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significant amount of the variation in trout growth.





- 16
















1 1


• mean

I standard error

I range

— y




— 1 —

n —


3 4 5

AGE (years)

FIGURE 3. Golden trout lengths by age class. Sample sizes for age classes 1-9 are given in Table
2. N = 58 for age 0.

TABLE 2. Actual and Predicted Standard Lengths and Weights of Trout of Ages 1-9. See Text for


12 3 4 5 6 7 8 9

n 10 27 47 28 10 10 5 1

preclictod length (cm) 7.3 10.1 11.7 12.9 13.8 14.5 15.1 15.6 16.1

actuallength (cm) 7.1 9.8 11.8 13.2 15.0 13.1 14.2 — 16.1

predicted weight (g) 2.9 16.6 24.7 30.4 34.9 38.5 41.6 44.2 46.6

actual weight (g) 6.4 14.0 23.9 31.7 47.3 33.2 33.2 — 55.0

TABLE 3. Results of Stepwise Multiple Regression Analysis of Trout Growth Measured As SL/age

(n = 95). Variables Are Listed As They Entered The Model. See Text for Definition of Inde-
pendent Variables.

Variable Slope P R'

fish age -0.76 0001 0.62

% stream vegetated 0.95 0.005 0.02

fish density (#/m-') -3.53 >0.10 0.01

When growth was measured as weight/age, regression analysis for 87 fish
from 11 streams indicated that golden trout density explained the largest
amount of the variation in growth (21%; Table 4). Elevation did not vary much
between sites (Table 1 ), but still explained 8% of the variation in trout growth.
The percent of the bank covered by vegetation explained an additional 7% of
the variation.


TABLE 4. Results of Stepwise Multiple Regression Analysis of Trout Growth Measured as Weight/Age
(n = 87). Variables are Listed as they Entered the Model. See Text for Definition of Inde-
pendent Variables.

Variable Slope P R'

fish density (#/100 m) -0.19 0.0001 0.21

elevation (m) 0.01 0.0001 0.08

% bank vegetated 7.99 0.004 0.07

Condition factors ranged from 1.16 to 1.47, with a nnean of 1.34 ± 0.11 S.E.
(Table 1 ). Although 106 fish were used in the model, none of the site-specific
stream variables satisfied the minimum significance level for entry into the
regression model.

Multiple regression analyses using fish density (measured as the number of
fish per 100 m of stream and as the number of fish per m ) as the dependent
variable resulted in none of the site variables satisfying the minimum required
significance level for entry into the regression model. Four streams were
eliminated from the analysis because of missing values.

The Pfankuch stream stability rating was significantly correlated with fish
growth measured as weight/age (r=— 0.35, p = 0.0001, n = 138), but not as
SL/age (r=— 0.09, p>0.30, n = 138). The correlation between the stream
stability rating and fish density measured as the number of fish/ 100 m was
marginally significant (r = 0.44, p = 0.08, n = 16), but the stream stability rating
and fish density measured as the number of fish/m ^ were not significantly
correlated (r = 0.05, p>0.50, n = 16). Trout condition was also not significantly
correlated with the stream stability rating (r=— 0.07, p>.15, n = 343).


Scales proved unsatisfactory for aging golden trout in this study. Reimers
(1958) experienced similar difficulties with scales taken from brook trout from
an alpine Sierra Nevada lake. Otoliths, however, proved highly suitable for age
determinations. The oldest fish sampled was 16.1 cm SL and was in its tenth
year of growth, making it the oldest golden trout on record. Six and seven year
old fish were common. Other species of trout occasionally attain similar ages in
streams (O. mykiss — 7 years, Greeley 1933; O. clarkii — 10 years, Oregon State
Game Comm. 1950; 5. trutta — 8 years, Sigler 1952). Most other records of
salmonids near 10 years of age or greater are from lake populations (Fenderson
1954, Sumner 1948) or are sea-run individuals (Sumner 1962).

The exceptionally low productivity of streams occupied by golden trout may
be a factor in their longevity as well as their retarded growth. In one remarkable
case, Reimers (1979) found that introduced brook trout, Salvelinus fontinalis,
survived for up to 24 years of age in a high altitude, low productivity Sierra
Nevada lake. Reimers accounted for their exceptional age by their minimal
energetic costs. Activity was reduced by low temperatures in conjunction with
extreme food depletion. These fish became highly stunted and did not
reproduce until age 16, when population densities declined and allowed food
levels to increase and make reproduction possible. Considerable evidence
correlates stunting due to reduced food ration and low temperature with
enhanced longevity (McCay et al. 1956, Comfort 1963). Golden trout were
clearly stunted, suggesting that their increased longevity may be the result of an
analogous situation.


In streams, golden trout growth rates are much lower than the rates reported
from lake populations (Needham and Vestal 1938, Curtis 1934, McAfee 1966).
This agrees with considerable information regarding other species of trout
(Carlander 1969), and may be due to several factors. In lakes, fish have access
to zooplankton and large prey items not available in streams. This is particularly
true following introduction of new populations (including O. aguabonita) to
fishless lakes, before the prey community composition has been altered
(Needham and Vestal 1938). Fish feeding behavior is different in lakes and
streams; in streams, fish must expend energy maintaining position and feeding
in fast currents (Jenkins 1969, Smith and Li 1983), reducing energy available for

Regression analyses suggested that several factors may influence the growth
of golden trout in our study streams. When growth rate was measured as
standard length/age, most of the variation was explained by age (Table 3);
younger age classes grew more rapidly than older age classes. The amount of
the stream covered with aquatic vegetation was positively correlated with trout
growth. Aquatic vegetation often provides important habitat for invertebrates
and may promote higher invertebrate abundance and diversity (Dudley et al.
1986). Thus, aquatic vegetation may increase the amount of food available to
golden trout.

Weight at each age class showed much more variation than size at each age
class ( Figures 3 and 4) . Since weight can be modified over a shorter time period
than length, growth rates based on weight may have been more sensitive to the
effects of the site variables used in the analyses than growth rates based on
length. Growth rates measured as weight/age were affected by numerous site
variables (Table 4). Sites with higher fish density (number of fish/m')
contained fish with significantly slower growth rates. Increased fish density may
result in decreased growth rates by decreasing per capita food availability or by
increasing competition for foraging sites or cover (Chapman 1966, Chapman
and Bjornn 1969, Elliot 1984). Such competition could force fish to expend
energy on agonistic interactions instead of on growth.

Density measured as the number of fish/ 100 m may be a better predictor of
growth rates than density measured as the number of fish/m' if these trout
populations are limited more by the availability of cover than by foraging sites.
Nearly all cover in the study streams occurred along the banks and was heavily
utilized by fish. Foraging sites were generally in mid-stream and may not have
been in short supply in the study streams, since individuals often changed sites
without interactions from conspecifics.

Fish from higher elevation streams had higher growth rates than those from
lower elevations. McAfee (1966) suggested that if higher elevation habitats
have lower fish densities than lower sites, reduced competition at higher sites
may result in faster growth. However, our analyses should have removed any
density effect and we are thus unable to provide a satisfactory explanation for
this relationship.

There was a positive relationship between the amount of streambank
vegetation and trout growth. Overhanging vegetation provides cover for fish
and may increase the number of terrestrial insects available to trout.








3 70-

,_ 60-

UJ 40-



1 I




'—I f 1




AGE (years)

FIGURE 4. Golden trout weights by age class. Samples sizes for each age class are given in
Table 2.

The negative correlation between the Pfankuch stream stability rating and
trout growth (weight/age) suggests that trout from streams with higher channel
stability gained weight faster than those from streams with lower channel
stability. Similar effects of channel stability on fish growth have been found for
rainbow trout (Van Velson 1979) and brown trout (Dahlem 1979) and were
suggested to result from increased food and cover.

Condition factors for 343 trout ranged from 0.90 to 2.16. Despite this
variability, our calculated mean K was 1.34, which is similar to K values
estimated for lake populations of golden trout (K = 1.315 in Needham and
Vestal 1938, 1.34 in Curtis 1934). Apparently, populations of golden trout
achieve quite similar condition relationships, even in very different habitats. K
values of other trout species vary considerably among habitats, but it appears
that trout in montane streams have K values similar to those of golden trout,
ranging from 1.15 to 1.63 (Carlander 1969). This uniformity in condition even
among different trout species may explain why none of the measured site
characteristics affected trout condition in our analysis.

Trout density was not affected by any of the measured site characteristics
used in the regression analysis. This analysis should be interpreted with caution,
however, as each stream was considered as a separate observation and only 13
streams were used in the analysis. Thus, even if any site characteristics (e.g.
amount of suitable spawning gravel or aquatic insect biomass) did affect trout
density, the analysis may have lacked the power to detect such effects. The
marginally significant correlation between trout density (number of fish /1 00m)


and the Pfankuch stream stability rating suggests that less stable stream channels
support higher densities of fish. Although we are unable to provide an
explanation for this relationship, it may suggest that fish grew more slowly in
streams with lower channel stability because of higher trout densities.

In summary, several site variables affected trout growth. Trout density, trout
age, and the Pfankuch stream stability rating were negatively correlated with
trout growth while the amount of aquatic vegetation, the amount of bank
vegetation, and elevation were positively correlated with trout growth. Differ-
ences between sites in stream stability, trout density, bank vegetation, and
aquatic vegetation may all influence trout growth by increasing or decreasing
the amount of available food or cover. Small increases or decreases in the
availability of food or cover may be important in these low productivity streams.
However, the low growth rates of golden trout throughout the study area were
probably a result of the low productivity of these unstable montane streams and
the short period of time available each year for rapid trout growth.


We thank many people for their assistance in organizing and conducting this
research, including Scott Cooper, Jon Diehl, Jim Killiam, the other Scott Cooper,
and Caria D'Antonio of the University of California, Ralph Giffen and Robin
Hamlin of the U.S. Forest Service, and Steve DeBenedetti of the National Park
Service. We also thank William Hayden for supplying us with the FISHPARM
software and Bill Berg for clarifying the systematics of golden trout. We
particularly appreciate the guidance, enthusiasm and philosophical wisdom of
Phil Pister of California Fish and Game. The people of Cottonwood Pack Station
did an admirable job of figuring out where we were. Research was in part
funded by California Water Resources Center Grant No. W628 and National
Science Foundation Grant No. BSR83-05837.


Albert, C. P. 1982. A survey of factors influencing the condition of the stream zone in the Golden Trout

Wilderness. MA. Thesis, Sonoma State University, California. 65 p.
Berg, B. 1987. Evolutionary genetics of rainbow trout, Parasalmo gairdneri (Richardson). Unpublished Ph.D.

dissertation, U.C. Davis. 184 p.
Campana, S. E. 1983. Feeding periodicity and production of daily growth increments in the otoliths of steelhead

trout iSa/mo gairdneri) and starry flounder (Platichthys slellatus). Can. ). Zool., 61: 1591-1597.
Campana, S, E. and J. D. Neilson. 1985. Microstructure of fish otoliths. Can ). Fish. Aq. Sci., 42: 1014-1032.
Carlander, K. D, 1969. Handbook of Freshwater Fishery Biology. Iowa State University Press, Ames, Iowa. 752 p.
Chapman, D. W. 1966. Food and space as regulators of salmonid populations in streams. Am. Nat., 100: 345-358.
Chapman, D. W. and T. C. Bjornn. 1969. Distribution of salmonids in streams, with special reference to food and

feeding. Pages 153-177 in T. C. Northcote, ed. Symposium on salmon and trout in streams. University of

British Columbia, Vancouver, B.C.
Comfort, A. 1963. Effect of delayed and resumed growth on the longevity of a fish Uebistes reticulatus Peters)

in captivity. Gerontologia, 8(2); 150-155.
Curtis, B. 1934. The golden trout of Cottonwood Lakes (Salmo aguabonita Jordan). Amer. Fish. Soc, Trans., 64:

Dahlem, E. A. 1979. The Mahogany Creek Watershed— with and without grazing. Pages 31-34 in O.B. Cope, ed.

Forum on grazing and riparian/stream ecosystems. Trout Unlimited, Inc.
Dudley, T. L., S. D. Cooper, and N. Hempill. 1986. Effects of macroalgae on a stream invertebrate community.

N. Amer. Benthol. Soc, )., 5: 93-106.
Elliott, ). M. 1982. The effects of temperature and ration size on the growth and energetics of salmonids in

captivity. Comp. Biochem. Physio., 73(1): 81-91.


Elliot, ). M. 1984. Numerical changes and population regulation in young migratory trout Salmo trutta in a Lake
District stream, 1966-1983. |. Anim. EcoL, 53; 327-350.

Fenderson, C. N. 1954. The brown trout in Maine. Maine Fish Bull., 2: 16 p.

Fisk, L. 1983. Golden trout of the High Sierra. Calif. Fish and Came, 16 p.

Greeley, ). R. 1933. The growth rate of rainbow trout from some Michigan waters. Amer. Fish. Soc, Trans., 63:

)ahns, R. H. 1954. Geology of Southern California. California Division of Mines and Geology, Bulletin 170.

Jenkins, T, M. 1969. Social structure, position choice and microdistribution of two trout species (Salmo trutta and
5. galrdneri) resident in a mountain stream. Anim. Behav. Monogr., 2: 57-123

Jordan, D. S. 1892. Description of the golden trout of Kern River. Bien. Rept. St. Bd. Fish. Comm., Calif., 5: 62-65.

Marshall, S. L. and S. S. Parker. 1982. Pattern identification in the microstructure of sockeye salmon
(Oncorhynchus nerka) otoliths. Can. J. Fish, and Aquat. Sci., 39: 542-547.

McAfee, W. R. 1966. Golden trout. Pages 216-221 in A. Calhoun, ed. Inland Fisheries Management. Calif. Dept.
Fish and Came.

McCay, C. M., F. Pope, and W. Lunsford. 1956. Experimental prolongation of the life span. Pages 29-39 in R. L.
Craig, ed. Problems of aging, 28th Grad. Sympos. New York Acad. Medicine, 1955. George Eliot Books, New
York. 221 p.

Needham, P. R., and E. H. Vestal. 1938. Notes on growth of golden trout (Salmo agua-bonila) in two High Sierra
lakes. Calif. Fish and Game, 24(3): 273-279.

Neilson, J. D. and C. H. Geen. 1982. Otoliths of chinook salmon (Oncorhynchus tshawytscha): daily growth
increments and factors influencing their production. Can. J. Fish. Aquat. Sci., 39: 1340-1347.

Oregon State Came Commission. 1950. Annual report. Fishery Division, 1951. 238 p.

Pfankuch, D. 1975. Stream reach inventory and channel stability evaluation. USDA Forest Service, Northern
Region. 26 p.

Prager, M. H., S. B. Saila, and C. W. Recksiek. 1987. FISHPARM: A microcomputer program for parameter
estimation of nonlinear models in fishery science. Old Dominion University Research Foundation. Technical
Report 87-10.

Purkett, C. A., Jr. 1951. Growth rate of trout in relation to elevation and temperature, Amer. Fish. Soc, Trans., 80:

Reimers, N. 1958. Conditions of existence, growth, and longevity of brook trout in a small, high altitude lake of
the eastern Sierra Nevada. Calif. Fish and Game, 44: 319-333.

Reimers, N. 1979. A history of a stunted brook trout population in an alpine lake: A lifespan of 24 years. Calif. Fish
and Game, 65: 196-215.

Seber, G. A. F., and E. D. LeCren. 1967. Estimating population parameters from catches large relative to the
population. J. Anim. EcoL, 36: 361-643.

Sigler, W. F. 1952. Age and growth of the brown trout, Salmo trutta fario Linnaeus, in Logan River, Utah. Amer.

Fish. Soc, Trans., 81: 171-178.
Smith, |. J. and H. W. Li. 1983. Energetic factors influencing foraging tactics of juvenile steelhead trout, Salmo

galrdneri. Pages 173-180 in L. G. Noakes et al., eds. Predators and prey in fishes. W. junk Publ., The Hague,


Sumner, F. H. 1948. Age and growth of steelhead trout, Salmo gairdnerii Richardson, caught by sport and
commercial fishermen in Tillamook County, Oregon. Amer. Fish. Soc, Trans., 75: 77-83.

Sumner, F. H. 1962. Migration and growth of the coastal cutthroat trout in Tillamook County, Oregon. Amer. Fish.
Soc, Trans., 91(1): 77-83.

Van Velson, R. 1979. Effects of livestock grazing upon rainbow trout in Otter Creek. Pages 53-55 in O. B. Cope,
ed. Forum — Grazing and Riparian/Stream Ecosystems, Trout Unlimited, Inc.


Calif. Fish and Came 76 ( 3 ): 1 74- 1 80 1 990







Oregon Department of Fish and Wildlife

17330 S. E. Evelyn St.,

Clackamas, Oregon 97015

We compared the efficiency and size selectivity of setlines, gillnets, and angling
to select a cost-effective means of capturing a large number of adult and subadult
white sturgeon, Acipenser transmontanus, unharmed while minimizing size selec-
tivity and catch of non-target game fish. Setlines provided the greatest catch rate
per sampling week (61.4), followed by gillnets (49.4) and angling (34.4). Setlines
also captured a wider size-range of sturgeon than gillnets or angling. No other game
fish were caught with setlines or angling while gillnets caught other game fish
including salmon and steelhead, Oncorhynchus spp.


White sturgeon, Acipenser transmontanus, is a valuable resource along the
Pacific Coast of North Annerica (Pycha 1956, Semakula and Larkin 1968,
Kohlhorst 1980, Cochnauer 1983, Oregon Department of Fish and Wildlife
1988). In the Colunnbia River, white sturgeon support recreational, commercial,
and tribal fisheries (Galbreath 1985) . With the decline of anadromous salmonid
fisheries (Raymond 1988), the white sturgeon fishery has rapidly increased in
importance. Total effort and landings have increased several-fold since 1970
(Oregon Department of Fish Wildlife 1988), and effort by recreational white
sturgeon anglers now exceeds effort by recreational salmon anglers down-
stream from Bonneville Dam (Hess and King 1988).

The status of white sturgeon varies within the Columbia River basin. Although
the population below Bonneville Dam has supported a harvest of over 50,000
fish annually in recent years, populations in the Snake and Kootenai rivers
(Columbia River tributaries) have diminished to the point where no harvest is
allowed. Populations have declined in tributaries, possibly for several reasons:
(i) migration of white sturgeon into the upper basin has been blocked by the
construction and operation of hydroelectric dams (Bajkov 1951, Lukens 1981 );
(ii) habitat, including food availability, flow, and temperature has been altered
by the creation of reservoirs formed by these dams (Bajkov 1951, Coon et al.
1977, Haynes et al. 1978, Lukens 1981); (iii) other biological and physical
factors such as predation and the level of pesticides also may have changed
(Bosley and Gately 1981).

We needed a gear that would collect a large sample of white sturgeon
unharmed to evaluate effects of dam construction and operation on white
sturgeon and to design management strategies to optimize yield (Rieman et al.
1987). Other considerations included sampling efficiently to minimize the cost

Accepted for publication )une 1990.



of sampling hundreds of kilometers of river, gear size selection which might bias
representation of the population ( Beamesderfer and Rieman 1988), and
incidental catch of other game fish. Hence, the objective of this report is to
describe the most effective gear for capturing subadult and adult white stureon
unharmed while minimizing size selectivity and catch of other game fish.


We selected The Dalles Reservoir, a mainstem impoundment of the Columbia
River (Figure 1 ), for our gear analysis because this reservoir is relatively small
compared with other impoundments in the Columbia River and access to all
parts of the reservoir is good. The Dalles Reservoir is located between The
Dalles and John Day dams (river kilometer 308 to 347). It was formed in 1957
with the closure of The Dalles Dam, a U.S. Army Corps of Engineers
hydroelectric, navigation, and flood control project. At mean operating level,
the reservoir has a surface area of 3,800 hectares, water elevation of 48.2 m
above mean sea level, and depth as great as 61 m. The upper reservoir is
riverine, and measurable current exists throughout the reservoir. Average daily
inflow and outflow ranges from 3,000 to over 12,000 m^/s.

Snake River

McNary Dam


John Day Dam

'Bonneville The Dalles Dam

FIGURE 1. Location of The Dalles Reservoir.


We chose setlines, gillnets, and angling as potential ways to collect white
sturgeon based on review of the literature and discussions with commercial
fishermen. We sampled from March through September, 1987. Effort of each
gear was evenly distributed throughout the reservoir and the period of sampling.

Setlines consisted of a 182-m long mainline of 6.4 mm diameter nylon rope,
along which 40 hook lines (gangions) were equally spaced. Each gangion
consisted of a removable, spring-loaded snap attached to a 0.5-m length of
parachute cord by a swivel, with a hook attached to the other end of the cord.
Each setline included 10 each of size 10/0, 12/0, 14/0 and 16/0 circle hooks.
Circle hooks have the point bent at a 90° angle to the shaft to better retain
hooked fish for long periods of time. Each end of a setline was held in place by



a 15-20 kg anchor. Each anchor ws also attached to a buoy with rope identical
to the mainline. Lines were set for 4-48 h in depths from 3 to 50 m. Hooks were
baited with 2.5- to 5-cm long cross-section slices of adult pacific lamprey,
Entosphenus tridentatus, or 2.5- to 10-cm^ pieces of adult coho salmon,
Oncorhynchus kisutch, with skin attached. Only one bait type was used on
each line. Setlines were deployed and retrieved from a 7 m figerglass skiff
equipped with a hydraulic pot hauler.

Gillnets were sinking type and set stationary and perpendicular to the current.
Each net was 45.6 m long and consisted of six, equal length, alternating panels
of 5.1 cm, 8.3 cm and 11.4 cm bar mesh. Net panels were constructed from
multifilament and cable nylon. Each panel was hung with 4.6 m deep mesh on
a framework with a 3-m long vertical slacker lines attached to the float and
leadline at 3.8 m intervals along the length of the net. Gillnets were held in place
by 4.5-20 kg anchors depending on current. A buoy marked each anchor.
Gillnets were fished for 1^ h in depths from 3 to 35 m. Nets were deployed and
retrieved by hand from the boat.






N = 765


N = 182




N = 30


100 200


1 2 3 5 7

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