps must be taken to understand and manage the
limited genetic diversity that exists in that population.
The blue and green lineage fish on the eastern slope were likely the result of fish stocking. In the short
term I would continue to conserve them. If the Bear Creek fish can be saved they should be used to found
additional populations and treated as the native cutthroat of the eastern slope.
Rio Grande cutthroat trout management should continue as it has been. Recognition of the diversity
between GMUs should be incorporated into the next revision of the Rio Grande cutthroat trout rangewide
conservation strategy.
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Panelist #14 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
Yes and No. Of the conclusions that are supported there are some limitations that must be acknowledged.
A very low number of samples were available (30 total to represent all Colorado lineages). Only mtDNA
from 2 genes (ND2, CO1) totaling 430 base pairs were used in analysis. These limitations do not mean
that conclusions are “wrong” but indicate a richer picture of lineages and interrelationships may exist that
are unrecognized with this study.
Hypothesis One: The prevailing view of 4 divergent lineages is not supported. The conclusion of 6
distinct lineages is supported. Four of these lineages are confirmed through evidence presented in other
studies (meristics).
Hypothesis Two: The prevailing view regarding the distribution of lineages (pleuriticus – western CO,
stomias – South Platte and Arkansas, macdonaldi – Twin Lakes and virginalis – Rio Grande) was not
supported. There is evidence for the distribution of historic lineage by drainage or adjacent drainage (but
see additional comments below).
Hypothesis Three: The current distribution of cutthroat lineages differs markedly from the historic
distribution could not be refuted.
The author’s conclusion that there is support for 11 North American cutthroat trout clades is supported by
the data presented but may be misleading. Colorado contained 6 of those 11 but 2 of the 6 have only been
revealed through examination of museum samples. Based on this result, if such an effort was taken across
the west many additional clades may be discovered.
The conclusion that the amount of genetic variation distributed among drainages has declined
significantly is supported.
The conclusion that the Bear Creek population is native to the South Platte River and not native to the
Arkansas River is supported by the haplotype data presented but could be disputed. It is true that in the
analysis the purple, yellow, and green lineages do clearly separate and all historic purples samples are
located in the South Platte River; however, the Arkansas River drainage is clearly more complex with two
historic lineages present. I do not think we can rule out the possibility that the purple lineage was also
historically present in the Arkansas River drainage and simply not represented in the museum samples.
The conclusion that the blue lineage fish were historically restricted to drainage basins on the western
slope is supported.
The inference that the blue lineage was historically restricted to the Yampa and Green River drainages is
not supported. This hypothesis is based on museum samples including only one fish from the Yampa
River drainage which is contradicted by a single blue lineage fish collected from the Colorado River
drainage. The authors’ are silent regarding the blue lineage sample in the Colorado River drainage. The
full historic distribution of blue lineage fish remains uncertain.
The conclusion that there was an extinction event in the San Juan River system is supported by the data
presented; however, modern samples from the San Juan River drainage have not undergone systematic or
extensive sampling (per Kevin Rogers) and this conclusion seems premature.
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The conclusion that there was an extinction event in the Arkansas River of O. c. macdonaldi is well
supported.
The conclusion that modern distribution is largely tied to stocking is supported in the blue lineage by
matching haplotypes from stocking sources (Trapper’s/Marvine Lakes) to modern blue lineages that
appear “out of place” and the clear documentation of stocking events from state and federal sources. The
green lineage does not fit this pattern as there is no connection between haplotypes from stocking sources
(Grand Mesa Lakes) to modern “out of place” populations. Explaining modern distribution by stocking
alone in the green lineage therefore could be disputed and alternative hypotheses should be explored.
I disagree with the interpretation that it is unlikely that green lineage was native to the Arkansas River.
Alternative lines of evidence that support the native hypothesis include the unique haplotypes of the green
lineage on the east side, matching SNP haplotypes between museum and a modern sample in the
Arkansas River drainage and intermediary meristic characteristics.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and Rio
Grande)?
Yes the two studies correlate in several ways. The meristic study found more support of the molecular
model (Metcalf et al. 2012) rather than the traditional geographic model. It also supported a population
and lineage structure organized by drainage basin. Additionally, there was support for two lineages on the
West Slope. Bear Creek fish (purple lineage) and the Rio Grande cutthroat were clearly distinct from
other lineages under all classification models. Blue lineage fish were also distinct from other lineages
under the molecular classification model. Additionally, all blue lineage fish from the East Slope in the
study had a single Trapper’s Lake haplotype and when compared specifically to Trapper’s Lake fish were
indistinguishable meristically. This lends clear support to the stocking hypothesis of blue lineage fish
from the West Slope to the East Slope.
The difference in the two studies arises in the green lineage fish where the meristic study revealed more
fine-scale differences. In the meristics study the East Slope and West Slope green lineage fish differed.
The West Slope green lineage is intermediate between the blue lineage and Rio Grande cutthroat.
Whereas, the East Slope green lineage had traits (lateral series scale counts, basibranchial tooth counts,
trunk spot counts, fore-spot and mid-spot ratios) that were intermediary between the West Slope green
lineage and Bear Creek. In analyses this resulted in the green lineage fish overlapping with the blue
lineage. However, a confounding factor is that three of the four East Slope green lineage populations were
classified as blue lineage when nuclear markers (AFLPs) were used. The pattern of mtDNA classification
in one lineage and nuclear DNA classification in another may indicate that these populations are admixed
native cutthroat (blue and green lineage). This would explain why these populations could not be sorted
easily into either green or blue lineages. Despite these differences the meristic data clearly show that most
traits have non-overlapping 95% confidence limits between the green lineage and the blue, Rio Grande
and Bear Creek lineage fish. Although more study is clearly warranted, at this time the green lineage
separates as unique in this study from the other three lineages in accordance with the Metcalf et al. 2012
findings.
3. To what extent are historical spatial distributions of green, blue lineages known?
It is clear that early stocking has obscured the historic spatial distributions of green and blue lineages and
there are still many questions. Based on the Metcalf et al. 2012 study and additional published and
unpublished work it appears that the blue lineage was native and limited to the West Slope. All East Slope
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blue lineage populations examined to date have an identical ND2 haplotype that is characteristic of
Trapper’s Lake. In addition, many of these East Slope blue lineage populations have clear stocking
records. I personally feel relatively confident based on these various lines of evidence that the blue
lineage is indeed a West Slope native.
The actual historic distribution of the blue lineage on the West Slope is less clear. Current evidence from
museum and modern samples suggest that the blue lineage was limited to the Yampa, Green and perhaps
Colorado River drainages. More work is needed to better inform the historic distribution on the West
Slope.
The green lineage is more complex. Current evidence from both the museum and modern samples suggest
that this lineage may be native to both the East and West slopes in the Gunnison, Dolores, Upper
Colorado and Arkansas River drainages. There are also modern samples in the South Platte River
drainage. Additional work is needed to clarify this species distribution and I am hesitant to make any clear
statements about historic distribution based on the current evidence.
The Bear Creek haplotype matches five haplotypes in the South Platte River . This provides good
evidence that the purple lineage was native to the South Platte River. It is less clear as to whether it was
native to the Arkansas River.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
To my knowledge there are no comparable studies for cutthroat trout that have used meristic data. Dr.
Shiozawa’s most recent comprehensive phylogeny of cutthroat trout using eight mtDNA genes and 8057
base pairs provides clear evidence that the green, blue, and Rio Grande lineages are as separate from one
another as are other cutthroat trout subspecies. Many additional published phylogenies lead to the same
conclusion (Brunelli et al. 2013, Loxterman and Keeley 2012, Pritchard et al. 2008 and Shiozawa et al.
2012). The Bear Creek lineage is also clearly separated on Shiozawa’s most recent phylogenetic tree with
an estimated divergence time from the green lineage over one million years ago. This distinctness of the
Bear Creek lineage from the other lineages (blue, green, Rio Grande) is at least as great as the separation
between the named subspecies.
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
To my knowledge yes.
Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
b. distinct population segments (DPS)?
c. other?
Yes, the four lineages (blue, green, Rio Grande and purple-Bear Creek) do rise to the level of a listable
entity. It seems consistent to list them as different subspecies based on the current listing of some of these
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lineages and in comparison to other cutthroat trout listings. In addition the East Slope green lineage
populations should be considered for listing as a DPS given the unique haplotypes present only on the
East Slope and geographic separation from other green lineage populations.
7. Is the Bear Creek population considered to be greenback cutthroat trout?
Yes, based on the museum samples the historic South Platte River native fish is matched today to the
modern Bear Creek fish.
8. How do we describe the East Slope green lineage?
The current research indicates that East Slope green lineage populations have unique haplotypes present
only on the East Slope and geographic separation from other green lineage populations. In addition,
meristically they appear a bit different than the West Slope green lineage. Although they are still clearly
green lineage fish both genetically and meristically, they should be managed separately at this time.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
If a decision had to be made today based on the current evidence (and invoking the precautionary
principle) I would describe the East Slope green lineage as a DPS of the overall green lineage. In mtDNA
and nuclear DNA studies the green lineage populations including those of the East Slope clearly separate
from the blue lineage and Rio Grande cutthroat. In the meristic study green lineage fish taken as a group
had 95% confidence levels separating most traits between it and the other lineages. For these reasons the
green lineage as a whole appears to warrant the classification of a separate subspecies. The East Slope
green lineage fish have unique haplotypes not seen on the West Slope. Their characteristics are more
intermediary with other lineages but they still seem to fall within the green lineage clade. For these
reasons DPS seems an appropriate conservative designation to recognize and conserve those geographic
and genetic differences within the green lineage.
A better approach would be to look at East Slope green lineage fish in more detail. In particular meristic
data from green lineage populations (East and West Slope) that have no evidence of possible admixture
with blue lineage, rainbow or Yellowstone is needed to see how similar or different these are from one
another. The current meristic study unknowingly used “green” lineage populations that sort as blue
lineage in program STRUCTURE. This may indicate admixture or simply the difficulty STRUCTURE
had in assigning these populations. If admixed, this likely explains the meristic overlap between green
and blue lineages and it would be informative to see if these lineages will clearly separate when “pure”
populations are used. Secondly, additional exploration of all East and West Slope green lineage
population haplotypes is needed to determine if any shared haplotypes exist with the West Slope. This
knowledge could be used to further refine a DPS description for the East Slope and potentially include
only those populations with unique haplotypes.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
Yes to an extent. There are multiple differing phylogenies in the literature but several recent publications
have converging phylogenies. It seems fairly accepted in the published phylogenies that all four lineages
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(Rio Grande, blue, green and Bear Creek) came from a common ancestral line (Brunelli et al. 2013,
Loxterman and Keeley 2012, Metcalf et al. 2007, Pritchard et al. 2008, and Shiozawa et al. 2010). The
blue lineage appears the first to separate which explains its positioning in many phylogenetic trees on a
separate branch from that of Rio Grande, green lineage and Bear Creek (Loxterman and Keeley 2012,
Metcalf et al. 2007, Pritchard et al. 2008, Rogers 2012, and Shiozawa et al. 2010). Rio Grande and green
lineage then separate and it appears that Bear Creek descended from green lineage. This leads to two
potential routes of colonization. The first is that cutthroat entered Colorado from the NW and then the Rio
Grande, green and Bear lineage moved south and eventually East over the Continental Divide
diversifying along the way. The second route is two separate events, one from the NW establishing the
blue lineage and one from the West/Southwest which moved East establishing the Rio Grande, green and
Bear Creek lineages. In either case the more established historical view that green lineage descended
directly from blue lineage has less current support than green lineage descending from Rio Grande.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
The East Slope-West Slope variation in the blue lineage is not significant. All East Slope blue lineage
populations to date correspond to a common Trapper’s Lake haplotype. Many of these populations also
have a clearly documented stocking history. When meristic data are used to compare East Slope blue
lineage fish with fish of the same haplotype found on the West Slope they are indistinguishable from one
another. The reason the East Slope blue lineage fish may separate from the rest of the blue lineage is
because all East Slope populations have identical haplotypes and therefore present a narrower and more
similar appearance to each other than the blue lineage as a whole.
The green lineage variation does show significant variation between the East and West Slope with no
clear explanation. The current research indicates that East Slope green lineage populations have unique
haplotypes present only on the East Slope. Phenotypically the East Slope green lineage fish have more
total spots and higher fore-spot and mid-spot ratios. These characteristics are more similar to the blue
lineage whereas the West Slope green lineage fish were more similar to Rio Grande (less spots, lower
ratios). There are several potential explanations for these differences. 1) Stocking hypothesis – the East
Slope green lineage fish were stocked by West Slope sources. Over time the haplotypes were lost on the
West Slope and now only remain on the East Slope. 2) Native expansion hypothesis – The green lineage
naturally expanded its range and crossed the Continental Divide. Founding effects resulted in only a small
number of haplotypes becoming established on the East Slope and these were subsequently lost in West
Slope populations. 3) Potential admixture hypothesis - A potential confounding factor is that three of the
four East Slope green lineage populations studied for the meristic research were classified as blue lineage
by program STRUCTURE when nuclear markers (AFLPs) were used. The pattern of mtDNA
classification in one lineage and nuclear DNA classification in another may indicate that these
populations are admixed native cutthroat (blue and green lineage) which could obscure the analysis. It
also could simply be a STRUCTURal problem. More research is needed to more clearly delineate which
of these hypotheses may be more likely. Until then the East Slope green lineage should be managed
cautiously to protect the populations and unique haplotypes present.
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Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
Genetic variability is clearly lacking as shown by A. Martin. As recovery efforts move forward it is first
important to replicate the existing Bear Creek population in several areas to insure their protection in the
future. Once that step is complete additional populations can be established with Bear Creek fish and
adding some diversity from another population, probably of green lineage, which appears to be most
closely related. These efforts will need to be carefully planned and monitored and the details go beyond
the scope of the workshop and my personal knowledge.
Surprisingly the range of phenotypic variation in the Bear Creek fish is similar to the green and blue
lineages for the traits measured. Despite this, attempts at hatchery rearing have been challenging
compared to green and blue lineage fish. This may indicate that genes driving fitness have less variability
and therefore Bear Creek fish are less able to survive under a variety of circumstances.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
Based on the information presented both the green lineage and Bear Creek lineage may be appropriate to
the Arkansas River basin. There is a possibility that the green lineage is native to the Arkansas River
basin. If additional information continues to support this hypothesis then the East Slope green lineage
would be most appropriate for reintroduction. Conversely, if evidence supports that the East Slope green
lineage populations are much more likely to be the result of stocking and are indeed native to the West
Slope then Bear Creek fish would be preferred. Although there is no evidence in museum samples that
Bear Creek fish are native to the Arkansas River basin it is still possible that they were and simply were
not preserved historically into the museum collections. The barriers between the South Platte and
Arkansas River drainages are far less than crossing the Continental Divide which is why the Bear Creek
fish would be preferred over green or blue lineages for reintroduction.
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
I have limited knowledge on next-generation sequencing. This technique shows promise and may be
useful in answering the remaining research questions outlined in question 15.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
Several key research priorities have come to light. One overarching goal is to make sure that all museum
samples within the range of any of the Colorado lineages have been found. The focus for the Metcalf et
al. 2012 study was greenback. Although it may be unlikely that more museum samples exist, a thorough
search for specimens from West of the Continental Divide would be helpful in identifying the historic
range and distribution of haplotypes present for all lineages.
Green Lineage: This scientific review process revealed that a key priority must be exploring the green
lineage, especially the East and West Slope differences. Specific research may include 1) analyzing all
extant green lineage populations on both the East and West Slope to identify the distribution of
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haplotypes; this will help inform the stocking vs. native hypotheses for the East Slope and specifically the
Arkansas River basin. 2) Sequencing the East Slope green populations used in the meristic analysis is
important to determine if admixture is of concern for the current results and conclusions. Additionally,
analyzing more East Slope green populations to see if the meristic differences continue to consistently
show the East Slope green populations as “different” will provide evidence for whether DPS or another
listing is warranted. In addition, further study on the West Slope of both green and blue lineages is needed
to inform their historic distribution, especially for the Colorado River drainage.
Blue Lineage: As stated above the key question for blue lineage is identifying historic distribution. One of
the blue lineage museum samples was in the Colorado River drainage and more research will help
determine if this is likely the result of stocking or if some native blue lineage populations naturally
expanded into this drainage.
San Juan River: For the San Juan River, searching extant populations to see if any San Juan fish do still
exist is critical. In addition, examining museum specimens to look at meristics such as spotting patterns
on the San Juan River fish would be of interest.
Bear Creek: With Bear Creek as the only extant South Platte River lineage population it would be useful
to examine the South Platte River museum samples to determine the original variability for meristic
characters studied. Using these data in comparison to Bear Creek will help determine if the Bear Creek
fish are representative of the South Platte as a whole or phenotypically unique due to small population
size, population bottleneck and genetic drift. Fitness studies as mentioned in question 16 (below) will also
be important for robust recovery of the subspecies.
16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish
from eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than some other stream and lake spawning attempts east of the Continental Divide
in Colorado.
-What conclusions can you make from these findings and what inference to future management of the
lineage can you predict?
-What steps or research could you take to better understand how these trout could successfully
produce viable populations if replicated in streams in the South Platte River drainage?
The paucity of genetic variation in the Bear Creek population may explain these differences. It is still
important to keep and replicate the Bear Creek population in several locations with its current genetic
make-up to safeguard this piece of the cutthroat puzzle. The long –term management of this species likely
cannot rest on the Bear Creek population alone but will need to include a plan to systematically diversify
targeted replicate populations by adding one or more closely related individuals.
There is an ongoing fitness study in the hatchery crossing Bear Creek and green lineage fish. This study
should be replicated in a field. In addition, a study to add diversity at a much lower introgression level,
such as one individual per generation, can be implemented and closely monitored. This would elucidate
whether a much lower level of crossing between Bear Creek and green will be effective at lowering or
eliminating deleterious effects.
17. Please provide other relevant comments not addressed in the above questions.
I feel I have answered and commented on all areas pertinent to the workshop.
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Panelist #15 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided
in this study? Are there alternative interpretations?
The conclusions reached in the Metcalf et al. paper represents a logical progression in the genetic studies
conducted during the last two decades. Improvements in techniques and an accumulation of new
information lead to their conclusions related to cutthroat trout lineages in Colorado. Historical stocking
data as well as meristic/morphometric studies support their findings. The identification of 4 populations
on the East Slope of Colorado that do not follow the normal “pattern” leads to some speculation. Were
there multiple invasions? Could the current major drainage locations possibly been altered over time
through natural stochastic events and influenced contraction and expansion of different lineages? It would
appear possible that further “refinement” may not be realistically possible. If further refinement is
possible then further separation of the Metcalf results could result in historic habitats for a given lineage
that we could manage over time. From that standpoint, their results provide a geographic area that is large
enough that individual lineages and their populations could be managed.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristic study
show a difference in phenotypic characteristics between blue lineage, green lineage, Bear Cr, and
Rio Grande)?
Yes, although I would have thought initially that the green and blue lineage would be more closely related
than the Rio Grande and Bear Creek. Thus it still could explain that the green lineage as well as front
range lineages moved into the current geographic areas at a different time period than the blue lineage, or
are from stocking.
3. To what extent are historical spatial distributions of green, blue lineages known?
I don’t think we understand the temporal migration of all the lineages, and unless we locate fossil or bone
remnants probably won’t. We can speculate. However, it may be more important to understand (agree) on
the current “boundaries” of the lineages and move forward to restore robust populations.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
The current results appear to be significant and explain the recent extent of the lineages. The studies we
have now are as robust as I have seen. I believe they are as sound as any others available.
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support
their assumptions/arguments/conclusions?
Yes
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Biodiversity Implications: Listable Entities?
6. Do lineages identified in genetics and meristic studies rise to the level of a listable entity?
To be consistent with other lineages, it appears that there are 4 living subspecies and 2 extinct. However,
socio/political influences could have an influence on nomenclature that should be avoided. One comment
I overheard from a panel member was “based on their involvement the separation both genotypically and
phenotypically are so far removed from the other lineages they should considered a new species”. While I
have no experience addressing nomenclature issues, this level of classification should not be totally ruled
out.
7. Is the Bear Creek population considered to be greenback cutthroat trout?
Yes, although the range has been changed to the South Platte River drainage only.
8. How do we describe the East Slope green lineage?
One speculation was that it was part of multiple movements over time, with these populations being left.
We also can’t rule out human movement of these fish. This is one of the questions to be answered. It
appears to me that they are a result of some stocking to me.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest
in terms of subspecies or ESU distinctions?
This question is too vague to answer. The term “subspecies” is a name under ESA. If the question relates
to the 4 East Slope green lineage populations I think we know too little to make these type of conclusions.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroats?
The studies focused primarily on differences between the different lineages. To me, the introduction of
the green lineage presents new information that may help answer this question. However, there are still
questions and there are never easy answers to these questions. Even within a given basin, it seems that
there would be many areas devoid of trout. It would seem that these trout would have continued to
disperse into new habitats, except for the influence of European settlers.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could
lead to those differences and are there any taxonomic implications?
I don’t completely understand this difference at the moment but it definitely seems to point out that we
don’t understand all the movement that occurred, either through multiple climatic events or through
human stocking. There are probably always going to be some taxonomic implications we are not
confident with. This could be a question for future research.
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Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be
considered to manage genetic variability in this lineage to ameliorate potential or actual inbreeding
effects?
The results of the current studies show that phenotypically as well as genotypically the Bear Creek trout
are indeed very distinct from other lineages, but appear to be the same as early collections from the
1800’s. While these fish are different from other lineages, they have fairly high phenotypic variability
within the population. In addition, the progeny in one generation in a hatchery situation revealed
basibranchial teeth not present in the wild. There could be more diversity than we think if placed in new
habitats.
I believe that reintroducing new genes or hybridization studies would be premature, based on these
findings. It would seem that understanding what adaptations within the Bear Creek trout when placed in
new environments would be a better first start. I also would suggest that this situation would provide an
opportunity to examine the potential for recovering from a strong “bottleneck” situation when placed in
new habitats.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
At this point, I would be more concerned with disease introductions and/or potential human movement
into the wrong drainages by the public. Most of our limited funding should be used for the study and
introduction of the lineages we are more confident in.
14. How next-generation DNA sequencing approaches should be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
I think the most important aspects are “firming” the information and data already used to make
conclusions with. Anything that helps show the spatial movement over time with reference to the
evolution of the lineages would be very helpful.
15. What are other prudent and reasonable management and research priorities for the species given
the outcome of these studies?
Management first – The South Platte River drainage is going to be far more difficult to find high quality
habitat if for no other reason than socio/political reasons. The extremely high population growth and past
and current drought related fire conditions will no doubt influence the ability to restore streams. In order
to make a compelling argument for reintroducing Bear Creek fish a very thorough knowledge of land use,
productivity and availability are needed. Decision makers are going to need information that relieves
political and social pressures if we are going to be successful in getting permissions to work there. The
recovery team will also have to be responsible in identifying “criteria” for identifying recovery sites.
Priorities for recovery should not be made on “convenience”, “lack of conflict”, or “short term time
frames”.
Research – Obviously there are a number of avenues that could be researched. One prudent research topic
I suggested previously discussed is understanding better the evolutionary pathway for these different
lineages. This type of research would help understand more clearly the final nomenclature of the taxa. I
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also do not agree that research on hybrid “vigor” should be our first step in restoration. Given the
variability in the Bear Creek fish, we should look at the effect that placing populations in new habitats
would have. Understanding habitat, as well as other physio/chemical parameters would be important for
restoration. Currently we are biased by our own limited experience. Possibly research on social
acceptance and what the public is willing to consider if a restoration project was introduced in an area
they were familiar with or visited.
16. Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish from
eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to, but
potentially greater than some other stream and lake spawning attempts east of the Continental Divide in
Colorado.
- What conclusions can you make from these findings and what inference to future management
of the lineage can you predict?
After hearing similarities in other cutthroat trout rearing efforts I believe the abnormalities could be
attributable to conditions in hatcheries probably more than in the wild. Different water quality,
temperature, feed and growth could all attribute to these abnormalities as least as much as any genetic
homogeneity.
- What steps or research could you take to better understand how these trout could successfully
produce viable populations if replicated in streams in the South Platte River drainage?
I think the research that Kevin Rogers is proposing would help. I also think that studying the fish that are
put in the wild in different environments would give us useful information on their plasticity physically as
well as their adaptability.
17. Please provide other relevant comments not addressed in the above questions.
This effort is extremely interesting and represents as much art as science. While we would like to predict
how these fish evolved and moved, I’m not sure we aren’t following our own biases for some of our
answers. There are so many confounding issues that face us that it is difficult to come to a very confident
conclusion. For now I’m comfortable going with the group consensus. Maintaining current lineages and
improving rare lineages is of more concern to me. While hopeful, I am not convinced that social values
will allow us to be very successful
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Panelist #16 Responses to Discussion Questions
Evaluation of the Science
1. Are the conclusions reached by Metcalf et al. (2012), including the identification of distinct cutthroat
lineages and inferences based on historical stocking, logical and supported by the evidence provided in
this study? Are there alternative interpretations?
Yes, I believe that based on the evidence presented at the workshop (including supporting stocking
records and historical information) and in their paper that their conclusions are supported relative to the
distinct 6 lineages as identified therein.
The only question I have is about resolution of the West Slope and East Slope green lineage fish and if the
South Fork Hayden Creek fish are native to the Arkansas River drainage rather than the West Slope.
2. Does the meristic study correlate with findings in the genetics study (i.e., does the meristics study show
a difference in phenotypic characteristics between blue lineage, green lineage, Bear Creek, and Rio
Grande)?
Yes the studies are remarkably consistent and reinforce the differences between lineages.
3. To what extent are historical spatial distributions of green, blue lineages known?
I believe that the historical stocking records are remarkably intact and represent the best information/
evidence we have to delineate the historical distributions of these fish. Inaccuracies aside which we have
no basis for evaluating, I believe we have a fairly strong concept of where these fish originated from
(supported by genetic data) and where they were moved to within a reasonable margin of error.
4. How does genetic and meristic variation identified in the studies compare with variation in other
cutthroat trout studies? Are levels of variation consistent with differences observed across species,
subspecies or ESUs in other cutthroat trout?
I cannot comment.
5. Did the genetic and meristic studies include all the necessary and pertinent literature to support their
assumptions/arguments/conclusions?
Not familiar enough with the current/past literature to comment.
BiodiversityImplications: Listable Entities?
6. Do lineages identified in genetics and meristics studies rise to the level of a listable entity?
a. different subspecies?
Yes, blue and green, Rio Grande and Bear Creek fish are different subspecies per genetics and meristics
data.
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b. distinct population segments (DPS)?
The Bear Creek fish may fit the designation of discreteness and significance for a DPS. It is also
markedly separate from other populations of the same taxa.
c. other?
7. Is the Bear Creek population considered to be greenback cutthroat trout?
No. Dr. Shiozawa’s data show separation between Bear Creek and “greenbacks” 1 million years ago.
Greenback cutthroat trout are the fish from the South Platte River but maybe due to founder effects, Bear
Creek fish, while the ancestor is from the South Platte River, are no longer “greenback” trout.
8. How do we describe the East Slope green lineage?
Unclear on this issue, more data may have to be analyzed to answer this question more fully and their
relative differences with the West Slope green lineage. Both genetic and meristic data suggest low
variation and that these two green fish lineages are different.
9. What do rare haplotypes and morphological consistencies of East Slope green lineage fish suggest in
terms of subspecies or ESU distinctions?
I cannot comment.
10. Do genetic and meristic studies provide any resolution to probable routes of colonization for green,
blue, greenback and Rio Grande cutthroat trout?
Yes, Dr. Shiozawa’s SNP data allows for more genes to look for variation and, as such, provided a
compelling argument for how these fish diverged and became isolated over time.
11. Is the East Slope - West Slope variation seen for green and blue lineages significant? What could lead
to those differences and are there any taxonomic implications?
I cannot comment.
Management Implications
12. The Bear Creek lineage exists as a single small population. What is the evidence for limited genetic
and meristic variability compared to green, blue lineages? What approaches, if any, should be considered
to manage genetic variability in this lineage to ameliorate potential or actual inbreeding effects?
AFLP data and basiobranchial counts (meristics) both indicate low variability in Bear Creek fish. Also
difficulties encountered in hatchery (deformities) also suggest a more homogeneous population when
compared to green and blue lineages.
I do not advocate for introducing additional genetic material or “forcing hybridization” but instead
translocating Bear Creek fish to a range of different habitats (gradient, temperature, aspect, etc) and
Panelist #16
Page 2
�Greenback Trout Genetics and Meristics Studies – Facilitated Expert Panel Workshop
U.S. Fish & Wildlife Service
Denver, Colorado
letting genetic selection exert pressure on each of these populations. Mixing them then at a later period
could then help preserve the extant genetics left in this population.
13. Which lineage or subspecies should be considered for reintroduction as the native cutthroat for the
Arkansas River basin?
Since the yellowfin is considered extinct, there is no native cutthroat for the Arkansas River Basin
14. How should next-generation DNA sequencing approaches be used in Colorado River, Bear Creek,
and Rio Grande cutthroat trout management?
I think these new techniques should be used to determine which fish are stocked in which drainage and be
used to double check all hatchery stocks and wild populations to ensure that the same mistakes aren’t
made again.
15. What are other prudent and reasonable management and research priorities for the species given the
outcome of these studies?
1. Resolution of West Slope green vs. East Slope green fish
2. Survival of different stocks over time and differences in recruitment strength
3. Translocation success of fish into different habitats
16.
Bear Creek trout sampled in the wild do not appear to have physical abnormalities, while fish
from eggs collected in the wild and reared in a hatchery often have noticeable abnormalities; similar to,
but potentially greater than some other stream and lake spawning attempts east of the Continental Divide
in Colorado.
-
What conclusions can you make from these findings and what inference to future
management of the lineage can you predict?
That these fish originated from a small founder population and moving them to different habitats will be
challenging and potentially problematic as they have little environmental plasticity in which to weather
variation.
-
What steps or research could you take to better understand how these trout could
successfully produce viable populations if replicated in streams in the South Platte River
drainage?
I would introduce them into a variety of habitats to see where they do best and survive.
17. Please provide other relevant comments not addressed in the above questions.
No response.
Panelist #16
Page 3
�Appendix F
Public Comments
Received on the
Greenback Cutthroat Trout Genetics and Meristics
�July 26, 2013
Leslie Ellwood
USFWS/ES/Colorado Field Office
134 Union Blvd, Suite 670
Lakewood, CO 80228
Re: Greenback Cutthroat Trout Scientific Review Workshop
Dear Leslie:
We write on behalf of Trout Unlimited and appreciate this opportunity to provide comment. As you
know, we have long been involved in conservation work on Bear Creek and Colorado TU and its
Cheyenne Mountain Chapter were financial contributors toward the Metcalf et al. study that is a part of
the information you will be reviewing through this workshop.
Our ability to provide meaningful comments to this type of workshop is very limited – both by the nature
of the process in which we cannot interact with your reviewers and raise questions, and by the fact that
one of the critical studies – the meristic analysis from Dr Bestgen – has not yet been made available to the
public. We hope that study will soon be published to help inform the interested public. If the study’s
publication is delayed – even as the Fish and Wildlife Service takes up important Endangered Species Act
issues for Colorado’s native cutthroat trout – then its results should be released to the public, so that
stakeholders can have informed involvement.
While our ability to offer meaningful input is limited, we asked Dr. Helen Neville, a research scientist and
geneticist with Trout Unlimited, to prepare some basic comments on the Metcalf et al. study drawing
from her own expertise in the field. Those comments are attached.
We appreciate the importance of having a frank discussion among various experts in the field to help
provide the Fish and Wildlife Service with a scientific basis for decisions on classification and listing of
native cutthroat trout. At the same time, we ask that you maintain as open of a process as possible. In the
interest of “sunlight” on agency efforts, we urge you to promptly release a list of workshop participants
and information on what areas of scientific agreement and disagreement are identified. Without such
information, the public cannot engage in a meaningful dialogue. We encourage you to follow a
reasonable sequence – developing technical information through processes like this workshop, providing
results to the public, and then using the combination of public input and technical data to inform
development of a draft listing rule. Given the important partnerships that have been developed on Bear
Creek, a specific briefing for the Bear Creek Roundtable would also be appropriate.
We appreciate the chance to offer these comments, and look forward to more extensive agency
engagement of the public as your review of Colorado’s native cutthroat trout proceeds.
Sincerely,
David Nickum
CTU Executive Director
Aaron Kindle
TU – Sportsmen’s Conservation Project
Trout Unlimited: America’s Leading Coldwater Fisheries Conservation Organization
Denver Office: 1536 Wynkoop Street, Suite 100, Denver, CO 80202
PHONE: (303) 440-2937 FAX: (303) 440-7933 EMAIL: dnickum@tu.org
��
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Contents
Current Range
Figures - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2
2
Characteristics of Conservation Populations
Tables - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3
3
Appendix C: Population and habitat data for all CRCT populations regardless of conservation status
32
Appendix C Tables - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Appendix C Figures - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Appendix D: Maps of each 4th level HUC containing historic habitat and each conservation
population.
57
Appendix D Figures - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Appendix E: Comparison maps showing changes in the database to the currently occupied
layer, historic habitat, and populations designated as no longer present.
93
Appendix E Figures - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
WyGISC; University of Wyoming
���
�Current Range
Figures Figure 1: (2010 Assessment Pg. 8)
Historic and current range of CRCT as of 2015.
2
�Characteristics of Conservation Populations
Tables Table 3: (2010 Assessment Pg. 10)
Characteristics of CRCT conservation populations in Colorado, Wyoming, and Utah. CRCT populations in
lakes were not evaluated in 2005.
State
Metric
2005
2010
2015
Colorado
Colorado
Colorado
Colorado
Colorado
Average Patch Length
Conservation Population
Current Range
Historic Range %
Lake Area Occupied
4.9
145.0
1141.0
5.0
0.0
7.4
198.0
1432.0
7.0
60.0
7.2
226.0
1628.9
8.3
68.8
Utah
Utah
Utah
Utah
Utah
Average Patch Length
Conservation Population
Current Range
Historic Range %
Lake Area Occupied
9.2
63.0
933.0
17.0
0.0
13.8
86.0
1105.0
20.0
327.0
12.9
87.0
1117.9
19.8
328.1
Wyoming
Wyoming
Wyoming
Wyoming
Wyoming
Average Patch Length
Conservation Population
Current Range
Historic Range %
Lake Area Occupied
6.0
85.0
816.0
12.0
0.0
12.7
87.0
866.0
13.0
242.0
10.9
80.0
868.5
13.3
242.4
Total
Total
Total
Total
Total
Average Patch Length
6.1
9.4
10.3
Conservation� Population� 285.0� 361.0� ���.0�
Current Range
2891.0 3403.0 3615.3
Historic Range %
8.0
11.0
11.0
Lake Area Occupied
0.0
629.0
639.3
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3
�Table 4: (2010 Assessment Pg. 12)
Stream length (km) of historic range within each GMU and 4th-level HUC. Proportion of historic range
occupied currently (as of 2015), rounded to the nearest whole number, in parentheses. Additional habitat
occupied (km) are populations resulting from human introduction outside the species’ historic range. Current
range (km) is the sum of all occupied habitat. GMU’s are in bold, HUC8 in plain text.
GMU / HUC-8
Historic
range km
Historic
occupied km (%)
Additional
km
Current
Range� km�
Dolores
Lower Dolores
San Miguel
Upper Colorado-Kane Springs
Upper Dolores
1791.2
228.9
470.7
133.2
916.3
86.7 (4.8)
0 (0)
28.1 (6)
0 (0)
51.3 (5.6)
8.0
0.0
5.5
0.0
2.4
94.7
0.0
33.6
0.0
53.7
Westwater Canyon
Gunnison
East-Taylor
Lower Gunnison
North Fork Gunnison
42.1
4594.9
762.3
472.7
661.4
7.3 (17.3)
154 (3.4)
0 (0)
6.7 (1.4)
69.7 (10.5)
0.0
66.0
0.0
30.3
12.9
7.3
220.0
0.0
37.0
82.6
Tomichi
Uncompahange
Upper Gunnison
Lower Colorado
Escalante
707.0
267.5
1724.0
586.6
174.8
0 (0)
14.7 (5.5)
63 (3.7)
75.9 (12.9)
33.1 (18.9)
0.0
0.1
22.8
12.0
10.8
0.0
14.8
85.8
87.9
43.9
Fremont
Muddy
Lower Green
Ashley-Brush
Duchesne
265.5
146.3
3564.7
253.5
907.7
42.8 (16.1)
0 (0)
535.2 (15)
95.2 (37.6)
150 (16.5)
1.2
0.0
111.7
0.0
1.6
44.0
0.0
646.9
95.2
151.6
Lower Green-Desolation Canyon
Lower Green-Diamond
Price
San Rafael
Strawberry
243.6
41.2
630.7
633.6
696.4
0 (0)
0 (0)
109.9 (17.4)
42.6 (6.7)
137.5 (19.7)
0.0
0.0
22.1
0.1
5.6
0.0
0.0
132.0
42.7
143.1
Willow
San Juan
Animas
Chinle
Lower San Juan-Four Corners
158.0
3392.5
724.1
268.9
255.0
0 (0)
68.3 (2)
20.5 (2.8)
0 (0)
0 (0)
82.2
56.8
33.6
0.0
0.0
82.2
125.1
54.1
0.0
0.0
Mancos
Middle San Juan
Montezuma
Piedra
Upper San Juan
191.3
248.7
34.9
597.2
1072.4
0 (0)
0 (0)
0 (0)
22.8 (3.8)
25 (2.3)
0.0
0.0
0.0
4.6
18.6
0.0
0.0
0.0
27.4
43.6
Upper Colorado
Blue
Colorado Headwaters
Colorado Headwaters-Plateau
Eagle
7240.1
758.8
3342.2
933.9
938.8
558.1 (7.7)
43.9 (5.8)
205.9 (6.2)
123.6 (13.2)
49 (5.2)
99.8
10.8
31.0
16.4
8.1
657.9
54.7
236.9
140.0
57.1
Parachute-Roan
Roaring Fork
Upper Green
Big Sandy
Blacks Fork
241.3
1025.1
6825.6
488.2
1341.4
74 (30.7)
61.7 (6)
1050.3 (15.4)
0 (0)
215.2 (16)
17.8
15.6
15.1
0.0
1.5
91.8
77.3
1065.4
0.0
216.7
4
�(continued)
GMU / HUC-8
Historic
range km
Historic
occupied km (%)
Additional
km
Current
Range km
Muddy
New Fork
Upper Green
Upper Green-Flaming Gorge Reservoir
Upper Green-Slate
535.4
584.3
2474.2
1196.8
112.5
42.2 (7.9)
0 (0)
479.5 (19.4)
313.4 (26.2)
0 (0)
0.0
0.0
6.9
6.7
0.0
42.2
0.0
486.4
320.1
0.0
Vermilion
Yampa
Little Snake
Lower White
Lower Yampa
92.7
4181.2
827.8
141.7
81.2
0 (0)
686.1 (16.4)
216.2 (26.1)
29.7 (21)
17.9 (22)
0.0
31.3
20.2
0.1
1.3
0.0
717.4
236.4
29.8
19.2
Muddy
Piceance-Yellow
Upper White
Upper Yampa
105.1
106.7
844.2
2074.6
32.7 (31.1)
12.9 (12.1)
91.8 (10.9)
284.9 (13.7)
0.1
0.0
1.9
7.8
32.8
12.9
93.7
292.7
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Table 5: (2010 Assessment Pg. 13)
Distribution of habitat patch lengths (km) occupied by stream-dwelling CRCT conservation populations.
Lake populations were not included in this analysis.
Patch Length
2010
2015
0.0 - 1.0
1.1 - 2.0
2.1 - 4.0
4.1 - 10.0
10.1 - 20.0
17
36
79
117
62
18
39
84
130
60
20.1 - 30.0
30.1 - 40.0
40.1 - 50.0
50.1 - 70.0
70.1 - 90.0
19
6
1
6
3
18
3
3
5
4
>= 90.1
2
3
5
�Table 6: (2010 Assessment Pg. 13)
Characteristics of CRCT conservation populations in 2005, 2010 and 2015. N is the number of conservation
populations, stream habitat occupied is presented in km, lake habitat occupied is presented in ha. Median
patch length and associated range of values (min - max) are for stream populations only. Information on lake
occupancy was not available in 2005.
GMU
Year
N
Stream habitat
occupied km
Lake habitat
occupied ha
Dolores
Dolores
Dolores
Gunnison
Gunnison
2005
2010
2015
2005
2010
4
10
20
25
36
23.0
56.0
94.7
149.0
196.0
0.0
0.0
9.3
0.0
6.0
5.8 (3.6-7.7)
5.2 (2.7-8.1)
5.5 (1.33-9.4)
5.3 (0.2-19.6)
4.4 (0.2-20.2)
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
2015
2005
2010
2015
2005
38
14
21
24
26
220.1
80.0
84.0
87.9
495.0
5.8
0.0
7.0
7.7
0.0
4.3 (0.21-20.5)
4.7 (0.5-21.7)
2 (0.5-23.5)
2 (0.45-23.1)
11.7 (0.7-95.6)
Lower Green
Lower Green
San Juan
San Juan
San Juan
2010
2015
2005
2010
2015
39
38
12
15
23
638.0
646.8
67.0
80.0
125.1
146.0
145.9
0.0
1.0
1.2
10.1 (1.4-96.4)
10.1 (1.73-95.5)
4.2 (1.3-13.8)
3.7 (1.3-14.2)
3.8 (1.29-17.4)
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
Upper Green
2005
2010
2015
2005
2010
75
101
107
76
75
485.0
605.0
657.9
1047.0
1073.0
0.0
35.0
35.4
0.0
417.0
5 (0.3-28.6)
5 (0.12-26)
5 (0.12-25.3)
9 (0.03-105.6)
9 (0.03-101.7)
Upper Green
Yampa
Yampa
Yampa
Total
2015
2005
2010
2015
2005
67
53
64
67
285
1065.4
545.0
671.0
717.4
2891.0
416.9
0.0
17.0
17.1
0.0
8.4 (0.03-99.9)
5.5 (0.7-60.4)
5.1 (0.3-78.1)
5.6 (0.31-85.3)
6 (0.03-105.6)
Total
Total
2010
2015
361
384
3403.0
3615.3
629.0
639.3
5.7 (0.03-101.7)
5.5 (0.03-99.9)
6
Median patch
length km
(range)
�Table 7: (2010 Assessment Pg. 13)
Distribution of barriers among CRCT conservation populations by GMU in 2005, 2010 and 2015.
GMU
Year
Complete
Partial
None
Unknown
Dolores
Dolores
Dolores
Gunnison
Gunnison
2005
2010
2015
2005
2010
2
5
6
9
13
0
1
1
2
6
2
4
0
14
14
0
0
0
0
3
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
2015
2005
2010
2015
2005
18
13
16
20
15
8
0
1
1
4
0
1
4
0
7
1
0
0
0
0
Lower Green
Lower Green
San Juan
San Juan
San Juan
2010
2015
2005
2010
2015
17
25
25
24
24
5
9
4
6
0
17
0
52
42
0
0
1
2
3
1
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
Upper Green
2005
2010
2015
2005
2010
11
13
53
38
43
0
0
17
15
11
0
1
0
22
41
1
1
13
6
6
Upper Green
Yampa
Yampa
Yampa
Total
2015
2005
2010
2015
2005
78
26
27
49
139
4
2
7
12
27
0
26
26
0
124
4
1
4
4
10
Total
Total
2010
2015
158
273
37
52
149
0
17
24
7
�Table 8: (2010 Assessment Pg. 14)
Connectivity of CRCT conservation populations for each GMU. For each connectivity level data are presented
as number of populations; stream km; lake ha. There are no lake data for 2005.
GMU
Connectivity
Year
Total Con.
Pops.
N
km
ha
Dolores
Dolores
Dolores
Dolores
Dolores
Isolated
Isolated
Isolated
Weak
Weak
2005
2010
2015
2005
2010
4
10
20
4
10
4
9
15
0
0
23
49
69
0
0
0
0
7
0
0
Dolores
Dolores
Dolores
Dolores
Dolores
Weak
Moderate
Moderate
Moderate
Strong
2015
2005
2010
2015
2005
20
4
10
20
4
0
0
0
1
0
0
0
0
9
0
0
0
0
0
0
Dolores
Dolores
Gunnison
Gunnison
Gunnison
Strong
Strong
Isolated
Isolated
Isolated
2010
2015
2005
2010
2015
10
20
25
36
38
1
4
19
29
30
7
17
89
131
150
0
3
0
6
6
Gunnison
Gunnison
Gunnison
Gunnison
Gunnison
Weak
Weak
Weak
Moderate
Moderate
2005
2010
2015
2005
2010
25
36
38
25
36
5
5
6
1
2
53
43
47
7
22
0
0
0
0
0
Gunnison
Gunnison
Gunnison
Gunnison
Lower Colorado
Moderate
Strong
Strong
Strong
Isolated
2015
2005
2010
2015
2005
38
25
36
38
14
2
0
0
0
12
22
0
0
0
56
0
0
0
0
0
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Isolated
Isolated
Weak
Weak
Weak
2010
2015
2005
2010
2015
21
24
14
21
24
18
19
2
3
5
54
51
24
30
37
7
8
0
0
0
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Moderate
Moderate
Moderate
Strong
Strong
2005
2010
2015
2005
2010
14
21
24
14
21
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Lower Colorado
Lower Green
Lower Green
Lower Green
Lower Green
Strong
Isolated
Isolated
Isolated
Weak
2015
2005
2010
2015
2005
24
26
39
38
26
0
15
21
20
7
0
110
160
160
119
0
0
118
118
0
Lower Green
Lower Green
Lower Green
Weak
Weak
Moderate
2010
2015
2005
39
38
26
12
12
1
170
170
49
7
7
0
8
�(continued)
GMU
Connectivity
Year
Total Con.
Pops.
N
km
ha
Lower Green
Lower Green
Moderate
Moderate
2010
2015
39
38
2
2
81
80
0
0
Lower Green
Lower Green
Lower Green
San Juan
San Juan
Strong
Strong
Strong
Isolated
Isolated
2005
2010
2015
2005
2010
26
39
38
12
15
3
4
4
11
14
217
227
236
57
69
0
21
21
0
1
San Juan
San Juan
San Juan
San Juan
San Juan
Isolated
Weak
Weak
Weak
Moderate
2015
2005
2010
2015
2005
23
12
15
23
12
20
1
1
2
0
94
11
11
14
0
1
0
0
0
0
San Juan
San Juan
San Juan
San Juan
San Juan
Moderate
Moderate
Strong
Strong
Strong
2010
2015
2005
2010
2015
15
23
12
15
23
0
1
0
0
0
0
17
0
0
0
0
0
0
0
0
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Isolated
Isolated
Isolated
Weak
Weak
2005
2010
2015
2005
2010
75
101
107
75
101
59
82
86
15
16
345
441
458
112
116
0
29
29
0
7
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Weak
Moderate
Moderate
Moderate
Strong
2015
2005
2010
2015
2005
107
75
101
107
75
18
1
1
1
0
151
29
25
25
0
7
0
0
0
0
Upper Colorado
Upper Colorado
Upper Green
Upper Green
Upper Green
Strong
Strong
Isolated
Isolated
Isolated
2010
2015
2005
2010
2015
101
107
76
75
67
2
2
32
35
32
23
24
276
306
287
0
0
0
62
62
Upper Green
Upper Green
Upper Green
Upper Green
Upper Green
Weak
Weak
Weak
Moderate
Moderate
2005
2010
2015
2005
2010
76
75
67
76
75
33
31
27
7
3
401
403
408
137
53
0
39
39
0
1
Upper Green
Upper Green
Upper Green
Upper Green
Yampa
Moderate
Strong
Strong
Strong
Isolated
2015
2005
2010
2015
2005
67
76
75
67
53
3
4
6
5
36
52
233
311
318
234
1
0
314
314
0
Yampa
Yampa
Yampa
Yampa
Isolated
Isolated
Weak
Weak
2010
2015
2005
2010
64
67
53
64
47
47
9
9
301
305
106
90
17
17
0
0
9
�(continued)
GMU
Connectivity
Year
Total Con.
Pops.
N
km
ha
Yampa
Weak
2015
67
11
107
0
Yampa
Yampa
Yampa
Yampa
Yampa
Moderate
Moderate
Moderate
Strong
Strong
2005
2010
2015
2005
2010
53
64
67
53
64
7
7
8
1
0
205
280
304
1
0
0
0
0
0
0
Yampa
Total
Total
Total
Total
Strong
Isolated
Isolated
Isolated
Weak
2015
2005
2010
2015
2005
67
284
361
384
284
1
188
256
269
72
1
1190
1511
1575
826
0
0
240
247
0
Total
Total
Total
Total
Total
Weak
Weak
Moderate
Moderate
Moderate
2010
2015
2005
2010
2015
361
384
284
361
384
76
81
17
15
18
1063
935
427
461
510
53
53
0
1
1
Total
Total
Total
Strong
Strong
Strong
2005
2010
2015
284
361
384
7
13
16
450
561
596
0
335
337
Table 9: (2010 Assessment Pg. 15)
Conservation populations in allopatry and sympatry within GMUs in 2005, 2010 and 2015. A valid stocking
record indicates there is the potential for hybridization. In 2005, conservation populations having either
a historic stocking record or confirmed non-native presence were pooled. Within each column data are
formatted as number of populations; stream km; lake ha. There are no lake data for 2005.
GMU
N
km
Non-Natives Absent, 2005
Dolores
1
13
Gunnison
13
73
Lower Colorado 8
46
Lower Green
8
253
San Juan
7
54
Upper Colorado 32
280
Upper Green
24
362
Yampa
22
275
Non-Natives Present, 2005
Dolores
3
13
Gunnison
12
131
Lower Colorado 6
68
Lower Green
18
401
San Juan
5
26
Upper Colorado 43
424
Upper Green
52
1224
Yampa
31
550
10
ha
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
�(continued)
GMU
N
km
ha
Non-Natives Absent, No Stocking Record, 2010
Dolores
4
25
0
Gunnison
14
45
6
Lower Colorado 12
44
1
Lower Green
14
128
13
San Juan
8
43
1
Upper Colorado 40
181
18
Upper Green
27
171
15
Yampa
33
0
0
Non-Natives Absent, Historic Stocking Record, 2010
Dolores
1
5
0
Gunnison
6
40
0
Lower Colorado 3
7
0
Lower Green
3
117
0
San Juan
3
18
0
Upper Colorado 17
99
14
Upper Green
12
161
0
Yampa
11
90
0
Non-Natives Present, Historic Stocking Record, 2010
Dolores
5
27
0
Gunnison
16
112
0
Lower Colorado 6
33
6
Lower Green
22
392
133
San Juan
4
19
0
Upper Colorado 44
326
3
Upper Green
36
741
402
Yampa
20
420
17
Non-Natives Absent, No Stocking Record, 2015
Dolores
8
27
9
Gunnison
14
46
6
Lower Colorado 13
35
0
Lower Green
9
96
2
San Juan
7
31
0
Upper Colorado 39
186
3
Upper Green
13
86
44
Yampa
30
136
2
Non-Natives Absent, Historic Stocking Record, 2015
Dolores
5
33
0
Gunnison
2
10
0
Lower Colorado 1
0
1
Lower Green
4
130
0
San Juan
4
19
0
Upper Colorado 15
62
4
Upper Green
3
20
0
Yampa
10
229
0
Non-Natives Present, No Stocking Record, 2015
Dolores
5
23
1
Gunnison
11
74
0
Lower Colorado 3
8
0
11
�(continued)
GMU
N
km
ha
Lower Green
8
155
0
San Juan
9
51
0
Upper Colorado 24
156
6
Upper Green
23
228
221
Yampa
15
111
16
Non-Natives Present, Historic Stocking Record, 2015
Dolores
2
12
0
Gunnison
11
89
0
Lower Colorado 7
45
7
Lower Green
17
265
144
San Juan
3
24
1
Upper Colorado 29
254
23
Upper Green
28
732
352
Yampa
12
241
0
Table 10: (2010 Assessment Pg. 15)
Life history diversity of CRCT conservation populations within each GMU. Conservation Populations noted
as Lacustrine below, were noted as Adfluvial in the 2010 Assessment.
GMU
Year
Resident
Fluvial
Lacustrine
Res;
Flu
Res;
Lac
Res;
Flu;
Lac
Total
Dolores
Dolores
Gunnison
Gunnison
Lower Colorado
2010
2015
2010
2015
2010
10
20
35
37
19
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
10
20
36
38
21
Lower Colorado
Lower Green
Lower Green
San Juan
San Juan
2015
2010
2015
2010
2015
21
35
34
15
23
0
0
0
0
0
2
2
2
0
0
0
1
1
0
0
1
0
0
0
0
0
1
1
0
0
24
39
38
15
23
Upper Colorado
Upper Colorado
Upper Green
Upper Green
Yampa
2010
2015
2010
2015
2010
97
104
69
61
61
1
1
0
0
1
2
2
2
2
0
0
0
2
2
2
0
0
2
2
2
0
0
0
0
0
100
107
75
67
66
Yampa
Total
Total
2015
2010
2015
62
341
362
3
2
4
0
8
9
0
5
3
2
5
5
0
1
1
67
362
384
12
�Table 11: (2010 Assessment Pg. 16)
Genetic status of CRCT conservation populations in 2010 and 2015 by GMU. Data are presented as stream
km occupied by populations of each genetic status. Populations were classified either with molecular data or
based on their past stocking history such that the resulting population is likely pure (Suspected unaltered,
SusUn), hybridized (Potentially hybridized, PotHyb), or composed of mixed stock of native and nonnative
species (Mixed).
GMU
Year
Unaltered
90-99%
80-89%
<80%
SusUn
PotHyb
Mixed
Total
Dolores
Dolores
Dolores
Gunnison
Gunnison
2010
2015
Change
2010
2015
29.8
25.9
-3.9
76.1
87.3
21.7
60.8
39.1
64.9
75.2
0.0
0.0
0.0
6.5
6.4
0.0
0.0
0.0
0.0
5.7
0.0
2.2
2.2
15.5
10.6
0.0
5.8
5.8
39.7
34.9
4.3
0.0
-4.3
10.1
0.0
55.8
94.7
38.9
212.8
220.1
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
Change
2010
2015
Change
2010
11.2
78.5
82.9
4.4
404.7
10.3
0.0
0.0
0.0
64.6
-0.1
0.0
0.0
0.0
0.0
5.7
0.0
0.0
0.0
23.9
-4.9
0.0
0.0
0.0
92.9
-4.8
5.2
5.1
0.0
51.8
-10.1
0.0
0.0
0.0
0.0
7.3
83.7
87.9
4.4
637.9
Lower Green
Lower Green
San Juan
San Juan
San Juan
2015
Change
2010
2015
Change
413.0
8.3
51.8
76.7
24.9
92.3
27.7
19.1
37.0
17.9
0.0
0.0
0.0
0.0
0.0
43.4
19.5
0.0
0.0
0.0
66.3
-26.6
6.4
0.0
-6.4
31.8
-20.0
3.1
11.5
8.4
0.0
0.0
0.0
0.0
0.0
646.8
8.9
80.4
125.1
44.7
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
Upper Green
2010
2015
Change
2010
2015
242.0
226.9
-15.1
320.3
337.0
128.3
256.7
128.4
128.3
163.1
0.1
7.5
7.4
36.4
40.7
28.5
0.0
-28.5
20.8
47.7
81.9
42.8
-39.1
242.1
170.9
124.3
101.5
-22.8
229.5
192.7
0.0
22.5
22.5
95.8
104.4
605.1
657.9
52.8
1073.2
1056.4
Upper Green
Yampa
Yampa
Yampa
Change
2010
2015
Change
16.7
312.9
306.8
-6.1
34.8
240.8
263.5
22.7
4.3
4.0
27.5
23.5
26.9
0.0
0.0
0.0
-71.2
56.4
62.0
5.6
-36.8
56.8
57.6
0.8
8.6
0.0
0.0
0.0
-16.8
670.9
717.4
46.5
13
�Table 12: (2010 Assessment Pg. 17)
Genetic status of lake populations of CRCT in 2010 and 2015 by GMU. Data are presented as hectares
occupied by populations of each genetic status. Populations were classified either with molecular data or
based on their past stocking history such that the resulting population is likely pure (Suspected unaltered,
SusUn), hybridized (Potentially hybridized, PotHyb), or composed of mixed stock of native and nonnative
species (Mixed).
GMU
Year
Unaltered
90-99%
80-89%
<80%
SusUn
PotHyb
Mixed
Total
Dolores
Dolores
Dolores
Gunnison
Gunnison
2010
2015
Change
2010
2015
0.0
9.3
9.3
6.0
5.8
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0.0
9.3
9.3
6.0
5.8
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
Change
2010
2015
Change
2010
-0.2
7.0
7.7
0.7
48.0
0.0
0.0
0.0
0.0
12.0
0
0
0
0
0
0
0
0
0
0
0.0
0.0
0.0
0.0
62.0
0.0
0.0
0.0
0.0
24.0
0
0
0
0
0
-0.2
7.0
7.7
0.7
146.0
Lower Green
Lower Green
San Juan
San Juan
San Juan
2015
Change
2010
2015
Change
66.8
18.8
0.0
1.2
1.2
0.0
-12.0
1.0
0.0
-1.0
0
0
0
0
0
0
0
0
0
0
55.0
-7.0
0.0
0.0
0.0
24.1
0.1
0.0
0.0
0.0
0
0
0
0
0
145.9
-0.1
1.0
1.2
0.2
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
Upper Green
2010
2015
Change
2010
2015
29.0
28.1
-0.9
26.0
27.2
1.0
0.8
-0.2
25.0
86.2
0
0
0
0
0
0
0
0
0
0
6.0
6.5
0.5
118.0
71.4
10.0
0.0
-10.0
248.0
232.2
0
0
0
0
0
46.0
35.4
-10.6
417.0
416.9
Upper Green
Yampa
Yampa
Yampa
Change
2010
2015
Change
1.2
2.0
1.6
-0.4
61.2
0.0
0.0
0.0
0
0
0
0
0
0
0
0
-46.6
16.0
15.5
-0.5
-15.8
0.0
0.0
0.0
0
0
0
0
-0.1
18.0
17.1
-0.9
14
�Table 13: (2010 Assessment Pg. 17)
Density categories, reported in units of sexually mature CRCT per mile, of conservation population-occupied
stream habitat (km) by state for reporting periods 2005, 2010 and 2015 are shown in addition change since
2010.
State
Density
2005
(km)
2010
(km)
2015
(km)
Change
(2010-2015
in km)
Colorado
Colorado
Colorado
Colorado
Colorado
0-50
51-150
151-400
>400
Unknown Density
163.1
266.3
379.3
64.8
272.4
254.4
456.4
296.4
166.9
157.4
236.1
508.6
494.7
192.3
197.0
-18.3
52.2
198.3
25.4
39.6
Colorado
Utah
Utah
Utah
Utah
Total
0-50
51-150
151-400
>400
1145.9
251.8
159.4
175.4
116.8
1431.7
253.6
233.0
258.3
186.1
1628.7
245.4
217.4
306.8
185.4
197.0
-8.2
-15.6
48.5
-0.7
Utah
Utah
Wyoming
Wyoming
Wyoming
Unknown Density
Total
0-50
51-150
151-400
235.9
939.3
207.0
209.1
189.8
174.2
1105.3
151.6
242.2
187.7
162.7
1117.8
177.0
323.8
159.4
-11.5
12.5
25.4
81.6
-28.3
Wyoming
Wyoming
Wyoming
>400
Unknown Density
Total
119.8
91.2
816.9
102.5
182.0
865.9
46.5
161.9
868.6
-56.0
-20.1
2.7
15
�Table 14: (2010 Assessment Pg. 19)
Density categories, reported in units of adult CRCT per mile, of conservation population-occupied stream
habitat (km) by GMU for 2005, 2010 and 2015.
GMU
Density
2005
(km)
2010
(km)
2015
(km)
Change
(2010-2015
in km)
Dolores
Dolores
Dolores
Dolores
Dolores
0-50
51-150
151-400
>400
Unknown Density
5.3
3.7
6.6
0.0
7.9
4.9
31.9
19.1
0.0
0.0
4.8
45.2
36.6
2.2
5.8
-0.1
13.3
17.5
0.0
5.8
Dolores
Gunnison
Gunnison
Gunnison
Gunnison
Total
0-50
51-150
151-400
>400
23.5
30.0
42.2
47.3
0.0
55.9
61.0
46.5
53.6
21.7
94.7
37.2
62.8
67.7
39.2
38.8
-23.8
16.3
14.1
17.5
Gunnison
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Unknown Density
Total
0-50
51-150
151-400
30.2
149.7
16.5
30.8
10.4
13.3
196.2
5.7
28.4
17.5
13.3
220.1
5.7
27.9
19.1
0.0
23.9
0.0
-0.5
1.6
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
Lower Green
>400
Unknown Density
Total
0-50
51-150
22.5
0.7
80.9
222.8
81.9
29.8
2.3
83.7
224.9
146.1
29.8
5.4
87.9
198.9
142.0
0.0
3.1
4.2
-26.0
-4.1
Lower Green
Lower Green
Lower Green
Lower Green
San Juan
151-400
>400
Unknown Density
Total
0-50
80.1
7.1
102.6
494.5
0.0
104.1
49.7
1132.0
637.9
0.0
132.3
60.8
112.8
646.8
18.1
28.2
11.1
-1019.2
8.9
0.0
San Juan
San Juan
San Juan
San Juan
San Juan
51-150
151-400
>400
Unknown Density
Total
32.0
18.8
16.4
0.0
67.2
30.4
18.1
25.8
6.0
80.3
36.4
23.8
22.6
24.2
125.1
6.0
5.7
-3.2
18.2
44.8
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
0-50
51-150
151-400
>400
Unknown Density
77.0
97.8
171.4
11.5
127.8
92.4
177.3
126.7
111.3
97.3
88.8
173.6
186.7
111.4
97.4
-3.6
-3.7
60.0
0.1
0.1
Upper Colorado
Upper Green
Upper Green
Upper Green
Upper Green
Total
0-50
51-150
151-400
>400
485.5
171.2
192.1
278.2
187.0
605.0
128.8
231.7
291.9
197.7
657.9
143.2
301.9
292.4
130.1
52.9
14.4
70.2
0.5
-67.6
Upper Green
Unknown Density
223.7
223.0
188.9
-34.1
16
�(continued)
GMU
Density
2005
(km)
2010
(km)
2015
(km)
Change
(2010-2015
in km)
Upper Green
Yampa
Yampa
Yampa
Total
0-50
51-150
151-400
1052.1
99.1
154.2
131.7
1073.1
141.9
239.6
211.5
1056.4
152.9
260.0
202.3
-16.7
11.0
20.4
-9.2
Yampa
Yampa
Yampa
>400
Unknown Density
Total
57.1
103.6
548.7
19.4
58.5
670.8
28.2
74.0
717.4
8.8
15.5
46.6
17
�Table 15: (2010 Assessment Pg. 20)
Quality of habitat patches occupied by conservation populations in Colorado, Utah, and Wyoming in 2005,
2010 and 2015.
State
Habitat
2005 (km)
2010 (km)
2015 (km)
Change
(2010-2015
in km)
Colorado
Colorado
Colorado
Colorado
Colorado
Excellent
Good
Fair
Poor
Unknown
150.1
642.8
234.5
77.6
40.8
243.0
783.1
324.7
62.6
18.3
261.5
859.4
415.1
76.2
16.6
18.5
76.3
90.4
13.6
-1.7
Colorado
Utah
Utah
Utah
Utah
Total
Excellent
Good
Fair
Poor
1145.8
210.0
374.5
249.7
57.4
1431.7
270.1
447.9
253.2
85.1
1628.8
230.9
453.9
294.1
90.2
197.1
-39.2
6.0
40.9
5.1
Utah
Utah
Wyoming
Wyoming
Wyoming
Unknown
Total
Excellent
Good
Fair
47.7
939.3
63.5
294.8
357.8
49.1
1105.4
76.5
356.1
331.4
48.8
1118.0
74.5
318.8
403.6
-0.3
12.6
-2.0
-37.3
72.2
Wyoming
Wyoming
Wyoming
Poor
Unknown
Total
64.1
36.7
816.9
76.7
25.2
865.9
70.3
1.4
868.5
-6.4
-23.8
2.6
18
�Table 16: (2010 Assessment Pg. 20)
Habitat quality of habitat (km) occupied by CRCT conservation populations in 2005, 2010 and 2015 by
GMU.
GMU
Habitat
2005 (km)
2010 (km)
2015 (km)
Change
(2010-2015
in km)
Dolores
Dolores
Dolores
Dolores
Dolores
Excellent
Good
Fair
Poor
Unknown
0.0
7.9
15.6
0.0
0.0
0.0
39.3
16.6
0.0
0.0
9.4
62.8
22.4
0.0
0.0
0.0
23.5
5.8
0.0
0.0
Dolores
Gunnison
Gunnison
Gunnison
Gunnison
Total
Excellent
Good
Fair
Poor
23.5
18.4
103.8
26.5
1.0
55.9
34.3
124.2
36.6
1.0
94.6
34.5
133.3
51.2
1.0
38.7
0.2
9.1
14.6
0.0
Gunnison
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Unknown
Total
Excellent
Good
Fair
0.0
149.7
19.3
30.1
21.4
0.0
196.2
19.2
35.6
21.2
0.0
220.0
18.8
33.6
24.6
0.0
23.8
-0.4
-2.0
3.4
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
Lower Green
Poor
Unknown
Total
Excellent
Good
10.1
0.0
80.9
3.5
176.1
7.7
0.0
83.7
5.8
304.5
10.8
0.0
87.8
5.8
303.8
3.1
0.0
4.1
0.0
-0.7
Lower Green
Lower Green
Lower Green
Lower Green
San Juan
Fair
Poor
Unknown
Total
Excellent
220.4
47.3
47.3
494.5
23.1
215.3
65.6
46.7
637.9
24.0
222.9
67.8
46.4
646.7
23.2
7.6
2.2
-0.3
8.8
-0.8
San Juan
San Juan
San Juan
San Juan
San Juan
Good
Fair
Poor
Unknown
Total
35.4
8.7
0.0
0.0
67.2
46.7
9.6
0.0
0.0
80.3
86.5
15.5
0.0
0.0
125.2
39.8
5.9
0.0
0.0
44.9
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Excellent
Good
Fair
Poor
Unknown
76.4
253.2
90.9
32.7
32.4
134.9
283.6
157.1
19.9
9.5
145.6
277.3
201.9
25.2
7.7
10.7
-6.3
44.8
5.3
-1.8
Upper Colorado
Upper Green
Upper Green
Upper Green
Upper Green
Total
Excellent
Good
Fair
Poor
485.5
201.1
422.3
328.8
62.7
605.0
255.4
411.6
290.2
88.5
657.7
214.2
384.7
371.9
81.8
52.7
-41.2
-26.9
81.7
-6.7
Upper Green
Upper Green
Unknown
Total
37.1
1052.1
27.5
1073.1
3.8
1056.4
-23.7
-16.7
19
�(continued)
GMU
Habitat
2005 (km)
2010 (km)
2015 (km)
Change
(2010-2015
in km)
Yampa
Yampa
Yampa
Excellent
Good
Fair
82.0
283.4
129.7
116.0
341.5
162.9
115.3
341.0
202.3
-0.7
-0.5
39.4
Yampa
Yampa
Yampa
Poor
Unknown
Total
45.2
8.0
548.7
41.7
8.8
670.8
49.9
8.9
717.4
8.2
0.1
46.6
Table 17: (2010 Assessment Pg. 21)
Width (ft) of stream habitat occupied by CRCT conservation populations by GMU.
GMU
Width
2005 (km)
2010 (km)
2015 (km)
Change
(2010-2015
in km)
Dolores
Dolores
Dolores
Dolores
Dolores
<5
5-10
10-15
15-20
20-25
9.1
14.5
0.0
0.0
0.0
14.8
32.3
8.8
0.0
0.0
16.7
49.0
29.0
0.0
0.0
1.9
16.7
20.2
0.0
0.0
Dolores
Dolores
Dolores
Gunnison
Gunnison
>25
Unknown
Total
<5
5-10
0.0
0.0
23.5
35.1
80.1
0.0
0.0
55.9
28.7
106.3
0.0
0.0
94.7
54.5
100.6
0.0
0.0
38.8
25.8
-5.7
Gunnison
Gunnison
Gunnison
Gunnison
Gunnison
10-15
15-20
20-25
>25
Unknown
33.8
0.0
0.0
0.0
0.7
48.1
13.0
0.0
0.0
0.0
52.1
12.9
0.0
0.0
0.0
4.0
-0.1
0.0
0.0
0.0
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Total
<5
5-10
10-15
15-20
149.7
7.0
37.6
30.3
1.0
196.2
8.2
38.0
31.6
0.8
220.1
15.1
42.8
24.2
0.8
23.9
6.9
4.8
-7.4
0.0
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
20-25
>25
Unknown
Total
<5
5.0
0.0
0.0
80.9
80.8
5.2
0.0
0.0
83.7
129.8
5.1
0.0
0.0
88.0
118.0
-0.1
0.0
0.0
4.3
-11.8
Lower Green
Lower Green
Lower Green
Lower Green
Lower Green
5-10
10-15
15-20
20-25
>25
190.1
118.9
11.6
29.2
3.9
266.7
119.8
23.2
35.1
3.9
265.2
127.8
23.7
48.7
4.0
-1.5
8.0
0.5
13.6
0.1
Lower Green
Unknown
59.9
59.5
59.3
-0.2
20
�(continued)
GMU
Width
2005 (km)
2010 (km)
2015 (km)
Change
(2010-2015
in km)
Lower Green
San Juan
San Juan
San Juan
Total
<5
5-10
10-15
494.5
0.0
33.1
0.0
637.9
0.0
39.4
5.6
646.7
0.0
63.2
15.1
8.8
0.0
23.8
9.5
San Juan
San Juan
San Juan
San Juan
San Juan
15-20
20-25
>25
Unknown
Total
20.2
13.9
0.0
0.0
67.2
21.1
14.2
0.0
0.0
80.2
32.6
14.1
0.0
0.0
125.0
11.5
-0.1
0.0
0.0
44.8
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
<5
5-10
10-15
15-20
20-25
21.7
249.2
97.4
53.1
31.4
54.3
310.2
144.5
47.7
29.5
69.3
332.8
156.7
53.9
29.2
15.0
22.6
12.2
6.2
-0.3
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
Upper Green
>25
Unknown
Total
<5
5-10
54.1
32.7
539.6
185.8
439.8
7.6
11.2
605.0
246.1
398.5
7.4
8.6
657.9
234.9
354.0
-0.2
-2.6
52.9
-11.2
-44.5
Upper Green
Upper Green
Upper Green
Upper Green
Upper Green
10-15
15-20
20-25
>25
Unknown
171.5
119.6
33.5
0.0
47.8
133.5
158.4
44.8
55.4
36.4
111.9
168.3
80.7
94.2
12.2
-21.6
9.9
35.9
38.8
-24.2
Upper Green
Yampa
Yampa
Yampa
Yampa
Total
<5
5-10
10-15
15-20
998.0
47.4
259.9
127.3
62.5
1173.1
81.5
300.8
152.7
79.4
1056.2
91.5
320.1
154.9
76.3
-116.9
10.0
19.3
2.2
-3.1
Yampa
Yampa
Yampa
Yampa
20-25
>25
Unknown
Total
24.2
2.3
25.1
548.7
35.5
2.4
18.5
670.8
43.9
2.5
28.1
717.3
8.4
0.1
9.6
46.5
21
�Table 18: (2010 Assessment Pg. 22)
Land management status of occupied habitat by conservation populations in 2005, 2010 and 2015. Change
indicates from 2010-2015.
State
Owner
2005
(km)
2005
(ha)
2010
(km)
2010
(ha)
2015
(km)
2015
(ha)
Colorado
Utah
Wyoming
Colorado
Utah
BLM
BLM
BLM
USFS NonWilderness
USFS NonWilderness
137
4
123
606
637
0
0
0
0
0
131
12
123
672
667
2
0
0
8
202
120
16
123
817
669
2
0
0
8
203
-11
4
0
145
2
0
0
0
0
1
Wyoming
Colorado
Utah
Wyoming
Colorado
USFS NonWilderness
USFS Wilderness
USFS Wilderness
USFS Wilderness
NPS
473
234
157
35
18
0
0
0
0
0
500
273
189
43
12
242
26
114
0
21
456
273
186
44
12
242
27
114
0
21
-44
0
-3
1
0
0
1
0
0
-1
Utah
Wyoming
Colorado
Utah
Wyoming
NPS
NPS
Private
Private
Private
1
0
279
100
148
0
0
0
0
0
1
0
309
120
148
0
0
2
12
0
0
0
343
122
184
0
0
5
12
0
-1
0
34
2
36
0
0
3
0
0
Colorado
Utah
Wyoming
Colorado
Utah
State
State
State
Tribal
Tribal
20
25
38
0
9
0
0
0
0
0
35
75
53
0
38
0
0
0
0
0
37
87
52
0
38
7
0
0
0
0
2
12
-1
0
0
7
0
0
0
0
Wyoming
Tribal
0
0
0
0
0
0
0
0
22
Change Change
(km)
(ha)
�Table 19: (2010 Assessment Pg. 23)
Risk of genetic contamination for CRCT conservation populations by GMU. N indicates total number of
conservation populations. Stream populations are listed as km and lake populations are listed as ha.
GMU
GeneticRisk
2010 N
2015 N
2010 km
2015 km
2010 ha
2015 ha
Dolores
Dolores
Dolores
Dolores
Dolores
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
1
1
7
1
0
2
4
12
2
0
4
6
43
3
0
10
18
55
12
0
0
0
0
0
0
0
0
9
0
0
Gunnison
Gunnison
Gunnison
Gunnison
Gunnison
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
12
2
21
1
0
12
4
21
1
0
60
14
102
20
0
56
26
118
20
0
6
0
0
0
0
6
0
0
0
0
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
15
0
5
1
0
18
0
5
1
0
69
0
9
5
0
74
0
9
5
43
7
0
0
0
0
8
0
0
0
0
Lower Green
Lower Green
Lower Green
Lower Green
Lower Green
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
22
2
12
3
0
21
2
12
3
0
305
9
286
39
0
304
9
296
39
39
97
0
28
21
0
98
0
28
21
0
San Juan
San Juan
San Juan
San Juan
San Juan
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
13
0
2
0
0
21
0
2
0
0
66
0
15
0
0
110
0
15
0
0
1
0
0
0
0
1
0
0
0
0
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
64
8
28
1
0
66
7
32
2
0
349
49
200
8
0
358
45
245
9
12
32
0
4
0
0
32
0
4
0
0
Upper Green
Upper Green
Upper Green
Upper Green
Upper Green
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
24
12
28
12
0
20
10
27
10
0
126
154
464
330
0
91
132
543
299
18
43
105
40
228
0
43
105
40
229
0
Yampa
Yampa
Yampa
Yampa
Yampa
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
31
9
21
3
0
33
9
21
3
1
190
91
336
53
0
206
90
359
53
9
17
0
0
0
0
17
0
0
0
0
Total
Total
Total
Total
Total
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
182
34
123
22
0
193
36
132
22
1
1169
323
1455
458
0
1209
320
1640
437
121
203
105
72
249
0
204
105
81
249
0
23
�Table 20: (2010 Assessment Pg. 24)
Risks of genetic contamination for CRCT conservation populations by degree of within population connectivity.
N indicates total number of conservation populations. Stream populations are listed as km and lake populations
are listed as ha.
Connectivity
GeneticRisk
2010 N
2015 N
2010 km
2015 km
2010 ha
2015 ha
Population Isolated
Population Isolated
Population Isolated
Population Isolated
Population Isolated
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
145
22
77
11
0
153
24
80
��
1
759
124
484
144
0
780
131
526
129
9
196
20
4
21
0
197
20
10
21
0
Weakly Connected
Weakly Connected
Weakly Connected
Weakly Connected
Weakly Connected
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
31
9
30
7
0
34
9
32
6
0
271
121
339
132
0
293
111
412
119
0
7
46
0
0
0
7
0
46
0
0
Moderately Connected
Moderately Connected
Moderately Connected
Moderately Connected
Moderately Connected
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
2
2
8
3
0
3
2
10
3
0
20
17
343
80
0
38
17
375
79
0
0
0
1
0
0
0
0
1
0
0
Strongly Connected
Strongly Connected
Strongly Connected
Strongly Connected
Strongly Connected
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
4
1
8
1
0
3
1
10
2
0
119
61
289
102
0
99
61
327
109
0
0
86
21
229
0
21
86
23
229
0
Total
Total
Total
Total
Total
No Risk
Low Risk
Moderate Risk
High Risk
Unknown
182
34
123
22
0
193
36
132
��
1
1169
323
1455
458
0
1209
320
1641
437
9
203
152
26
250
0
225
105
81
249
0
24
�Table 21: (2010 Assessment Pg. 25)
Ranked risks associated with catastrophic diseases of conservation populations by GMU. N indicates total
number of conservation populations. Stream populations are listed as km and lake populations are listed as
ha.
GMU
DiseaseRisk�
2010� N�
Dolores
Dolores
Dolores
Dolores
Dolores
Limited Risk
Minimal Risk
Moderate Risk
High Risk
Infected
1
5
4
0
0
3
10
6
1
0
4
32
19
0
0
11
46
28
9
0
0
0
0
0
0
0
3
7
0
0
Gunnison
Gunnison
Gunnison
Gunnison
Gunnison
Limited Risk
Minimal Risk
Moderate Risk
High Risk
Infected
16
11
9
0
0
16
13
9
0
0
71
85
40
0
0
69
111
40
0
0
0
0
6
0
0
0
0
6
0
0
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Limited Risk
Minimal Risk
Moderate Risk
High Risk
Infected
16
2
1
0
2
19
1
0
0
4
39
13
6
0
26
44
1
0
0
43
6
1
0
0
0
6
0
0
0
1
Lower Green
Lower Green
Lower Green
Lower Green
Lower Green
Limited Risk
Minimal Risk
Moderate Risk
High Risk
Infected
31
3
1
1
3
30
2
1
1
4
540
53
9
2
34
535
62
9
2
39
146
0
0
0
0
146
0
0
0
0
San Juan
San Juan
San Juan
San Juan
San Juan
Limited Risk
Minimal Risk
Moderate Risk
High Risk
Infected
10
5
0
0
0
18
5
0
0
0
59
22
0
0
0
103
22
0
0
0
1
0
0
0
0
1
0
0
0
0
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Limited Risk
Minimal Risk
Moderate Risk
High Risk
Infected
58
29
11
2
1
60
31
14
1
1
311
169
87
26
12
320
218
104
3
12
29
6
0
0
0
29
6
0
0
0
Upper Green
Upper Green
Upper Green
Upper Green
Upper Green
Limited Risk
Minimal Risk
Moderate Risk
High Risk
Infected
47
19
7
2
0
41
17
5
2
2
552
384
75
61
0
566
353
65
63
18
47
242
0
128
0
47
242
0
128
0
Yampa
Yampa
Yampa
Yampa
Yampa
Limited Risk
Minimal Risk
Moderate Risk
High Risk
Infected
36
19
5
2
2
38
19
5
2
2
255
311
61
1
42
296
309
61
1
41
2
16
0
0
0
2
16
0
0
0
Total
Total
Total
Total
Total
Limited Risk
Minimal Risk
Moderate Risk
High Risk
Infected
215
93
38
7
8
225
98
40
7
13
1831
1069
297
90
114
1944
1122
308
79
153
231
265
6
128
0
231
266
13
128
1
2015� N��
2010� km�
2015� km�
2010� ha�
2015� ha
��0OF�OFX� ���� �DPOTFSWBUJPO�QPQVMBUJPO�JO�UIF�:BNQB�(.6�UIBU�XBT�EFTJHOBUFE�BT��6OLOPXO��EJTFBTF�SJTL�JT�OPU�JODMVEFE�JO�UIF�
UBCMF�
25
�Table 22: (2010 Assessment Pg. 26)
Ranked risks associated with diseases for the conservation populations by degree of within population
connectivity (networks). N indicates total number of conservation populations. Stream populations are listed
as km and lake populations are listed as ha.
Connectivity
DiseaseRisk
2010
N
2015
N
2010
km
2015
km
2010
ha
2015
ha
Population Isolated
Population Isolated
Population Isolated
Population Isolated
Population Isolated
Limited Risk
Minimal Risk
Moderate Risk
High Risk
Infected
154
69
29
1
2
162
71
28
1
6
813
482
203
0
11
832
503
187
3
41
156
35
6
43
0
157
34
13
43
1
Population Isolated
Weakly Connected
Weakly Connected
Weakly Connected
Weakly Connected
Unknown
Limited Risk
Minimal Risk
Moderate Risk
High Risk
0
48
15
4
5
1
49
16
6
4
0
556
188
25
29
9
601
212
41
7
0
53
0
0
0
0
53
0
0
0
Weakly Connected
Weakly Connected
Moderately Connected
Moderately Connected
Moderately Connected
Infected
Unknown
Limited Risk
Minimal Risk
Moderate Risk
5
0
6
5
3
6
0
8
5
4
63
0
186
190
46
74
0
227
189
56
0
0
0
1
0
0
0
0
1
0
Moderately Connected
Moderately Connected
Moderately Connected
Strongly Connected
Strongly Connected
High Risk
Infected
Unknown
Limited Risk
Minimal Risk
0
1
0
7
4
0
1
0
6
6
0
39
0
276
210
0
38
0
284
218
0
0
0
21
229
0
0
0
21
231
Strongly Connected
Strongly Connected
Strongly Connected
Strongly Connected
Total
Moderate Risk
High Risk
Infected
Unknown
Limited Risk
2
1
0
0
215
2
2
0
0
225
23
61
0
0
1831
24
70
0
0
1944
0
86
0
0
230
0
86
0
0
231
Total
Total
Total
Total
Total
Minimal Risk
Moderate Risk
High Risk
Infected
Unknown
93
38
7
8
0
98
40
7
13
1
1070
297
90
113
0
1122
308
79
153
9
265
6
129
0
0
266
13
128
1
0
26
�Table 23: (2010 Assessment Pg. 31)
Population health ratings for stream-dwelling CRCT conservation populations. N indicates total number of
conservation populations. Populations are listed as km of stream habitat.
Indicator
Rating
2010 N
2015 N
2010 km
2015 km
Temporal Variability
Temporal Variability
Temporal Variability
Temporal Variability
Population Size
High
Moderate-High
Moderate-Low
Low
High
2
14
87
245
40
5
12
82
268
57
198
769
1412
1024
1224
456
656
1341
1162
1705
Population Size
Population Size
Population Size
Production Potential
Production Potential
Moderate-High
Moderate-Low
Low
High
Moderate-High
112
131
65
6
322
131
128
51
106
253
1215
656
308
46
2902
1052
653
205
648
2879
Production Potential
Production Potential
Population Connectivity
Population Connectivity
Population Connectivity
Moderate-Low
Low
High
Moderate-High
Moderate-Low
20
0
14
15
76
8
0
14
18
80
454
0
570
461
863
89
0
596
510
935
Population Connectivity
Composite Rating
Composite Rating
Composite Rating
Composite Rating
Low
High
Moderate-High
Moderate-Low
Low
243
9
100
196
43
255
29
209
127
2
1509
497
1701
1065
140
1575
1263
1860
477
15
27
�Table 24: (2010 Assessment Pg. 32)
Composite population health rating for stream-dwelling CRCT conservation populations by GMU. N
indicates total number of conservation populations. Populations are listed as km of stream habitat.
GMU
Rating
2010 N
2015 N
2010 km
2015 km
Dolores
Dolores
Dolores
Dolores
Gunnison
High
Moderate-High
Moderate-Low
Low
High
0
0
10
0
0
0
9
8
0
0
0
0
56
0
0
0
57
38
0
0
Gunnison
Gunnison
Gunnison
Lower Colorado
Lower Colorado
Moderate-High
Moderate-Low
Low
High
Moderate-High
4
28
3
0
5
18
19
0
0
9
52
138
7
0
50
151
69
0
0
66
Lower Colorado
Lower Colorado
Lower Green
Lower Green
Lower Green
Moderate-Low
Low
High
Moderate-High
Moderate-Low
14
1
3
14
17
13
0
5
24
7
31
2
173
308
146
22
0
298
300
41
Lower Green
San Juan
San Juan
San Juan
San Juan
Low
High
Moderate-High
Moderate-Low
Low
4
0
5
9
1
1
2
10
11
0
11
0
47
29
3
8
30
58
37
0
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
High
Moderate-High
Moderate-Low
Low
High
1
5
14
1
1
2
61
37
0
13
29
258
270
48
224
42
461
155
0
603
Upper Green
Upper Green
Upper Green
Yampa
Yampa
Moderate-High
Moderate-Low
Low
High
Moderate-High
31
28
11
1
16
34
17
1
7
44
617
182
49
71
368
392
63
8
292
374
Yampa
Yampa
Total
Total
Total
Moderate-Low
Low
High
Moderate-High
Moderate-Low
36
10
6
80
156
15
0
29
209
127
212
20
497
1700
1064
51
0
1263
1860
477
Total
Low
31
2
140
15
28
�Table 25: (2010 Assessment Pg. 33)
Composite population health rating for CRCT conservation populations by level of connectivity. N indicates
total number of conservation populations. Populations are listed as km of stream habitat.
Connectivity
Rating
2010 N
2015 N
2010 km
2015 km
Strongly Connected
Strongly Connected
Strongly Connected
Strongly Connected
Moderately Connected
High
Moderate-High
Moderate-Low
Low
High
6
5
3
0
1
8
6
0
0
12
372
169
29
0
71
536
60
0
0
450
Moderately Connected
Moderately Connected
Moderately Connected
Weakly Connected
Weakly Connected
Moderate-High
Moderate-Low
Low
High
Moderate-High
13
1
0
2
36
6
0
0
7
52
378
12
0
53
585
59
0
0
216
625
Weakly Connected
Weakly Connected
Population Isolated
Population Isolated
Population Isolated
Moderate-Low
Low
High
Moderate-High
Moderate-Low
34
4
0
46
158
21
0
2
145
106
201
23
0
569
823
95
0
62
1116
382
Population Isolated
Total
Total
Total
Total
Low
High
Moderate-High
Moderate-Low
Low
39
9
100
196
43
2
29
209
127
2
117
496
1701
1065
140
15
1263
1860
477
15
29
�Table 26: (2010 Assessment Pg. 33)
Number and percentage of designated CRCT conservation populations where various land uses were identified.
Multiple land uses may be associated with a single conservation population.
LandUse
2005 %
2005 N
2010 %
2010 N
2015 %
2015 N
Angling
De-watering
Fish Stocking (e.g.
non-native fish)
Hydroelectric,
water storage
and/or flood
control
Mining
71
16
4
202
45
12
60
15
5
216
54
17
56
14
4
214
54
16
1
3
1
3
1
3
4
12
3
12
3
12
None
Other (list in
comments)
Range (Livestock
grazing)
Recreation
(non-angling)
Roads
1
13
4
36
3
10
9
37
3
10
11
37
68
195
66
237
66
253
73
207
68
246
65
249
42
120
37
132
35
134
Timber Harvest
Unknown
24
1
67
3
21
3
74
10
19
3
74
12
30
�Table 27: (2010 Assessment Pg. 34)
Number of CRCT conservation populations that have had various types of conservation, restoration, and
management actions implemented to conserve them. Multiple actions may be associated with a single
conservation population.
Conservation Action
2005
2010
2015
Water lease/In-stream flow enhancement
Channel restoration
Bank stabilization
Riparian restoration
Diversion modification
20
9
12
7
5
27
13
13
20
8
27
14
14
22
8
Barrier removal
Barrier construction
Culvert replacement
Installation of fish screens to prevent loss
Fish ladders to provide access
3
51
4
3
1
10
65
27
4
1
9
66
3
4
2
Spawning habitat enhancement
Woody debris placement
Pool development
Increase irrigation efficiency
Grade control
8
3
10
1
3
14
8
11
1
4
15
7
12
1
5
In-stream cover habitat
Re-founding pure population
Riparian fencing
Physical removal of competing/hybridizing species
Chemical removal of competing/hybridizing species
8
54
17
41
35
8
62
26
54
51
9
60
27
55
48
Public outreach efforts at site (Interpretative site)
Population Restoration/Expansion
Population supplementation (e.g. to implement genetic swamping or to reduce
potential of bottle necking, etc.)
Special Angling Regulations
Land-use mitigation direction and requirements (e.g. Forest Plan direction,
regulation, permit req., coordination stipulations, etc)
6
24
0
16
59
0
12
71
6
140
60
143
96
8
95
32
43
44
32
80
39
96
39
136
Population covered by special protective mgt emphasis (e.g. Nat’l Park,
wilderness, special mgt area, conservation easement, etc.)
Other (List in comments)
None
31
�Appendix C: Population and habitat data for all CRCT populations
regardless of conservation status
Appendix C Tables -
32
�Appendix C Table 1: (2010 Assessment Pg. 69)
Historic and currently occupied CRCT stream habitat (km) by GMU and fourth-level Hydrologic Unit Code
(HUC) as of 2015. Percentage of historic range occupied is overestimated in several HUCs where CRCT have
been introduced outside their historic range. GMU’s are in bold, HUC8 in plain text.
GMU / HUC8
Historic
Range km
Current
Range km
% of
Historic
Range
Dolores
Lower Dolores
San Miguel
Upper Colorado-Kane Springs
Upper Dolores
1791
229
471
133
916
270
77
68
0
118
15
34
15
0
13
Westwater Canyon
Gunnison
East-Taylor
Lower Gunnison
North Fork Gunnison
42
4595
762
473
661
7
626
58
65
228
17
14
8
14
34
Tomichi
Uncompahange
Upper Gunnison
Lower Colorado
Escalante
707
268
1724
587
175
43
74
159
122
44
6
28
9
21
25
Fremont
Muddy
Lower Green
Ashley-Brush
Duchesne
266
146
3565
254
908
44
34
1407
140
482
17
23
40
55
53
Lower Green-Desolation Canyon
Lower Green-Diamond
Price
San Rafael
Strawberry
244
41
631
634
696
20
0
225
86
297
8
0
36
14
43
Willow
San Juan
Animas
Chinle
Lower San Juan-Four Corners
158
3392
724
269
255
157
297
174
0
0
99
9
24
0
0
Mancos
Middle San Juan
Montezuma
Piedra
Upper San Juan
191
249
35
597
1072
0
0
0
52
70
0
0
0
9
7
Upper Colorado
Blue
Colorado Headwaters
Colorado Headwaters-Plateau
Eagle
7240
759
3342
934
939
1022
95
346
270
96
14
12
10
29
10
241
92
38
Parachute-Roan
33
�(continued)
GMU / HUC8
Historic
Range km
Current
Range km
% of
Historic
Range
Roaring Fork
Upper Green
Big Sandy
Blacks Fork
1025
6826
488
1341
123
1290
0
260
12
19
0
19
Muddy
New Fork
Upper Green
Upper Green-Flaming Gorge Reservoir
Upper Green-Slate
535
584
2474
1197
112
56
0
620
354
0
10
0
25
30
0
Vermilion
Yampa
Little Snake
Lower White
Lower Yampa
93
4181
828
142
81
0
818
242
31
19
0
20
29
22
24
Muddy
Piceance-Yellow
Upper White
Upper Yampa
105
107
844
2075
33
13
156
323
31
12
18
16
34
�Appendix C Table 2: (2010 Assessment Pg. 71)
Genetic status of CRCT summarized as stream km and lake ha within each genetic status category for both 2010 and 2015. SusUn – suspected
unaltered, not tested; PotHyb – potentially altered, not tested; Mixed – mixed stock of altered and unaltered genetics. % Current range is the
percentage of the total CRCT current range included in each genetic category. % Historic range is the percentage of the total CRCT historic range
included in each genetic category and includes current range that is outside estimated historic range. % Historic range are not available for lake
populations.
Genetic
Status
Current
Range km
2015
Current
Range ha
2015
% Current
Range km
2015
% Current
Range ha
2015
% Historic
Range km
2015
Current
Range km
2010
Current
Range ha
2010
% Current
Range km
2010
% Current
Range ha
2010
% Historic
Range km
2010
Unaltered
90% - 99%
80% - 89%
< 80%
SusUn
1630
1127
165
410
536
228.2
127.7
0.6
131.3
161.8
28
19
3
7
9
19
11
0
11
13
5.1
3.5
0.5
1.3
1.7
1522
961
135
308
647
197
40
1
209
215
27
17
2
5
11
16.9
3.4
0.1
18.0
18.5
4.7
3.0
0.4
1.0
2.0
PotHyb
Mixed
Total
1810
174
5852
522.8
37.7
1210.1
31
3
100
43
3
100
5.6
0.5
18.2
1926
181
5680
501
0
1163
34
3
100
43.1
0.0
100.0
6.0
0.6
17.7
35
�Appendix C Table 3: (2010 Assessment Pg. 72)
CRCT genetic status for populations within each GMU in 2010 and 2015. Data are summarized as stream
km within each genetic status category. SusUn – suspected unaltered, not tested; PotHyb – potentially
hybridized, not tested; Mixed – mixed stock of altered and unaltered genetics.
GMU
Year
Unaltered
9099%
8089%
<80%
SusUn
Dolores
Dolores
Dolores
Gunnison
Gunnison
2010
2015
Change
2010
2015
34.7
25.9
-8.8
85.5
95.2
21.7
73.9
52.2
75.8
124.5
15.0
36.7
21.7
8.5
19.2
29.3
29.9
0.6
54.7
100.0
0.0
2.2
2.2
68.8
41.6
85.9
91.3
5.4
307.4
237.4
4.4
10.3
5.9
29.6
8.2
191.0
270.2
79.2
630.3
626.1
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
Change
2010
2015
Change
2010
9.7
80.6
82.9
2.3
411.2
48.7
0.0
0.0
0.0
89.1
10.7
0.0
0.0
0.0
11.7
45.3
17.9
18.0
0.1
100.6
-27.2
10.5
10.8
0.3
155.4
-70.0
10.5
10.4
-0.1
621.7
-21.4
0.0
0.0
0.0
0.0
-4.2
119.5
122.1
2.6
1389.7
Lower Green
Lower Green
San Juan
San Juan
San Juan
2015
Change
2010
2015
Change
431.0
19.8
106.6
109.5
2.9
116.4
27.3
19.7
37.7
18.0
25.5
13.8
0.0
0.0
0.0
123.9
23.3
4.5
4.5
0.0
117.2
-38.2
16.5
2.9
-13.6
593.2
-28.5
112.6
139.6
27.0
0.0
0.0
2.7
2.8
0.1
1407.2
17.5
262.6
297.0
34.4
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
Upper Green
2010
2015
Change
2010
2015
242.9
238.8
-4.1
320.3
337.0
197.9
329.0
131.1
141.2
177.9
11.3
11.0
-0.3
36.4
40.7
42.7
8.6
-34.1
93.1
120.0
145.9
79.6
-66.3
264.4
193.6
398.4
312.0
-86.4
344.6
315.0
37.2
42.5
5.3
96.7
105.4
1076.3
1021.5
-54.8
1296.7
1289.6
Upper Green
Yampa
Yampa
Yampa
Change
2010
2015
Change
16.7
397.3
310.0
-87.3
36.7
120.9
267.3
146.4
4.3
38.3
31.6
-6.7
26.9
5.2
5.3
0.1
-70.8
94.9
87.8
-7.1
-29.6
130.8
111.1
-19.7
8.7
4.5
4.5
0.0
-7.1
791.9
817.6
25.7
36
PotHyb Mixed
Total
�Appendix C Table 4: (2010 Assessment Pg. 72)
Genetic status of lake populations of CRCT. Data are summarized as lake ha within each genetic status
category. SusUn – suspected unaltered, not tested; PotHyb – potentially hybridized, not tested; Mixed –
mixed stock of altered and unaltered genetics.
GMU
Year
Unaltered
9099%
8089%
<80%
SusUn
Dolores
Dolores
Dolores
Gunnison
Gunnison
2010
2015
Change
2010
2015
0.0
9.3
9.3
15.0
14.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
5.0
5.0
0.0
0.0
0.0
3.0
3.0
0.0
0.0
0.0
97.0
0.0
0.0
9.3
9.3
120.0
22.5
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
Change
2010
2015
Change
2010
-0.5
7.0
7.7
0.7
106.0
0.0
0.0
0.0
0.0
12.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
70.0
0.0
0.0
0.0
0.0
239.0
-97.0
0.0
0.0
0.0
0.0
-97.5
7.0
7.7
0.7
427.0
Lower Green
Lower Green
San Juan
San Juan
San Juan
2015
Change
2010
2015
Change
124.4
18.4
1.0
2.8
1.8
0.0
-12.0
1.0
0.0
-1.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
63.3
-6.7
0.0
0.0
0.0
276.2
37.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
463.9
36.9
2.0
2.8
0.8
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
Upper Green
2010
2015
Change
2010
2015
41.0
40.8
-0.2
26.0
27.2
2.0
2.1
0.1
25.0
119.0
0.0
0.0
0.0
0.0
0.0
39.0
0.0
-39.0
32.0
0.0
6.0
6.5
0.5
118.0
71.4
10.0
10.1
0.1
248.0
232.2
0.0
37.7
37.7
0.0
0.0
98.0
97.2
-0.8
449.0
449.7
Upper Green
Yampa
Yampa
Yampa
Change
2010
2015
Change
1.2
2.0
1.6
-0.4
94.0
0.0
6.6
6.6
0.0
1.0
0.6
-0.4
-32.0
138.0
131.3
-6.7
-46.6
16.0
15.5
-0.5
-15.8
1.0
1.3
0.3
0.0
0.0
0.0
0.0
0.7
158.0
157.0
-1.0
37
PotHyb Mixed
Total
�Appendix C Table 5: (2010 Assessment Pg. 75)
Historic Range km is Historically occupied stream habitat. Current Range km within Historic is 2015 occupied
stream within historic habitat. ConPop Range km within Historic is length of stream habitat within historic
habitat that was occupied by conservation populations in 2015. Current Range ha is 2015 occupied lake
habitat in ha. ConPop Range ha is area of lake habitat occupied by conservation populations in 2015.
Elevation
Range
Historic
Range km
Current
Range km
within
Historic
% Historic
Range km
Currently
Occupied
ConPop
Range km
within
Historic
Current
Range ha
ConPop
Range ha
< 1,400
1,400-1,600
1,600-1,800
1,800-2,000
2,000-2,200
4.9
140.1
497.2
3878.0
5945.8
0.0
0.0
0.0
68.6
507.7
0.0
0.0
0.0
1.8
8.5
0.0
0.0
0.0
26.1
257.2
0.0
0.0
0.0
0.0
11.7
0.0
0.0
0.0
0.0
11.7
2,200-2,400
2,400-2,600
2,600-2,800
2,800-3,000
3,000-3,200
6354.0
6155.2
4353.6
2795.5
1415.2
924.6
1302.2
1042.1
583.6
513.4
14.6
21.2
23.9
20.9
36.3
505.5
906.2
558.7
435.2
376.3
2.8
0.0
302.9
203.2
258.8
2.8
0.0
302.4
68.1
78.5
3,200-3,400
3,400-3,600
3,600-3,800
> 3,800
Total
519.3
98.6
17.0
2.3
32176.8
205.8
43.0
1.4
1.5
5194.0
39.6
43.6
8.1
65.6
16.1
120.7
19.7
0.0
0.0
3205.7
338.0
10.6
1.2
9.7
1138.9
165.1
2.9
1.2
6.7
639.3
38
�Appendix C Table 6: (2010 Assessment Pg. 77)
Density (number of fish/mile) of sexually mature (> 15 centimeters in total length) Colorado River cutthroat
trout occupying stream habitat (length in kilometers, km) compared by state between 2010 and 2015, including
percentage change in stream length over time.
State
Density
Current Range
km 2015
Current Range
km 2010
% Change
Colorado
Colorado
Colorado
Colorado
Colorado
0 to 50 fish/mi
50 to 150 fish/mi
151 to 400 fish/mi
> 400 fish/mi
Unknown
537.2
764.3
660.0
226.8
598.4
618.6
687.4
581.7
200.2
544.9
-13.2
11.2
13.5
13.3
9.8
Colorado
Utah
Utah
Utah
Utah
Total
0 to 50 fish/mi
50 to 150 fish/mi
151 to 400 fish/mi
> 400 fish/mi
2786.8
767.3
295.1
382.7
263.5
2632.8
687.4
333.9
323.2
268.7
5.8
11.6
-11.6
18.4
-2.0
Utah
Utah
Wyoming
Wyoming
Wyoming
Unknown
Total
0 to 50 fish/mi
50 to 150 fish/mi
151 to 400 fish/mi
297.4
2006.0
240.9
401.6
194.8
378.6
1991.8
224.0
323.9
230.3
-21.5
0.7
7.6
24.0
-15.4
Wyoming
Wyoming
Wyoming
> 400 fish/mi
Unknown
Total
46.5
174.9
1058.7
102.5
184.4
1065.1
-54.7
-5.2
-0.6
39
�Appendix C Table 7: (2010 Assessment Pg. 78)
Density (number of fish/mile) of sexually mature (>15 centimeters in total length) Colorado River cutthroat
trout occupying stream habitat (length in kilometers, km) for each Geographic Management Unit (GMU)
compared between 2010 and 2015, including percent change in stream length over time.
GMU
Density
Current Range
km 2015
Current Range
km 2010
% Change
Dolores
Dolores
Dolores
Dolores
Dolores
0 to 50 fish/mi
50 to 150 fish/mi
151 to 400 fish/mi
> 400 fish/mi
Unknown
32.7
61.4
94.9
14.1
67.2
37.5
48.2
61.3
11.9
32.2
-12.7
27.3
54.7
18.8
108.7
Dolores
Gunnison
Gunnison
Gunnison
Gunnison
Total
0 to 50 fish/mi
50 to 150 fish/mi
151 to 400 fish/mi
> 400 fish/mi
270.3
111.6
157.4
131.0
67.0
191.1
141.9
134.2
118.3
39.8
41.4
-21.3
17.3
10.7
68.3
Gunnison
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Unknown
Total
0 to 50 fish/mi
50 to 150 fish/mi
151 to 400 fish/mi
159.1
626.1
19.9
27.9
19.1
166.4
600.6
19.6
28.4
18.4
-4.4
4.2
1.5
-1.9
3.7
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
Lower Green
> 400 fish/mi
Unknown
Total
0 to 50 fish/mi
50 to 150 fish/mi
48.7
6.6
122.1
686.1
219.8
50.6
3.4
120.4
620.3
247.0
-3.7
92.9
1.4
10.6
-11.0
Lower Green
Lower Green
Lower Green
Lower Green
San Juan
151 to 400 fish/mi
> 400 fish/mi
Unknown
Total
0 to 50 fish/mi
200.3
103.3
197.7
1407.3
102.2
162.0
95.1
262.2
1386.6
102.4
23.7
8.7
-24.6
1.5
-0.2
San Juan
San Juan
San Juan
San Juan
San Juan
50 to 150 fish/mi
151 to 400 fish/mi
> 400 fish/mi
Unknown
Total
69.9
39.3
22.6
62.9
296.9
50.7
33.4
25.8
43.2
255.5
37.8
17.6
-12.5
45.7
16.2
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
0 to 50 fish/mi
50 to 150 fish/mi
151 to 400 fish/mi
> 400 fish/mi
Unknown
181.9
249.7
216.6
118.0
255.2
217.7
258.8
173.1
119.8
269.2
-16.4
-3.5
25.1
-1.5
-5.2
Upper Colorado
Upper Green
Upper Green
Upper Green
Upper Green
Total
0 to 50 fish/mi
50 to 150 fish/mi
151 to 400 fish/mi
> 400 fish/mi
1021.5
219.1
379.8
331.5
134.7
1038.6
203.3
313.4
326.4
202.1
-1.6
7.8
21.2
1.6
-33.4
Upper Green
Upper Green
Unknown
Total
224.5
1289.6
251.4
1296.6
-10.7
-0.5
40
�(continued)
GMU
Density
Current Range
km 2015
Current Range
km 2010
% Change
Yampa
Yampa
Yampa
0 to 50 fish/mi
50 to 150 fish/mi
151 to 400 fish/mi
191.9
295.3
204.9
187.3
264.7
232.2
2.5
11.6
-11.7
Yampa
Yampa
Yampa
> 400 fish/mi
Unknown
Total
28.2
97.3
817.7
26.2
76.9
787.3
7.8
26.5
3.9
41
�Appendix C Table 8: (2010 Assessment Pg. 80)
Habitat quality for Colorado River cutthroat trout occupying stream habitat (length in kilometers, km)
compared by state between 2010 and 2015, including percent change in stream length over time.
State
Habitat
Current Range
km 2015
Current Range
km 2010
% Change
Colorado
Colorado
Colorado
Colorado
Colorado
Excellent
Good
Fair
Poor
Unknown
417.4
1493.6
678.0
84.9
112.9
400.8
1419.9
613.4
77.8
120.9
4.1
5.2
10.5
9.2
-6.6
Colorado
Utah
Utah
Utah
Utah
Total
Excellent
Good
Fair
Poor
2786.8
329.8
801.7
668.4
156.2
2632.8
336.9
851.1
615.5
138.2
5.8
-2.1
-5.8
8.6
13.0
Utah
Utah
Wyoming
Wyoming
Wyoming
Unknown
Total
Excellent
Good
Fair
50.0
2006.0
76.1
329.7
569.0
50.3
1992.0
78.2
379.6
483.6
-0.5
0.7
-2.6
-13.1
17.7
Wyoming
Wyoming
Wyoming
Poor
Unknown
Total
70.3
13.6
1058.7
76.7
37.0
1055.1
-8.4
-63.2
0.3
42
�Appendix C Table 9: (2010 Assessment Pg. 81)
Habitat quality for Colorado River cutthroat trout occupied stream habitat (length in kilometers, km) for
each Geographic Management Unit (GMU) compared between 2010 and 2015, including percent change of
stream length over time.
GMU
Habitat
Current Range
km 2015
Current Range
km 2010
% Change
Dolores
Dolores
Dolores
Dolores
Dolores
Excellent
Good
Fair
Poor
Unknown
9.4
156.6
104.3
0.0
0.0
0.0
88.4
102.7
0.0
0.0
100.0
77.1
1.6
0.0
0.0
Dolores
Gunnison
Gunnison
Gunnison
Gunnison
Total
Excellent
Good
Fair
Poor
270.3
81.7
387.2
137.8
6.8
191.1
77.7
376.6
121.7
6.8
41.4
5.2
2.8
13.2
0.4
Gunnison
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Unknown
Total
Excellent
Good
Fair
12.5
626.1
21.4
65.3
24.6
17.8
600.6
21.7
67.7
23.3
-29.6
4.2
-1.4
-3.6
5.8
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
Lower Green
Poor
Unknown
Total
Excellent
Good
10.8
0.0
122.1
73.0
606.4
7.7
0.0
120.4
37.9
663.8
40.3
0.0
1.4
92.6
-8.7
Lower Green
Lower Green
Lower Green
Lower Green
San Juan
Fair
Poor
Unknown
Total
Excellent
546.4
133.8
47.6
1407.3
64.3
521.4
118.7
47.9
1389.7
74.9
4.8
12.7
-0.5
1.3
-14.1
San Juan
San Juan
San Juan
San Juan
San Juan
Good
Fair
Poor
Unknown
Total
171.6
60.9
0.0
0.0
296.9
132.9
47.6
0.0
0.0
255.4
29.2
28.0
0.0
0.0
16.2
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Upper Colorado
Excellent
Good
Fair
Poor
Unknown
210.9
412.2
291.8
28.2
78.5
196.1
455.9
275.8
29.3
81.5
7.6
-9.6
5.8
-3.9
-3.7
Upper Colorado
Upper Green
Upper Green
Upper Green
Upper Green
Total
Excellent
Good
Fair
Poor
1021.5
244.1
406.2
541.5
81.8
1038.6
288.3
435.1
445.5
88.5
-1.6
-15.3
-6.6
21.5
-7.5
Upper Green
Upper Green
Unknown
Total
16.0
1289.6
39.3
1296.7
-59.3
-0.5
43
�(continued)
GMU
Habitat
Current Range
km 2015
Current Range
km 2010
% Change
Yampa
Yampa
Yampa
Excellent
Good
Fair
118.5
419.5
208.0
119.2
430.3
174.5
-0.6
-2.5
19.2
Yampa
Yampa
Yampa
Poor
Unknown
Total
49.9
21.8
817.7
41.7
21.6
787.3
19.8
1.1
3.9
Appendix C Table 10: (2010 Assessment Pg. 83)
Stream width (feet, ft) for Colorado River cutthroat trout occupied stream habitat (length in kilometers, km)
compared by state between 2010 and 2015, including percent change in stream length over time.
State
Width
Current Range
km 2015
Current Range
km 2010
% Change
Colorado
Colorado
Colorado
Colorado
Colorado
< 5 feet
5 to 10 feet
10 to 15 feet
15 to 20 feet
20 to 25 feet
311.5
1147.7
634.5
316.7
215.3
267.7
1149.1
584.7
273.8
201.5
16.3
-0.1
8.5
15.7
6.9
Colorado
Colorado
Colorado
Utah
Utah
> 25 feet
Unknown
Total
< 5 feet
5 to 10 feet
22.8
138.3
2786.8
382.6
720.5
23.2
133.2
2633.2
388.7
709.8
-1.6
3.9
5.8
-1.6
1.5
Utah
Utah
Utah
Utah
Utah
10 to 15 feet
15 to 20 feet
20 to 25 feet
> 25 feet
Unknown
270.5
241.6
146.8
141.3
102.7
269.6
264.6
186.1
68.6
103.6
0.3
-8.7
-21.1
106.0
-0.8
Utah
Wyoming
Wyoming
Wyoming
Wyoming
Total
< 5 feet
5 to 10 feet
10 to 15 feet
15 to 20 feet
2006.0
221.0
367.2
78.9
99.3
1991.0
233.8
393.2
99.3
88.0
0.8
-5.5
-6.6
-20.6
12.9
Wyoming
Wyoming
Wyoming
Wyoming
20 to 25 feet
> 25 feet
Unknown
Total
178.0
89.8
24.5
1058.7
141.8
50.7
48.2
1055.0
25.5
77.1
-49.1
0.4
44
�Appendix C Table 11: (2010 Assessment Pg. 84)
Stream width for Colorado River cutthroat trout occupied stream habitat (length in kilometers, km) for each
Geographic Management Unit (GMU) compared between 2010 and 2015, including percent change in stream
length over time.
GMU
Width
Current Range
km 2015
Current Range
km 2010
% Change
Dolores
Dolores
Dolores
Dolores
Dolores
< 5 feet
5 to 10 feet
10 to 15 feet
15 to 20 feet
20 to 25 feet
35.3
111.6
72.9
50.6
0.0
32.9
105.7
39.3
13.2
0.0
7.3
5.5
85.4
283.1
0.0
Dolores
Dolores
Dolores
Gunnison
Gunnison
> 25 feet
Unknown
Total
< 5 feet
5 to 10 feet
0.0
0.0
270.3
77.9
211.8
0.0
0.0
191.1
53.5
211.3
0.0
0.0
41.4
45.6
0.3
Gunnison
Gunnison
Gunnison
Gunnison
Gunnison
10 to 15 feet
15 to 20 feet
20 to 25 feet
> 25 feet
Unknown
161.2
81.2
74.9
0.0
19.1
159.3
82.2
75.6
0.0
18.9
1.2
-1.3
-1.0
0.0
1.0
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Total
< 5 feet
5 to 10 feet
10 to 15 feet
15 to 20 feet
626.1
15.1
52.7
40.7
0.8
600.8
10.2
48.5
48.1
0.8
4.2
47.9
8.6
-15.4
-1.7
Lower Colorado
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
20 to 25 feet
> 25 feet
Unknown
Total
< 5 feet
12.9
0.0
0.0
122.1
280.4
12.8
0.0
0.0
120.4
290.8
0.6
0.0
0.0
1.4
-3.6
Lower Green
Lower Green
Lower Green
Lower Green
Lower Green
5 to 10 feet
10 to 15 feet
15 to 20 feet
20 to 25 feet
> 25 feet
462.3
170.3
150.7
106.4
134.4
455.2
161.1
172.2
145.4
61.4
1.6
5.7
-12.5
-26.8
118.9
Lower Green
Lower Green
San Juan
San Juan
San Juan
Unknown
Total
< 5 feet
5 to 10 feet
10 to 15 feet
102.7
1407.3
8.5
137.0
39.7
103.6
1389.7
8.4
134.0
26.8
-0.8
1.3
1.2
2.3
48.2
San Juan
San Juan
San Juan
San Juan
San Juan
15 to 20 feet
20 to 25 feet
> 25 feet
Unknown
Total
48.4
63.2
0.0
0.0
296.9
25.3
61.0
0.0
0.0
255.5
91.3
3.7
0.0
0.0
16.2
Upper Colorado
Upper Colorado
< 5 feet
5 to 10 feet
135.4
478.1
131.6
486.9
2.9
-1.8
45
�(continued)
GMU
Width
Current Range
km 2015
Current Range
km 2010
% Change
Upper Colorado
Upper Colorado
Upper Colorado
10 to 15 feet
15 to 20 feet
20 to 25 feet
201.4
75.3
33.4
195.6
92.9
29.5
3.0
-18.9
13.1
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
Upper Green
> 25 feet
Unknown
Total
< 5 feet
5 to 10 feet
22.8
75.0
1021.5
254.8
429.1
23.2
79.1
1038.8
268.4
462.0
-1.6
-5.2
-1.7
-5.1
-7.1
Upper Green
Upper Green
Upper Green
Upper Green
Upper Green
10 to 15 feet
15 to 20 feet
20 to 25 feet
> 25 feet
Unknown
113.1
168.4
205.5
94.2
24.5
134.6
158.4
169.7
55.4
48.2
-16.0
6.3
21.1
70.0
-49.1
Upper Green
Yampa
Yampa
Yampa
Yampa
Total
< 5 feet
5 to 10 feet
10 to 15 feet
15 to 20 feet
1289.6
107.6
352.8
184.5
82.3
1296.7
94.4
349.5
188.7
81.5
-0.5
14.0
0.9
-2.2
1.0
Yampa
Yampa
Yampa
Yampa
20 to 25 feet
> 25 feet
Unknown
Total
43.9
2.5
44.2
817.7
35.5
2.4
35.2
787.2
23.5
2.9
25.6
3.9
Appendix C Table 12: (2010 Assessment Pg. 85)
Currently-occupied Colorado River cutthroat trout stream (length in kilometers, km) and lake habitat (area
in hectares, ha) by state for which records of stocking with non-native salmonids has not (No Stocking) or
has (Non-Native Stocking) occurred and comparison to 2010 data.
State
Stocking
Current
Range
km 2015
Current
Range
km 2010
%
Change
km
Current
Range
ha 2015
Current
Range
ha 2010
%
Change
ha
Colorado
Colorado
Colorado
Utah
Utah
No Stocking
Non-Native Stocking
Total
No Stocking
Non-Native Stocking
1328.9
1457.9
2786.8
1033.8
972.2
1164
1469
2633
1019
972
14.2
-0.8
5.8
1.4
0.0
131.2
157.6
288.8
106.6
572.3
82
198
280
75
565
60.0
-20.4
3.1
42.1
1.3
Utah
Wyoming
Wyoming
Wyoming
Total
No Stocking
Non-Native Stocking
Total
2006.0
457.1
601.6
1058.7
1991
456
599
1055
0.8
0.2
0.4
0.4
678.9
242.4
0.0
242.4
640
242
0
242
6.1
0.2
0.0
0.2
46
�Appendix C Table 13: (2010 Assessment Pg. 86)
Currently-occupied Colorado River cutthroat trout stream (length in kilometers, km) and lake (area in
hectares, ha) habitat by Geographic Management Unit (GMU) for which records of stocking with non-native
salmonids has not (No Stocking) or has (Non-Native stocking) occurred and comparison to 2010 data.
GMU
Stocking
Current
Range
km
2015
Current
Range
km
2010
%
Change
km
Current
Range
ha
2015
Current
Range
ha
2010
%
Change
ha
Dolores
Dolores
Dolores
Gunnison
Gunnison
No Stocking
Non-Native Stocking
Total
No Stocking
Non-Native Stocking
130.8
139.5
270.3
224.3
401.8
111
80
191
199
402
17.9
74.4
41.5
12.7
-0.1
9.3
0.0
9.3
14.5
8.1
0.0
0.0
0.0
14.0
8.0
100.0
0.0
100.0
3.5
0.6
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
Total
No Stocking
Non-Native Stocking
Total
No Stocking
626.1
67.4
54.8
122.1
645.8
601
62
58
120
640
4.2
8.7
-5.6
1.8
0.9
22.5
0.0
7.7
7.7
10.3
22.0
0.0
7.0
7.0
10.0
2.4
0.0
9.4
9.4
2.8
Lower Green
Lower Green
San Juan
San Juan
San Juan
Non-Native Stocking
Total
No Stocking
Non-Native Stocking
Total
761.5
1407.3
170.4
126.5
296.9
750
1390
131
124
255
1.5
1.2
30.1
2.0
16.4
453.7
463.9
1.6
1.2
2.8
416.0
426.0
0.5
1.2
1.7
9.1
8.9
222.2
-2.8
63.4
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
Upper Green
No Stocking
Non-Native Stocking
Total
No Stocking
Non-Native Stocking
487.2
534.4
1021.5
592.2
697.4
444
595
1039
615
682
9.7
-10.2
-1.7
-3.7
2.3
80.2
17.0
97.2
338.7
111.0
43.0
56.0
99.0
307.0
141.0
86.6
-69.6
-1.8
10.3
-21.3
Upper Green
Yampa
Yampa
Yampa
Total
No Stocking
Non-Native Stocking
Total
1289.6
501.7
316.0
817.7
1297
438
350
788
-0.6
14.6
-9.7
3.8
449.7
25.6
131.3
157.0
448.0
24.0
133.0
157.0
0.4
6.7
-1.2
0.0
47
�Appendix C Table 14: (2010 Assessment Pg. 87)
Currently-occupied Colorado River cutthroat trout stream (length in kilometers, km) and lake habitat (area
in hectares, ha) by state for which non-native salmonids have or have not been documented sympatric with
CRCT and comparison to 2010 data. % Change column is the comparison of the kilometers of stream or
hectares of lake with or without non-natives in 2015 compared to 2010.
State
Presence
Current
Range km
2015
Current
Range km
2010
Colorado
Non-Natives
Absent
Non-Natives
Present
Total
Non-Natives
Absent
Non-Natives
Present
1172.6 (42.1%)
1084 (41.2%)
8.2
1614.2 (57.9%)
1549 (58.8%)
2786.8
801.7 (40%)
Total
Non-Natives
Absent
Non-Natives
Present
Total
Colorado
Colorado
Utah
Utah
Utah
Wyoming
Wyoming
Wyoming
Current
Range ha
2010
%
Change
ha
134.6 (46.6%)
124 (44.4%)
8.5
4.2
154.2 (53.4%)
155 (55.6%)
-0.5
2633
773 (38.8%)
5.8
3.7
288.8
71.2 (10.5%)
279
71 (11.1%)
3.5
0.3
1204.3 (60%)
1218 (61.2%)
-1.1
607.7 (89.5%)
569 (88.9%)
6.8
2006
462.2 (43.7%)
1991
509 (48.2%)
0.8
-9.2
678.9
0 (0%)
640
14 (5.8%)
6.1
-100.0
596.5 (56.3%)
546 (51.8%)
9.3
242.4 (100%)
229 (94.2%)
5.9
1058.7
1055
0.4
242.4
243
-0.2
48
% Current
Change Range ha
km 2015
�Appendix C Table 15: (2010 Assessment Pg. 88)
Colorado River cutthroat trout occupied stream (length in kilometers, km) and lake habitat (area in
hectares, ha) by Geographic Management Unit (GMU) for which non-native salmonids have or have not been
documented sympatric. Comparisons (% Change) are made between 2015 and 2010 for stream km and lake
ha.
GMU
Presence
Current
Range km
2015
Current
Range km
2010
Dolores
Non-Natives
Absent
Non-Natives
Present
Total
Non-Natives
Absent
Non-Natives
Present
87.9 (32.5%)
78 (40.8%)
12.7
182.4 (67.5%)
113.1 (59.2%)
270.3
173.3 (27.7%)
Dolores
Dolores
Gunnison
Gunnison
Gunnison
Lower Colorado
Lower Colorado
Lower Colorado
Lower Green
Lower Green
Lower Green
San Juan
San Juan
San Juan
Upper Colorado
Upper Colorado
Upper Colorado
Upper Green
Upper Green
Upper Green
Yampa
Yampa
Yampa
Current
Range ha
2010
%
Change
ha
9 (97.1%)
0 (0%)
100.0
61.3
0.3 (2.9%)
0 (0%)
100.0
191.1
139.9 (23.3%)
41.4
23.9
9.3
19.5 (86.7%)
0
19.5 (86.7%)
100.0
0.2
452.8 (72.3%)
460.8 (76.7%)
-1.7
3 (13.3%)
3 (13.3%)
0.2
Total
Non-Natives
Absent
Non-Natives
Present
Total
Non-Natives
Absent
626.1
67 (54.9%)
600.7
65.1 (54.1%)
4.2
3.0
22.5
2 (25.8%)
22.5
1.2 (17.4%)
0.2
64.4
55.1 (45.1%)
55.3 (45.9%)
-0.4
5.7 (74.2%)
5.7 (82.6%)
-0.3
122.1
511 (36.3%)
120.4
489.4 (35.2%)
1.4
4.4
7.7
15.8 (3.4%)
6.9
15.8 (3.7%)
11.0
0.1
Non-Natives
Present
Total
Non-Natives
Absent
Non-Natives
Present
Total
896.3 (63.7%)
900.3 (64.8%)
-0.4
448.1 (96.6%)
410.9 (96.3%)
9.1
1407.3
157.3 (53%)
1389.7
133.7 (52.3%)
1.3
17.7
463.9
2.8 (100%)
426.7
1.7 (100%)
8.7
63.4
139.5 (47%)
121.8 (47.7%)
14.6
0 (0%)
0 (0%)
0.0
296.9
255.5
16.2
2.8
1.7
450.6 (44.1%)
429.5 (41.3%)
4.9
84.3 (86.7%)
84.3 (85.3%)
0.0
571 (55.9%)
609.2 (58.7%)
-6.3
13 (13.3%)
14.5 (14.7%)
-10.7
1021.5
501.3 (38.9%)
1038.7
549.2 (42.4%)
-1.7
-8.7
97.2
53.5 (11.9%)
98.8
67.3 (15%)
-1.6
-20.6
788.3 (61.1%)
747.5 (57.6%)
5.5
396.2 (88.1%)
381.4 (85%)
3.9
1289.6
488.1 (59.7%)
1296.7
483.1 (61.4%)
-0.5
1.0
449.7
19 (12.1%)
448.7
19 (12.1%)
0.2
0.1
329.6 (40.3%)
304.3 (38.6%)
8.3
137.9 (87.9%)
137.9 (87.9%)
0.0
817.7
787.4
3.8
157
156.9
0.0
Non-Natives
Absent
Non-Natives
Present
Total
Non-Natives
Absent
Non-Natives
Present
Total
Non-Natives
Absent
Non-Natives
Present
Total
49
% Current
Change Range ha
km 2015
63.4
�Appendix C Table 16: (2010 Assessment Pg. 89)
Colorado River cutthroat trout (CRCT) occupied stream (length in kilometers, km) and lake (area in hectare,
ha) habitat within the various land ownership boundaries by Geographic Management Unit (GMU) in 2015.
Percentage represent amount of total CRCT habitat occupied by land ownership.
GMU
BLM
PVT
STATE
USFS
NonWilderness
USFS
Wilderness
Tribal
NPS
DOD
Dolores
11� km
��ha
40.9 km
3 ha
4.1 km
��ha
21.3 km
0 ha
4� km�
��ha
54.8 km
2.5 ha
80� km�
��ha
8.7� km�
��ha
325 km
11.7 ha
32.6 km
1.6 ha
23.8 km
6.7 ha
3.2� km
��ha
–
6.1� km
� 0� ha�
187.7� km�
��ha
–
o
–
–
–
–
–
–
–
–
163.1 km
218.2 ha
44.5� km�
��ha
172.7 km
0 ha
–
0� km�
��ha
–
–
99.8 km
3 ha
144� km�
��ha
51.6 km
0 ha
376.7
(6.4%)
6
(0.5%)
188.2 km
38.6 ha
337.9 km
0 ha
188� km�
��ha
1215.2
(20.8%)
54.4
(4.1%)
18.8 km
0 ha
57.3 km
0 ha
31.1 km
0 ha
275
(4.7%)
6.7
(0.5%)
174.6� km
��ha
314.2 km
14.5 ha
109.4� km�
109.4� ha�
584.4� km�
234.1� ha�
215.8� km�
1.1� ha�
452.6� km�
8.2� ha�
600.7� km�
343.2� ha�
457.5� km�
��ha
2909.2
(49.7%)
710.5
(54.2%)
205.9 km
23.4 ha
149.6 km
106.5 ha
89.5 km 157
ha
846.4
(14.5%)
510.1
(38.9%)
–
–
30.7 km
24.1 ha
–
25.4 km
0 ha
–
–
–
–
172.7
(3%)
0
0%)
30.7
(0.5%)
24.1
(1.8%)
25.4
(0.4%)
0�
(0%)
Gunnison
Lower Colorado
Lower Green
San Juan
Upper Colorado
Upper Green
Yampa
Total km
Total ha
140.8 km
0 ha
–
50
–
�Appendix C Table 17: (2010 Assessment Pg. 90)
Change in Colorado River cutthroat trout (CRCT) occupied stream habitat (length in kilometers, km) and
lake (area in hectare, ha) within land ownership boundaries by Geographic Management Unit (GMU) between
2010 and 2015.
GMU
BLM
PVT
STATE
USFS
NonWilderness
USFS
Wilderness
Tribal
NPS
DOD
Dolores
-0.9 km
0 ha
10.6 km
0.2 ha
-0.1 km
0 ha
-1� km�
��ha
2� km�
��ha
40.2 km
100 ha
2.3� km�
��ha
-1.5 km
0 ha
0.1 km
-0.3 ha
13 km
-3.1� ha
0.8 km
100 ha
1.2� km�
��ha
–
78.4� km�
��ha
-3.7� km�
0.9�ha
–
–
–
–
–
–
–
–
–
–
4.5� km�
����ha
-0.9� km�
0�ha
-1.2 km
0 ha
–
-100 km
0 ha
–
–
-23.8 km
-0.9� ha�
0.1� km�
0�ha
-0.9� km
0 ha
-14�
(-10.9%)
-0.7
(-0.2%)
-4.6� km�
100� ha�
17.7� km�
0� ha�
7.9� km�
0�ha
75.1
(58.6%)
196.6
(48%)
1.3� km�
��ha
17.2 km
0 ha
-0.6 km
0 ha
19.5
(15.2%)
100
(24.4%)
53.3� km�
��ha
9.3� km�
�����ha
0� km
0� ha
12.4� km�
17.9� ha
21.4� km�
100�ha
0.2� km�
-0.2�ha
-9.9� km�
0.3�ha
2.5� km�
-100�ha
64.4
(50.3%)
17.9
(4.4%)
-2� km������������������o
0� ha������
0� km�
–
0� ha
7.5� km�
–
����ha
83.8
-1.2
(65.4%)
(-0.9%)
101.6
0
(24.8%)
0%)
0.5 km
-6 ha
–
0� km�
��ha
–
–
–
-99.5�
(-77.7%)
-6
(-1.5%)
0�
(0%)
0�
(0%)
Gunnison
Lower Colorado
Lower Green
San Juan
Upper Colorado
Upper Green
Yampa
Total km
Total ha
-0.4 km
0 ha
–
51
–
�Appendix C Figures Appendix C Figure 1: (2010 Assessment Pg. 68)
Current range (blue) and historic range (dark gray) of CRCT as of 2015. Conservation populations are also
shown in red.
52
�Appendix C Figure 2: (2010 Assessment Pg. 73)
Genetic status of currently occupied Colorado River cutthroat trout (CRCT) stream segments. Waters
designated as “Other” are comprised of all genetic results less than 90% pure, untested and suspected
hybridized, and mixed stocks of unaltered and hybridized CRCT.
53
�Appendix C Figure 3: (2010 Assessment Pg. 75)
Kilometers (km) of stream habitat occupied by Colorado River cutthroat trout historically (light blue),
currently (dark blue), and by conservation populations (>90% genetic purity) (green) in relation to elevation
range (meters). Habitats are presented as a fraction of total historic stream habitat (km).
8000
6000
Type
ConPop Range km within Historic
4000
Current Range km within Historic
Historic Range km
2000
1, < 1
40 ,4
0 0
1, −1 0
60 ,6
0 0
1, −1 0
80 ,8
0 0
2, −2 0
00 ,0
0 0
2, −2 0
20 ,2
0 0
2, −2 0
40 ,4
0 0
2, −2 0
60 ,6
0 0
2, −2 0
80 ,8
0 0
3, −3 0
00 ,0
0 0
3, −3 0
20 ,2
0 0
3, −3 0
40 ,4
0 0
3, −3 0
60 ,6
0− 00
3,
8
> 00
3,
80
0
0
54
�Appendix C Figure 4a: (2010 Assessment Pg. 77)
Elevation range (meters, m) of current occupied lake habitat (in hectares, ha) (light blue) of Colorado River
cutthroat trout and identified conservation populations (>90% genetic purity) (dark blue). Conservation
population habitat is a fraction of total current occupied lake habitat.
600
400
Type
ConPop Range ha
Current Range ha
200
0
80
0
3,
>
80
0
60
0−
3,
0
60
3,
3,
0−
40
3,
40
0
55
3,
0−
3,
20
3,
20
0
00
0−
00
0
3,
3,
80
0−
80
0
2,
0−
60
2,
0
60
2,
2,
40
0−
40
0
2,
2,
0−
2,
20
2,
20
0
2,
00
0−
00
0
2,
80
0−
1,
80
1,
60
0−
1,
60
1,
0−
1,
40
<
1,
40
0
0
0
�Appendix C Figure 4b: (2010 Assessment Pg. 91)
Currently occupied CRCT habitat associated with the primary agencies (USFS, BLM, NPS, State, and
Tribal).
56
�Appendix D: Maps of each 4th level HUC containing historic habitat and each conservation population.
Appendix D Figures Appendix D - Animas: (2010 Assessment Pg. 93)
57
�Appendix D - Colorado Headwaters: (2010 Assessment Pg. 94)
58
�Appendix D - Blue: (2010 Assessment Pg. 95)
59
�Appendix D - Eagle: (2010 Assessment Pg. 96)
60
�Appendix D - Roaring Fork: (2010 Assessment Pg. 97)
61
�Appendix D - Colorado Headwaters - Plateau: (2010 Assessment Pg. 98)
62
�Appendix D - Parachute Roan: (2010 Assessment Pg. 99)
63
�Appendix D - Upper Gunnison: (2010 Assessment Pg. 100)
64
�Appendix D - North Fork Gunnison: (2010 Assessment Pg. 101)
65
�Appendix D - Lower Gunnison: (2010 Assessment Pg. 102)
66
�Appendix D - Uncompahgre: (2010 Assessment Pg. 103)
67
�Appendix D - Westwater Canyon: (2010 Assessment Pg. 104)
68
�Appendix D - Upper Dolores: (2010 Assessment Pg. 105)
69
�Appendix D - San Miguel: (2010 Assessment Pg. 106)
70
�Appendix D - Upper Green: (2010 Assessment Pg. 107)
71
�Appendix D - New Fork: (2010 Assessment Pg. 108)
72
�Appendix D - Upper Green - Flaming Gorge: (2010 Assessment Pg. 109)
73
�Appendix D - Blacks Fork: (2010 Assessment Pg. 110)
74
�Appendix D - Muddy - Upper Green: (2010 Assessment Pg. 111)
75
�Appendix D - Upper Yampa: (2010 Assessment Pg. 112)
76
�Appendix D - Lower Yampa: (2010 Assessment Pg. 113)
77
�Appendix D - Little Snake: (2010 Assessment Pg. 114)
78
�Appendix D - Muddy - Yampa: (2010 Assessment Pg. 115)
79
�Appendix D - Upper White: (2010 Assessment Pg. 116)
80
�Appendix D - Piceance - Yellow: (2010 Assessment Pg. 117)
81
�Appendix D - Lower Green - Diamond: (2010 Assessment Pg. 118)
82
�Appendix D - Ashley - Brush: (2010 Assessment Pg. 119)
83
�Appendix D - Duchesne: (2010 Assessment Pg. 120)
84
�Appendix D - Strawberry: (2010 Assessment Pg. 121)
85
�Appendix D - Willow: (2010 Assessment Pg. 122)
86
�Appendix D - Price: (2010 Assessment Pg. 123)
87
�Appendix D - San Rafael: (2010 Assessment Pg. 124)
88
�Appendix D - Fremont: (2010 Assessment Pg. 125)
89
�Appendix D - Escalante: (2010 Assessment Pg. 126)
90
�Appendix D - Upper San Juan: (2010 Assessment Pg. 127)
91
�Appendix D - Piedra: (2010 Assessment Pg. 128)
92
�Appendix E: Comparison maps showing changes in the database to the currently occupied
layer, historic habitat, and populations designated as no longer present.
Appendix E Figures Appendix E - Upper Colorado: (2010 Assessment Pg. 130)
93
�Appendix E - Gunnison: (2010 Assessment Pg. 131)
94
�Appendix E - Dolores: (2010 Assessment Pg. 132)
95
�Appendix E - Upper Green: (2010 Assessment Pg. 133)
96
�Appendix E - Yampa: (2010 Assessment Pg. 134)
97
�Appendix E - Lower Green: (2010 Assessment Pg. 135)
98
�Appendix E - Lower Colorado: (2010 Assessment Pg. 136)
99
�Appendix E - San Juan: (2010 Assessment Pg. 137)
100
�
Dublin Core
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Aquatics Research
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