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Session 5—Contributed Papers
Working Together to Ensure the Future of Wild Trout
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255
Stocking Trout of Wild Parentage to Restore Wild
Populations: An Evaluation of Wisconsin’s Wild
Trout Stocking Program
M. G. Mitro
Coldwater Fisheries Research Scientist, Wisconsin Department of Natural
Resources, Monona, Wisconsin
ABSTRACT—The Wisconsin Department of Natural Resources (WDNR)
manages trout streams using a combination of stream habitat protection and
improvement, fishing regulations, and stocking of hatchery-reared trout. The
WDNR initiated a wild trout stocking program in 1995 to improve the quality of
hatchery-reared brook and brown trout by raising offspring of wild parentage. The
goals of the wild trout stocking program are to increase the survival and longevity
of trout stocked in streams and to ultimately develop self-sustaining populations
of wild trout. It is thought that hatchery trout of wild parentage maintain the
genetic diversity and better embody the characteristics found in wild populations
and may therefore improve restoration success. I collectively analyzed
evaluations of wild trout stocking across Wisconsin to determine whether
program goals were being fulfilled and to identify any research gaps. Preliminary
analyses indicated survival rates 2-4 times greater for stocked trout of wild
versus domestic parentage, and some increases in natural reproduction have
been observed. Habitat, however, may be limiting the restoration of self-
sustaining populations in some streams. Future research will address habitat
limitations to survival and reproduction of stocked wild trout and the long-term
viability of source populations for the wild trout stocking program.
Introduction
The Wisconsin Department of Natural Resources (WDNR) manages trout
fisheries in 10,371 miles of classified trout streams using a combination of
stream habitat protection and improvement, fishing regulations, and stocking of
hatchery-reared trout. About 40% of the trout stream mileage (Class I) support
natural reproduction sufficient for the maintenance of wild trout populations, but
populations in 45% (Class II) require supplementation by stocking and
populations in 15% (Class III) are wholly dependent on stocking. Through
WDNR management efforts, miles of Class I and II streams have increased and
miles of Class III streams have decreased in recent years. Trout habitat has been
improved by land conservation measures, which have reduced siltation from
erosion and improved groundwater flow (Gebert and Krug 1996), and by the
restoration of damaged stream habitat (Hunt 1993). Hunt (1988) and Avery
(2004) documented a half century (1953-2000) of evaluations of trout stream
habitat improvement projects, which have been supported by annual trout stamp
sales since 1978.
Trout stocking has a long history in Wisconsin dating back to the 19
th
century. Significant changes, however, have occurred in recent years. The
WDNR initiated a wild trout stocking program in 1995 in contrast to its long-
standing domestic trout stocking program. The idea of stocking trout of wild
parentage has been around at least since the 1960’s but rearing wild trout in a
hatchery was impractical at that time (Flick and Webster 1964; Mason et al.
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Wild Trout VIII Symposium (September 2004)
1967). Domestic strains of hatchery-reared trout often failed to sustain a fishery
beyond the early season and failed to contribute to natural reproduction in
Wisconsin streams (Avery et al. 2001). Poor survival of domestic trout stocked in
Wisconsin streams was observed in the early 1990’s during a time of severe
drought and harvest prohibition (Avery et al. 2001). This prompted interest in
developing a wild trout stocking program to improve the quality of hatchery-
reared trout and their potential for sustaining stream fisheries.
Wisconsin’s wild trout stocking program involves taking wild brook trout
Salvelinus fontinalis and brown trout Salmo trutta from streams, spawning them at
a fish hatchery, and later returning the spawned trout to the streams from which
they came. Offspring of the wild parents are raised at reduced densities in a
hatchery and stocked elsewhere in the state as spring or fall (autumn) fingerlings or
spring yearlings. It is thought that these trout of wild parentage better maintain the
genetic diversity found in wild populations and embody the characteristics of wild
trout as compared to offspring from domestic broodstock. To help maintain
“wildness” in the trout, human contact is minimized by partially shading tanks at
the hatchery and feeding trout continuously throughout the day using an automatic
feeder. The 2003-2004 wild brook trout stocking quota included 95,500 spring
fingerlings and 7,600 fall fingerlings; the wild brown trout stocking quota included
40,700 spring fingerlings, 28,250 fall fingerlings, and 6,980 spring yearlings. Wild
brown trout were stocked statewide and wild brook trout were only stocked in the
southwestern genetic management zone.
The goal of the wild trout stocking program is to use hatchery-reared trout of
wild parentage to develop self-sustaining populations of brook trout and brown
trout in waters that lack such populations. Specific objectives include increasing
the survival and longevity of stocked trout in streams and establishing natural
reproduction. This program has become an integral part of trout management in
the state. It is generally acknowledged that overall the trout fisheries in
Wisconsin today have improved over what they were in the past, and it is thought
that the wild trout program has played a key role in this recovery. The goal of
this study was to evaluate Wisconsin’s wild trout stocking program by
collectively analyzing evaluations of wild trout stocking across the state to
determine whether program goals and objectives were being fulfilled.
Methods
I distributed a memorandum to WDNR fisheries mangers and biologists
requesting them to provide any available data, analyses, and reports pertaining to
the evaluation of wild brook and brown trout stocking. I also requested that they
include similar information that may be available concerning the evaluation of
domestic brook and brown trout stocking prior to the start of the wild trout
stocking program, particularly for streams that later received wild trout. I
received unpublished data and reports on wild brown trout stocking in 15 streams
and wild brook trout stocking in 1 stream. Included is one published report on
wild and domestic brown trout stocking in two streams, the Waupaca River and
the West Fork Kickapoo River (Avery et al. 2001).
I evaluated the data, analyses, and reports to determine if stocked wild trout
had higher survival and longevity rates compared to domestic trout and to
determine if natural reproduction was occurring as a result of wild trout stocking
efforts. Survival was estimated by comparing densities of trout over time
(number per mile); densities were estimated using a single marking run and a
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257
single recapture run unless noted otherwise. I reported survival rates as apparent
survival rates because comparisons of densities more accurately reflected losses,
which could be attributable to mortality or movement. The initial density used in
apparent survival calculations was the initial stocking density. However, in some
reanalyses of the data as noted in the results section, I used the estimated density
after stocking had occurred as the initial density.
Results
There were sufficient data to evaluate survival, longevity, or reproductive
success for stocked wild versus domestic trout in 9 of 15 streams stocked with
brown trout (Table 1).
Table 1. Summary of wild brown trout stocking results in terms of survival, longevity, and reproductive
success compared to domestic brown trout stocking. If there were insufficient data or results were
inconclusive for a stream then the column was left blank.
Stream name
Stocked wild trout
survival greater than
domestic trout survival?
Stocked wild trout longevity
greater than domestic trout
longevity?
Successful
reproduction from
stocked wild trout?
Hunting River Yes Yes
McCaslin Brook No No No
North Branch Oconto
River
No No No
Onion River Yes
Peshtigo River Yes Yes
Rocky Run Yes
Rowan Creek Yes
Waupaca River Yes
West Fork Kickapoo River Yes
Apparent Survival
There was evidence that apparent survival rates of stocked wild brown trout
exceeded apparent survival rates of domestic brown trout in five streams. Avery
et al. (2001) evaluated the performance of stocked wild, domestic, and optimum
domestic brown trout in the Waupaca and West Fork Kickapoo rivers. Optimum
domestic trout were reared under conditions similar to those for hatchery wild
trout: little human contact and at about half the density of standard hatchery
protocol. Wild, optimum domestic and domestic fall fingerlings (age 0) brown
trout were stocked in the Waupaca River in fall 1993 and 1994. Apparent
survival φ was about 2−4 times greater for wild (φ = 0.22−0.34) versus optimum
domestic (φ = 0.06−0.13) or domestic trout (φ = 0.10) after one year and about
4−8 times greater for wild (φ = 0.08) versus optimum domestic (φ = 0.02) or
domestic trout (φ = 0.01) after two years. Wild, optimum domestic, and domestic
spring yearling (age 1) brown trout were stocked in the West Fork Kickapoo
River in spring 1994 and 1995. Densities in electrofishing stations increased for
wild trout (indicating recruitment) and decreased for optimum domestic and
domestic trout between the spring stocking and fall. I recalculated apparent
survival rates using density in the fall after the spring stocking as the initial
density and found that apparent survival from age 1 to age 2 was about 5 times
greater for wild (φ = 0.53) versus optimum domestic (φ = 0.10) or domestic trout
(φ = 0.11). A similar calculation for the Waupaca River showed that apparent
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Wild Trout VIII Symposium (September 2004)
survival from age 1 to age 2 was about 1.4−2.3 times greater for wild (φ = 0.23)
versus optimum domestic (φ = 0.17) or domestic trout (φ = 0.10). Apparent
survival in the West Fork Kickapoo River from age 1 to age 2.5 (fall 1994 to
spring 1996) was about 5-31 times greater for wild (φ = 0.31) versus optimum
domestic (φ = 0.06) or domestic trout (φ = 0.01).
Wild brown trout were stocked as spring fingerlings in six small Columbia
County streams in southwestern Wisconsin. Apparent survival from age 0 (fall)
to age 1 (fall) was about 2 times greater for stocked wild versus domestic brown
trout (Tim Larson, WDNR, unpublished data). Average apparent survival was
about 0.19 for stocked wild trout (2001-2003) versus less than 0.10 for domestic
trout (1984-1987) in Rocky Run and Rowan Creek. Average apparent survival
for stocked wild trout in four other streams was about 0.22 (Dell, Honey,
Jennings, and Leech creeks, 2001-2003), but there were no data on apparent
survival rates for domestic trout in these streams for comparison.
Apparent survival of stocked wild brown trout in the Peshtigo River was
greater than that of domestic brown trout as was evident by the densities of age 2
and age 3 and older trout (David L. Brum, WDNR, unpublished data). There was
no evidence of survival of domestic trout to age 3 and older in 1988 and 1997,
even though many of those trout were stocked as spring yearlings. The number of
domestic brown trout per mile based on single-pass electrofishing samples was
35 (age 1) and 7 (age 2) trout in 1988 and 26 (age 1) and 2 (age 2) trout in 1997.
There was evidence of survival to age 3 and older for stocked wild brown trout in
2001-2003 (wild trout stocking began in 1998), with densities higher than
densities of age-2 domestic trout. Average densities of stocked wild brown trout
for 1998-2003 were 149 (age 0), 104 (age 1), 16 (age 2), and 9 (age 3 and older).
A comparison of densities of stocked wild brown trout showed apparent survival
rates of 0.11-0.15 from age 1 to age 2.
Stocked wild brown trout did not survive better than domestic brown trout in
McCaslin Brook and the North Branch Oconto River (Lee Meyers, WDNR,
unpublished data). McCaslin Brook is a tributary of the North Branch Oconto
River. Wild brown trout were first stocked in the North Branch Oconto River in
1996 and in McCaslin Brook in 1997. Historic population estimates showed
brown trout densities of 139 per mile in 1973, 385 per mile in 1988, and 74 per
mile in 1996 in McCaslin Brook. Brook trout were also present (10 per mile in
1973 and 55 per mile in 1988). After wild brown trout were stocked in 1997,
densities increased to 545 per mile in 1997 and 1,300 per mile in 1998. However,
warm water temperatures of 26.7 °C and higher were recorded on three occasions
in July 1999, and the brown trout density had decreased to 218 per mile by
August 1999. The brook trout density, however, had not decreased (63 per mile
in 1999). Similar population estimates were not available for the North Branch
Oconto River, but a creel survey confirmed that stocked wild brown trout did not
provide for a significant fishery. Concerns that stocked wild brown trout were not
surviving prompted a return to stocking domestic yearling brown trout in 2000. A
creel survey in 2000 found that the trout harvest included 71% domestic brown
trout, 25% wild brook trout, and 4% wild brown trout (stocked or naturally
occurring; all from the North Branch Oconto River).
Apparent survival could not be estimated for brown trout in the Hunting
River, Onion River, and Pine River and brook trout in the West Branch Eau
Claire River because stocked wild naturally produced and domestic fish or age
classes could not be separated in the data. Therefore, these evaluations were
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Session 5—Contributed Papers
Working Together to Ensure the Future of Wild Trout
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259
inconclusive on the question of whether stocked wild versus domestic trout
survive better in these streams.
Longevity
Longevity of stocked wild brown trout was not greater than longevity of
domestic brown trout in McCaslin Brook and the North Branch Oconto River
because survival of stocked wild brown trout was poor as outlined above. There was,
however, evidence of increased longevity for stocked wild brown trout in the Hunting
and Peshtigo rivers. The 1,000 wild brown trout stocked in the Hunting River in 1996
at age 0 had a year-specific fin clip and two of these fish were recaptured in 2003 at
age 7 (David A. Seibel, WDNR, unpublished data). In the Peshtigo River there was
no evidence of survival of domestic brown trout past age 2 in 1988 and 1997, but
there was evidence of stocked wild brown trout surviving to age 3 and older (2001-
2003 with stocking beginning in 1998). Longevity of stocked trout could not be
evaluated for any of the other streams because age classes could not be separated in
the data or the length of the study was too short.
Reproduction
Evidence of reproduction consistent with wild trout stocking was observed in
the Hunting and Onion rivers. Young-of-year brown and brook trout were
observed from 1999 to 2003 in the Hunting River, indicating that natural
reproduction had occurred. Population estimates also suggested that natural
reproduction had occurred (Table 2). The density of stocked wild brown trout
(last stocked in 2001) generally decreased from 1998 to 2003, whereas the
density of stocked domestic (last stocked in 1999) and naturally produced brown
trout, which were confounded in the data, increased from 1998 to 2000.
Domestic and naturally-produced brown trout decreased thereafter, but densities
were 5 to 9 times greater than stocked wild brown trout. The increase in density
of domestic and naturally produced brown trout in 2000 and sustained higher
densities thereafter were consistent with reproduction that may have resulted
from stocked wild brown trout. Reproduction from domestic trout cannot,
however, be ruled out.
Table 2. Number of stocked wild and domestic brown trout by age and density (number per mile (No./mi)) of
stocked wild brown trout and combined stocked domestic and naturally produced brown trout (age 1
and older).
Age 1995 1996 1997 1998 1999 2000 2001 2002 2003
Number of stocked wild brown trout
0 1,000 2,000 1,000 500 2,000 1,000
No./mi 482 125 134 83 32 17
Number of stocked domestic brown trout
1
0 1,000
1 1,000 1,000 1,000 1,000
2 644
No./mi 67 414 467 546 439 201 159
1
Density (No./mi) is combined stocked domestic and naturally-produced brown trout
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Wild Trout VIII Symposium (September 2004)
Evidence of reproduction in the Onion River was observed in an increase in
the number of unclipped brown trout over time (Table 3) (John E. Nelson,
WDNR, unpublished data). The Onion River was historically stocked with
domestic brown trout. Spring yearling domestic brown trout were stocked in
1995 and were last stocked in 1997 along with some age-2 trout. The stocking of
wild brown trout started in 1997 with the transplant of age-1 wild brown trout
from two streams in the Coon Valley watershed. These fish received an adipose
clip. Fall fingerling wild brown trout were also stocked in 1997, but these did not
receive an adipose clip. No fish were stocked in 1998, spring yearling wild
brown trout were stocked in 1999 (adipose clip), and fall fingerling wild brown
trout were stocked in 2000 (adipose clip). There have been no subsequent
stockings in the Onion River watershed. The number of unclipped trout per mile
(single-pass electrofishing counts) increased from 100 in 1999 to 281 in 2001.
This increase in unclipped trout was consistent with the potential spawning of
wild trout stocked in 1997 (adult transfers and fall fingerlings). Evidence of
reproduction was found in the unclipped trout observed in 1999-2001, many of
which were less then four inches in total length.
Table 3. Number of unclipped and clipped brown trout per mile from 1997 to 2001 in the
Onion River.
Year
Number of unclipped
trout per mile
Number of clipped
trout per mile
1997 89
1998 161 80
1999 100 110
2000 180 31
2001 281 56
Reproduction of stocked wild brown trout was not observed in McCaslin
Brook and the North Branch Oconto River because survival of stocked wild
brown trout was poor as outlined above. Reproductive success of stocked trout
could not be evaluated for any of the other streams because stocked fingerlings
were unmarked and could not be distinguished from naturally-produced trout or
it was not an objective of the study (e.g., Avery et al. 2001).
Discussion
Early investigations of the performance of stocked wild trout versus domestic
trout showed higher survival rates for stocked wild trout. Flick and Webster
(1964) investigated differences in survival during the first year after stocking for
spring and fall fingerling brook trout of domestic versus wild parentage.
Oversummer survival was greater for wild (0.65-0.76) versus domestic (0.43-
0.53) brook trout fingerlings; overwinter survival did not differ but was likely
confounded with the larger size advantage of domestic trout. Mason et al. (1967)
investigated survival of domestic, wild, and domestic/wild hybrid brook trout
stocked in five central Wisconsin streams as fall fingerlings. Domestic brook
trout had a higher overwinter survival rate (0.38) than stocked wild brook trout
(0.25); however, after one complete year, stocked wild brook trout had a higher
survival rate (0.10) than domestic brook trout (0.007).
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The study by Avery et al. (2001) on wild trout stocking in the Waupaca and
West Fork Kickapoo rivers was initiated to further quantify the field performance
of stocked wild versus domestic trout specifically in Wisconsin streams. Early
results in this study were positive in favor of wild trout stocking, and the wild
trout stocking program was spread to other streams throughout the state. The
original intent of wild trout stocking was for it to be a temporary management
action towards establishing self-sustaining populations. This goal may have been
achieved in the Hunting River. Although survival rates could not be determined
from the data for stocked wild versus domestic brown trout in the Hunting River,
there was evidence of longevity in the observation of age-7 stocked wild trout
and there was evidence of reproduction. No stocking will occur in the Hunting
River from 2002 to 2006, whereupon the need to resume stocking will be
evaluated. The Onion River has also had successful reproduction since being
stocked with wild brown trout. There has been no stocking in the Onion River
since 2000; future evaluations of the trout population will determine the ultimate
success of wild trout stocking in the Onion River.
Apparent survival rates of stocked wild trout have exceeded apparent
survival rates of domestic trout as long as habitat was not a limiting factor.
Apparent survival rates were generally at least two times greater for stocked wild
versus domestic brown trout from age 0 to age 1 or from age 1 to age 2. Survival
rates to older ages were even greater for stocked wild trout and have resulted in
increased longevity. Stream habitat may, however, determine just how much
greater the survival of stocked wild trout versus domestic trout may be. For
example, the apparent survival from age 1 to age 2 for stocked wild versus
domestic brown trout was about 5 times greater in the West Fork Kickapoo River
as compared to about 2 times greater in the Waupaca River. The West Fork
Kickapoo River is a highly fertile river compared to the Waupaca River and it
has been suggested that the higher growth rates observed in the West Fork
Kickapoo River were responsible for the higher survival rates (Avery et al.
2001).
Habitat was a limiting factor in McCaslin Brook and the North Branch
Oconto River, where summer maximum water temperature exceeded 26 °C on
several occasions in 1999. The wild trout stocking observations from these
streams underscores the importance of stream habitat to supporting wild trout
populations. A wild trout stocking program cannot substitute for quality trout
habitat. Wisconsin’s active stream habitat restoration program, which has a
dedicated funding source via the sale of trout stamps, and Wisconsin’s land
conservation measures have helped to improve trout stream conditions such that
the wild trout stocking program serves as a viable management tool.
Apparent survival of stocked trout can be improved by using trout of wild
parentage, but successful reproduction may not necessarily follow. Many streams
may support juvenile and adult trout but fail to provide adequate spawning
habitat. Here again, habitat limitations need to be surpassed before the goal of
establishing self-sustaining trout populations can be realized. However, the
question is raised as to whether wild trout stocking may be preferred over
domestic trout stocking in situations where successful reproduction may not be
realized. If stocked wild trout can survive from year to year in streams that lack
spawning areas, then wild trout stocking will work for supporting trout fisheries
in those streams. Fisheries managers will have to determine whether the costs of
a wild versus domestic trout stocking program are justified for such streams and
their fisheries.
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Wild Trout VIII Symposium (September 2004)
Brook trout are the only stream salmonid native to Wisconsin. Brown trout
have been successfully introduced throughout the state and coexist with brook
trout in many streams. However, brown trout have also displaced brook trout in
many streams. Successful wild brown trout stocking may therefore be an
impediment to protecting or restoring brook trout populations. Mixed brook trout
and brown trout populations were present in the Pine River, McCaslin Brook, and
the North Branch Oconto River. Brook trout were not stocked in McCaslin Brook
and the North Branch Oconto River, but they were self-sustaining and constituted
about 25% of the trout fishery. Interestingly, whereas high summer water
temperatures limited stocked wild brown trout in 1999, wild brook trout
persisted, possibly by finding suitable refuge. Future wild brown trout stocking
will be avoided in McCaslin Brook, the North Branch Oconto, and other similar
streams with brook trout populations in northeastern Wisconsin (Lee S. Meyers,
WDNR, personal communication).
The potential for brook trout restoration should also be a consideration when
deciding to stock wild brown trout in streams without self-sustaining trout
populations. David M. Vetrano (WDNR, personal communication) has
commented that wild brown trout populations have been established in
westcentral Wisconsin streams that at the time would not have supported brook
trout. Subsequent improvements in land use have improved groundwater flow
such that those streams would now have been suitable for brook trout. The
presence of brown trout is now an obstacle to brook trout restoration.
When developing a wild trout stocking program, consideration should be
given to the genetics of the source populations. Stocking trout derived from wild
parents helps to avoid overwhelming native genetic diversity and to prevent the
loss of genetic diversity. Fields and Philipp (1998) documented levels of genetic
diversity consistent with distinct stocks of brook trout. Therefore, different
source populations for brook trout are needed for different parts of the state.
Brook trout from the Ash Creek source population are currently stocked in the
southwestern genetic management zone. Brook trout source populations for the
northern part of the state were recently identified in Dority Creek and the South
Fork of the Hay River (Heath M. Benike, WDNR, personal communication).
Other source populations have been used in the early stages of the wild trout
stocking program but have been discontinued from use due to disease issues.
Genetic analyses of Wisconsin brown trout populations have determined that
wild brown trout from the southwestern Timber Coulee Creek source population
can be stocked statewide. However, stocked wild brown trout from northeast
source populations (West Branch White River and Brule River) were found to
have survival rates about four times greater than those from the southwestern
population when stocked in the Waupaca River in northeastern Wisconsin (Al
Niebur, WDNR, unpublished data).
Future studies of wild trout stocking are needed to better understand how
habitat conditions determine the improvement in survival for wild stocked trout
versus domestic stocked trout and therefore in which types of streams better
success can be expected. Large annual variation in salmonid survival is common
(Needham et al. 1945; Hunt 1969; Seelbach 1993; Mitro and Zale 2002);
therefore, long-term studies may be necessary. Study designs should ensure that
stocked wild trout and domestic trout can be distinguished from each other and
from naturally-produced trout in the study stream, and if possible, among
cohorts. Batch tags such as visible implants of fluorescent elastomer (Northwest
Marine Technology, Inc.) used in different colors and locations on the trout are
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suitable for this purpose. Clipping fins can also be used to distinguish batches of
fish, but batch codes are obviously somewhat limited. Consistent use of the same
electrofishing stations from year to year will ensure that valid comparisons of
densities can be made among years.
I am currently initiating a study to investigate the long-term viability of wild
brook trout and brown trout populations as source populations for Wisconsin’s
wild trout stocking program. Wild brook trout have been obtained from Ash
Creek since 1999 and wild brown trout have been obtained from Timber Coulee
Creek since 1995. Little is known about the trout population in either stream.
Each stream supports a wild trout population protected from harvest by a no-kill
regulation. A sufficient number of trout have been captured to meet yearly egg
quotas (about 198,000 brook trout eggs and 114,000 brown trout eggs in 2002)
for the wild trout stocking program. However, we do not know what effect the
annual removal of reproductive output from each stream has had on the long-
term viability of each source population. Dr. Brian Sloss (Wisconsin Cooperative
Fisheries Research Unit, University of Wisconsin-Stevens Point) is initiating a
companion study to examine the potential and realized genetic impacts of wild
broodstock selection in Wisconsin’s wild trout stocking program. Together, these
studies will result in a quantitative understanding of the effects of broodstock
selection and egg collection on the source populations for the wild trout stocking
program and will aid management decisions such that the viability of the source
populations for the wild trout stocking program can be maintained.
Acknowledgements
I thank the WDNR fisheries mangers and biologists who contributed data,
analyses, reports, and comments pertaining to the evaluation of wild brook and
brown trout stocking in Wisconsin streams.
References
Avery, E. L., A. Niebur, and D. Vetrano. 2001. Field performance of wild and domestic
brown trout strains in two Wisconsin rivers. Wisconsin DNR Research Report 186:1-
16. http://www.dnr.state.wi.us/org/es/science/publications/PUB_SS_586_2001.pdf
Avery, E. L. 2004. A compendium of 58 trout stream habitat development evaluations in
Wisconsin—1985-2000. Wisconsin Department of Natural Resources Research
Report 187.
Fields, R.D. and D.P. Philipp. 1998. Genetic analysis of Wisconsin brook trout: Final
Report. INHS Aquatic Ecology Technical Report 98/2.
Gebert, W. A., and W. R. Krug. 1996. Streamflow trends in Wisconsin's driftless area.
Water Resources Bulletin 32(4):733-744.
Hunt, R. L. 1969. Overwinter survival of wild fingerling brook trout in Lawrence Creek,
Wisconsin. Journal of the Fisheries Research Board of Canada 26:1473-1483.
Hunt, R. L. 1988. A compendium of 45 trout stream habitat development evaluations in
Wisconsin during 1953-1986. Wisconsin Department of Natural Resources
Technical Bulletin No. 162.
Hunt, R. L. 1993. Trout Stream Therapy. University of Wisconsin Press, Wisconsin.
Mason, J. W. O. M. Brynildson, and P. E. Degurse. 1967. Comparative survival of wild
and domestic strains of brook trout in streams. Transactions of the American
Fisheries Society 96:313-319.
Mitro, M. G., and A. V. Zale. Seasonal survival, movement, and habitat use of age-0
rainbow trout in the Henrys Fork of the Snake River, Idaho. Transactions of the
American Fisheries Society 131:271-286.
Session 5—Contributed Papers
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Wild Trout VIII Symposium (September 2004)
Needham, P. R., J. W. Moffett, and D. W. Slater. 1945. Fluctuations in wild brown trout
populations in Convict Creek, California. Journal of Wildlife Management 9:9-25.
Seelbach, P. W. 1993. Population biology of steelhead in a stable-flow, low-gradient
tributary of Lake Michigan. Transactions of the American Fisheries Society 122:179-
198.
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Quirk Creek Brook Trout Suppression Project
Jim D. Stelfox
1
, Dean M. Baayens
2
, Greg R. Eisler
3
, Andrew
J. Paul
4
, and Georgina E. Shumaker
5
1
Fisheries Biologist, Fish and Wildlife Division, Alberta Sustainable Resource
Development, Calgary, Alberta, Canada;
2
Fisheries Technician, Trout Unlimited Canada, Calgary;
3
Fisheries Biologist, Trout Unlimited Canada, Calgary;
4
Research Associate, University of Calgary, Calgary;
5
Fisheries Technician, Grande Prairie, Alberta
ABSTRACT— A brook trout Salvelinus fontinalis suppression project utilizing
anglers was initiated in 1998 to facilitate recovery of native westslope cutthroat
trout Oncorhynchus clarkii lewisi and bull trout Salvelinus confluentus populations
in Quirk Creek, Alberta. Participating anglers were required to pass a fish
identification test, harvest all brook trout caught and release all other fish. Only
15 of the 7955 fish harvested were not brook trout. Although brook trout catch
rates remained relatively high (1.0-2.5 fish/angler-h) and brook trout dominated
the angler catch (54-73%), brook trout density has declined since 2000 while the
abundance of juvenile cutthroat trout increased in 2003, resulting in a decline in
the proportion of brook trout in the electrofishing catch.
Introduction
Brook trout Salvelinus fontinalis, although not native to Alberta, are present
in many montane and foothills waters as a result of extensive stocking. In
southern Alberta, brook trout populations have generally increased while native
westslope cutthroat trout Oncorhynchus clarkii lewisi and bull trout Salvelinus
confluentus populations have declined. Brook trout life history attributes (early
spawning age, reduced longevity and low catchability) have resulted in the
replacement of native bull trout and cutthroat trout fisheries with fisheries for
smaller, less-catchable, non-native brook trout.
Management programs to reduce or eliminate non-native trout populations
often involve pesticides and/or electrofishing (Moore et al 1983; Buktenika 1997;
Kulp and Moore 2000). However, Larson et al. (1986) suggested that experimental
angling programs might offer a cost-effective, alternative method for reducing
densities of non-native trout. Although Larson’s study only ran nine weeks, it
appeared that anglers reduced the non-native trout population by about 10%.
Since pesticides are only suitable in certain situations and there are
insufficient resources to attempt removal of non-native trout by electrofishing in
all streams where native trout populations appear to be threatened, the option of
selectively removing non-native trout by angling provides an appealing
alternative. Our objective in this study was to determine whether angling could
be an effective method for reducing densities of non-native brook trout in Quirk
Creek, Alberta, to facilitate recovery of the native trout population.
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Study Area
Quirk Creek is located 50 km southwest of Calgary in a designated off-
highway vehicle (OHV) area. A good dirt road comes within 0.5 km of the creek
for most of its length. Anglers participating in this project were allowed direct
vehicle access to this road by fording the Elbow River, but only on supervised
outings under the direction of the volunteer coordinator. A locked gate prevents
anglers on unsupervised outings from crossing the Elbow River by vehicle.
Most of Quirk Creek meanders through a large wet meadow dominated by
grasses and low (< 1 m) shrubs. Although cattle and OHVs have degraded
streambanks in a few areas, most of the streambanks are undamaged and provide
good fish habitat, consisting of deeply undercut banks with overhanging
terrestrial vegetation. The lower 2 km of creek flows through a narrow valley
before joining the Elbow River at an elevation of 1530 m. There are no
permanent barriers on the creek, although beaver dams up to 1.5 m high are
scattered along the creek.
Brook trout colonized Quirk Creek subsequent to their introduction to the
Elbow River watershed in 1940. Although native cutthroat trout and bull trout
were the only fish captured in Quirk Creek in 1948, brook trout had colonized the
lower 3 km of the creek by 1978, comprising 35% of the fish population, and
spread throughout the entire creek by 1995, comprising 92% of the fish
population. These changes occurred despite the implementation of reduced bag
limits and minimum size limits designed to provide more protection for native
trout (Stelfox et al. 2001a). Since 1998, harvest of all fish has been prohibited in
Quirk Creek, except by anglers participating in the project.
A bridge divides Quirk Creek into upper and lower reaches, with the lower
reach serving as a control during the first two years of the project. Surface areas of
the upper and lower reaches were estimated to be 1.65 and 1.8 ha, respectively, by
extrapolating the mean widths of the creek (3.3 and 3.6 m) within the respective
electrofishing sites to the approximate lengths of each reach (5 km).
Methods
Fish Identification Education
To participate in the project, all anglers had to pass a fish identification test
on an annual basis to demonstrate their ability to identify the three fish species
found in Quirk Creek. If a person failed the test on their first attempt, they were
given a dichotomous key with pictures of the key-identifying features (a list of
key-identifying features in 1998) and were permitted to take the test a second
time with the key (list) in front of them. For a more detailed discussion of the fish
identification test, refer to Stelfox et al. (2001b).
Angling
Participating anglers were required to harvest all brook trout caught and were
initially only allowed to harvest brook trout from the upper reach of Quirk Creek on
supervised outings. However, beginning in 2000, anglers also harvested fish from the
lower reach to assess brook trout immigration and, starting in 2001, some of the more
skilled anglers harvested fish on unsupervised outings. Anglers only fished from June
to October, could not use bait, and were required to release all bull trout and cutthroat
trout after recording the length of each fish in 5-cm size classes.
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All harvested brook trout were delivered whole to the volunteer coordinator at the
end of each outing for measuring (fork length, nearest 1 mm) and weighing (nearest 1
g) and then returned to the angler. Anglers on unsupervised outings recorded fork
lengths (nearest 1 mm) of all brook trout caught and filled in creel cards.
Electrofishing
Removal-method estimates of the fish population in Quirk Creek were obtained
by electrofishing sections of both reaches between mid-August and early
September (Paul 2004). With the exception of 1987, when the mark-recapture
method was used, attempts were made to capture all fish, including age-0 brook
trout (< 100 mm) and cutthroat trout (< 70 mm).
To assess immigration of large (> 150 mm) brook trout into the upper reach
from the lower reach, the upper 2.5 km of the lower reach was electrofished on 6
May 2000 and 2 June 2001 to capture, mark, and release 750 and 92 large (> 150
mm) brook trout, respectively. All bull trout and cutthroat trout, and marked brook
trout, were measured before release. A mark-recapture estimate of the population
of large brook trout present in the lower reach on 6 May 2000 was obtained by
applying the Petersen estimate, corrected for size, to the marked brook trout
recaptured by anglers in the lower reach in 2000.
Ageing and Maturity
Fish were aged by otoliths collected from a subsample of the fish captured by
electrofishing in 1987, 1995 and 2000, and from any cutthroat trout and bull trout
mortalities encountered during the study (Stelfox et. al. 2001a). Maturity was
determined for all fish from which otoliths were collected.
Results
Fish Identification Education
Of 376 people who had never before taken the test, 52% failed on their first
attempt. However, of those who failed their first attempt, 76% passed their second
attempt, after shown the key-identifying features for each species. Mean scores on
the first and second attempt were 90% and 97%, respectively. Most (≈ 75%) of the
people who took the test were experienced anglers, reporting that they had fished
for more than 10 years.
During the 1998–2000 periods, 54 individual anglers took the test in more than
one year. Although 33% of these anglers failed the test on their very first attempt,
the failure rate in subsequent years on the first attempt was only 9% and none
failed their second attempt.
Angling
Average annual catch rate for brook trout in the upper reach remained high (2.2–2.5
fish/h) during the first three years of the study, but declined to 1.0 fish/h by 2002 (Table
1). In contrast, catch rates for brook trout in the lower reach changed little, ranging from
1.3 to 1.8 fish/h. Aggregate catch rates in both reaches were generally about 1.0 fish/h
higher than for brook trout alone (Table 1).
Fishing effort peaked at 397 h/ha in the upper reach in 1999 and 549 h/ha in the
lower reach in 2000 (Figure 1). Since then, fishing effort has been consistently higher
in the lower reach, but has declined substantially in both reaches.
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Wild Trout VIII Symposium (September 2004)
Table 1. Angling data summary for Quirk Creek, 1998-2003. All brook trout were harvested.
Number Number of fish caught Number Catch rate Percentage of catch
of Bull Cutthroat Brook of hours (brook Bull Cutthroat Brook
Year anglers trout trout trout Total fished (fish/h) trout/h) trout trout trout
Upper reach
1998
97 63 349 1076 1488 436.0 3.4 2.5 4.2 23.5 72.3
1999
146 161 735 1412 2308 655.5 3.5 2.2 7.0 31.8 61.2
2000
111 68 522 1128 1718 477.3 3.6 2.4 4.0 30.4 65.7
2001
70 19 276 511 806 271.3 3.0 1.9 2.4 34.2 63.4
2002
26 1 71 83 155 82.5 1.9 1.0 0.6 45.8 53.5
2003
15 1 45 57 103 55.5 1.9 1.0 1.0 43.7 55.3
Upper Total 465 313 1998 4267 6578 1978.0 3.3 2.2 4.8 30.4 64.9
Lower reach
2000
204 115 807 1644 2566 988.8 2.6 1.7 4.5 31.4 64.1
2001
142 39 544 1101 1684 619.0 2.7 1.8 2.3 32.3 65.4
2002
119 12 287 555 854 432.5 2.0 1.3 1.4 33.6 65.0
2003
56 12 211 373 596 206.0 2.9 1.8 2.0 35.4 62.6
Lower total 521 178 1849 3673 5700 2246.3 2.5 1.6 3.1 32.4 64.4
Grand total 986 491 3847 7940 12278 4224.3 2.9 1.9 4.0 31.3 64.7
0
500
1000
1500
1998 1999 2000 2001 2002 2003
Year
Angler hours
Supervised
Unsupervised
Figure 2. Number of hours fished by anglers on supervised
and unsupervised outings on Quirk Creek.
0
1
2
3
2001 2002 2003
Year
Brook trout / hour
Unsupervised
Supervised
Figure 3. Brook trout catch rates for anglers on supervised
and unsupervised outings on Quirk Creek.
0
25
50
75
100
2001 2002 2003
Year
Percentage
Lower reach
Upper reach
Figure 4. Percentage of brook trout harvested by anglers
on unsupervised outings on Quirk Creek.
0
200
400
600
1998 1999 2000 2001 2002 2003
Year
Hours/ha
0
200
400
600
800
1000
Brook trout/ha
Figure 1. Fishing effort (solid lines) and brook trout harvest
rates (dashed lines) in the upper (squares) and lower
(triangles) reaches of Quirk Creek.
The number of hours fished on supervised outings has declined substantially
since initiation of unsupervised outings in 2001 (Figure 2). This decline, in
conjunction with the higher catch rates of anglers on unsupervised outings
(Figure 3), has resulted in an increase in the relative importance of unsupervised
outings for brook trout harvest (Figure 4). By 2003, about 2/3 of all brook trout
harvested were taken by anglers on unsupervised outings.
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Table 2. Fish population estimates for, and brook trout harvested from, Quirk Creek. With the
exception of the mark-recapture estimate in 1987, all population estimates were obtained by
the removal method.
Trout population estimates Brook
Brook trout
Reach Year Total Bull Cutthroat All
>
150 mm
harvested
Number per hectare
Upper
1998 2285 64 264 1958 958 652
1999 1652 33 167 1452 639 856
2000 3491 39 715 2736 773 684
2001 310
2002 1082
b
73 1009 161 50
2003 1709 79 476 1155 176 35
Lower
1987 778
a
50
a
508
a
219
a
114
1995 233
b
22 211 44
1996 431
b
28 403 197
1997 1456 22 361 1072 475
1998 2008 42 269 1697 650
1999 1428
b
175 1253 525
2000 2975 31 444 2500 608 913
2001 612
2002 1083
b
150 933 428 308
2003 1217 56 775 386 139 207
Kilograms per hectare
Upper
1998 111.5 7.0 13.0 91.5 73.3 56.3
1999 106.7 2.7 12.1 82.7 59.1 81.9
2000 114.5 4.2 17.9 92.4 73.0 60.7
2001 20.9
2002 26.1
b
1.5 24.5 11.2 3.3
2003 34.8 1.8 4.5 28.5 13.3 3.4
Lower
1987 65.6 4.2 31.7 29.7 11.6
1995 6.9
b
0.6 6.4 2.5
1996 20.6
b
2.5 18.1 13.9
1997 56.9 0.3 8.6 46.9 37.2
1998 88.9 1.9 8.6 78.3 63.1
1999 85.0
b
15.3 69.7 58.3
2000 98.9 3.9 17.2 77.8 60.6 94.4
2001 41.3
2002 46.1
b
8.3 37.8 27.5 23.4
2003 25.6 1.4 9.7 14.4 12.2 18.0
a
Does not include age-0 fish.
b
Too few bull trout were captured to obtain an estimate.
Harvest rates peaked at 913 brook trout/ha (94.4 kg/ha) in the lower reach in
2000 (Table 2). Since then, harvest rates have declined substantially in both
reaches to a low of 35 brook trout/ha in the upper reach in 2003, but have been
consistently greater in the lower reach (Figure 1). Mean length of harvested
brook trout has changed relatively little over the study, ranging from 173 to 203
mm (Figure 5).
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Wild Trout VIII Symposium (September 2004)
Only 4% of the angler-caught brook trout in the upper reach were longer than
250 mm, compared to 32% of the bull trout and 23% of the cutthroat trout. The
relationship was similar in the lower reach, where only 6% of the angler-caught
brook trout were longer than 250 mm, compared to 22% of the bull trout and
25% of the cutthroat trout.
While the percentage of brook trout in the angler catch in the upper reach
declined from 72% in 1998 to 54% in 2002, it remained virtually unchanged (63–
65%) in the lower reach (Table 1).
Since inception of the project, anglers have harvested 7955 fish, of which only
15 (0.2%) were not brook trout. All of the misidentified fish were cutthroat trout.
Electrofishing
During the 1987–2003 period, the aggregate trout population in the lower
reach declined from 778 fish/ha in 1987 to 233 fish/ha in 1995, and then
increased to 2975 fish/ha in 2000 (Table 2).
In 1978, bull trout comprised 54% of the fish population in the uppermost 7
km of the creek and 8% in the lowermost 3 km (Table 3). However, the
proportion of bull trout in the fish population of both reaches plummeted to only
1% by 2000. Since 1987, bull trout have not exceeded 80 fish/ha in either reach
and numbers of bull trout captured have often been too low to obtain valid
population estimates (Table 2).
From 1987 to 1995, cutthroat trout declined from 64% to 5% of the fish
population in the lower reach (Table 3), and from 508 to 22 fish/ha, respectively
(Table 2). Since then, cutthroat trout have comprised less than 25% of the fish
population in the lower reach, until 2003, when they increased to 63% of the fish
population and a high of 775 fish/ha. In the upper reach, density of cutthroat trout
also increased in 2003, to 476 fish/ha, and the percentage of cutthroat trout in the
fish population increased to 25%, up from 6% the previous year, but well below
the 46% recorded in 1978 (Table 3). Although the density of cutthroat trout in the
lower reach in 2003 was higher than in 1987, the biomass of cutthroat trout (9.7
kg/ha) was only about 1/3 as great as in 1987 (Table 2). Similarly, the biomass of
cutthroat trout in the upper reach in 2003 (4.5 kg/ha) was much lower than in
most of the previous years.
In 1978, brook trout comprised 35% of the fish population in the lowermost
3 km of the creek, and were not found in any of the four sites electrofished in the
uppermost 7 km (Table 3). During the 1995–2002 period, when brook trout
comprised 74–92% of the fish population in both reaches, density of large (> 150
mm) brook trout peaked at 958 fish/ha (Table 2). In 2003, the proportion of
0
1000
2000
3000
1995 1997 1999 2001 2003
Year
Brook trout/ha
Figure 6. Densities of large (> 150 mm) brook trout (solid
lines) and all brook trout (dashed lines) in the upper
(
trian
g
les
)
and lower
(
squares
)
reaches of Quirk Creek.
100
120
140
160
180
200
1998 1999 2000 2001 2002 2003
Year
Fork length (mm)
Lower reach
Upper reach
Figure 5. Mean lengths of brook trout harvested by anglers
from the upper and lower reaches of Quirk Creek.
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brook trout in the fish population declined to 32% in the lower reach and 70% in
the upper reach — the lowest levels recorded since 1998.
The harvest of 652 and 856 brook trout/ha in the upper reach in 1998 and
1999, respectively, appeared to have very little impact on the density of large (>
150 mm) brook trout in the upper reach relative to the lower reach, which served
as a control section until 2000 (Table 2; Figure 6). Subsequent to initiation of
brook trout harvest in the lower reach in 2000, the density of large (> 150 mm)
brook trout in the lower reach declined by 77% to 139 fish/ha in 2003 — the
lowest level recorded since 1998 (Table 2; Figure 6). However, the density of
large (> 150 mm) brook trout in the upper reach also declined by 77% to 176
fish/ha, even though fishing effort and brook trout harvest in the upper reach was
usually less than half as great as in the lower reach during the 2000–03 period
(Table 2; Figure 1).
A comparison of the length-frequency distributions of brook trout caught by
angling and electrofishing in 1999 indicates that vulnerability to angling declined
below about 210 mm (Figure 7). Anglers were very ineffective at catching brook
trout smaller than 150 mm. Brook trout < 150 mm comprised 50–70% of the
electrofishing catch, but only 3–11% of the brook trout harvest in the upper reach
during the 1998–2000 period. Of 32 brook trout collected for ageing on 26
August 2000, the smallest mature female was 180 mm and none of the mature
females were younger than age 3. Age-1, -2, and -3 brook trout averaged 117,
170 and 206 mm, respectively.
Of the 750 large (> 150 mm) brook trout marked in 2000, anglers
subsequently harvested 391 (52%) — 349 (46%) in 2000 and 42 (6%) in 2001.
Only eight (2%) of these marked fish were taken from the upper reach — four in
2000 and four in 2001. Of the 92 large brook trout marked in 2001, anglers
subsequently harvested 33 (36%) in 2001. None were taken from the upper reach.
Based on recapture in the lower reach of 345 of the 750 brook trout marked
on 6 May 2000, and by adjusting for growth over the course of the 2000 fishing
season, we estimated that there were 2532 ± 164 (SD) large (> 150 mm) brook
trout present in the lower reach on 6 May 2000, or 1407 large brook trout/ha.
Using the mean weight (106 g) of the 750 brook trout that were marked on 6
May, the estimated biomass of large brook trout was 149 kg/ha.
0
5
10
15
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Fork length (mm)
Harvested
n=1412
0
5
10
15
40 80 120 160 200 240 280 320 360
Electrofished
n=200
Figure 7. Size distribution of brook trout harvested
in 1999 and electrofished on 16 August 1999
from the upper reach of Quirk Creek.
Frequency (%)
Fork length (mm)
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Wild Trout VIII Symposium (September 2004)
By adding each removal-method estimate to the number of brook trout
harvested prior to the electrofishing date, we extrapolated the number of large (>
150 mm) brook trout present at the start of each fishing season. Using this
approach, we estimated that anglers harvested 45, 68, 57, 27 and 18% of the
population of large brook trout in the upper reach in 1998, 1999, 2000, 2002 and
2003, respectively, and 64, 43 and 61% of the population of large brook trout in
the lower reach in 2000, 2002 and 2003, respectively.
Discussion
The fish identification key proved to be effective in teaching anglers how to
identify fish, considering that only 15 of the 7955 fish harvested by anglers
participating in this project were not brook trout. Additionally, long-term
retention of the key-identifying features by anglers was encouraging, given that
only 9% of the anglers failed the test on their first attempt in subsequent years,
even though the failure rate on their very first attempt was 33%.
Angler harvest of more than 650 brook trout/ha (55 kg/ha) from the upper
reach in 1998 and 1999 appeared to have little impact on brook trout catch rates,
the mean length of brook trout caught or the density of large (> 150 mm) brook
trout in the upper reach relative to the lower reach. In contrast, average annual
angler harvest of 25 kg/ha of trout over a 10-year period from Sagehen Creek,
California, which equated to 66% of the average standing crop of trout, had a
relatively large effect, given that the average total number and weight of all trout
nearly doubled and the number of trout ≥ 200 mm increased 14-fold in a portion
Table 3. Species composition of the fish population in Quirk Creek.
Percent composition
a
Reach
Year
Sample
size
Bull
trout
Cutthroat
trout
Brook
trout
Upper
1978
b,c
132 54 46 0
1998 278 3 12 85
1999 200 2 11 87
2000 416 1 21 78
2002 122 3 6 91
2003 178 5 25 70
Lower
1978
b,d
208 8 57 35
1987 187 7 64 29
1995 79 3 5 92
1996 72 1 7 92
1997 255 2 24 74
1998 280 2 14 84
1999 195 1 13 86
2000 355 1 16 83
2002 186 2 12 86
2003 205 5 63 32
a
Determined from the number of fish in the electrofishing catch.
b
Calculated from data in Volume II (Appendices) of Tripp et al. (1979).
c
The section electrofished in 1978 was the uppermost 7 km of the creek.
d
The section electrofished in 1978 was the lowermost 3 km of the creek.
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of the creek subsequently closed to angling for a six-year period (Gard and
Seegrist 1972). Immigration could have reduced the effects of brook trout harvest
in the upper reach of Quirk Creek. Gowan and Fausch (1996) found that
movement was relatively common, with brook trout usually moving in the
upstream direction during and just after runoff, and before spawning. However,
in our study, upstream movement did not appear to be sufficient to mask the
effects of brook trout harvest in the upper reach, since only 2% of the recaptured
brook trout had immigrated into the upper reach.
The apparent lack of impact therefore suggests that angler harvest of 45–68%
of large (> 150 mm) brook trout during the 1998–1999 period was insufficient to
collapse the population. Although proportions harvested are based on population
estimates extrapolated to the start of the fishing season, we feel these
extrapolations are reasonable, given the similarity between the independent
mark-recapture estimate of large (> 150 mm) brook trout present in the lower
reach at the start of the 2000 fishing season (1407 fish/ha) and the extrapolated
estimate (1429 fish/ha). However, our extrapolations should still be used with
caution, as they do not account for all brook trout mortality or growth that
occurred during the approximately two-month angling period prior to the
electrofishing dates.
The population estimates suggest that a 1:100-year flood that occurred in
June 1995 had a major impact on the fish population. Within five years of the
flood, the aggregate population estimate for trout increased numerically by 13-
fold and in biomass by 14-fold in the lower reach. Hanson and Waters (1974)
documented similar effects following a flood in a Minnesota stream, with a 20-
fold increase in brook trout numbers and a 6-fold increase in biomass within four
years.
While densities of large (> 150 mm) brook trout have declined in both
reaches since 2000, there has been surprisingly little change in the proportion of
brook trout in the angler catch, although fishing effort and brook trout harvest has
declined substantially in both reaches, especially in the upper reach. However,
the electrofishing data suggests that a change may soon occur, given that
cutthroat trout densities increased substantially in both reaches due to an influx of
age-0 and age-1 cutthroat trout in 2003 (Paul 2004). A 5-fold increase in
cutthroat trout density in the lower reach, in conjunction with a decline in brook
trout density, resulted in cutthroat trout comprising 63% of the fish population in
the lower reach in 2003, up from 12% in 2002. Although there was a larger (6.5-
fold) increase in cutthroat trout density in the upper reach, the effect was
diminished by a slight increase in brook trout density, resulting in cutthroat trout
comprising 25% of the fish population in 2003, up from 6% in 2002.
Whether the increase in juvenile cutthroat trout density in 2003 translates
into an increase in catchable-sized cutthroat trout in the future will depend on
survival rates. Survival rates apparently varied greatly between the strong year-
classes of cutthroat trout in 1996 and 2000 (Stelfox et al. 2001). Although age-0
cutthroat trout were absent from the 1996 electrofishing catch because sampling
was conducted two weeks earlier than in 2000 (Paul 2004), survival of the 1996
year-class appears to have been relatively good based on the size distribution
(Stelfox et al. 2001) and relatively high densities of cutthroat trout in the
following two years. In contrast, survival of the 2000 year-class appears to have
been relatively poor, since the density of cutthroat trout in 2002 was lower in
both reaches than in any year since 1996.
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Wild Trout VIII Symposium (September 2004)
It is possible that density of large brook trout affects the survival of cutthroat
trout. Larson and Moore (1985), in a study of stream populations of brook trout
and rainbow trout, found that abundance of age-0 fish of either species was
greatly reduced in the presence of 300 or more adults/ha of the other species. A
comparable relationship may exist between brook trout and cutthroat trout in
Quirk Creek, given that relatively good survival of the 1996 cutthroat trout year-
class occurred when there were less than 200 large (> 150 mm) brook trout/ha,
whereas relatively poor survival of the 2000 cutthroat trout year-class occurred
when there were more than 600 large brook trout/ha.
If density of large brook trout is a major factor in the survival of cutthroat
trout fry, then recovery of the cutthroat trout population will be contingent upon
preventing the adult brook trout population from increasing to previous high
levels. However, this may be difficult to accomplish on the upper reach, where
only 18% of the extrapolated population of large (> 150 mm) brook trout were
harvested in 2003 compared to 61% in the more accessible lower reach, largely
due to a reduction in the number of supervised outings.
Bull trout and cutthroat trout have the potential to provide a better quality
fishery in Quirk Creek, based on their larger size and higher catchability. Paul et
al. (2003) determined that the catchability of similar-sized bull trout and cutthroat
trout was 2.5-fold greater than for brook trout. This higher catchability, however,
could prevent a recovery of the native trout population. Paul et al. (2003), using a
model developed with data from the Quirk Creek brook trout suppression project,
calculated that bull trout and cutthroat trout populations in the upper reach would
be extinct within five years at a hooking mortality rate of 10% and an angler
effort of 656 angler-hours/year — equivalent to the angler effort in 1999. At
hooking mortality rates of 2.5 and 5%, they could still decline.
Although the brook trout population has declined since 2000 and the
cutthroat trout population increased in 2003, we cannot yet conclude that angling
is an effective means of suppressing non-native trout populations, since the
control section was lost when harvest began in the lower reach in 2000 to assess
brook trout immigration. However, the project has demonstrated that
misidentification of trout is a problem among anglers, but one that can be readily
overcome by showing anglers key-identifying features for each trout species. It
has also made anglers more aware of the differences between native and non-
native trout. Finally, the project has demonstrated that brook trout in Quirk Creek
are highly resilient to overexploitation.
Acknowledgements
The Quirk Creek Brook Trout Suppression Project is a joint project involving
the Fish & Wildlife Division of Alberta Sustainable Resource Development, and
Trout Unlimited Canada. We thank the many volunteers who participated by
taking the fish identification test and by harvesting brook trout. We also thank the
volunteers, especially the Westwind Flyfishers of Calgary, who assisted with the
electrofishing. Applied Aquatic Research Ltd. provided in-kind support, and
funds from Anadarko Canada Corporation, the Alberta Conservation Association
and the Parks Venture Fund supported this project. Earlier versions of this
manuscript were improved by comments from D. G. Christiansen, M. G. Sullivan
and H. J. Norris.
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References
Buktenika, M. K. 1997. Bull trout restoration and brook trout eradication at Crater Lake
National Park, Oregon. Pages 127–135 in Brewin, M.K., A.J. Paul, and M. Monita,
editors. Bull trout II conference proceedings, c/o Trout Unlimited Canada, Calgary,
Alberta.
Gard, R., and D. W. Seegrist. 1972. Abundance and harvest of trout in Sagehen Creek,
California. Transactions of the American Fisheries Society 101:463–477.
Gowan, C., and K .D. Fausch. 1996. Mobile brook trout in two high-elevation Colorado
streams: re-evaluating the concept of restricted movement. Canadian Journal of
Fisheries and Aquatic Sciences. 53:1370–1381.
Hanson, D. L., and T. F. Waters. 1974. Recovery of standing crop and production rate of
a brook trout population in a flood-damaged stream. Transactions of the American
Fisheries Society 103:431–439.
Kulp, M. A., and S. E. Moore. 2000. Multiple electrofishing removals for eliminating
rainbow trout in a small southern Appalachian stream. North American Journal of
Fisheries Management 20:259–266.
Larson, G. L., and S. E. Moore. 1985. Encroachment of exotic rainbow trout into stream
populations of native brook trout in the southern Appalachian Mountains.
Transactions of the American Fisheries Society 114:195–203.
Larson, G. L., S. E. Moore, and D. C. Lee. 1986. Angling and electrofishing for removing
nonnative rainbow trout from a stream in a national park. North American Journal of
Fisheries Management 6:580–585.
Moore, S. E., B. L. Ridley, and G. L. Larson. 1983. Standing crops of brook trout
concurrent with removal of rainbow trout from selected streams in Great Smoky
Mountains National Park. North American Journal of Fisheries Management 3:72–80.
Paul, A. J., J. R. Post and J. D. Stelfox. 2003. Can anglers influence the abundance of
native and nonnative salmonids in a stream from the Canadian Rocky Mountains?
North American Journal of Fisheries Management 23:109–119.
Paul, A. J. 2004. Quirk Creek population estimates, 2003. Prepared for Alberta
Sustainable Resource Development, Fish and Wildlife Division by Applied Aquatic
Research Ltd., Calgary, Alberta.
Stelfox, J. D., D. M. Baayens, A. J. Paul and G. E. Shumaker. 2001a. Quirk Creek brook
trout suppression project. Pages 37–46 in Brewin, M.K., A.J. Paul, and M. Monita,
editors. Bull trout II conference proceedings, c/o Trout Unlimited Canada, Calgary,
Alberta.
Stelfox, J. D., G. E. Shumaker and D. M. Baayens. 2001b. Fish identification education.
Pages 63–66 in Brewin, M.K., A.J. Paul, and M. Monita, editors Bull trout II
conference proceedings, c/o Trout Unlimited Canada, Calgary, Alberta.
Tripp, D. B., P. T. P. Tsui, and P. J. McCart. 1979. Baseline fisheries investigations in the
McLean Creek ATV and Sibbald Flat snowmobile areas. Volume II. Prepared for the
Alberta Department of Recreation, Parks and Wildlife by Aquatics Environment
Limited.
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Regaining Public Trust … and Keeping It!
A.J. Faast
1
and S.K. Sahnow
2
1
Staff Biologist, U.S. Fish and Wildlife Service, Portland, Oregon
2
Director, Forestry Education Project, Oregon State University, Corvallis,
Oregon
ABSTRACT─“Ethics are a kind of community instinct in the making.” Aldo
Leopold, A Sand County Almanac, 1949. A definable ethic that contributes to
respect, that in turn leads to trust, may well be the "mode of guidance" suggested
by Leopold for effectively meeting the social dimension of natural resource
decision-making of the future. The authors contend that fair, open, and honest
are the necessary elements of our management behavior that comprise the core
of an ethical approach for conducting agency programs that are increasingly
under intense public scrutiny. Simply gaining the elusive public trust is not
enough, however, as the public continues to respond to the authenticity exhibited
by agencies and their respective professionals, maintaining credibility over time
by carrying through on what our agencies say we are going to do, is critical to
maintaining public trust. The authors will define how to “make sure actions on the
ground match the words on the page.” Drawing on their extensive public process
experience, the authors contend that if natural resource agency professionals, as
a community, embrace the fair, open, and honest philosophy as the cornerstone
of public process, then Leopold's "mode of guidance" will have been defined for
the coming century.
Introduction
“An ethic may be regarded as a mode of guidance for meeting ecological
situations so new or intricate... that the path of social expediency is not
discernible to the average individual... Ethics are a kind of community instinct in
the making.”
Aldo Leopold, A Sand County Almanac, 1949
Fifty years after Leopold (1949) penned those words, the human component
of natural resource science is "so new and intricate" that the path of social
expediency is, indeed, "not discernible."
As biologists, foresters, and environmental educators, we have become more
than sources of information and data. We've also become professional facilitators
embroiled in high stakes, natural resource issues and decisions. We've seen
everything from wildly successful public and agency partnerships to dismal
failures where litigation seems to be the only solution. We've pondered, time and
time again, why some public interactions succeed and others fail; why some
proposals move forward and others go to court.
We've analyzed various public involvement models, techniques and
processes, such as focus groups, comment periods, public meetings, even
charettes. Employing different models or processes doesn't seem to make a
significant difference; effective, positive interactions are possible regardless of
the model used. We've come to the conclusion that success is not model-
dependent; the question then remains as to what factors make or break a public
and resource interaction.
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Our success is dependent on processes that bring together people and
information in a way that promotes, encourages, and supports interactions based
on trust. We contend that ethical principles are the framework for establishing
trust. These ethics are the driving force for successful collaboration among
diverse internal and external publics. They are also the driving force in how
information is gathered and shared. In this paper, we advance the premise that
fair, open and honest are fundamental principles that comprise the ethics required
for successful resource decisions. Fair, open, and honest—the basic components
of ethical behavior…that establish credibility... that can lead to trust.
We suggest that, as Leopold stated, a definable ethic is our "mode of
guidance" for natural resource decision-making of the future, and second, that a
fair, open, and honest ethic is that mode. Further, we contend that this ethic is an
action-oriented component, not one in which we simply reflect upon past actions,
but one that we use every day to make critical natural resource decisions.
Even today authors continue to support the notion that ethics are key to
successful leadership...and that’s what we are talking about here: Providing
leadership based in ethics. Authors Kouzes and Posner surveyed thousands of
businesses and government executives over the course of two decades, asking the
question: What values (personal traits or characteristics) do you look for and
admire in your leader? They received over 225 different traits and characteristics.
After a series of analysis, the list was reduced to 20 characteristics with
synonyms for clarification, onto a questionnaire that was then distributed to over
seventy-five thousand people around the globe. The results? Consistently over
time and across continents, honesty ranks the highest, emerging as the single
most important characteristic of a leader. Attributes of integrity and character,
were consistently among the top rated. Constituents, whether internal or external
want their leaders to be ethical. They expect to be included in processes that
recognize and honor the diversity of their contributions. We all want to make
progress in our management efforts and decision-making. We can only do that by
practicing these fundamental principles in our interactions.
Let’s be clear. If your process is not fair, open, and honest, it will not
succeed. If you are not ethical how can you sustain credibility and trust among
your constituents? It’s not that we are purposely or fundamentally unethical. Our
science is intense, dynamic, and complex. Practicing ethical behavior means
paying close attention to all aspects of what we are doing. Ethics provides the
compass that guides our actions through some of our toughest interactions and
management decision.
Principle Ethics in Building Trust
Fair
Being fair means several things. For example:
• Providing realistic opportunities for people to participate.
This means providing times and locations that meets the needs of your
diverse audiences. We might have to acknowledge that sometimes, the high
school playoffs are more important than your public meeting.
• Providing everyone the same information at the same time.
• Providing a safe physical and intellectual environment for the exchange
of ideas.
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• Making sure the people who are affected by your group's decisions, help
make those decisions.
Does everyone have the same opportunity to reflect and respond?
A few self-directed questions are the litmus test for this component of our
ethic. How fair is it for biologists to spend two years in obscurity writing a
species recovery plan, then say to the public, "You have thirty days to review and
comment on this 3-lb document, and, by the way, the clock started ticking last
Thursday when the notice was printed in the Federal Register?"
Does everyone get the information and do they get it at the same time?
How fair is it when we provide information to some and not to others? When
the others suddenly "find out" what's going on, agency credibility is in jeopardy.
Everyone who cares about the issue needs to be involved in the process, not just
the supporters or the locals.
For example, one Resource Manager had his predator control program
suddenly "blow up" when animal rights advocates found out about it at the very
end of the public comment period. When asked why he didn't let national groups
know of the process sooner, the answer was, "Well, everyone around here knew
about it and thought it was OK."
We need to ask ourselves a fundamental question, “Would we consider this
fair if this happened to us?”
Open
The conditions for being open include:
• The process is understandable
• All input is welcome (really welcome)
• All pertinent information is shared
The essence of open is the questions:
Are you really
listening?
Supreme Court Judge Stephen Breyer in his confirmation hearing responded
to the question, "What is the role of the Supreme Court?" He stated eloquently,
"To listen...listening gives dignity to the person being listened to."
In many ways our actions regarding public process have actually trained our
constituents to be skeptical of our public involvement strategies. They have
become wary of agency “input opportunities” as agencies routinely seek input
from the public when a decision has essentially already been made.
Is your process designed to receive information from a diverse
audience?
In most cases, natural resource professionals represent public agencies. The
public has a fundamental right to provide input on issues that affect them. We
need to give them a variety of ways to talk to us-public forums, solicited and
unsolicited surveys and assessments, letters, phone calls, whatever is the outreach
mode of the moment ...and then we need to really listen to their comments and
factor them into public decision processes.
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Is there a process for dealing with the information?
We often tend to seek validation or acceptance of our plan or strategy, rather
than seeking legitimate public input within a truly collaborative process.
Margaret Wheatley in her book Leadership and the New Science says, “No one is
successful if they merely present a plan in finished form to others. It doesn’t
matter how brilliant or correct the plan is – it simply doesn’t work to sign on
when they haven’t been involved in the plan.”
Honest
Honesty, the heart of integrity and subsequently a key element of personal
and agency credibility, is a step along the path to that elusive trust we seek as
Agencies. We are responsible for processes that bring people and information
together in a way that’s clear.
The conditions for being honest are:
• Letting people know what you can and can not do
• Sharing what kind of information and science we have . . . and how
good it is!
• Explaining how information and science will be applied to the
problem
• The timeline … some things take awhile, don’t be afraid to say so
• How we will use their input
Fundamental questions we should ask ourselves are:
Is all the information on the table? Is the information understandable? Clear
to everyone, not just scientists? (would your neighbor understand it?) Have we
shared the alternative and consequences?
At Stake: Credibility
The characteristics of fair, open and honest often overlap as this example
illustrates. In one painfully memorable public meeting, the author asked the
Assistant Director of the agency, five minutes before the meeting began, "What
do we tell them about how their input will be used?" The Assistant Director
shrugged and replied, "It doesn't matter… we cut a deal with all the key players
at three o'clock yesterday." The public input meeting was held anyway, but had
they known the truth, how would those 38 participants have felt about the
fairness, openness, and honesty of that public agency and its process? How much
dignity was afforded to that audience on that day? More than that - why is it
considered acceptable to treat our constituents in that manner?
The examples shared above illustrate a breach of agency credibility.
Credibility is at stake when there is a disconnect between our words and actions.
It is not enough to espouse to these principles as important: we must give voice
to our commitment to them and then set the example with our actions. It is only
through consistent words and actions that we are seen as authentic and thus
credible, in our management efforts. When our actions do not match our words,
our future words become suspect and labeled insincere, ineffective,
untrustworthy, or untruthful. When we are consistent in our words and actions
people are willing to engage with us in future ventures. They say things like, “I
may not agree with the action, but I was treated respectfully”, or “they practice
what they preach”, “it was a tough decision, but at least they were fair about it”.
We all know how quickly news about our interactions travels throughout our
networks. Margaret Wheatley says, “The capacity of a network to communicate
with itself is truly awe inspiring; its transmission capability far surpasses any
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other mode of communication. But a living network will transmit only what it
decides is meaningful”. We want that “meaningful information” traveling
through our agency networks to be that we are fair, open and honest.
If we have no credibility, how can we ever hope to regain the public trust?
When our words and actions don’t match up… when we are not authentic …
people become less willing to engage in any future productive interactions. After
all, in the absence of trust everything we do is perceived manipulation.
We contend that our personal and agency credibility, are on the line every
time we interact with our constituents. We simply cannot afford to be unethical in
our actions.
Trust … A Two-Way Street
You’ve often heard trust described as a two-way street, something that has to
be mutual. The public doesn’t trust government these days for a lot of very valid
reasons! By the same token, Agencies often don’t trust the public ... again, for a
lot of very valid reasons.
Air Force General Chuck Horner, General Schwarzkopf’s Deputy
Commander in the Gulf War, had some interesting comments about one of our
mutual “publics” - the media! When asked, “why the military had such a distrust
of the media?” He could have been speaking for natural resource agencies as well
when he responded:
Fear of the media seems to go with the job description of soldier, sailor, or
airman [we can easily include biologist]. Why? God only knows. When you think
about it, if you can trust the press and the TV commentator to tell the truth, and I
do, then it’s not the media we fear but the American people ... a sad commentary
on our military mid-set.
Sometimes you...we...all of us do asinine things. If you are doing something
stupid, pursuing a poor policy, or wasting taxpayers’ dollars, and the press or
television paints you in an embarrassing light that is probably a good thing. In
the long run, the exposure, no matter how painful, is good for the military and
the nation. If, on the other hand, you are getting the job done skillfully, pursuing
a noble cause, or managing a military operation with efficiency (how rare that
is!), then you have much to gain from media exposure. The American people are
quite capable of judging good and bad for themselves. I guess the bottom line is
we have little to fear if we trust the judgment of the folks who pay the bills.
Individually or as agencies, we may or may not trust our many and varied
publics but we’re pretty sure these days it’s safe to say, the public doesn't trust
us! This mistrust is borne not from an intentional, faulty process, or procedure,
but often of actions that have inadvertently been exhibited by agencies and
individuals that have preceded us (myself included). If we are perceived by our
publics as being unethical we can only dispel that perception by being, from this
point on - fair, open and honest.
However, in discussing this topic with colleagues, we often hear the
complaint, “why should we be ethical in dealing with the public - they aren’t
dealing ethically with us!” Our response is simply “who’s the professional here?
Who should be the first to break the cycle of mistrust ... in order to craft a new
cycle of trust?”
We need public support more than ever to do our jobs, yet in many cases, the
public doesn't trust us as partners and are suspicious of our motives. This
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suspicion destroys our credibility and erodes our capability to manage our natural
resources.
It is clear then, that we need a new approach in natural resource decision-
making, one based on mutual trust between the public and public agencies. We
advocate a new approach that learns from the past, recognizes the complexities of
our current social and biological interactions, and applies a fundamentally ethical
approach to managing our natural resources in the future.
Conclusion
We must begin engaging people in a process that is fair, open, and honest.
This means
● we include everyone in a proactive process
● we are
sincerely listening
● we honor the diversity of ideas
● we engage in truthful dialogue.
Only then, can we can be credible in the eyes of our publics and begin to
regain the trust critical to the health and sustainability of our natural resources.
It only takes one person to make a difference. Several years ago, we
witnessed one courageous agency individual take a stand when these ethical
principles were breached in one small community. The Fish and Wildlife Agency
was in the middle of its angling regulation process. There was a proposed change
in possession limit that would have severely affected the recreation, and
associated business, in a small rural community. The agency had scheduled
routine public meetings in the same large towns they always held them in, and
advertised in the same publications they used every year.
However, one agency staff member, working in the office serving this
community, realized the local folks had not been informed of the proposed
regulation change! He took it upon himself to organize an agency public meeting
in the community by quickly faxing information about the change and the
meeting to community businesses, newspapers, and the radio. He pulled together
biologists to plan and conduct a meeting that would provide a forum for sharing
information and for hearing community members concerns. As you would
imagine the public outcry was swift and loud: “Trying to hide something? Too
little, too late? Our input doesn’t matter? You don’t care about us?” Yes, the
agency had some explaining to do, but they could (and did). At least this state
agency had taken the first step toward handling an issue in an ethical manner!
So what’s next?
We are not expecting you to keep a three-ring binder full of process,
procedure, and policy statements in your head to guide your every natural
resource decision. What we are saying is that there are simply three fundamental
principles that can be tested with some simple questions: Is what we are doing
fair, open, and honest? Is what we are doing perceived by others as fair, open,
and honest?
These are the questions that will keep you grounded in ethical natural
resource management. Will they save us when the issues get hot? Who knows?
We only know what happens when we aren’t ethical in our actions. – our
credibility, and therefore, our trust is destroyed. Ethics is a choice we make and a
trust we keep with those around us.
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General Chuck Horner has one other telling point regarding that elusive
quality we call trust. He says simply, “trust takes time, but when you have it you
have a wonderful gift.”
This is one gift we can give to ourselves … we should make it so.
****************************************
References
Breyer, Stephen. 1995. Televised U.S. Supreme Court confirmation hearings.
Clancy, Tom; with Chuck Horner. 1999. Every Man a Tiger. G.P. Putnam’s Sons.
Faast, T. and Simon-Brown, V. (1999). A Social Ethic for Fish and Wildlife
Management. Journal of Human Dimensions of Wildlife, Fall 1999. v. 4, n. 3, pp 86-
92.
Leopold, Aldo. 1949. A Sand County Almanac. Oxford: Oxford University Press and
Ballantine Books.
Kouzes, J. M. & Posner B. Z. (2002). Leadership the Challenge. San Francisco: Jossey-
Bass
Wheatley, M.J. (1999) Leadership and the New Science. San Francisco: Berrett-Koehler
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Long-term Results of Mitigating Stream
Acidification Using Limestone Sand in St. Mary’s
River, Virginia
Larry O. Mohn
1
, Paul E. Bugas, Jr.
2
, Dawn M. Kirk
3
, and
Daniel M. Downey
4
1
Regional Fisheries Manager, Virginia Department of Game and Inland
Fisheries, P.O. Box 996, Verona, VA. 24486;
2
Senior Fisheries Biologist, Virginia Department of Game and Inland Fisheries,
P.O. Box 996, Verona, VA. 24486;
3
Forest Fisheries Biologist, George Washington/Jefferson National Forest, P.O.
Box 10, Natural Bridge Station, VA. 24579;
4
Professor of Chemistry, MSC 7701, James Madison University, Harrisonburg,
VA. 22807
ABSTRACT—The Virginia Department of Game and Inland Fisheries has been
studying the impacts of acid deposition on the biota of the St. Mary’s River in
Augusta County, Virginia for the past 30 years. During the period preceding
1999, invertebrate diversity decreased by over 50% and the number of fish
species dropped from 12 to 4 with only native brook trout still present in
significant numbers. From 1994 through 1997, the stream experienced
reproductive failure of brook trout for three of the four years. The Department,
along with the U.S. Forest Service who administers the area, agreed that the
cause of the loss of aquatic life was atmospheric acid deposition and that water
quality manipulation was needed to protect the remaining aquatic species as well
as restore species that had been extirpated. In a project designed by James
Madison University (JMU), limestone sand treatment was proposed for mitigation
of the acidity. After much environmental analysis (EA), public debate, and careful
consideration, the project was approved and implemented in March of 1999 with
140 tons of limestone sand introduced to six stream locations within the drainage
using a helicopter. Improvements to water quality occurred immediately, aquatic
invertebrate response was noted within three months and upstream
recolonization of some fish species was observed within six months. Water
chemistry data have been collected and analyzed quarterly by JMU from 22
sampling locations within the wilderness and weekly samples have been
collected at the wilderness boundary. In addition, aquatic invertebrate and fish
populations have been surveyed annually. The pH, ANC, calcium concentrations,
and calcium/hydronium ratios have all increased as a result of the limestone
treatment and have remained at acceptable levels during the 5-year study period.
Aquatic invertebrate diversity recovered to levels not seen in 30 years and brook
trout numbers initially exploded then settled to levels about 50% higher than
long-term pre-treatment averages. In September 2003, Hurricane Isabel dumped
up to 51 cm of rain in the drainage and significantly disturbed stream channels
and riparian vegetation. Despite the catastrophic flood event, the limestone beds
remained intact and continued to provide suitable water quality. The study clearly
demonstrates that this treatment method can provide long-term benefits to
aquatic resources.
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Introduction
Acid deposition has been impacting aquatic resources in the mid-Atlantic and
southeastern United States for at least the past two decades (Herlihy, et al., 1993;
Webb, et al., 1994). The pH of pre-industrial precipitation in Virginia has been
estimated to be in the 5.3 to 5.6 range (Webb, 1987) while recent readings in the
Shenandoah National Park averaged 4.4 (U.S. EPA, 1998). This represents a
tenfold increase in precipitation acidity since the beginning of the 20
th
century.
Acid deposition is not necessarily harmful to aquatic life. A watershed’s
ability to buffer acid deposition determines whether the system suffers long-term
biological degradation. In western Virginia, most of the larger stream systems are
well buffered due to underlying limestone geology, but most of the wild trout
resource occurs on mountain slopes composed of sandstone, quartzite and shale.
These slopes provide limited buffering capacity and are subject to acidification.
In 1987, a synoptic survey of water quality parameters in 350 of Virginia’s 450
wild trout streams was funded by the Department of Game and Inland Fisheries.
The result of that investigation indicated that 78% of the sampled waters had
ANC (acid neutralizing capacity) of less than 100 ueq/L, meaning they were
sensitive to acidification. Of these acid sensitive streams, 11% were already
acidified (ANC< 0). One of these acidified streams was the St. Marys River, once
considered one of the state’s premier wild trout fisheries.
Study Area
St. Marys River is a third order coldwater stream that drains the west slope of
the central Blue Ridge Mountains in southeastern Augusta County, Virginia. Its
27 km
2
watershed is the centerpiece of the 4000 hectare St. Mary’s River
Wilderness Area. St. Mary’s River originates at 951 m above sea level and
descends at a gradient of 39 m/km to its confluence with Spy Run, 11.4 km
downstream. The stream is very scenic with numerous falls, cascades, large
boulders and deep clear pools. The watershed includes five major tributaries. St.
Mary River’s low ANC levels can be traced to the geologic formations that
underlie the upper watershed. Antietam quartzite is the primary rock formation
while formations of Hampton quartzite underlie the upper watersheds of
Sugartree Branch, Mine Bank Creek, Bear Branch, Chimney Branch, and lower
reaches of St. Mary’s (Werner, 1966). Both formations are known to have low
solubility, thus providing few base cations and carbonate to neutralize acidic
input (Downey, 1994).
The St. Mary’s River has long been recognized as one of Virginia’s premier
wild trout fisheries. In 1935 (Surber, 1951), it was reported to support a good
population of wild rainbow trout. By 1948, the lower portions of the stream
began receiving stocked trout as part of the federal/state effort to expand trout
fishing opportunity. The floods of 1969 and 1972 eliminated access for stocking
and the stream reverted to wild trout management. At that time, St. Mary’s River
was one of the few streams in the state that contained reproducing populations of
brook, brown and rainbow trout. It became one of the state’s earliest special
regulation streams when the Department so designated it in 1974 after study and
recommendations by Trout Unlimited. The drainage was later proposed as a
federally designated wilderness and in 1984 became one of Virginia’s first
wilderness areas. The primary feature of the area that drew support for
wilderness designation was the wild trout fishery and the scenic qualities of the
St. Mary’s River.
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Biological Surveys
Surber (1951) provided the earliest data on biological communities in the St.
Mary’s River. He collected detailed aquatic macro-invertebrate data from a
number of sites in both 1936 and 1937. These data provide a valuable baseline
which precedes likely impacts due to industrial based acidification. The
Department of Game and Inland Fisheries collected extensive fisheries and
invertebrate data as part of a statewide trout stream inventory in 1976 (Mohn and
Bugas, 1980). With the designation of St. Mary’s River as an acidified trout
stream by Webb (1987), the Department began a program of intensive fisheries
and invertebrate data collection on a biennial basis from 1986 through 1998.
Since the liming operation in 1999, fish and invertebrate data have been collected
annually.
The 1976 survey by the Department of Game and Inland Fisheries provided
the first recorded fisheries survey of the St. Mary’s River. Six sample stations
were established on the mainstem. These stations were established at
approximately equal intervals along the mainstem from the lower wilderness
boundary to the headwaters (Mohn, et al., 2000). Stations varied in length from
76 to 171 m and included at least three riffle, pool, and run sequences. Block nets
were placed at each end of the sample stations and three-run depletions were
used to estimate fish abundance and biomass. In addition, a Carle sampler (Carle,
1976) was used to collect three 0.26 m
2
invertebrate samples from riffle areas at
each site. This collection technique and the sample locations compared favorably
with methods used by Surber in 1936/37.
Fourteen species of fish have been collected from the St. Mary’s River since
1976 but several are considered transient. The most species collected in any one-
survey year was 12 in 1976. During the pre-treatment survey period 1976 – 1998,
the number of fish species steadily declined from 12 to 4. In addition, several
species, which were found throughout large portions of the drainage in 1976,
such as blacknose dace, fantail darter, and mottled sculpin, had their ranges and
numbers severely reduced. Rainbow trout, for which the St. Mary’s River was
best known, were extirpated from the drainage by 1994. Due to its greater acid
tolerance, the native brook trout remained abundant through 1994. However, the
1996 survey indicated year class failures in two of the previous three years and a
sharp drop in brook trout population numbers. The magnitude of this drop in
population prompted the Department to immediately begin discussions with the
USFS on acid mitigation.
The aquatic invertebrate data have shown a more gradual but no less
significant reduction in both species numbers and diversity (Kauffman, et. al,
1999). Many genera of stonefly, mayfly and caddisfly were extirpated from the
drainage by the mid-1980s while populations of acidophobic taxa such as the
Plecoptera, Leuctra/Alloperla and Chironomidae showed significant increases.
The invertebrate diversity as measured by the Shannon Diversity Index showed a
significant decline throughout the pre-treatment study period (Figure 1).
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Acid Mitigation Methodology
The USFS, Chemistry Department at James Madison University and Virginia
Department of Game and Inland Fisheries have developed a low cost
methodology for treating stream acidification using limestone sand introduced
directly into the stream (Downey, et al., 1994, Hudy, et al., 2000). This
methodology was utilized on March, 1999 when 140 tons of limestone were
placed at six sites within the St. Mary’s River Wilderness Area using a helicopter
(Mohn, et al., 2000). It was estimated that this treatment would effectively
mitigate the impacts of acid deposition for a period of five years. Although the
use of limestone sand has become a commonly used treatment method in this
region of the country, the St. Mary’s River project was unique in that it would
occur within a federally designated wilderness area. In this instance, there are not
only biological and chemical aspects to limestone mitigation, but social, political,
economic, and legal aspects as well. The process for dealing with the issues and
concerns of treating a wilderness stream are described in Mohn, et al. (2000).
The limestone sand mitigation method is based on placing enough limestone
to treat the receiving water for a specified period. In this study, it was estimated
that the treatment would be effective for a period of five years. This calculation is
based on the consumption rate of the limestone at the average annual rainfall for
the drainage. Flow rates for this study period were far from normal. At time of
treatment, the area was in the first year of a severe 4-year drought. That period
was followed in 2002 with one of the wettest years on record and finished in the
fall of 2003 with one of most devastating floods on record. In September 2003,
the St. Mary’s River drainage took a direct hit from Hurricane Isabel. Rain
gauges at the head of the drainage recorded as much as 51 cm of rain within a 18
hour period, far more than fell anywhere else in the storm’s path. This discharge
resulted in major streambed alteration including establishment of new channels
Figure 1
Diversity (Shannon) Index
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
1936 1937 1976 1986 1988 1990 1992 1994 1996 1998 1999 2000 2001 2002 2003
Year
Limed in March, 1999
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and severe downcutting of the channel bed. This event caused concern for the
continued stability and function of the limestone sand beds.
Water Quality Response
Water chemistry monitoring of the St. Mary’s River began in January 1999,
three months before the date of the liming treatment. A sampling site was located
at the lower boundary where the stream exits the Wilderness Area. A staff gauge
was installed here for recording stream discharge on sampling days. Samples
have been collected no less frequently than once a week since the date of liming.
The top graph in Figure 2 provides the observed pH for the 67 months since the
project started. The data points are connected for clarity. A value of pH 5.5 was
chosen as a minimum for protection of certain aquatic insects and fishes that
were native to the St. Mary’s drainage. Figure 2 reveals that the pH values were
often less than the minimum acceptable value at the sampling site prior to the
introduction of limestone. The average value for this period was pH 5.53 +
0.26.
In the 64 months that have elapsed since the liming, the average has been pH
6.14 +
0.30. The bottom graph in Figure 2 shows the peaks and valleys in
measured discharge that accompanied wet and dry periods. The graph ends on
Day 1645 when the flood after Hurricane Isabel destroyed the gauging site.
Storm events generally caused short-term decreases in pH as shown by the
graphs, but even the decreases were significantly mitigated compared to the pre-
liming conditions. The years 2002, 2003 and 2004 have been wet with above
average discharge and it is evident from the data that pH has dropped during that
time period. It is interesting to note that pH remained stable after the Hurricane
Isabel flood, indicating that the limestone sand beds are effect even under
catastrophic conditions. The pH drop, however, does signal a need for reliming.
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Another water quality parameter of interest is the acid neutralizing capacity
(ANC). Figure 3 provides the weekly ANC data on the top graph. The bottom
graph in Figure 3 shows the calculated parameter of calcium to hydronium ion
(Ca/H) ratio versus time. These are included in the same figure because both
parameters are important for assessing the impact of acidity on aquatic life. The
ANC values were quite low for the St. Mary’s River prior to liming, often
showing negative values. The pre-liming ANC average was 2.1 +
5.0 :eq/L. The
low values are the result of a lack of carbonate bearing mineral in the Antietam
formation of quartzite rock that makes up most of the St. Mary’s wilderness
watershed. Thus little natural buffer is available to mitigate acidic inputs. The
post-liming ANC values have increased due to the slow dissolution of the
introduced limestone sand to an average 21.3 +
12.7 :eq/L.. Recently the ANC
values have fallen below the target also indicating that reliming will be necessary
soon.
Biological Response
Post treatment trout biomass and number estimates show a dramatic response
(Figure 4). However, all of this response cannot be attributed to the limestone
treatment as populations began recovery in 1998. Virginia experienced a
prolonged drought period that resulted in stable, low flow, mild winters from
1997 through early 2001. These conditions generally produce exceptional year-
classes of brook trout. In the case of St. Mary’s River and other acidified streams,
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the low flows not only produced good flow conditions for reproduction and
recruitment but the lack of significant rainfall resulted in winter pH values higher
than normal. However, brook trout numbers leveled off in 2002 and 2003, both
high low years, at about 600/km which is about 50% higher than the pre-
treatment average. The sharp decline in 2004 is attributed to the severe impact of
Hurricane Isabel.
Non-game fish species have also shown a recovery. Prior to treatment, St.
Mary’s contained only 4 species of fish with only brook trout present in
significant numbers. The number of species has now increased to 7 (Figure 5)
with most species now present in good numbers at lower sampling sites.
St. Marys Brook Trout Density
0
200
400
600
800
10 0 0
12 0 0
14 0 0
16 0 0
18 0 0
1976 1986 1988 1990 1992 1994 1996 1998 1999 2000 2001 2002 2003 2004
Year
Watershed was limed in March, 1999
St. Marys River - Fish Species Collected
0
2
4
6
8
10
12
14
1976 1986 1988 1990 1992 1994 1996 1998 1999 2000 2001 2002 2003 2004
Ye a r
Number collected
Limed in March, 1999
Figure 4
Figure 5
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Wild Trout VIII Symposium (September 2004)
The aquatic invertebrate populations, as measured by the Shannon diversity
index, has been our most reliable indicator of stream decline over the history of
our studies of the St. Mary’s River. It is interesting to note that the index
rebounded to 1976 levels within only 3 months of treatment (Figure 1) and has
remained fairly consistence throughout the study period.
Conclusion
The use of limestone sand has proven to be an effective and cost efficient
method of treating stream acidification. Stream discharge has varied significantly
during the study period, yet the treatment remained effective at mitigating
acidification. Despite a catastrophic flow event late in the study, the limestone
sand beds remained intact and continued to be effective. The original
methodology (Mohn, et.al., 2000) used to estimate the quantity of limestone
needed to cover a minimum five-year treatment period appears to have been
appropriate. The data indicate the need to add additional lime in the near future.
References
Carle, F. L. 1976. An evaluation of the removal method for estimating bentic populations
and diversity. M.S. Thesis, Virginia Tech, Blacksburg, VA. 170 pp.
Downey, D. M. 1994. Mitigation of acid degradation of Coles Run and Mills Creek
Lakes. Report to the Environmental Protection Agency, Clean Lakes Grant Program,
James Madison University, Harrisonburg, VA. 199 pp
Downey, D. M., C. R. French and M. Odom, 1994. Low cost limestone treatment of acid
sensitive trout streams in the Appalachian Mountains of Virginia. Water, Air and
Soil Pollution, 77: 49-77.
Herlihy, A. T., P. R. Kaufmann, M. R. Church, P. J. Wigington, Jr., J. R. Webb, & M. J.
Sale. The effects of acidic deposition on streams in the Appalachian Mountian and
Piedmont region of the mid-Atlantic United States. Water Resources Reseach 29:
2687-2703.
Hudy, M., D. M. Downey & D. W. Bowman. 2000. Successful restoration of an acidified
native brook trout stream through mitigation with limestone sand. North American
Journal of Fisheries Management 20: 453-466.
Kauffman, J. W., L. O. Mohn, & P. E. Bugas, Jr. 1999. Effects of acidification on benthic
fauna in St. Marys River, Augusta County, Virginia. Banisteria, No. 13: 183-190.
Mohn, L. O., & P. E. Bugas, Jr. 1980. Virginia trout stream and environmental inventory.
Final Federal Aid Report F-32, Department of Game and Inland Fisheries,
Richmond, VA. 70 pp.
Mohn, L.O., P.E. Bugas, Jr., D.M. Kirk, & D.M. Downey 2000. Mitigating stream
acidification in a wilderness watershed using limestone sand. Wild Trout VIII. 274pp.
Surber, E. W. 1951. Bottom fauna and temperature conditions in relation to trout
management in St. Mary’s River, Augusta County, Virginia. Virginia Journal of
Science 2: 190-202.
U. S. Environmental Protection Agency. 1998. National Atmospheric Deposition
Program. http://nadp.sws.uiuc.edu/isopleths/maps1996/fldh.gif.
Webb, J. R. 1987. Virginia trout stream sensitivity study, 1987: Summary report to the
Virginia Department of Game and Inland Fisheries, University of
Virginia,Charlottesville,VA.4 pp
Webb, J. R., F. A. Deviney, J. N. Galloway, C. A. Rinehart, P. A. Thompson, & S.
Wilson. 1994. The acid-based status of native brook trout streams in the mountains
of Virginia, a regional assessment based on the Virginia trout stream sensitivity
study. Report to the Virginia Department of Game and Inland Fisheries. 75 pp.
Werner, H. J. 1966. Geology of the Vesuvius quadrangle, Virginia. Virginia Division of
Mineral Resources, Charlottesville, VA. 53 pp.
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Wild Trout in an English Chalk Stream: Modeling
Habitat Juxtaposition as an Aid to Watershed
Rehabilitation
A. Burrows
1
, S. Kett
2
, and M. A. House
2
1
University Field Station – Loch Lomond, Rowardennan, Glasgow, Scotland, UK,
G63 0AW. Tel. 01360 870515, Fax 01360 870381. troutdoctor@hotmail.com
2
Flood Hazard Research Centre, Middlesex University, Queensway, Enfield
London, UK, EN3 4SF. tel. 020-8411-5359, fax. 020 8411 5403,
ABSTRACT—Wild brown trout (Salmo trutta, Linnaeus, 1758) populations in
southern England are subject to both habitat degradation and overstocking, even
in the internationally famous streams where dry fly-fishing began. Habitat
rehabilitation within such degraded watersheds can be improved by better
understanding the integration of habitat and ecological processes operating
simultaneously at a range of scales. We quantify the influence of local meso-
habitat juxtaposition upon wild brown trout population dynamics in two
contrasting sectors of the River Piddle, Dorset, UK. Sectors examined represent
‘typical’ semi-natural chalk-stream conditions in the Piddle/Frome Watershed.
PHABSIM was used to model meso-scale habitat composition (WUA) and habitat
durations, which were tested for correlation against age-specific trout densities,
obtained from eight years quantitative electrofishing data. Analyses indicate; (1)
availability and location of marginal meso-habitats with abundant cover is critical
to adult over-winter survival and (2) appropriate juxtaposition of spawning and
rearing meso-habitats strongly influence juvenile brown trout recruitment. In the
light of these data we examined the potential for integrating meso-habitat
juxtaposition into initial design stages of river rehabilitation schemes. We argue
that such an approach should form an integral component of watershed
restoration strategies as it offers effective manipulation of natural mechanisms
regulating brown trout populations at a multi-scalar level.
Introduction
The brown trout (Salmo trutta Linnaeus 1758.) is a polymorphic species
indigenous to British rivers but there is considerable evidence of widespread and
on-going decline in the status of wild stocks (Giles, 1989; Crisp, 1989).
Anthropogenic influences destructive to river channel structure and ecosystem
function cause widespread and severe loss of salmonid habitats (Crisp, 1989;
White, 2002). In the UK, rivers have been so modified and engineered for
purposes such as flood defence, land drainage and navigation that few can be
regarded as in a “pristine” condition (Brookes and Shields, 1996). In recent
decades, increasing development of floodplains has increased the need for river
engineering to improve flood defence. Population growth, particularly in the south
of England, has increased pressure on groundwater resources. In addition, on-
going degradation of logic environments is largely due to agricultural land use
practises associated with intensification under the EU Common Agricultural
Policy (CAP). Large scale dredging programmes in the 1950’s and 1960’s aided
wetland drainage in order to bring fertile floodplain land into production. Soil
erosion from ploughed arable land increases sediment supply to rivers and
exacerbates problems of eutrophication caused by intensive application of
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fertilisers. Destruction of river banks by sheep and dairy cattle in over-grazed
riparian zones has become a major source of habitat loss everywhere from
southern chalk streams to Scottish mountain burns. The recent “Salmon and
Freshwater Fisheries Review” (Warren, 2000) recognised the need to place
habitat enhancement at the core of wild stock conservation and recommended
urgent research into factors affecting long-term sustainability and effectiveness
of habitat restoration as a fisheries management tool. In this context the present
study addresses the response of a wild brown trout population to temporal and
spatial variation in stream habitat and, in particular the influence of local meso-
habitat juxtaposition on population structure in a small chalk-stream.
The Study Area
The River Piddle is a third order stream draining a catchment of Upper
Cretaceous Chalk approximately 183 km
2
in area and flows approximately 40 km
south and east to form a common estuary with the River Frome, before
discharging into the English Channel via Poole Harbour. Land use on the
floodplain is predominantly permanent pasture and arable land. The Piddle is a
typical “chalk stream” characterised by low mean gradient (2.18m/km) and base-
rich alkaline waters (CaCO3 > 200 mg/l). Groundwater rises at a relatively
constant 9-10
o
C throughout the year maintaining stable seasonal and diel
temperature regimes. The buffering effect of the aquifer produces a stable flow
regime with an absence of extreme low flows and sudden spates. Winter high
flows rarely exceed bankfull stage and summer base flows are maintained by
groundwater (Mann et al.,1989). Long-term mean monthly flows at Tolpuddle
(1965-2000) range from 0.18 m
3
/s in August/September to 2.4 m
3
/s in February.
Median flow (Q50) over the period is 0.54 m
3
/s. Primary production is dominated
by large aquatic macrophytes, mainly Ranunculus spp. which supports high
macroinvertebrate productivity forming the basis of trout diet (Maitland and
Campbell, 1992). Dominant fish species are resident and anadromous brown
trout and Atlantic salmon, with minnow, bullhead, stone loach, pike, and eel
common (Strevens, 1999).
The morphology of low gradient chalk streams tends to produce more habitat
features, such as undercut banks, trench pools and low width-depth ratios, in
comparison to moderate gradient reaches, and these features are positively
correlated with a high mean standing stock of trout (Kozel et al., 1989).
However, the Piddle has suffered many problems common to intensively farmed
lowland catchments. Physical habitat degradation from overgrazing resulting in
loss of riparian vegetation has led to widespread channel over-widening and
increased sedimentation. Habitat diversity has been lost due to historical
anthropogenic manipulations particularly associated with milling, irrigation and
land drainage. Run-off from agricultural land has caused siltation problems
detrimental to salmonid spawning (Crisp, 1989) and elevated nitrate levels have
resulted in widespread algal colonization of substrates. The catchment is heavily
abstracted for a variety of water uses which has exacerbated low flow problems
since the mid-1980s. This has had significant ecological impacts including severe
reduction in juvenile trout habitats over a 10-km length of the middle river
(Strevens, 1999).
A programme of physical restoration was initiated at Tolpuddle in 1994
primarily to restore channel diversity and improve spawning habitat and refugia
for larger wild trout (Summers et al., 1996; Summers et al., 1997). Fencing and
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substrate re-distribution using current deflectors and weirs were the most
commonly used techniques (Langford et al., 2001). The fishery has been
managed for over twenty years on a “catch and release” basis and retains a
significant self-sustaining population of native resident and anadromous brown
trout, which is not subject to angler harvest, or stocking of hatchery trout. Pike
(Esox lucius) which were present prior to 1993 were removed and subsequently
controlled to alleviate the effects of piscivorous predation and physical habitat
was assumed to be the most important population-limiting factor. The study site
comprised two main stem river sectors approximately 2 km apart and 0.5 km in
length both divided into 4 electrofishing sections. The trout population was
monitored annually by electrofishing in early autumn over the period 1993-2001.
Methods
Two representative reaches of contrasting habitat characteristics and
population dynamics were selected for both sectors for application of the
Physical Habitat Simulation Model (PHABSIM). Both reaches were coincident
with electrofishing sections. Sector 1 was of higher habitat diversity flowing
through fenced open pasture with a trout population dominated by adults. Sector
2 was more uniform, partly over-shaded by riparian trees and consisted
principally of age 0+ and 1+ trout.
Hydraulically linked transects were used to characterize hydraulic and
physical habitat attributes of each study reach in accordance with PHABSIM
requirements (Bovee et.al., 1998). Transects were placed to represent
mesohabitat types present in approximate proportion to the contribution of each
habitat type to the total make-up of the river sector. Approximate cell boundaries
were determined from habitat mapping and located at intervals ranging from 5 –
23m depending on microhabitat complexity. All mesohabitats present were
represented by at least one transect to accurately represent habitat availability and
continuity thus ensuring that habitat juxtaposition was accurately sampled. Field
measurements of depth (cm), and mean column velocity (m/s) at 0.6 depth at
each transect were taken for a minimum of three discharges over one
hydrological cycle as outlined by Bovee et al. Substrate and cover were measured
twice (summer and winter) at corresponding intervals between 0.3 – 0.6 m along
transects to define a series of cells around measurement points. Hydraulic models
were calibrated using standard procedures described by Elliott et al, (1996). The
stage discharge and water surface profile models were used to simulate hydraulic
characteristics for each cell at specified discharges, the latter being more reliable
for simulating flows above the highest calibration flow. Category 2 Habitat
Suitability Criteria developed for brown trout on the River Piddle (Bird et al,
1995) were used in the HABTAE programme to calculate composite suitability
indices for cells that were aggregated to derive total Weighted Useable Area
(WUA) and mesohabitat WUA for each reach.
Time series were derived from habitat (WUA) – flow functional relationships
in order to show duration and extent of habitat availability. Monthly time steps
were aggregated into seasonal time steps as follows; (1) winter habitat durations
(Nov – Mar) for spawning/incubation and adult life stages (2) summer growing
season habitat (June – Oct) for fry and adult life stages. Habitat specific time
series were also generated for meso-habitat types using the same procedure.
Indices of habitat availability were developed representing different perspectives
of the time series for each trout life stage. For example, habitat shortages during a
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Wild Trout VIII Symposium (September 2004)
particular season were evaluated using minimum habitat to represent acute low
habitat events and the mean of the lowest 50% of values was used to depict
longer-term effects of habitat minima. Habitat metrics were also developed for
“near-shore” zones within 2 metres of the bank to evaluate importance of
marginal habitats and for specific meso-habitat types. Length-frequency
histograms of trout numbers allowed three age cohorts to be identified
corresponding to fry (age 0+), juvenile trout (age 1+), and adult trout (age >1+).
Trout abundance (N) in each age class was expressed in terms of density (N/m
2
)
to take account of variations in area between reaches and was used to assess
annual changes in population structure in response to temporal habitat variations.
Linear regression analyses and Pearson correlation coefficients (r) were used
to test for association between age specific trout densities and habitat (WUA).
Where appropriate habitat data were natural log transformed in cases where
variances exceeded mean values in order to stabilise variance and approximate a
normal distribution, as in Nehring and Anderson (1993). The nature of the
variables was such that associations could be assumed to be uni-directional and
thus one-tailed tests of significance were employed. Relationships where p < 0.05
were considered to be significant.
Results
Adult Trout
Winter habitat durations (Nov – Mar) demonstrated effects of low mean
monthly flows (MMF) in winter in depressing adult habitat availability.
Moderate to high winter flows (MMF>1.0m
3
s
-1
) made little difference. Time
series for streamside marginal habitats indicated these were a critical resource for
adults in winter (fig. 1). Seasonal variations in marginal habitat showed that adult
habitat availability was greater in winter than in summer, winter habitat
exceeding summer habitat 80% of the time.
0
200
400
600
800
1000
1200
1400
93/4
94/5
95/6
96/7
97/8
98/9
99/00
Years
Weigthed Useable Area (WUA =
sq.m/km)
Winter (Nov - Mar) Summer (Jun - Oct)
Fig 1. Time series comparison of mean monthly marginal habitat durations for
adult trout in summer and winter
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Adult densities were strongly correlated with winter habitat metrics (fig. 2)
but no significant relationships with summer habitat were present in any study
reaches. Availability of high quality marginal habitats in winter accounted for
91% of variation in adult densities in the upper sector but there were no
associations with mean winter habitat suggesting overall habitat availability was
relatively unimportant for adults compared to marginal habitats.
R
2
= 0.9207
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
60 70 80 90 100 110 120 130 140
WUA (sq.m)
DENSITY (per 100m)
TOLPUDDLE COBBS
Fig 2. Relationship between annual adult density (1994 – 2000) and mean
marginal habitat winter (WUA) for adults
Juveniles Trout: Spawning
Riffle zones provided better quality spawning than glides and pools over
most of the simulated flow range except at very low winter flows (below 0.2
m
3
/s) when glides provided the best areas (fig. 3). Most spawning habitat was
consistently available when winter flows fluctuated between approximately 0.5 –
2.0 m
3
/s showing the importance of a stable flow regime over the egg deposition
to hatching period. Moderate flows during incubation, hatching and swim-
up/dispersal of fry (Jan – Mar) resulted in the strongest 0+ year classes.
0
1
2
3
4
5
6
7
00.511.522.533.5
Discharge (cumecs)
Weigthed Useable Width
GLIDES POOLS RIFFLES
Fig 3. Habitat - discharge relationships for selected meso habitats
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Wild Trout VIII Symposium (September 2004)
During the critical (hatching) period in February/March, mean spawning
habitat availability in riffles was significantly correlated with densities of 0+
trout accounting for 65% of variability (F=9.33; p=0.028) (fig. 4). Mean riffle
habitat was more highly correlated with fry density than total spawning WUA
during the same period (r
2
= 0.65; p = 0.014 and r
2
= 0.59; p=0.025 respectively).
There were no relationships with spawning metrics for other time periods.
Densities of trout age 1+ the following year were significantly correlated with
riffles and glides but showed a stronger association with glides. Mean glide
hatching period (r
2
= 0.74, p=0.014) was virtually as good a predictor of juvenile
density as total mean hatching period in the upper sector (r
2
= 0.82, p=0.006).
R
2
= 0.6503
-0.5
0
0.5
1
1.5
2
55 55.5 56 56.5 57 57.5 58 58.5 59 59.5
Riffle WUA (spawning hatching period)
0+ density (per 100m)
Fig.4. Relationship between spawning habitat in riffles during
incubation/hatching period (February/March) and 0+ densities the following
September
Juveniles Trout: Summer growing season
R
2
= 0.4869
0
0.5
1
1.5
2
2.5
3
0 500 1000 1500 2000 2500 3000 3500
Minimum Fry WUA (summer)
0+ density (per 100m)
Fig. 5. Relationship between minimum fry rearing habitat during the first
summer and 0+ density in September
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Young-of-year habitat during the first growing season was positively
correlated with 0+ fry densities in both reaches. Average summer habitat (July –
September), summer minima and near shore habitat metrics were the best
predictors of fry densities. Habitat predictions for young-of-year growing season
combined for all reaches produced significant correlations with 0+ densities (r
2
=
0.49; p=0.001). Minimum monthly habitat availability was the best predictor of
fry densities, accounting for 49% of variance (F= 18.1; p<0.01) (fig.5).
In the lower sector all meso-habitat metrics (except maxima) were
significantly positively correlated with 0+ density for the three meso-habitat
types present (riffles, glides, flats) but no one habitat type was found to be more
important. Time series analysis of meso-habitat durations indicated that spawning
habitat was in the order of 50% greater in riffles relative to glides but glides were
more important as summer rearing habitats (fig. 6).
94
95
96
97
98
99
0
50
100
150
200
250
Weighted Useable Area
Years
RIFFLE FLAT GLIDE
Fig 6. Time series (1994 – 1999) showing variations in summer habitat (WUA)
for 0+ trout during the first growing season (June – October) in selected
meso habitat types.
Metrics developed for a glide-riffle-glide habitat assemblage, which
represented the best juxtaposition of rearing habitats significantly explained
between 30 – 44% of variance in 0+ and 1+ densities. The best overall predictor
of 0+ densities across all reaches was a combination of spawning WUA during
the critical hatching period and minimum rearing habitat availability in summer.
A multiple regression model indicated these two metrics explained 68% of
variation in 0+ densities (F=19.28; p<0.01).
Discussion
Analysis of population data suggested population size was primarily
regulated by year on year variations in recruitment of 0+, which showed an
increasing trend with time and increased in relation to spawning stock size.
Substantial increases in the ratio of adults to young-of-year in the Lower sector
indicated pike predation was probably a major population-limiting factor at the
commencement of the study period. Trout biomass becomes asymptotic in later
years indicating that, even in high productivity chalk streams, density can have a
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major effect on growth, and that biological productivity may have become a
more important limiting factor than physical habitat in the Lower River.
However, availability of spawning and rearing areas played a fundamental
role in limiting 0+ recruitment, especially where local recruitment was evident.
Our findings indicated that juxtaposition of spawning and rearing meso-habitats
strongly influenced juvenile brown trout recruitment. The importance of riffles
and glides was evident and the significance of longer-term summer habitat
minima associated with low flows in the first growing season was marked,
especially in the lower sector where 0+ densities were highest. This is in line
with the findings of Elliott (1994) who demonstrated that spawning success in a
Cumbrian stream had no effect on densities of surviving fry, which were
regulated by density-dependent mortality in response to low amounts of nursery
habitat. Time series of meso-habitat durations for young-of-year showed
significant increases in contributions of riffles and glides to summer habitat in
later years (Fig. 6). This reflects the role of flow augmentation in reducing
critical low flow periods and consequent habitat depletion that caused widespread
reductions in juvenile stocks throughout the middle catchment up to the mid
1990’s (Strevens, 1999). These habitat increases corresponded with ongoing
upward trends in 0+ densities throughout the study area over the survey period.
The high densities of 0+ and 1+ trout in the lower reach demonstrated
competitive segregation with juveniles dominant in the upper part and fry in the
lower part. 1+ trout tend to be dominant and expel 0+ fry to shallow riffles and
low velocity river margins where they are most commonly found (Bohlin, 1977;
Cunjak and Power, 1986). In the upper sector where 0+ recruitment was low, the
importance of spawning riffles to year class strength was more apparent, possibly
due in part to lower availability of early rearing habitat and intra-specific
competition between fry and parr.
Adult brown trout normally maintain station close to a shelter (Boussu, 1954;
Heggenes, 1988b) and availability and diversity of cover have a significant effect
on population density by increasing the numbers of territories and hence stream
carrying capacity. In the Upper sector where the relative proportion of adults was
higher, winter availability of meso-habitats associated with abundant marginal
cover were critical to over-winter survival. Brown trout tend to have a strong
preference for positions beneath overhead cover (Lewis, 1969), either above
stream cover (<1m) or in-stream submerged cover. In summer, overhead cover
provides shading that is important to adult trout, which become increasingly
negatively phototropic as they develop progressively stronger shelter seeking
behaviour with age (Bachman, 1984; Bagliniere and Maisse, 1999). In chalk
streams, expansive tresses of ranunculus providing both velocity shelter and
submerged overhead cover are abundant throughout the channel in summer. This
abundance together with the relatively lower importance of “edge” habitats
probably explains why no relationships with adult population size were observed.
In winter, overhead cover can become a critically limiting resource often
restricted to the stream margins where die-back of lush emergent marginal plants
creates long tangled rafts of weed which snag around obstructions and woody
debris creating complex cover zones of overhead and obstacle cover. When
combined with sufficient depth these “features” provide excellent winter refugia
for larger trout. Cunjak and Power (1986) demonstrated that association to cover
was significantly greater in winter than summer for brown trout and that
submerged cover was utilised more frequently than above water cover (Cunjak
and Power, 1987). Low water temperatures may encourage adults to seek out
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299
habitats characterised by slower velocities than preferred in summer in response
to reduced nutritional requirements, drift availability and the need to conserve
energy (Cunjak and Power, 1986). Territorial behaviour also tends to decrease as
temperatures fall and feeding ceases with the onset of winter (Mason and
Chapman, 1965; Cunjak and Power, 1986). The lack of variation in adult
densities and the strength of the association with marginal cover (r
2
= 0.92)
suggest that available winter habitat is the primary factor limiting adult carrying
capacity at the reach scale. Our findings support the view that submerged cover is
an important factor effecting winter survival of salmonids and that in small
lowland streams marginal cover is a critical determinant of carrying capacity.
A juxtaposition of micro-habitats comprising a variety of specific stations
used at different times makes up a trout “home range” (Shirvell and Dungey,
1983). The limited movement of resident brown trout in chalk streams (Soloman
and Templeton, 1976) suggests habitat selection that enables trout to complete
their life cycles within a relatively “local” area (Bachman, 1984). Thus, habitat
juxtaposition is important in mitigating life history strategies of brown trout
populations. Greater habitat diversity increases the likelihood that a self-
sustaining population will be maintained by “local” adult stock. Furthermore,
better understanding of the importance of different meso-habitat combinations
for different life stages offers a means of enabling river rehabilitation schemes to
more effectively manipulate natural population regulating mechanisms.
References
Bachman, 1984. Foraging behaviour of free ranging wild and hatchery brown trout.
Transactions of the American Fisheries Society 113: 1-32.
Bagliniere and Maisse, 1999. Biology and ecology of the brown and sea trout. Springer
Bird, Lightfoot and Stevens, 1995. Microhabitat use by young salmon and trout in a
southern UK chalkstream. Proc. Inst. Fisheries Management. 25
th
Annual Study
Course, 99 -113.
Bohlin, 1977. Habitat selection and intercohort competition of juvenile sea trout. Oikos
29: 112-117.
Bovee, Lamb, Bartholow, Stalnaker, Taylor and Henriksen, 1998. Stream habitat analysis
using the instream flow incremental methodology. USGS, Biological Resources
Division Information and Technology Report USGS?BRD-1998-0004.
Boussu, 1954. Relationships between trout populations and cover on a small stream.
Journal of Wildlife Management 18: 229-239.
Brookes and Shields, 1996. River channel restoration. Wiley Crisp, 1989. Some impacts
of human activity on trout populations. Freshwater Biol. 21:1, 21 – 33
Cunjak and Power, 1986. Winter habitat utilisation by stream resident brook trout and
brown trout. Canadian Journal of Fish and Aquatic Science 43: 1970-1981.
Cunjak and Power, 1987. Cover use by stream resident trout in winter: a field
experiment. North American Journal of Fisheries Management 7: 539-544.
Elliott, 1994. Quantitative ecology and the brown trout. Oxford University Press
Elliott, Johnson, Sekulin, Dunbar and Acreman, 1996. Guide to the use of the Physical
Habitat Simulation System. Ecologically Acceptable Flows Phase 2. Environment
Agency R&D Technical Report W20.
Giles, 1989. Assessing the status of British wild brown trout stocks: a pilot study utilising
data from game fisheries. Freshwater Biology 221: 125-133.
Heggenes, 1988b. Physical habitat selection by brown trout in riverine systems. Nordic
Journal of Freshwater Research 64: 74-90.
Kozel, Hubert and Parsons, 1989. Habitat features and trout abundance relative to
gradient in some Wyoming streams. Northwest Scientist 63: 175-182.
Session 5—Contributed Papers
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300
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Wild Trout VIII Symposium (September 2004)
Langford, Somes and Bowles, 2001. Effects of physical restructuring of channels on the
flora and fauna of three Wessex Rivers. Report of Pisces Conservation Ltd.
Lewis, 1969. Physical factors influencing fish populations in pools of a trout stream.
Transactions of the American Fisheries society 98: 14-19.
Maitland and Campbell, 1992. Freshwater Fishes of the British Isles. HarperCollins.
Mann, Blackburn and Beaumont, 1989. The ecology of brown trout in English
chalkstreams. Freshwater Biology 21: 57-70.
Mason and Chapman, 1965. Significance of early emergence, environmental rearing
capacity and behavioural ecology of juvenile coho salmon in stream channels. J of
the Fish. Res. Board. Of Canada 22; 173-190.
Nehring and Anderson, 1993. Determination of population limiting critical salmonid
habitats using PHABSIM. Rivers 4: 1-19.
Shirvell and Dungey, 1983. Microhabitats chosen by brown trout for feeding and
spawning in rivers. Transactions of the American Fisheries Society 112: 355-367.
Soloman and Templeton, 1976. Movements of brown trout in a chalkstream. Journal of
Fish Biology 9: 411-423.
Strevens, 1999. Impacts of groundwater abstraction on the trout fishery of the River
Piddle, Dorset; and an approach to their alleviation. Hydrological Processes 13: 487-
496.
Summers,Giles and Willis,1996.Restoration of riverine trout habitats. Environment
Agency R&D Report 18
Summers, Shields, Phillips and Giles, 1997. River Piddle trout study. Draft Progress
Report. Game Conservancy Trust.
Warren (2000) Salmon and Freshwater Fisheries Review. Report of Review Group.
Ministry of Agriculture Fisheries and Food. HMSO.
White, 2002. Restoring streams for salmonids; where have we been? Where are we
going? Proc. Of 13
th
International Salmonid Habitat Enhancement Workshop.
Central Fisheries Board, Ireland.
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301
Volunteers as an Integral Component of the
Fisheries Program in Yellowstone National Park
T.M. Koel and T.R. Bywater
Fisheries and Aquatic Sciences Section, Center for Resources, P.O. Box 168,
Yellowstone National Park, Wyoming 82190, todd_koel@nps.gov
ABSTRACT—During the past decade, integrity of Yellowstone National Park
aquatic resources has been threatened by a convergence of nonindigenous
species. Priorities for research and monitoring have shifted and a majority of
funding for fisheries in Yellowstone is now directed at the new emerging crises.
At the same time, there are many basic questions regarding park fisheries that
require immediate attention. To address this issue, a new program was
established that brings dedicated volunteers, mostly from the angling community,
to Yellowstone where they can participate as a member of a team directed at
projects using fly-fishing as a collection technique. In 2002 and 2003, 114 fly-
fishing volunteers from throughout the United States assisted with several
specific fisheries projects, directed at genetic status, life history patterns, and
species composition. The fly-fishing volunteer program has been successful at
educating the public about fisheries issues in Yellowstone while providing a
useful database of information for park biologists, garnered through stream and
lake sampling with rod and reel. Future efforts will include a study where fish
population information as measured by electrofishing is compared to that
collected by fly-fishing. If similarities exist, angling could potentially be used to
estimate other important fish population metrics.
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Wild Trout VIII Symposium (September 2004)
Population Trends and an Assessment of Extinction
Risk for Westslope Cutthroat Trout in Select Idaho
Waters
D.J.C. Schill, E.R.J. M. Mamer, and T.C. Bjornn
Idaho Department of Fish and Game, Nampa, Idaho and University of Idaho,
Cooperative Fish Research Unit, Moscow, Idaho
ABSTRACT—Despite westslope cutthroat trout (Oncorhynchus clarki lewisi)
being petitioned for listing under the Endangered Species Act, formal evaluations
of extinction risk for the sub-species have been quite limited. In this study, we
summarize existing population trend data for westslope cutthroat trout, use the
trend data to estimate population growth rates, and combine these with various
likely initial population sizes to assess generalized extinction risk for westslope
cutthroat trout within select Idaho drainages. Population data consisted of over
30 years of snorkel trend counts for westslope cutthroat trout across a broad
geographic area in Idaho. Results of trend analysis including both inspection of
graphs, and calculation of infinitesimal growth rates, indicate that westslope
cutthroat trout have maintained or increased their population abundance over a
large area within the state of Idaho during the past 15-34 years. Total estimates
of westslope cutthroat trout numbers within various Geographic Management
Units (GMU’s) conservatively range from 6,500 to 341,000 fish, with a combined
estimate of approximately 1.2 million fish for the GMUs considered in this study.
Mean sub-basin population size ranged from about 400 to 13,000 fish.
Population persistence for 100 years ranged from high to low for various
individual local populations. However, the study results suggest that numerous
sub-populations within most GMU’s, available to interact within a classic or less
traditional metapopulation framework, would result in a high (>
95%) probability
of westslope cutthroat trout persistence over 100 years.
Introduction
The westslope cutthroat trout (Oncorhynchus clarki lewisi) is one of two
recognized sub-species of cutthroat trout residing in the Columbia and upper
Missouri river basins. Although westslope cutthroat trout have been the subject
of numerous localized investigations, relatively few authors have focused on
general sub-species status on a broad geographic scale. McIntyre and Rieman
(1995) noted that range declines have occurred across historic westslope
cutthroat trout range. Causes of declines include predation by, and competition
with exotic native species, overharvest, genetic introgression, habitat degradation
and fragmentation (Liknes and Graham 1988; Rieman and Apperson 1989;
Thurow et al 1997).
Westslope cutthroat trout were petitioned for listing under the Endangered
Species Act in 1997. This petition was initially found to be unwarranted by the
United States Fish and Wildlife Service (USFWS) which concluded that a large
number of westslope cutthroat trout populations exist across the sub-species
range (Federal Register 65Fed.reg.20120). However, a subsequent legal decision
required the USFWS to reevaluate the status of westslope cutthroat trout. Results
of the second evaluation completed in 2003 also concluded that the sub-species
does not need ESA protection (Federal Register 68.reg.46989).
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Despite two formal ESA reviews, quantitative evaluations of extinction risk
for westslope cutthroat trout populations using Population Viability Analysis
(PVA) have been quite limited. McIntyre and Rieman (1995) summarized data
for 6 westslope cutthroat trout populations in Idaho and Montana, and calculated
variances of infinitesimal rate of growth. Using the modeling approach of Dennis
et al. (1991), the authors concluded that stochastic extinction risk will increase
sharply for populations that drop to fewer than 2000 individuals. They assumed
their study populations varied around an equilibrium with no long-term trend in
population number. Thus, their results represent risk associated with random and
not deterministic factors. Using a complex Bayesian modeling approach, Shepard
et al. (1997) estimated extinction probabilities for 144 westslope cutthroat trout
populations in the upper Missouri River basin in Montana. Ninety percent of the
populations evaluated had a high or very high probability of going extinct during
100 years based on model projections.
The studies of McIntyre and Rieman (1995) and Shepard et al. (1997)
suggest that some westslope cutthroat trout populations could be in jeopardy of
extinction but the applicability of those findings to the entire sub-species range is
unknown. For example, Shepard et al. (1997) noted that most of the populations
considered in their study were small and resided in isolated headwater stream
segments less than 10 km long. In Idaho, the presence of fluvial populations in
large river systems within the Federal Wilderness system with histories of
restrictive fishing regulations dating back 30 years or more may provide
increased population resiliency.
In this study, we 1) summarize existing population trend data for westslope
cutthroat trout to provide perspective on their current status in Idaho, and 2) use
these trend data to estimate population growth rates and combine these with
rough approximations of population sizes to assess generalized extinction risk for
westslope cutthroat trout within select Idaho drainages.
Methods
Population Trends
Historical snorkel counts
With assistance from IDFG personnel, we summarized snorkeling data
collected over three decades from mainstem river sites in four westslope
cutthroat trout streams including the St. Joe, Coeur d’Alene, Selway, and Middle
Fork Salmon rivers. Snorkeling techniques used on these rivers are similar and
described in detail in Rankel (1971), Corley (1972), Lindland (1974), and
Johnson and Bjornn (1978). Briefly, one or two divers float downstream counting
all westslope cutthroat trout observed, either in the entire stream channel or
within prescribed counting lanes.
Snorkel counts were begun on 27 sites on the mainstem St. Joe River in
1969, 29 mainstem and tributary sites on the Coeur d’Alene River in 1973, 27
sites on the Selway River in 1973, and 12 sites on the Middle Fork Salmon
(Figure 1). Snorkel site lengths and/or counting lane widths were measured
periodically during the sampling periods to ensure the same reaches were being
sampled and to enable calculation of fish densities (fish/100m
2
).
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Wild Trout VIII Symposium (September 2004)
Figure 1. Location of historical snorkel count sites used to monitor westslope
cutthroat trout abundance in Idaho, 1969 to present.
General Parr Monitoring counts
In addition to the above historical counts, a sizeable number of additional
snorkel count sites have been established for a shorter time across many waters
within westslope cutthroat trout range in Idaho. Since 1985, these trend counts
have been conducted by IDFG personnel funded via several Bonneville Power
Administration-funded research projects as part of what has been termed General
Parr Monitoring (GPM). Although originally designed to track trends for
anadromous species, observations on all resident fish present have been recorded
as well. The dataset contains cutthroat trout density estimates for a few mainstem
river sites, but the bulk are conducted in smaller tributary streams typically
snorkeled by crawling upstream. Petrosky and Holubetz (1986) provide a more
detailed description, including snorkeling techniques, physical parameter
measurements, and conversion of raw fish counts to densities (fish/100m
2
).
To evaluate westslope cutthroat trend using the above data, we first
subdivided the area containing snorkel counts into Geographic Management
Units or GMU’s (Figure 2) (Lentsch et al 1997). GMU’s were large segments of
major drainages likely to contain metapopulations (Hanski 1991) based on expert
opinion and on extensive westslope cutthroat movement studies conducted in the
past (Bjornn and Mallet 1964; Hunt and Bjornn (1991). For each GMU, we
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305
subsequently queried the General Parr Monitoring database (J. Griswold IDFG,
unpublished dataset) for those snorkel sites where 1) counts were conducted in 10
or more years since 1985 and 2) where 1 or more westslope cutthroat trout were
observed during the entire counting period (Figure 2). These individual
monitoring sites average about 100 m in length and ranged in number from 1 to
10 on individual streams. Mean density (fish/100m
2
) of westslope cutthroat trout
observed from 1985 to present was calculated for all such monitoring sites within
each GMU. We subjectively considered five individual snorkel sites as the
minimum necessary to derive mean
trend values for a GMU.
Figure 2. Streams in Idaho westslope cutthroat range within 10 Geographical
Management Units (GMUs) and location of GPM snorkel sites (n=206) with ten or
more years of data and where WCT were observed in at least one count year.
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Wild Trout VIII Symposium (September 2004)
Estimation of GMU Population Sizes
To approximate the number of westslope cutthroat trout residing in select
GMUs we began by summarizing stream lengths inhabited by westslope
cutthroat trout in those basins. We relied on the most recent IDFG estimate of
inhabited stream kilometers in Idaho within each GMU, derived from existing
population data and professional judgment as summarized in a 2002 multi-state
status review (Shepard et al. 2003).
In addition to those sites monitored over many years for trend information,
the GPM database contains a large number of snorkel sites where one-time
population estimates are conducted. The entire GPM database consists of 6,300
counts of trout and salmon abundance conducted at 2300 different sampling
locations scattered across anadromous fish-bearing portions of the state since
1985 (IDFG, unpublished data). We considered all GPM snorkel estimates
conducted during the period 1996-2000, including those with and without
westslope cutthroat trout present, useful in approximating current cutthroat trout
population size for a GMU. For all such snorkel counts, the number of westslope
cutthroat trout observed was divided by the length of stream snorkeled to obtain a
linear estimate of fish density (fish/km). We subsequently calculated mean linear
densities of cutthroat observed for each GMU.
To estimate total GMU-wide population sizes, the estimates of stream km
occupied by westslope cutthroat trout within each GMU described above were
multiplied by the mean estimate of linear density (fish/km) for the sub-species in the
same GMU. Because the GMU boundaries we originally selected for the Upper
Salmon and Lower Salmon GMU’s did not coincide with geographic subdivisions
used in mapping present westslope cutthroat distribution (Shepard et al. 2003), we
did not attempt to estimate total population sizes for these two areas.
The extinction risk modeling effort below evaluates the effect of multiple
subpopulations on persistence probabilities for westslope cutthroat within an
entire GMU. Stream basins from third to fourth order in size are thought to mark
the boundary between local sub-populations of westslope cutthroat trout (B.
Rieman, USFS, pers. communication). To provide a rough approximation of
average sub-population size in the various study waters, we used ArcView GIS
software to calculate the proportion of stream kilometers within third and fourth
order basins for each GMU. This value was multiplied by the total GMU-wide
population estimate above. We subsequently divided these estimates by the
number of third or fourth order drainages within a GMU to yield approximate
mean sub-basin population sizes.
Extinction Risk Modeling
We analyzed westslope cutthroat trend data from both the historical and
GPM snorkel counts above using the stochastic exponential growth model of
Dennis et al. (1991). The mean instantaneous rate of population change (
μ ) and
the variance in rate of change (
σ
2
) were calculated for trend datasets within each
GMU using STOCHMVP, a software program developed to facilitate use of the
Dennis model (E.O. Garton, Dept of Fish and Wildlife Resources, University of
Idaho). For those GMU’s where two sources of long-term data were available
(Middle Fork Salmon and Selway rivers), the longer of the available datasets was
used to estimate
μ and σ
2
.
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307
We utilized estimates of these two parameters and a range of population sizes
to estimate probability of single populations persisting for 100 years within the
various GMU’s, again with the aid of the program STOCHMVP. As in Reiman
and McIntyre (1993), the sensitivity of model results to a persistence threshold
was evaluated by comparing results for two arbitrarily selected thresholds; in the
present study 10 and 100 fish.
Estimates of
μ are often imprecise and a given value can have major impacts
on extinction risk using the Dennis model (Goodman 2002). Accordingly, we
estimated the probability of persistence for individual populations of westslope
cutthroat trout in various GMU’s using two estimates of instantaneous growth rate.
These values included a calculated growth rate from observed data, along with the
associated variance estimate, and an assumed
μ of 0.0 reflecting a population at
equilibrium (Rieman and McIntyre 1993). The equilibrium growth rate was
assumed to have a variance identical to the observed value for a given GMU.
Many of the large, relatively pristine drainages in Idaho that are protected by
wilderness designation likely harbor numerous local populations in a
metapopulation structure (Hanski 1991). Accordingly, the probability of
persistence (100 years) for a single large population composed of multiple sub-
populations was also estimated as 1-(P
1
·P
2
·….P
i
) where P
i
= the probability of
falling below the threshold in each of the i sub-populations (Rieman and
McIntyre 1993). This process was repeated for three paired
μ and σ
2
values
likely to encompass the range for Idaho populations based on the calculated
values for individual GMU’s above. We selected an extinction threshold of 10
fish and assumed no re-founding or temporal correlations in population size
among sub-populations in this final modeling effort.
Results and Discussion
Population Trends
Historical snorkel counts
Trend counts in the historical mainstem St. Joe, Middle Fork Salmon, and
Selway River snorkel sites all increased markedly during the mid- to late-1970s
during a period following establishment of special regulations on much or all of
their length (Figure 3). The sharp rise in the St. Joe River cutthroat trout population
during this period was studied intensively and attributed to reductions in angler
exploitation from a trophy fish regulation adopted in 1972 (Johnson and Bjornn
1978). The increase in cutthroat abundance on the Selway and Middle Fork Salmon
Rivers is less well understood, but Ortmann (IDFG, unpublished data) observed
that population increases on the latter water were less likely related to fishing
regulation change than to natural factors.
Following three to five-fold increases in population numbers during the first
15 years of trend monitoring, populations in the two waters containing
anadromous fish (Selway and Middle Fork Salmon Rivers) declined substantially
during the late-1980’s and early-1990’s (Figure 3). In contrast, the St. Joe River
population appeared to peak in size in 1995 and then declined.
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Wild Trout VIII Symposium (September 2004)
Declines in all three of these streams occurred despite a continuation of
mainstem special regulations and expansion of catch-and-release to most or all
tributaries. The Selway and Middle Fork Salmon populations appear to have
declined in near synchrony. All three populations appear to have increased
sharply in the mid-1990s. Although data are more limited, cutthroat abundance in
the Coeur d’Alene River also improved markedly during the late-1990s. An
evaluation of possible reasons for the similarity of trends in these populations is
outside the scope of this paper. However, it is worth noting that in general,
drought conditions prevailed across Idaho from 1987 to 1994 (except 1993) with
improved water conditions in subsequent years.
0.0
0.5
1.0
1.5
2.0
2.5
1965 1970 1975 1980 1985 1990 1995 2000 2005
Year
Fish per 100m2
0
5
10
15
20
25
Fish per transect
CDR
MF Salmon
St. Joe
Selway
Figure 3. Trends in westslope cutthroat trout abundance (fish/100m2) determined by
snorkeling in the St. Joe, Middle Fork Salmon, and Coeur d’Alene rivers, 1969-
2000. Selway River data are available only in fish/transect (right scale).
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Selway
0.00
0.50
1.00
1.50
2.00
2.50
1984 1986 1988 1990 1992 1994 1996 1998 2000
Year
Density (fish/100m2)
SF Clearwater SubBasin
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1984 1986 1988 1990 1992 1994 1996 1998 2000
Year
Density (fish/100m2)
SF Salmon SubBasin
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1984 1986 1988 1990 1992 1994 1996 1998 2000
Year
Density (fish/100m2)
Upper Salmon SubBasin
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
1984 1986 1988 1990 1992 1994 1996 1998 2000
Year
Density (fish/100m2)
Clearwater
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
1984 1986 1988 1990 1992 1994 1996 1998 2000
Year
Density (fish/100m2)
Lochsa
0.00
0.50
1.00
1.50
2.00
2.50
3.00
1984 1986 1988 1990 1992 1994 1996 1998 2000
Year
Density (fish/100m2)
4
4
Lower Salmon
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1984 1986 1988 1990 1992 1994 1996 1998 2000
Year
Density (fish/100m2)
Middle Fork Salmon
0.00
0.50
1.00
1.50
2.00
2.50
1984 1986 1988 1990 1992 1994 1996 1998 2000
Year
Density (fish/100m2)
n = 12
n = 9
n = 22
n = 26
n = 27
n = 31
n = 33
n = 33
Figure 4. Trends in westslope cutthroat abundance (fish/100m2) determined by snorkeling at General
Parr Monitoring (GMU) locations having 10 or more years of data during 1985-2000; n = numbers
of individual count sites within the GMU.
General Parr Monitoring counts
Examination of the GPM snorkel data suggests that most westslope cutthroat
trout populations monitored within waters supporting anadromous species are
either stable or increasing. Mean density (fish/100m2) in four of eight GMU’s
being monitored, including the Lochsa River, Lower Salmon River, South Fork
Clearwater River, and South Fork Salmon River appeared to be flat, or nearly so
(Figure 4). Mean density in the Middle Fork Salmon GPM sites appear to have
declined since 1985, although data collected from the historical trend sites over a
longer period do not demonstrate the same results. Conversely, westslope
cutthroat populations in the Clearwater, Selway, and Upper Salmon rivers appear
to have increased during the period from 1985 to 2000, as characterized by
relatively steep trend line increases (Figure 4).
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Wild Trout VIII Symposium (September 2004)
Estimation of GMU Population Sizes
For the GMU’s considered in this study, estimates of stream length occupied
by westslope cutthroat trout range from 1,057 km for the South Fork Clearwater
River to 3,351 km for the Middle Fork Salmon River (Table 1). Estimated mean
linear density ranged from 5 to 149 fish/km on the South Fork Salmon and
Selway rivers, respectively. With the exception of the mainstem historical
snorkel counts, electronic data pertaining to fish densities on the St. Joe River
were unavailable. However, historically available estimates of density on the St.
Joe River have typically been high relative to other streams (Figure 3). We
approximated what is likely a minimum number of fish present in the St. Joe
River drainage assuming an average value of westslope abundance of 68 fish/km
derived from all other drainages in this study (Table1). Estimates of westslope
cutthroat trout numbers within the various GMU’s ranged from 6,568 to 341,767
fish (Table 1) with a total combined estimate of approximately 1.2 million fish
for the GMU’s considered. Although space limitations preclude a detailed
discussion of possible positive or negative biases in the above estimates, it is
likely that total GMU population estimates for westslope cutthroat trout in this
study (Table 1) were underestimated rather than overestimated.
Table 1. Approximate numbers of westslope cutthroat trout (WCT) present in geographic management
areas (GMU’s) based on linear “density” estimates (WCT/km) and number of km with WCT present.
Basin
Stream
length
1
w/WCT
( km)
Mean
WCT/km
Total
estimated
WCT
No. of 3rd-
4th order
sub-basins
% GMU
stream km in
3rd-4th orde
r
sub-basins
Estimated
WCT in
3rd-4th
order sub-
basins
Mean
populations
size/sub-
basin
Middle Fork
Salmon River
3351 88 294,878 28 75% 221,158 7,899
St. Joe River 2185 68
2
148,565 20 74% 109,938 5,497
Coeur d'Alene
River 1446 15 21,058 13 74% 15,583 1,199
Selway River 2294 149 341,767 21 78% 266,578 12,694
Clearwater
River 3507 40 139,504 33 79% 110,208 3,340
Lochsa River 1340 134 179,547 17 67% 120,297 7,076
South Fork
Clearwater 1057 25 26,415 15 74% 19,547 1,303
South Fork
Salmon 1314 5 6,568 13 84% 5,517 424
1
As summarized by IDFG fishery management 2002 (Corsi unpublished data)
2
Minimum estimate assuming average WCT/km across all drainages.
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Assuming the total GMU-wide population estimates are within the realm of
true abundance, the approximate mean sub-population sizes within the various
GMU’s ranged from about 400 to nearly 13,000 fish (Table 1). This estimate is
admittedly a crude approximation. However, despite some limitations, these
estimates provide a general range of sub-population sizes for Idaho westslope
cutthroat trout populations for use when considering results from the extinction
risk modeling below.
Extinction Risk Modeling
Estimated instantaneous rates of change (μ) for westslope cutthroat trout
populations in 10 Idaho streams ranged from –0.059 to 0.1643 (Table 2). Based
on the historical and GMP trend datasets, eight of 10 estimates were positive over
the monitoring period implying increased population growth. Only two trend
datasets including the Lochsa River and South Fork Salmon River counts,
produced estimates of negative population growth.
Estimates of variance of instantaneous rates of change (
σ
2
) differed markedly
among the four historical datasets and the shorter-term GPM trend sites (Table
2). Within the historical snorkeling datasets, estimates of
σ
2
ranged from 0.07 to
0.37; estimates from the GPM database ranged from 0.50 to 4.03. With the
exception of the highest estimate (4.03), the present estimates of variance around
μ were similar to the range (0.07-1.02) reported by McIntyre and Rieman (1995)
for seven westslope cutthroat trout populations in Idaho and Montana.
Table 2. Estimated mean (
μ
) and variance (
σ
2
) for instantaneous rates of change in westslope cutthroat
trout populations calculated from snorkel counts in Idaho streams, 1969-2002.
1
Basin Dataset period Years obs.
Sites
counted
μ σ
2
MFk Salmon River 1971-1999 15 12
0.0421 0.37
St. Joe River 1969-2002 20 27
0.0155 0.12
Coeur d'Alene River 1973-2002 13 29
0.0272 0.07
Selway River 1973-1999 19 27
0.0284 0.23
Clearwater River 1986-1998 10 9
0.054 1.05
Lower Salmon River 1985-2000 15 26
0.1643 1.28
Lochsa River 1985-2000 15 22
-0.0277 0.50
SFk Clearwater River 1985-2000 15 31
0.0777 0.74
SFk Salmon River 1986-2000 14 17
-0.059 4.03
Upper Salmon River 1985-2000 14 33
0.1004 0.89
1
Calculated after Dennis et al. 1991
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Wild Trout VIII Symposium (September 2004)
Predicted probabilities of persistence for 100 years in single local
populations of westslope cutthroat trout in Idaho were strongly influenced by
both the estimate of μ employed (observed versus an assumed equilibrium value
of 0.0), and by the selection of an extinction threshold (Table 3). Not
surprisingly, populations with low estimates of σ
2
(e.g., Coeur d’Alene River =
0.07 from Table 2) had a high probability of 100-year persistence, while
populations with high variance (e.g. South Fork Salmon River = 4.03) had low
probabilities of persistence regardless of the selected value for μ (Table 3).
Persistence probabilities were relatively insensitive to changes in initial
population size over the three population sizes modeled when holding all other
factors constant. These results are similar to those reported by Rieman and
McIntyre (1993) in their assessment of bull trout extinction risk.
Stream 10 100 10 100 10 100 10 100 10 100 10 100
MF Salmon .637 .403 .827 .617 .694 .480 .866 .695 .746 .551 .898 .760
St. Joe .899 .648 .951 .782 .947 .743 .971 .855 .991 .820 .984 .907
CDA 1.000 .779 .997 .952 1.000 .868 .999 .978 1.000 .935 1.000 .990
Selway .752 .498 .886 .683 .808 .586 .918 .762 .856 .664 .942 .824
Clearwater .410 .247 .576 .380 .456 .297 .624 .445 .500 .347 .668 .505
Lower Salmon .376 .225 .774 .576 .419 .272 .813 .649 .460 .317 .846 .709
Lochsa .565 .351 .428 .241 .621 .420 .483 .297 .672 .485 .535 .354
SF Clearwater .479 .292 .751 .543 .530 .351 .794 .618 .578 .408 .830 .681
SF Salmon .217 .127 .158 .090 .243 .155 .179 .110 .269 .181 .200 .131
Upper Salmon .442 .267 .753 .550 .490 .322 .796 .623 .536 .375 .831 .686
Table 3. Estimated probabilities of persistence for single populations of Idaho westslope cutthroat trout given
three different initial sizes. I alternately assumed extinction thresholds of 10 or 100 fish and also alternated
estimates of
μ
and
σ
2
and from existing trend data or an equilibrium value of
μ
(0.0) with observed
σ
2
.
Pop size = 5000Pop size = 2500 Pop size = 10,000
μ =
0.00
μ =
observed
Threshold
μ =
observed
Threshold
μ =
0.00
Threshold Threshold
μ =
0.00
Threshold
μ =
observed
Threshold
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If large numbers of local populations of westslope cutthroat trout in Idaho
were believed to function in complete isolation within the range of three
population sizes modeled (2,500 to 10,000 fish), then many would be assumed to
be at risk of extinction within 100 years based on the results of Table 3. Isolated
populations may indeed exist in some instances (e.g. South Fork Salmon) where
the approximated sub-population size averaged less than one thousand
individuals (Table 1) and westslope cutthroat trout are not widely distributed
within the GMU (Thurow 1985). In addition, other large stream systems with less
prominent westslope cutthroat populations than those considered in the present
study (e.g., The St Maries River) may be areas for concern. However, given the
widespread distribution of westslope cutthroat trout in many of the relatively
pristine watersheds in central Idaho, and extensive movement patterns
documented for fluvial populations (Bjornn and Mallet 1964; Hunt and Bjornn
1991), it is likely that many local sub-populations within the study area function
as a classic metapopulation (Levins 1970) or a less traditional form often
observed (Harrison 1991). In either event, an increased probability of overall
persistence would be expected compared to the above estimates of persistence for
single local populations (Harrison 1991; Doak and Mills 1994).
An assessment of the number of westslope cutthroat trout populations
necessary to ensure a high probability of persistence in the absence of dispersal
provides some perspective on extinction risk for such meta-populations. For
populations ranging in initial size from 500 to 20,000 individuals, the number of
sub-populations needed to maintain a 95% probability of at least one population
persisting 100 years ranged from two to seven populations for the two
simulations involving modest growth and equilibrium growth (Figure 5). In the
case of a declining population experiencing high variance, the number of
populations needed for 95% persistence ranged from eight to 18 populations,
across the same initial population size range.
A major limitation of the PVA modeling approach used in this study is that
in calculating extinction risk, the Dennis et al. (1991) model assumes that no
density-dependence occurs. McFadden (1977) argued for the widespread reality
of density-dependent processes in fish populations noting that the existence of
such processes comprise the very core of fishery science. Assuming density-
dependence actually occurs, Goodman (2002) observed that most combinations
of reasonable parameter values in the Dennis et al. (1993) model will result in
projections either trending to unrealistically high levels or to short-term
extinction. Use of a positive growth value in the model will likely result in
optimistic estimates of persistence, although results could not be biased past the
predictions observed for equilibrium growth (Figure 5). Conversely, use of a
negative growth value in the model will result in unduly pessimistic persistence
predictions (Goodman 2002). Because the majority of available trend data for
Idaho westslope cutthroat trout suggest a either positive population growth or
equilibrium growth, the curve in Figure 5 based on equilibrium growth (μ= 0.0)
is probably the best point estimate. This curve suggests that, under the range of
population sizes modeled (250-30,000), only three to nine sub-populations would
be needed to ensure population persistence. Results of Table 1 suggest that the
number of sub-populations present (3
rd
-4
th
order drainages) in many Idaho
GMU’s exceed these levels and they should therefore be adequate for
persistence.
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Wild Trout VIII Symposium (September 2004)
A very conservative approach to assessing westslope cutthroat extinction risk
would be to consider the area between the curves for equilibrium and negative
population growth as the guideline for assessing risk (Figure 5). As an example,
for multiple sub-populations with initial sizes of 10,000, the number of sub-
populations necessary to ensure 100 year persistence would be 4 to 9. For
populations with initial sizes of 1,000 the number of populations needed would
range from 7 to 15. Again, based on the rough estimates of sub-basin population
sizes for various GMU’s (Table 1), a sufficient number of populations appear
available in most cases.
Although generalizations on the number of sub-populations needed for
persistence in this study should only be viewed as approximations, it seems likely
that they are quite conservative. The GMU population sizes developed to put the
various extinction estimates into general perspective are likely underestimated
given the use of snorkel counts and location of GPM sample sites. Perhaps the
most compelling reason to suspect the persistence estimates produced by this
study are conservative relates to sampling error likely involved in our estimation
of population trends. The variance (
σ
2
)
associated with point estimates of
Figure 5. Estimated number of westslope cutthroat trout populations necessary to
ensure a 0.95 probability of persistence for at least one population, given a range of
likely sizes. Modest growth values from Middle Fork Salmon River (µ = 0.042,
σ
2
=
0.37), equilibrium µ assumed to be 0.0 with moderate variances of 0.75, declining
population µ from the SFk Salmon River (µ = -0.059) with high variance (1.28) from
the Lower Salmon River. All populations assumed to be completely independent.
Equilibrium growth value the best point estimate for most Idaho populations based
on available trend data; shaded area a conservative estimate due to inability of
Dennis et al (1993) model to consider density dependence (see text).
0
5
10
15
20
25
0 2500 5000 7500 10000 12500 15000 17500 20000 22500 25000 27500 30000
Initial Population Size
Number of Populations Needed
Modest growth, low var
Equilibrium growth, modest var
Declining pop, high var
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315
infinitesimal population growth rate (Table 2) assume no measurement error in
the population trend data; i.e., 1) all variation in snorkel counts is due solely to
population changes and 2) counts within the snorkel trend count zones reflect the
stream-wide population trend perfectly. In reality, differences in personnel
snorkeling skills, possible annual differences in fish movement, and a host of
other factors are reflected in the snorkel count data. In past extinction
assessments, sampling error associated with population trend data has turned out
to be important, creating considerable negative bias in the persistence
probabilities derived via the Dennis model (Rieman and McIntyre 1993; B.
Rieman, USFS, personal communication).
Applying the model projections of Table 3 and Figure 5 directly to specific
estimates of sub-population size is impossible; the requisite data are not
available. Even if available, it is questionable whether such absolute extinction
risk estimates would be rigorous enough (Ralls et al 2002). Instead, we have
opted to develop some simple, generalized risk models that compare the relative
extinction risk for various populations with a range of population size and growth
rates characterized by available data. The use of such generalized PVA models to
evaluate relative extinction risk can be quite useful when viewed as thought
experiments (Ralls et al. 2002). In fact, it has been argued that use of such a
simplistic modeling approach is preferable to more “realistic” spatial models that
are often too poorly parameterized to be of much use (Doak and Mills 1994).
Conclusions
The dataset developed for assessing trend in this study is comprised of 301
individual sites where westslope cutthroat trout trends counts have been
conducted via snorkeling over a 10 to 34 year period. Given the extensive
monitoring period and the relatively broad dispersion of the snorkel monitoring
sites used in this study, these data likely comprise the most extensive monitoring
effort for a resident trout species ever conducted in America. Taken collectively,
the data do not suggest that westslope cutthroat trout are declining in abundance
within Idaho. Rather, the broad distribution of sites involved in both the historical
sites (Figure 1) and the GPM dataset (Figure 2) and results of the trend analysis
(Figures 3 and 4; Table 2) demonstrates that westslope cutthroat trout have
maintained or increased their population abundance over a very large area within
the state of Idaho during the past several decades.
Total estimates of westslope cutthroat trout numbers within the various
GMU’s ranged from 6,568 to 341,767 fish with a total estimate of approximately
1.2 million fish for all GMU’s combined. Although estimates of precision for
these estimates are not presented due to non-random sampling, consideration of
possible sources of bias indicates that the above estimates are likely to be
conservative.
Although estimates of population persistence for 100 years ranged from high
to low for various individual local populations, the above study results suggest
that numerous large sub-populations within most GMU’s, available to interact
within in a classic or less traditional metapopulation framework, would result a
high ( >
95%) probability of persistence over 100 years in many instances.
Session 5—Contributed Papers
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Wild Trout VIII Symposium (September 2004)
Acknowledgments
We would like to thank E. O. Garton, Kevin Meyer, and Judy Hall-Griswold
for their assistance with this work.
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317
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