Ecology of Freshwater Fish 2008: 17: 554–566
Printed in Malaysia Æ All rights reserved
No claim to original US government works
2008 Blackwell Munksgaard
ECOLOGY OF
FRESHWATER FISH
Exploring the relative influence of biotic
interactions and environmental conditions on the
abundance and distribution of exotic brown trout
(Salmo trutta) in a high mountain stream
Budy P, Thiede GP, McHugh P, Hansen ES, Wood J. Exploring the relative
influence of biotic interactions and environmental conditions on the
abundance and distribution of exotic brown trout (Salmo trutta) in a high
mountain stream.
Ecology of Freshwater Fish 2008: 17: 554–566. No claim to original
US government works 2008 Blackwell Munksgaard
Abstract – In the Logan River, UT, USA, exotic brown trout demonstrate
a strong allopatric distribution and occur at high densities at low-elevation
sites and in tributaries, and in low densities at native trout dominated,
high-elevation sites. Summer temperatures and discharge do not appear
limiting for growth; adult growth rates were high overall and were greatest
when fish were held experimentally at high elevation where they do not
occur naturally. Brown trout are superior competitors; competition for
space or food was stronger with their own con-specifics than with other
species. Evidence of density dependence was not observed at the
juvenile life stage; no consistent relationships were detected between
brown trout density and age-1 condition or lagged, age-0 weight (g). In
contrast, adult brown trout demonstrated density-dependent effects on
condition and growth when reared experimentally. Field estimates of
adult growth rates (gÆday)1), although variable, declined subtly with
increasing density, and annual survival was significantly greater in the
mainstem sites (mean = 52%) relative to a high-density tributary site
(mean = 22%). Annual predicted age-0 brown trout growth potential was
four-times greater at the lowermost site, compared with the highest
elevation site, although fish lost weight over winter months at all sites.
While adult density dependence may influence population abundance at
some sites, extreme spring–winter conditions may ultimately limit the
upper elevational extent of brown trout in this system. With changing
climatic conditions and the potential for habitat degradation in the future,
these results have important implications for native fish conservation.
Introduction
Physical factors of natural stream ecosystems typically
change along a longitudinal gradient from headwaters
to low elevation outlets into larger rivers. This
longitudinal arrangement of physical factors is then
manifested in the organisation of biological communities in river ecosystems (e.g., Rahel & Hubert 1991;
Taniguchi & Nakano 2000). For temperate mountain
554
P. Budy1, G. P. Thiede1, P. McHugh2,
E. S. Hansen1, J. Wood1
1
US Geological Survey, Utah Cooperative Fish
and Wildlife Research Unit, Department of
Watershed Sciences, Utah State University,
Logan, UT, USA, 2Washington Department of Fish
and Wildlife, Olympia, WA, USA
Key words: brown trout; exotic species; growth;
survival; density dependence; temperature
P. Budy, US Geological Survey, Utah Cooperative
Fish and Wildlife Research Unit, Department of
Watershed Sciences, 5210 Old Main Hill, Utah
State University, Logan, UT, 84322-5210, USA;
e-mail: [email protected]
Accepted for publication March 3, 2008
streams dominated by trout species, two of the
most influential physical properties affecting fish
species distribution and composition are temperature
and flow regime (e.g., Fausch 1989; Poff & Allen
1995; Magoulick & Wilzbach 1998). When stream
ecosystems remain largely undisturbed, these physical
factors change predictably along the elevational and
longitudinal gradient of most streams, with temperatures and discharge increasing with decreasing
doi: 10.1111/j.1600-0633.2008.00306.x
Abiotic and biotic influences on brown trout distribution
elevation, and a concordant shift in dominant fish
species (e.g., Rahel & Hubert 1991; de la Hoz Franco
& Budy 2005).
Anthropogenic impacts to stream ecosystems, both
abiotic (e.g., water development) and biotic (e.g.,
introduced species), often alter the longitudinal gradient of physical conditions and natural distribution of
fish, frequently restricting native fishes to habitat
fragments and upper elevational headwater reaches
(de la Hoz Franco & Budy 2005; McHugh & Budy
2005). Further, anthropogenic impacts to streams may
dramatically alter species zonation (e.g., temperaturemediated competition; Fausch 1989; Fausch et al.
1994; Taniguchi & Nakano 2000), and altered habitat
may be less suitable for native species and more
favourable for exotic species, facilitating their expansion, establishment and integration (Keleher & Rahel
1996; Moyle & Light 1996a,b; Kolar & Lodge 2001,
2002). In the Intermountain West, USA, there are
numerous such examples where the combination of
habitat degradation and the introduction of exotic trout
restricts native trout to high elevation, headwater areas
which remain relatively undisturbed (Behnke 1992;
Dunham et al. 2002; Rieman et al. 2006). In response
to these combined impacts (including exotic pathogens
such as Myxobolus cerebralis), many, if not most
native and endemic cutthroat trout (Oncorhynchus
clarkii Richardson) in the Intermountain West are
declining in abundance and occupy only a portion of
their native range.
Bonneville cutthroat trout (O. c. utah Richardson),
which historically occupied most streams of the Bonneville Basin (includes parts of Utah, Idaho, Wyoming
and Nevada), are one of these imperiled fishes; they
now occupy 33% of their historic distribution and are
managed under a multi-agency Conservation Agreement (Lentsch et al. 1997, 2000). Brown trout were
introduced into many streams of the Intermountain
West (and elsewhere) in the early 1900s and now
co-occur with Bonneville cutthroat trout throughout
much of their remaining distribution (Sigler & Sigler
1996). While these exotic fish were once thought to be
relatively benign in terms of their impact on native trout
(Quist & Hubert 2005), their ability to out-compete
cutthroat trout has since been firmly established (Wang
& White 1994; McHugh & Budy 2005, 2006; Shemai
et al. 2007). Natural variation in environmental factors
(e.g., drought), further habitat degradation (e.g.,
impacts from grazing, water withdrawal) and even
large-scale environmental change (e.g., global climate
change) may all affect the future distribution of brown
trout in native trout streams. A better understanding of
factors limiting the current distribution of brown trout
will aid in prioritising and guiding management actions
aimed at cutthroat trout conservation (e.g., brown trout
removal, stream restoration).
The goal of this study was to evaluate the relative
influence of environmental variation and biotic interactions on the abundance and distribution of exotic
brown trout in the Logan River. Brown trout were
introduced into the Logan River in the early 1900s,
reproduce naturally, and dominate low-elevation areas
historically occupied by native, cutthroat trout (de la
Hoz Franco & Budy 2005). We consider four mechanisms hypothesised to limit the abundance and
distribution of brown trout in this system using
complementary data sources: (i) environmental conditions over the key summer growth period, (ii) interspecific competition with cutthroat trout (discussed
here, but previously evaluated in McHugh & Budy
2005, 2006), (iii) density dependence (e.g., growth,
survival) and (iv) the effects of extreme winter
temperatures. We used vital rates and demographic
characteristics measured along an elevational gradient
and across several years, as well as model predictions
of growth potential over winter, to evaluate the
influence of these factors in determining the abundance, distribution and upper elevational extent of
brown trout.
Study area
The Logan River runs 64 km from southeast Idaho,
through northern Utah, and eventually drains into the
Bear River, terminal to the Great Salt Lake.
The climate of the area is characterised by cold,
snowy winters (January air temperature: low, )9 C;
high, 0 C; mean precipitation 4.0 cm) and hot, dry
summers (July air temperature: low, 15 C; high,
31 C; mean precipitation 1.6 cm), yielding a hydrograph dominated by a spring-snowmelt flood (average
16 m3Æs)1) followed by base-flow conditions (approximately 3 m3Æs)1). In addition to Bonneville cutthroat
trout and brown trout (stream resident only), the river
is also inhabited by mountain whitefish (Prosopium
williamsoni Girard) and mottled sculpin (Cottus bairdi
Girard) as well as a very small number of exotic brook
trout (Salvelinus fontinalis Mitchill) and stocked
exotic rainbow trout (O. mykiss Walbaum) in isolated
areas.
Our studies have been concentrated at eight longterm sites that encompass more than 50 stream
kilometre distributed along the longitudinal gradient
of the river, and over the time-period 2001–2006.
These sites were selected as index sites based on
previous sampling throughout the drainage and capture the range of physical and biological characteristics
present. The index sites range from 2023 to 1352 m
elevation and include two tributaries: (i) Franklin
Basin (headwaters); (ii) Red Banks; (iii) Forestry
Camp; (iv) Temple Fork (tributary); (v) Twin Bridges;
(vi) Right Hand Fork (tributary); (vii) Third Dam and
555
Budy et al.
430,000
450,000
440,000
Study site location
460,000
Franklin
Basin
2091 m
Red Banks
1970 m
4,630,000
Cache
National
Forest
4,620,000
Logan
River
Chokecherry
1564 m
Lower
Canyon
1503 m
Right
Hand
Fork
440,000
UTM easting
0 1 2 3 4 5 km
450,000
(viii) Lower Logan (Fig. 1). Temperature, discharge
and other limnological information were collected at
each site hourly (e.g., temperature) or monthly (e.g.,
discharge) when physically possible. More detail on
abiotic and biotic site characteristics can be found in
de la Hoz Franco & Budy (2005), McHugh & Budy
(2005) and Budy et al. (2007). The river can be
generally described as high-quality, continuous habitat
with the exception of some anthropogenic degradation
in upper-elevation tributaries and at low-elevation sites
near the city of Logan, Utah (Budy et al. 2007). River
water is retained in three small reservoirs; the uppermost of the dams is Third Dam (Fig. 1), and
withdrawn via canals at, and downstream from, this
point.
Methods
Abundance and distribution
Fish were sampled annually to assess abundance and
distribution using electrofishing during summer baseflow conditions (late July to early August) using a
backpack-mounted electrofishing unit in smaller tributaries and a canoe-mounted electrofishing unit in
larger mainstem reaches. Based on the combination of
size–frequency modes, a sub-sample of scale-aged fish
sampled across size classes and years (N = 59), and
annual growth measurements from a subset of tagged
and recaptured fish (N = 345), brown trout were
grouped into age (size) classes as: age-1
(100–179 mm total length, TL), age-2 (180–259 mm
TL) and age-3 and above (‡260 mm TL). As
460,000
4,620,000
430,000
Twin
Bridges
1715 m
UTM northing 4,630,000
Tony
Grove
1891 m
N
556
4,640,000
4,640,000
Beaver
Creek
Fig. 1. Map of the Logan River drainage in
northern Utah, USA. Long-term index sites
are labelled with shaded symbols and site
name.
elsewhere, subadults were determined to be fish age1 and age-2 that were not sexually mature, and adult
brown trout were sexually mature at age-3 and older
(Elliott 1994; Alp et al. 2003). In this system, trout
<100 mm (age-0) are less efficiently captured using
electrofishing techniques, and the minimum size
threshold for tagging is 120 mm. Therefore our
analyses of population abundance and related measures best reflect fish >100 mm; growth and survival
estimates reflect fish >120 mm (the size category for
all response variables is provided).
Based on incidental catch during electrofishing,
while mountain whitefish densities approach 0.04
fishÆm)2 (but are extremely variable at the lowermost
site in elevation; Lower Logan); however, densities of
both mountain whitefish and sculpin are extremely low
at most mainstem sites (<0.01 and 0.03 fishÆm)2,
respectively), and both fishes are virtually absent in the
tributaries.
Population abundance was estimated using a threepass, closed model, generalised maximum-likelihood
removal estimator (White & Burnham 1999) for all
fish (>100 mm) at each site. Abundance was then
scaled up to population density per site (troutÆm)2)
based on reach length and width, and estimates
were expressed with 95% confidence intervals (CI).
Population trend was estimated using the population
estimates (2001–2006) based on linear regression of
log-transformed annual changes in population growth
rate as a function of time step (Morris & Doak 2002).
Population trend per site was expressed as lambda (k),
the annual population growth rate, with 95%CI, and an
overall k based on aggregated abundance estimates
Abiotic and biotic influences on brown trout distribution
of environmental factors that could limit brown trout
growth and survival at high elevation.
Annual survival rates were calculated based on
individual encounter histories for all tagged brown
trout. Survival (F) and recapture probability (P) were
estimated using a Cormack–Jolly–Seber open survival
model based on maximum-likelihood estimation procedures in program MARK (White & Burnham 1999).
Known unnatural mortalities (e.g., from sampling)
were excluded, and trout were grouped by site and age
group at initial capture. A stage-structured survival
modelling framework was developed whereby fish in
age groups age-1 and age-2 grew (i.e., transitioned)
into the next stage each time iteration (representing a
year), and fish in the last age group (i.e., age-3 and
older) remained in that group. A small set of a priori
candidate models were considered based on biological
hypotheses of factors affecting survival, and models
were ranked according to Akaike’s Information Criteria (AIC; Burnham & Anderson 2002). The best model
for recapture probability (P) was first estimated by
varying recapture structure (i.e., the PIM global model
and then eight reduced versions with a constant
survival structure [i.e., S(Æ)] and combinations of
group effects on P were estimated for fish age, site and
time (year) as per Franklin et al. (2004). The top
survival (F) model, that allowed us to compare
survival rates across sites, was then estimated based
on the best ‘P’ model. Lastly, survival rates were
pooled across age and evaluated for statistical differences in survival rates at the mainstem sites (omitting
the Lower Logan site because of anthropogenic
influences on survival) and compared with the tributary site using a t-test for unequal variance (a = 0.05).
Patterns in condition were assessed across index
sites using both experimental and survey data: (i)
recreated from small-scale (20 m2) enclosure experiments introduced above (McHugh & Budy 2005)
and (ii) from fish measured in the field as part of
across the index sites that contained brown trout was
also calculated as a measure of the population growth
rate for the entire Logan River population of brown
trout. A k > 1.0 indicates positive population trend,
k = 1.0 indicates no change in population growth rate,
and a k < 1.0 indicates the population is declining.
Losses of fish because of sampling (for parasite and
diet analyses; de la Hoz Franco & Budy 2004, 2005)
and mortalities incurred during sampling events
because of electrofishing or other stressors are
accounted for analytically; therefore, k values represent the observed trend at each site in the absence of
these minor fish losses.
Growth, survival and condition
Captured brown trout >120 mm, the minimum size
threshold for these tags, were marked at each site with
individually-coded, T-bar anchor tags using site-specific colours (2002–2006; Table 1). Site fidelity was
assessed by determining the number fish tagged at one
location that ere subsequently recaptured at that same
location; fish were recaptured either: (i) through our
annual electrofishing surveys, or (ii) by anglers.
Measurements of weight and length for individually
marked and recaptured fish were used to estimate
mean annual growth rate of brown trout as gÆday)1 for
each site [(sizet+1–sizet) ⁄ days]. In addition, growth
rate information from a previous cutthroat trout
competition study (e.g., brown trout were a treatment
effect; McHugh & Budy 2005) was used to characterise the brown trout growth rate potential along the
elevational gradient, particularly for high elevation
sites where brown trout are not typically captured.
In that study, native cutthroat trout were held in
replicated experimental enclosures with and without
brown trout, and growth (gÆday)1) and condition (see
below) of both species was estimated over a 42-day
summer period, thus also allowing for an assessment
Table 1. Relative location, total number of tagged and recaptured fish, mean population abundance and range (range across years by index site), and population
growth rates (k) with 95% confidence intervals for brown trout (>100 mm) at eight index sites over the 6-year period, 2001–2006.
Index site
Franklin Basin
Red Banks
Forestry Camp
Temple Fork
Twin Bridges
Right Hand Fork
Third Dam
Lower Logan
Pooled estimate
Elevation
(m)
River
km
Average stream
width (m)
Number of
fish tagged
Number of unique
recaptured fish
Mean abundance
(fishÆm)2)
Range
(fishÆm)2)
2023
1923
1855
1745
1691
1588
1509
1352
9.2
13.2
16.2
22.5
26.6
36.1
43.0
56.8
8.4
9.8
11.6
6.7
13.0
3.7
10.2
11.3
0
10
9
115
165
418
516
281
1514
0
1
2
6
60
97
130
74
0
0.003
0.004
0.120
0.029
0.623
0.161
0.087
–
0.001–0.006
0–0.012
0.001–0.349
0.020–0.042
0.179–1.050
0.111–0.223
0.027–0.248
(46)
(49)
(49)
(12)
k-value
95% CI
–
1.04
–
–
0.93
0.83
0.95
0.70
0.79
–
0.82–1.31
–
–
0.80–1.07
0.55–1.24
0.67–1.36
0.47–1.04
0.59–1.08
‘–’ signifies that estimate is not available or applicable.
Number of unique recaptured fish refers to fish encountered once, and the number in parenthesis denotes number of those same unique fish captured on 1–4
additional occasions.
557
Budy et al.
annual surveys described above. Relative weight
(Wr = W ⁄ Ws · 100; Anderson & Neumann 1996)
was used as a relative measure for comparisons of
condition along the elevation gradient and to evaluate
inter-specific competition, where: W is the observed
mass (g) of a fish, and Ws is the predicted mass (g)
based on its total length (mm) and a standard length–
weight relationship for wild brown trout in the Logan
River (Ws = 1.708 · 10)5 TL2.905; McHugh & Budy
2005). Fulton’s K (KTL = W ⁄ L3 · 100,000) was used
as a measure of condition to test for density-dependent
effects on juvenile fish (below), and facilitated comparison with other studies evaluating density dependence (Anderson & Neumann 1996).
Inter-specific competition and density dependence
Measures of condition described above were used to
compare adult brown trout performance in sympatry
(with Bonneville cutthroat trout) to allopatry, to assess
the relative influence on inter- and intra-specific
competitive interactions. In addition, the impacts of
density-dependent effects on all life stages were
assessed using linear-regression analyses. The relationship between the weight (g) of age-0 brown trout
(as the dependent variable) and subadult and adult (all
brown trout >100 mm) brown trout density (fishÆm)2
as the independent variable – from the previous year),
and similarly, the relationship between condition of
age-1 brown trout (Fulton’s K as the dependent
variable) and subadult and adult (all brown trout
>100 mm) brown trout density (fishÆm)2 as the
independent variable) were evaluated. Finally, the
relationship between subadult and adult brown trout
growth (gÆday)1 as the dependent variable) and
subadult and adult brown trout density (fishÆm)2 as
the independent variable) was independently assessed
using an exponential decay function.
Growth potential: winter temperatures
The Elliott growth model (Elliott et al. 1995) was used
to predict the relative growth potential of age-0 brown
trout during their first year of life for the four index
sites for which year-round temperature data were
available. Average, maximum and minimum daily
temperatures were continuously recorded at the Franklin Basin, Red Banks, Twin Bridges and Lower Logan
sites. Growth was assumed to be zero at lower and
upper temperature thresholds of 3.56 and 19.48 C,
respectively, and optimal growth was assumed to
occur at 13.11 C as per Jensen et al. (2003).
The average weight of an age-0 brown trout in July
as the starting weight (3.4 g), and the site-specific
potential growth of an average brown trout was
estimated for 1 year (July–June), based on the average
558
daily temperature at each site. Growth potential was
calculated over monthly intervals for 1 year, and
growth rates were expressed as gÆday)1 for comparison
to other studies.
Results
Abundance, distribution and trend
Mean (across 6 years) densities of brown trout ranged
from a high of 1.03 fishÆm)2 at a low elevation
tributary site (Right Hand Fork) to lows of <0.0025
fishÆm)2 at the uppermost end of their distribution
(Red Banks; Table 1). When these data were used to
estimate the population growth rate (k; i.e., trend),
k was <1.0 at all sites (with one exception; Red Banks)
and <1.0 for the pooled estimate (Table 1). While a
k < 1.0 indicates the population is declining, 95%
confidence intervals of k were consistently wide and
overlapped 1.0, because of inter-annual variability and
small sample size (only 6 years), indicating we cannot
conclude with certainty that the population is declining. The one exception is the trend in brown trout
abundance at the lower-most site, Lower Logan, where
abundance has demonstrated a substantial and consistent decline over time most likely in response to damrelated activities directly upstream (k = 0.70; 95%
CI = 0.47–1.04; Table 1).
Similar to the pattern documented in isolated years
as part of other studies, the 5-year mean abundance of
brown trout and cutthroat trout demonstrated a distinct
allopatric pattern of species segregation along an
elevational gradient (Fig. 1). Cutthroat trout dominate
upper (>1800 m) elevation areas, brown trout dominate lower elevation areas (<1700 m), and there is a
zone in the middle where both species are present
albeit at low density (Fig. 2). Although there is some
inter-annual variability, the overall pattern of species
distribution was generally consistent across years
(N = 6).
Environmental conditions: spring to summer growth
period
The range of temperature and discharge measured
across each index site, over the spring to summer time
period in the Logan River, does not appear to be
limiting for brown trout growth. Mean stream temperatures over this period ranged from lows of
approximately 8–10 C at high elevation sites and in
spring-fed tributaries to a high of approximately 16 C
at the lowermost site (Fig. 3). Post-spring spate and
summer (i.e., base-flow) discharge generally remains
<3 m3Æs)1 (Fig. 3). Spring maximum discharge
typically occurs in late May or June, as a function of
snow melts, and approaches 35 m3Æs)1.
Abiotic and biotic influences on brown trout distribution
0.15
Fish / m2
20
18
16
14
12
10
8
6
4
2
0
5
Cutthroat trout
Brown trout
Temperature (°C)
0.20
0.10
0.05
0.00
2100 2000 1900 1800 1700 1600 1500 1400 1300
Fig. 2. The species-zonation distribution of brown trout (black
circles) and cutthroat trout (open circles) across the elevational
gradient of the Logan River, as measured at long-term index sites
(tributary sites not included). Estimates of trout abundance
represent means in population estimates (fishÆm)2) across years
(2001–2006) ±1 standard error (SE bars may be hidden by
symbols).
4
Discharge (m3·s–1)
Elevation (m)
3
2
1
0
From July 2002 through August 2006, 1514 brown
trout were tagged and 559 brown trout were recaptured
(Table 1). Based on mark-recapture estimates of
annual growth, on average, brown trout (>100 mm)
demonstrated the highest growth rates at the Red
Banks and Lower Logan sites (up to 0.6 gÆday)1) and
the lowest growth rates in the tributaries; however,
growth rates were extremely variable across years at
some sites (Fig. 4). When brown trout were reared
experimentally in enclosures at five of the index sites,
the greatest growth rates (and condition; not shown
here) were observed at the three sites highest in
elevation (Fig. 4; see McHugh & Budy 2005 for
details). Growth rates were as high as 0.6 gÆday)1 at
the uppermost site, an area where wild brown trout are
typically not captured during annual surveys.
Recapture probability (P = 0.73; 95% CI = 0.65–
0.80) and site fidelity (approximately 100%) were
relatively high and many fish were recaptured repeatedly at the same location; only one tagged fish (1 of
1514; 0.07%) was detected at a location different from
the site where it was tagged. The only exception was
the tributary Temple Fork site, where despite relatively
high densities of fish sampled, only six tagged fish
were recaptured (Table 1). The low recapture probability (P) at this site is unsurprising because: (i) it is a
transition zone between major river zones for brown
trout and cutthroat trout, and between brown trout
moving in and out of the tributary, perhaps associated
with spawning, and (ii) the site experiences frequent
habitat changes of large magnitude when beaver
(Castor canadensis) dams are constructed and subsequently breached under high flows.
s
sin
Growth, survival and condition
k
lin
an
Fr
nk
Ba
d
Re
Ba
ry
st
re
Fo
s
p
m
Ca
in
Tw
Elevation
Th
ird
Da
ga
o
rL
we
Lo
rk
rk
n
m
ge
id
Br
e
pl
Fo
m
Te
ht
nd
Fo
Ha
g
Ri
Tributaries
Fig. 3. Mean spring to summer (May–September) temperatures
(C ± range; top panel) and mean spring to summer discharge
(m3Æs)1 ± range; bottom panel) for each index site (2001–2004).
Range is minimum to maximum. Shaded area in the top panel
depicts optimum growth range for brown trout (Elliott et al. 1995;
Ojanguren et al. 2001).
Mean annual estimates of survival rate were generally similar across age classes, yet declined with
decreasing elevation (model = {F(age + site); p(Æ)};
Fig. 5). Estimates of survival could not be obtained for
high elevation sites because of their naturally low
sample sizes, and the low survival rates at the Lower
Logan site were caused by sporadic dam sluicing
operations upstream, and associated fish kills, and
likely do not reflect natural survival rates. When
pooled across age classes, survival rates were significantly greater in the mainstem sites (Twin Bridges and
Third Dam; N = 6, mean = 52%) relative to the
tributary (Right Hand Fork; N = 3; mean = 22%)
(P = 0.03, d.f. = 3). The lowest and most variable
annual survival rates observed (mean = 10%) were for
age-3 and older fish in the Right Hand Fork tributary,
where the highest average adult fish densities occur in
the river.
Inter-specific competition
Based on earlier field experiments, brown trout
consistently out-competed cutthroat trout when reared
559
Budy et al.
1.0
7
6
tional gradient of the Logan River. Furthermore,
brown trout were unaffected by the presence of
cutthroat trout and temperature did not appear to be
a strong mediator of competition during this life stage
or time of year.
Field
experiments
0.8
8
0.6
7
8
Density dependence
0.2
Markrecapture
0.8
34
0.6
1
2
0.4
80
152
73
0.2
3
0.0
sin
n
kli
an
Fr
Ba
ed
R
s
nk
Ba
try
s
re
Fo
s
p
m
Ca
in
Tw
ge
id
Br
T
rd
hi
m
Da
w
Lo
Elevation
rk
an
og
L
er
e
pl
m
Te
Fo
rk
d
an
Fo
tH
gh
Ri
Tributaries
)1
Fig. 4. Summer growth rates (gÆday ± 1 SD) of brown trout
raised in experimental enclosures at five sites along the elevational
gradient (top panel). Annual growth rates (gÆday)1±1 SD) of tagged
and recaptured adult brown trout (>100 mm TL) at seven sites
where they occur on the Logan River, Utah over the period
2002–2006 (bottom panel). Numbers above bars indicate sample
size.
80
Age-1
Age-2
Age-3 +
Survival (%)
60
40
20
0
Twin Bridges Third Dam Lower Logan
Elevation
Right Hand Fork
Tributary
–1
Condition (K) of age-1 Growth (g·day ) of adults
0.0
No evidence of density dependence was observed at
early life stages of brown trout, despite the relatively
high densities of brown trout at some sites (see above).
Similarly, no consistent relationships were detected
between condition (Fulton’s K) of age-1 brown trout
and density (R2 = 0.00006, d.f. = 28, P = 0.97) of
brown trout (>100 mm; Fig. 6) or age-0 brown trout
weight (g) and brown trout density in the previous
year (R2 = 0.001, d.f. = 19, P = 0.88; Fig. 6).
In contrast, adult brown trout demonstrated evidence of density dependence when reared in experimental enclosures in the presence of cutthroat trout
(N = 4 brown trout, N = 4 cutthroat trout) as compared with when reared alone at the same density
(N = 8 brown trout; Fig. 4; see McHugh & Budy 2005
1.0
Weight (g) of age-0
Growth (g·day–1)
0.4
5.0
Twin Bridges
Temple Fork
Right Hand Fork
Third Dam
Lower Logan
0.8
0.6
0.4
0.2
0.0
1.3
1.2
1.1
1.0
0.9
5.5
4.5
4.0
3.5
3.0
2.5
2.0
Fig. 5. Site-specific, annual Cormack–Jolly–Seber survival rates
(±95% confidence intervals) for tagged and recaptured brown trout
across three age groups (age-1, age-2, age-3 and older) at sites
where they occur (and sufficient data were available) over the
period August 2002–August 2006 on the Logan River, Utah, USA.
in enclosures (Fig. 4). Specifically, adult brown trout
suppressed cutthroat trout growth and condition, and
the pattern was generally consistent across the eleva560
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
Brown trout density (fish/m2)
Fig. 6. The relationship between growth (gÆday)1) of adult brown
trout (>100 mm) and brown trout density (fishÆm)2; top panel),
condition (Fulton’s K) of age-1 brown trout and brown trout density
(fishÆm)2; middle panel), and mean weight (g) of age-0 brown trout
and brown trout densityt)1 (fishÆm)2; bottom panel). Points selected
from 5 years of data (2001–2006) collected at the long-term index
sites.
Abiotic and biotic influences on brown trout distribution
Cumulative weight (g)
25
20
Franklin Basin
Red Banks
Twin Bridges
Lower Logan
15
10
5
0
Start July Aug Sept Oct Nov Dec Jan Feb Mar April May June
Fig. 7. Cumulative annual growth of an age-0 brown trout (3.4 g
initial weight) from Elliott et al.’s (1995) model, predicted based on
the observed temperature data from four index sites. Model
predictions are based on an optimal temperature for growth of
13 C and full ration.
for statistical models). Condition was greater when
brown trout were raised at a lower density of their own
species but also in the presence of their competitive
inferior (cutthroat trout; see above), indicating brown
trout experience negative effects of intra-specific
interactions at higher densities and the potential for
density-dependent effects (McHugh & Budy 2005).
Further, growth rates (gÆday)1) of subadult and adult
brown trout observed in the field demonstrated a weak,
albeit insignificant, negative relationship with increasing brown trout density (R2 = 0.15, d.f. = 13,
P = 0.17; Fig. 6).
Growth potential: winter temperatures
A wide range of growth potential was observed across
four of the index sites based on predictions of annual
growth of age-0 brown trout using the Elliott growth
model (Fig. 7). After 1 year of growth, age-1 brown
trout at the Lower Logan site were 22.0 g (Gi = 1.6),
whereas at the highest elevation site, Franklin Basin,
age-1 brown trout achieved only 6.0 g (Gi = 0.3).
The pattern in these predicted growth rates parallels
our observations of age-0 brown trout growth based on
limited size-at-age data available for lower elevation
sites. Although age-0 brown trout lost weight over the
winter months at a similar rate at all sites, the total
amount of weight loss was greatest at the second
highest elevation site (Red Banks), and age-0 brown
trout recovered the least amount of weight by July of
the next year at the upper-most site (Franklin Basin).
Discussion
The goal of this study was to explore factors
potentially limiting the distribution and abundance of
exotic brown trout in a stream currently home to one
of the largest remaining metapopulations of endemic
Bonneville cutthroat trout (Budy et al. 2007).
A distinct allopatric pattern of species distribution
was observed, a pattern that appeared to fluctuate little
across years; native cutthroat trout dominate high
elevation (>1800 m) sites and exotic brown trout
dominate low elevation (<1700 m) sites with an
intermediate zone of low abundance of both species.
We evaluated four hypothesised mechanisms that
could explain this pattern, and discuss evidence for
and against each of these factors. Factors with the
potential to limit the upper elevational extent of brown
trout, where they may interact with or exclude native
trout from remaining habitat fragments, were of
notable interest.
Environmental conditions: spring to summer growth
period
Temperature and discharge are perhaps two of the most
influential abiotic factors determining fish distribution
in streams; both physical variables change predictably
along the longitudinal and elevational gradient of the
Logan River and may be important in structuring the
fish community (de la Hoz Franco & Budy 2005).
In this system, summer (base flow) discharge generally
remains <3 m3Æs)1, within the range thought to be
acceptable for brown trout age-1 and older (Heggenes
& Traaen 1988; Jensen & Johnsen 1999). Similarly,
spring-to-summer temperatures during this important
time period for growth were generally within the range
considered optimal or suitable for brown trout growth
and consumption across all index sites (12.8–16.9 C)
and were never outside the physiological thresholds for
survival (Elliott & Hurley 2000; Ojanguren et al.
2001; Jensen et al. 2003).
Accordingly, across the sites where brown trout
occur (only up to 1800 m elevation), the patterns of
growth, survival rates and population trend (k)
observed in the Logan River did not correspond to
longitudinal and elevational changes in temperature
and discharge. Annual survival rates of brown trout in
the Logan River ranged 10–66% across sites and age
classes, but were high at mid-elevation sites and lower
in the low-elevation tributary (Right Hand Fork).
Others have documented comparable survival rates in
introduced populations of brown trout in the USA
(e.g., 19–56%, McFadden & Cooper 1962; approximately 30–50%, Carlson & Letcher 2003) and native
populations in Norway (juvenile survival across three
streams, 41%; Lund et al. 2003) and Scotland (juvenile survival 70%; Egglishaw & Shackley 1977).
In addition, growth rates of wild brown trout at colder,
higher-elevation sites were similar to rates observed at
low-elevation warmer sites; however, when reared
561
Budy et al.
experimentally at colder, high-elevation sites where
they do not occur naturally, brown trout grew faster as
compared with low-elevation sites (this study;
McHugh & Budy 2005). Further, although direct
comparisons are difficult to find, growth rates of wild
brown trout in the Logan River generally exceeded
rates documented in other published studies from other
countries (Greenberg & Dahl 1998; Lobon-Cervia &
Rincon 1998; Johnson et al. 2006; but see Jensen et al.
2006). In temperate streams like the Logan River,
temperatures are within the range suitable for growth
over a limited time period from spring through early
autumn (May–September), and most of the annual fish
growth occurs over this time period (this study;
Lobon-Cervia & Rincon 1998). As a result, we
conclude that environment conditions over the spring
to summer growth period alone do not limit the upper
elevational extent of brown trout.
Inter-specific competition
Inter-specific competition has the potential to limit the
distribution of fishes and to interact with abiotic
factors along an elevational stream gradient through
processes such as temperature-mediated competition
(Fausch 1989; Fausch et al. 1994) and shifts in habitat
use (Gatz et al. 1987). Densities of nontrout fishes
(sculpin and whitefish) in the Logan River are
extremely low with distributions that do not suggest
evidence for inter-specific competition with brown
trout [e.g., contrast with sculpin densities reported by
Hesthagen & Heggenes (2003)]. Sculpin densities are
similar both at sites where brown trout occur in high
density and sites where brown trout occur only in low
abundance; note however, that these data are limited as
they are based on incidental catch. Inter-specific
competition between brown trout and cutthroat trout
in the Logan River was evaluated previously as part of
other studies (de la Hoz Franco & Budy 2005;
McHugh & Budy 2005, 2006). These studies and
others (e.g., Wang & White 1994; Shemai et al. 2007)
demonstrate that brown trout consistently out-compete
cutthroat trout. Although, the overall distribution of
brown trout was negatively associated with increased
diel temperature fluctuation (de la Hoz Franco & Budy
2005), their interactions with cutthroat trout did not
appear to be temperature-dependent (McHugh & Budy
2005). Quist & Hubert (2005) similarly demonstrated
that the influence of brown trout on cutthroat trout
density overrode the effects of physical habitat
conditions. We conclude that while brown trout likely
exclude cutthroat trout at lower elevations, interspecific competition between brown trout and cutthroat trout does not limit the upper distribution and
abundance of brown trout (but see density dependence
below) in the Logan River.
562
Density dependence
In contrast to inter-specific interactions, there are
numerous examples identifying the importance of
density dependence (intra-specific interactions) in
regulating brown trout populations through intraspecific effects on recruitment, growth, and survival
or mortality (e.g., Elliott 1984, 1994; Lobon-Cervia
2004). Despite the relatively high densities of brown
trout at some sites (1.03 fishÆm)2), little evidence of
density dependence was observed operating at the
early life stages of brown trout, nor was there a
relationship between age-0 or juvenile brown trout
size and condition and total brown trout density.
Jenkins et al. (1999) warn that density-dependent
effects can be difficult to detect based on observational
data in high-density streams and given the influence of
both scale and inter-annual variation in growth; these
factors could obscure the effects of density dependence at early life stages in our study. However, across
several years and three scales of evaluation (site,
stream and river drainage), Lobon-Cervia (2007)
similarly observed no evidence for density dependence
as a driver of population size.
Conversely, several patterns were observed indicating the potential for density dependence operating at
the subadult and adult life stages. First, brown trout
reared in sympatry with cutthroat trout demonstrated
higher growth rates than when raised at the same
densities of brown trout only, indicating that brown
trout compete more strongly for space or food with
their own con-specifics than with other species
(McHugh & Budy 2005, 2006). Second, albeit variable, adult growth rates appear to decline non-linearly
with increased brown trout density, and mean annual
survival and growth rates were generally lowest at the
sites with the highest brown trout density (but see
growth discussion below). Density-dependent effects
on subadult and adult fish growth and survival could
be manifested through a variety of mechanisms
including the reduction in the availability of food
(Lobon-Cervia 2005) and territorial behaviour, the
later of which has been demonstrated to be both
density- and size-dependent (Elliott 1990, 1994).
Based on the observations from our study, we
conclude that density dependence has the potential to
influence adult brown trout abundance; however, this
factor alone appears insufficient to explain the
observed distribution of brown trout in the Logan
River.
Growth potential: winter temperatures
Quite the opposite to the near-optimal abiotic conditions present over the spring-to-summer growth
period, spring spate and winter conditions in the
Abiotic and biotic influences on brown trout distribution
Logan River are much more severe and potentially
limiting for brown trout. We predicted annual growth
potential at four of our sites with the most complete
temperature data (temperature loggers are frequently
blown out and lost during the spring spate) using the
Elliott growth model (Elliott et al. 1995). Based on
these model predictions, age-0 brown trout lost weight
over winter months at all sites; however, after 1 year,
age-1 brown trout at the warmer, low-elevation sites
were as much as four-times larger than juvenile brown
trout at the upper-most site. There are populations of
brown trout that appear to demonstrate enhanced local
thermal adaptation resulting in relatively high growth
rates at extremely low (e.g., in Norway; Jensen et al.
2003) or high temperatures (e.g., northern Spain;
Lobon-Cervia & Rincon 1998). The original source
population of brown trout stocked into Utah rivers
remains unknown and most likely originated in more
moderate temperate streams of Europe (MacCrimmon
& Marshall 1968; Lever 1996). It should be noted that
these Elliott-model growth rates are based on theoretical model predictions with some simplified assumptions about excess ration, feeding behaviour and fish
size (Hayes et al. 2000; Rincon & Lobon-Cervia 2002;
de la Hoz Franco & Budy 2005). Nevertheless, these
model simulations highlight the importance of extreme
winter temperatures, conditions that may be especially
influential during early life-history stages of brown
trout – life stages that can be extremely sensitive and
influential in determining the abundance and distribution of stream fishes (Milner et al. 2003). In related
research, we are evaluating the spawning density and
distribution of redds, egg-to-fry survival, and the
factors that influence these life stages along the
elevational gradient of the Logan River (Wood and
Budy in press).
In addition to extreme winter temperatures, the
timing and magnitude of the spring spate also has the
potential to limit brown trout. The Logan River is a
high gradient and steep-sided stream, composed
primarily of riffles and runs with few pools.
In addition, spring spates (May–June) in the Logan
River are typically large in magnitude and occur over a
relatively concentrated time period as a function of
rapid snow melt (approximately 2–4 weeks); discharge during this time period often approaches
35 m3Æs)1, a level at which water velocity and bed
scour can be detrimental to brown trout fry (Latterell
et al. 1998). Brown trout in the Logan River spawn
during autumn at base flow and demonstrate variable
emergence timing, ranging from early May at the lowelevation sites to early July at upper elevation sites
(Wood and Budy in press). High water velocity and ⁄ or
discharge during the spring spate could result in direct
mortality through bed scour while fry are still in the
gravel and lethal displacement during emergence (e.g.,
Heggenes & Traaen 1988; Montgomery et al. 1996;
Jensen & Johnsen 1999); high flows may also have
indirect negative effects on fry and juvenile growth
and survival via dislocation into sub-optimal, high
energy habitat (e.g., reduction of available food or
space; Elliott 1990; Cattaneo et al. 2002), or because
of the synergistic effect of temperature and discharge
on fry swimming ability at low temperatures
(Heggenes & Traaen 1988; Jensen & Johnsen 1999).
Lobon-Cervia (2007) recently demonstrated that a
large amount of spatiotemporal variability in recruitment could be explained by merely two factors:
discharge during emergence and site depth. In light of
these findings and given that brown trout may not be
adapted to the timing and magnitude of the spring
spate in these high elevation, mountain rivers relative
to their native habitat (Fausch et al. 2001), the effects
of spring conditions warrant further research and
consideration.
Implications
Within the context of native fish conservation and
recovery, there is an urgent need to understand the
factors that limit the distribution of exotic brown trout
within native trout habitat (McHugh & Budy 2005,
2006; Budy et al. 2007). Both natural (e.g., climate
variability) and anthropogenic impacts to stream
ecosystems (e.g., habitat degradation, global warming)
have the potential to alter habitat conditions in the
future such that the habitat may become more, or less
susceptible, to brown trout invasion and range expansion (Moyle & Light 1996a,b; Hari et al. 2006;
Rieman et al. 2007). In this study, we demonstrated
that inter-specific competition and abiotic conditions
over the spring-to-summer growth period do not limit
the upper extent of brown trout in a native cutthroat
trout stream. Rather, density dependence at the
subadult and adult life stages appears to be influential
in determining the abundance and spring ⁄ winter
conditions appear important in determining the distribution (and upper elevational extent) of brown trout.
Alterations to natural temperature regimes, whether
natural or anthropogenic, could result in a further
expansion of exotic brown trout into native trout
habitat (e.g., Borgstrom & Museth 2005). Conversely,
habitat restoration may offer a management strategy
for reducing brown trout growth based on lower
stream temperatures achieved through the re-establishment of riparian vegetation and, potentially, hyporheic exchange (Hancock 2002; Hansen 2007).
Acknowledgements
Primary funding for this research was provided by the Utah
Division of Wildlife Resources (UDWR), Project XII, Sport
563
Budy et al.
Fisheries Research, Grant Number F-47-R, and the volunteer
assistance of the UDWR Dedicated Hunters program. Other
funding and support was provided by the Utah State
University (USU) Community-University Research Initiative,
the USU Water Initiative, and the U.S. Geological Survey
Utah Cooperative Fish and Wildlife Research Unit at USU.
Pete McHugh was partially supported by a PhD fellowship
from the Quinney Foundation. We would like to thank the
UDWR Fisheries Experiment Station, UDWR-Salt Lake City
office and UDWR Northern Region office for field assistance
and support. Thanks to the U.S. Forest Service, Logan
Ranger District, for providing continued assistance, and to
our field crews, lab technicians and graduate students in the
Fish Ecology Lab at USU. Four anonymous reviewers
provided constructive criticism of a previous draft of this
manuscript.
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