Transactions of the American Fisheries Society 139:1536–1550, 2010
Ó Copyright by the American Fisheries Society 2010
DOI: 10.1577/T09-151.1
[Article]
Introduced Lake Trout Produced a Four-Level Trophic Cascade
in Yellowstone Lake
LUSHA M. TRONSTAD*1
AND
ROBERT O. HALL, JR.
Department of Zoology and Physiology, University of Wyoming, Laramie, Wyoming 82071-3166, USA
TODD M. KOEL
Fisheries and Aquatic Sciences Program, Center for Resources,
Yellowstone National Park, Wyoming 82190, USA
KEN G. GEROW
Department of Statistics, University of Wyoming, Laramie, Wyoming 82071-3332, USA
Abstract.—Introduction of lake trout Salvelinus namaycush into a system can add a trophic level,
potentially affecting organisms at lower trophic levels. Similar to many lakes and reservoirs in the western
United States, lake trout were introduced into Yellowstone Lake, Wyoming. Previous studies showed that
lake trout reduced the population and altered the size structure of native Yellowstone cutthroat trout
Oncorhynchus clarkii bouvieri in Yellowstone Lake, but we sought to determine the degree to which lake
trout predation changed lower trophic levels. We predicted that the structure of lower trophic levels would
change in conformance with trophic cascade theory because Yellowstone cutthroat trout consume
zooplankton. We compared zooplankton and phytoplankton assemblages between the period when
Yellowstone cutthroat trout were abundant and the period after they declined. As predicted by trophic
cascade theory, zooplankton biomass shifted from being dominated by copepods before lake trout
introduction to being dominated by cladocerans after lake trout introduction, with zooplankton body lengths
17% longer after introduction. Vertical water clarity increased by 1.6 m because of a twofold decrease in
chlorophyll a and a three- to sevenfold decrease in phytoplankton biovolume. Thus, the introduction of lake
trout and subsequent decline of Yellowstone cutthroat trout likely altered lower trophic levels in Yellowstone
Lake. Trophic cascades may be common in western U.S. lakes and reservoirs where native salmonids are
present and where lake trout have been introduced.
Lake trout Salvelinus namaycush are introduced
predators in many lakes and reservoirs in the western
United States (Martinez et al. 2009). Lake trout are
apex predators (Post et al. 2000) and can cause native
and nonnative fishes to decline (Martinez et al. 2009).
For example, lake trout reduced the populations of
native Lahontan cutthroat trout Oncorhynchus clarkii
henshawi in Lake Tahoe, California, and bull trout
Salvelinus confluentus in Lake McDonald, Glacier
National Park, Montana. However, the degree to which
lower trophic levels are affected by the introduction of
lake trout is largely unknown.
Introduction of lake trout into a system may add a
trophic level to a food web, potentially producing a
four-level trophic cascade (Fretwell 1987; Post and
Takimoto 2007). Research has focused on the func* Corresponding author: [email protected]
1
Present address: Wyoming Natural Diversity Database,
University of Wyoming, Laramie, Wyoming, 82071-3381,
USA.
Received August 19, 2009; accepted May 12, 2010
Published online September 29, 2010
tional controls of the common two- and three-level
trophic cascades (Borer et al. 2005; Halpern et al. 2005;
Shurin and Seabloom 2005). Four-level trophic
cascades have seldom been included in meta-analyses,
probably because they are more difficult to observe in
longer food chains as top-down effects from predators
attenuate down the food chain (Shurin et al. 2002).
Additionally, the cumulative probability of strong
interactions among four trophic levels is lower than
that for two or three trophic levels. Nonetheless,
nonexperimental four-level trophic cascades have been
observed. For example, overfishing and removal of
Atlantic cod Gadus morhua, which served as the fourth
trophic level of the Scotian Shelf food web, increased
phytoplankton standing stocks (Frank et al. 2005).
Characteristics of the plankton assemblages depend
on the number of trophic levels in the ecosystem (e.g.,
Carpenter et al. 1987, 2001). The addition of piscivores
reduces planktivorous fish abundance, causing largebodied zooplankton to dominate the herbivore assemblage. The biomass of zooplankton and large zooplankton species (length . 1 mm) is higher in
piscivore-dominated lakes because of lower predation
1536
TROPHIC CASCADE IN YELLOWSTONE LAKE
1537
FIGURE 1.—Predicted characteristics of the zooplankton and phytoplankton assemblages of Yellowstone Lake under three
trophic levels (Yellowstone cutthroat trout dominated) and four trophic levels (lake trout dominated).
on zooplankton by planktivorous fish (Carpenter et al.
1987, 2001). Conversely, in lakes with three trophic
levels, the zooplankton assemblage is dominated by
small zooplankton species (length , 1 mm) because
planktivorous fish consume large-bodied zooplankton
(Brooks and Dodson 1965). These differences in the
zooplankton assemblage alter the phytoplankton assemblage. In experimental lakes with four trophic
levels, phytoplankton biomass and biovolume were
lower than those in lakes with three trophic levels
because of higher grazing by zooplankton (Carpenter et
al. 2001).
Lake trout were introduced into Yellowstone Lake,
where native Yellowstone cutthroat trout O. clarkii
bouvieri were previously the top predator. The
introduction of lake trout potentially increased food
chain length from three to four trophic levels. Lake
trout reduced the Yellowstone cutthroat trout population in Yellowstone Lake (Ruzycki et al. 2003; Koel et
al. 2005); our goal was to evaluate the extent to which
lake trout affected lower trophic levels via a trophic
cascade. We tested 10 predictions based on trophic
cascade theory to evaluate the degree to which lake
trout induced a trophic cascade in Yellowstone Lake
(Figure 1). We tested these predictions using data from
before and after the lake trout introduction. Taken
together, tests of these predictions represent an
approach that uses multiple lines of evidence to assess
the degree to which a trophic cascade occurred in
Yellowstone Lake. Our specific questions were (1) ‘‘To
what degree did a trophic cascade occur in Yellowstone
Lake after the introduction of lake trout?’’; (2) ‘‘How
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TRONSTAD ET AL.
did the strength of interactions among trophic levels
compare with trophic cascades in other ecosystems?’’;
and (3) ‘‘What other factors in the Yellowstone Lake
ecosystem could potentially cause changes in the
plankton of Yellowstone Lake?’’
Study Site
Yellowstone Lake is on the Yellowstone Plateau,
Wyoming, and is the largest high-elevation (2,357-m)
lake in North America (Gresswell et al. 1997), with a
surface area of 341 km2 and average depth of 43 m
(Kaplinksi 1991). Yellowstone Lake is mesotrophic
(Kilham et al. 1996) and ice covered from December
through May (Gresswell and Varley 1988). Surface
water temperatures during the ice-free season vary
between 98C and 188C (Koel et al. 2007).
The plankton assemblage in Yellowstone Lake is
composed of relatively few species that are abundant.
Phytoplankton are dominated by diatoms (Stephanodiscus spp., Cyclotella bodanica, Aulacoseira subarctica, and Asterionella formosa; Interlandi et al. 1999).
The crustacean zooplankton in Yellowstone Lake
consist of three species of copepods (Diacyclops
bicuspidatus thomasi, Leptodiaptomus ashlandi, and
Hesperodiaptomus shoshone) and two species of
cladocerans (Daphnia schødleri and Daphnia pulicaria; U.S. Fish and Wildlife Service [USFWS],
unpublished data).
The fish assemblage in Yellowstone Lake includes
two native species: Yellowstone cutthroat trout and the
less-abundant longnose dace Rhinichthys cataractae
(Gresswell et al. 1997). Adult Yellowstone cutthroat
trout (.325 mm total length [TL]) live in the littoral
zone and consume both benthic macroinvertebrates and
zooplankton (Benson 1961). Jones et al. (1990)
demonstrated that Yellowstone cutthroat trout in
Yellowstone Lake rely heavily on zooplankton. Gut
contents collected in 1989 indicated that 20% of
Yellowstone cutthroat trout ate copepods (1.6% by
volume) and 89% ate cladocerans (78% by volume, n ¼
132; Jones et al. 1990).
Lake trout were introduced into Yellowstone Lake
(Kaeding et al. 1996) in approximately 1985 (Munro et
al. 2005). Based on bioenergetics modeling of
consumption, lake trout predation is a serious threat
to the native Yellowstone cutthroat trout population in
Yellowstone Lake (Ruzycki et al. 2003). The abundance of Yellowstone cutthroat trout has declined by
60% in Yellowstone Lake and by 99% in a spawning
stream since 1990 (Koel et al. 2007). To conserve
Yellowstone cutthroat trout, the National Park Service
(NPS) actively removes lake trout by using gill nets
and electrofishing and requires anglers to kill all
captured lake trout (Koel et al. 2005). Between 1994
and 2006, the NPS removed more than 198,000 lake
trout from the lake (Koel et al. 2007).
Other threats to Yellowstone cutthroat trout include
whirling disease and drought. Myxobolus cerebralis,
the parasite that causes whirling disease, was discovered in Yellowstone Lake in 1998 and primarily affects
age-0 Yellowstone cutthroat trout only in some
spawning streams (Koel et al. 2006). Additionally,
recent drought affected age-0 Yellowstone cutthroat
trout in small tributary streams by causing the stranding
of individuals (Koel et al. 2005). The decline of
Yellowstone cutthroat trout is widespread; thus, most
Yellowstone cutthroat trout losses over the past decade
have been attributed to predation by lake trout (Koel et
al. 2008).
Methods
Inter-gill-raker spaces of Yellowstone cutthroat trout
and zooplankton width.—We compared the spaces
between gill rakers and zooplankton width to assess the
size of zooplankton that could potentially be consumed
by Yellowstone cutthroat trout in Yellowstone Lake.
We measured five inter-gill-raker spaces (GRSs) on the
first gill arch of 31 unpreserved Yellowstone cutthroat
trout (200–500 mm TL) that accidentally perished in
gill nets (Langeland and Nost 1995; Link and Hoff
1998; Budy et al. 2005). To estimate the size of
zooplankton that could be filtered by Yellowstone
cutthroat trout, we measured mean width (mm; the two
narrowest body dimensions) on arbitrarily selected
samples of over 10 individuals of each zooplankton
species. We assumed that the GRS does not change
during feeding and that gill rakers function similar to a
sieve (i.e., we assumed that zooplankton smaller than
the GRS were not retained; O’Brien 1987).
To estimate the filtering potential of Yellowstone
cutthroat trout populations before and after lake trout
introduction, we calculated the number of Yellowstone
cutthroat trout that could potentially consume each
zooplankton species. First, the maximum size of
Yellowstone cutthroat trout that could eat each
zooplankton species was determined based on zooplankton width and Yellowstone cutthroat trout GRSs.
Using estimates of the number of Yellowstone
cutthroat trout in each 10-mm size-class before and
after the introduction of lake trout (L. M. Tronstad,
unpublished data), we calculated the number of
Yellowstone cutthroat trout that could potentially
consume each zooplankton species in Yellowstone
Lake.
Zooplankton sampling.—To measure zooplankton
density, biomass, size, and production, we collected
two samples every 2–4 weeks during the ice-free
season in 2004 at four locations of Yellowstone Lake
1539
TROPHIC CASCADE IN YELLOWSTONE LAKE
(east of Stevenson Island, West Thumb, South Arm,
and Southeast Arm). These are the same sites that were
sampled by the USFWS prior to the invasion of lake
trout. In 2004, we collected zooplankton with 20-m
vertical hauls using the same procedures and nets (80lm mesh size) as used by USFWS between 24 May
and 3 October 1977–1980 (n ¼ 20 pre-introduction
zooplankton samples preserved in formalin). We
collected zooplankton samples on nine dates between
21 May and 19 October 2004 (n ¼ 72 postintroduction
samples preserved in cold sugared formalin). We
enumerated and measured both pre- and postintroduction zooplankton samples under a dissecting microscope. Because the density, biomass, and size of the
zooplankton assemblage during 1977–1980 were
similar among years (analysis of variance: P . 0.05),
we combined data among years. We calculated
zooplankton biomass (dry mass [DM]) using published
length–mass regressions (Dumont et al. 1975; Downing and Rigler 1984). We divided zooplankton into
length categories: (1) small species, which were less
than 1 mm in length (Diacyclops, Leptodiaptomus, and
nauplii), and (2) large species, which were greater than
1 mm in length (Hesperodiaptomus, Daphnia schødleri, and Daphnia pulicaria).
We calculated zooplankton production (lg
DM L1 d1) during the ice-free season in both time
periods using the egg ratio method (Downing and
Rigler 1984) for Daphnia and the size-frequency
method for copepods (Guerrero and Rodriguez 1994).
To calculate Daphnia secondary production (Downing
and Rigler 1984), we estimated density (individuals/L),
mean individual biomass (lg DM/individual), and
instantaneous birth rate (b; d1) on each sampling date.
We assumed that the finite birth rate (b) was equal to b
(i.e., birth rate ¼ death rate) and growth rate (g; d1),
and we calculated b as
b¼g¼b¼
Neggs
;
Nfemales Deggs
ð1Þ
where Neggs is the total number of Daphnia eggs
(counted both inside and outside of individuals),
Nfemales is the total number of female Daphnia, and
Deggs is the development time of eggs (d) calculated
using the model of Bottrell (1975):
loge Deggs ¼ 3:4 þ 0:22 loge T 0:34 loge T 2 ;
ð2Þ
where T is surface water temperature (8C) measured in
the past (1977–1980; Theriot et al. 1997) and present
(2004). We calculated total biomass on each date i by
multiplying density by mean individual mass. Secondary production (P) was estimated by
P¼
t
X
DBi bi Ddi ;
ð3Þ
i¼1
where DB is the change in biomass (lg DM/L), and Dd
is the number of days between sampling dates.
We calculated copepod secondary production using
the size-frequency method (Guerrero and Rodriguez
1994), which is used when a species is constantly
reproducing. To calculate copepod production, we
divided individuals into six equal length-classes and a
nauplius (immature copepod) size-class. Because we
could not identify nauplii, we divided nauplii among
the species based on the percent abundance of each
copepod taxon. We calculated biomass by multiplying
the density of individuals within each size-class across
all sampling dates by individual biomass. We calculated production as
P¼
s
X
DBi S;
ð4Þ
i¼1
where S is the number of size-classes. To calculate
copepod production on a per-unit-time basis, the cohort
production interval (total sampling interval/development time) was multiplied by P. To derive the cohort
production interval, we used an empirical model
developed by Gillooly (2000) to estimate the postembryonic development time (D; d) of zooplankton:
D¼
ð138M0:3 Þ
;
T
ð5Þ
where M is adult copepod DM (lg) and T is between
58C and 208C.
Phytoplankton sampling.—To measure density and
biomass of the postintroduction phytoplankton assemblage, we collected water from 5- and 15-m depths
using an Alpha bottle (Wildco) every 2–4 weeks during
the ice-free season of 2004 in the same four areas used
for zooplankton sampling. We preserved 100 mL of
water to a final concentration of approximately 0.5%
glutaraldehyde, and we permanently mounted samples
on 25-mm, white-gridded HAWG filters (0.45-lm pore
size; Millipore Corporation, Billerica, Massachusetts).
Using phase contrast on a compound microscope, we
estimated phytoplankton abundance and biovolume by
scanning at 1603 for large species and at 4003 for
smaller species. Knight (1975) measured phytoplankton biovolume at five locations to 20-m depth in the
West Thumb of Yellowstone Lake between 14 June
and 24 September 1972. Interlandi et al. (1999) and
Interlandi and Kilham (2001) measured phytoplankton
density and biovolume in northern Yellowstone Lake
down to 50-m depth during the open-water seasons of
1996 and 1997. From these data, we used only
1540
TRONSTAD ET AL.
information from the epilimnion (i.e., top 20 m of
water column). We used the same phytoplankton
identifications as Interlandi et al. (1999). Knight
(1975) identified phytoplankton differently than Interlandi et al. (1999), but we matched similar taxa using
the key developed by Patrick and Reimer (1966) and
cell size.
We estimated phytoplankton biomass based on
chlorophyll a by collecting approximately 125 mL of
lake water in the West Thumb from 5 m in 2004 and
1,200 mL of water from 5, 10, and 15 m in 2005. To
concentrate phytoplankton, we filtered sample water
through 25-mm, type-A/E glass-fiber filters (Pall Life
Sciences, Port Washington, New York). We extracted
chlorophyll a by incubating filters overnight in a 90%
solution of ethanol buffered with MgCO and measured
chlorophyll-a concentration using the acid method with
a pheopigment correction (Nusch 1980) on a TD-700
fluorometer (Turner Designs, Sunnyvale, California).
We calibrated a secondary solid standard using a
primary chlorophyll-a commercial standard of Anacystis nidulans (Sigma-Aldrich) before each field season.
Knight (1975) measured chlorophyll-a concentrations
to 20-m depth in the West Thumb during 1972 by
using acetone extraction and a spectrophotometer
(Strickland and Parsons 1972). We corrected Knight’s
(1975) chlorophyll-a concentrations using Nusch’s
(1980) comparisons of acetone and ethanol extractions.
Water clarity was measured by the NPS using a
Secchi disk during the ice-free seasons of 2003–2006
in three areas of Yellowstone Lake (east of Stevenson
Island, South Arm, and West Thumb). Historical water
clarity data for the ice-free seasons of 1976–1991 at the
same sites are from Theriot et al. (1997).
Statistical analysis.—To calculate the filtering
ability of Yellowstone cutthroat trout, we used ordinary
least-squares (OLS) regression to estimate the relationship between Yellowstone cutthroat trout TL and GRS.
To quantify the filtering size of the zooplankton
assemblage in Yellowstone Lake, we regressed mean
width against length for each zooplankton species by
using OLS linear regression.
We compared the size structure of Yellowstone
cutthroat trout and zooplankton in Yellowstone Lake
before and after the introduction of lake trout. To
quantify the size structure of Yellowstone cutthroat
trout, we compared the number of Yellowstone
cutthroat trout per net (standardized index of Yellowstone cutthroat trout abundance in Yellowstone Lake)
in each size-class by using the Kolmogorov–Smirnov
goodness-of-fit test (Zar 1999). We binned individuals
into 100-mm TL classes, calculated the percentage of
fish in each length-class, and compared the percentages
of Yellowstone cutthroat trout in each bin between pre-
introduction (1977) and postintroduction (2004) data.
We tested for differences in the distribution of
zooplankton sizes between pre-introduction (1977–
1980) and postintroduction (2004) periods using a
Kolmogorov–Smirnov goodness-of-fit test. We binned
zooplankton individuals into 1-mm size-classes and
calculated the percentage of individuals in each sizeclass.
To compare density and biomass of zooplankton
between 1977–1980 and 2004, we used a bootstrap
procedure. For each of the 36 sample pairs (two
samples per date and location), we randomly selected
two observations with replacement. For the 1977–1980
period, the data collected had only one observation at
some of the time points. Thus, we used a parametric
bootstrap, resampling each datum from a normal
distribution with a mean equal to the logarithm of the
observed datum (or the mean of values for dates with
multiple observations) and SDs. These values were
then back-transformed to become the bootstrap values
for each sampling event. Bootstrap means of 1977–
1980 and 2004 data were repeated 1,000 times, and we
calculated the difference in their means. The SD of
these difference values was used as our bootstrap
estimate of the SE of the mean difference.
Phytoplankton density and biovolume were sampled
at even intervals among time periods. To compare the
differences in mean phytoplankton density and biovolume between pre- and postintroduction time periods,
we estimated the SE for each period using a sequential
differences formula designed to reduce the upward bias
in the variance estimator based on the usual sample
variance (Wolter 1984). For both zooplankton and
phytoplankton, we calculated the difference in the
means between the two time periods and a 95%
confidence interval (CI) for that difference (upper and
lower 2.5% of data were removed), assuming the two
samples to be independent. Confidence intervals that
did not include zero implied biologically significant
differences. Finally, we compared chlorophyll-a concentrations using a t-test. West Thumb concentrations
in 2004 and 2005 were not different (t-test: t ¼ 0.40,
df ¼ 17, P ¼ 0.70), so we combined these data and
compared the concentrations with those collected in
1972 (Knight 1975).
To evaluate whether Secchi depths changed through
time, and because this variable was the only one that
was measured continuously, we checked for first-order
autocorrelations using a Durbin–Watson (DW) test
(test statistic values range from 0 to 2) and for higherorder correlations using autocorrelation functions in the
Statistical Package for the Social Sciences (version
12.0.1; SPSS, Inc., Chicago, Illinois). We did not
detect temporal autocorrelation (i.e., DW test statistic
TROPHIC CASCADE IN YELLOWSTONE LAKE
1541
FIGURE 2.—(A) Box-and-whisker plot showing the median and 10th, 25th, 75th, and 90th percentiles of width (mm; mean of
the two smallest body dimensions) for each zooplankton species in Yellowstone Lake (three copepod taxa plus copepod nauplii;
two cladoceran taxa: Daphnia schødleri and Daphnia pulicaria). Horizontal lines are the inter-gill-raker spaces (GRSs; mm) for
a 200- or 400-mm total length (TL) Yellowstone cutthroat trout. Based on GRSs, a 200-mm individual can eat most zooplankton
in the lake, but a 400-mm individual can only retain the largest zooplankton, D. pulicaria. (B) The size-frequency distribution of
Yellowstone cutthroat trout in the lake changed between 1977 (before lake trout introduction) and 2004 (postintroduction), with
fewer and larger fish in 2004. (C) The number of Yellowstone cutthroat trout that could potentially consume each zooplankton
species was higher in the pre-introduction period, when Yellowstone cutthroat trout were smaller and more abundant.
; 2); thus, we used multiple regression. To account for
increases in water clarity throughout summer stratification, we used multiple regression with year and
Julian day as independent variables and Secchi depth
as the dependent variable.
To estimate the effect size for each variable before
1998 compared with after 2003, we used the log
response ratio log(Xpresent /Xpast), where Xpast is the
mean of the variable before 1998 and Xpresent is the
mean of the same variable after 2003 (Osenberg et al.
1997; Hedges et al. 1999; Shurin et al. 2002).
Results
Effect of Yellowstone Cutthroat Trout on Zooplankton
Yellowstone cutthroat trout in Yellowstone Lake
were able to consume zooplankton throughout their
lives, even when they reached sizes exceeding 400 mm
TL. The GRS (mm) was positively related to TL (mm)
of Yellowstone cutthroat trout:
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TRONSTAD ET AL.
FIGURE 3.—Yellowstone cutthroat trout densities declined both in Yellowstone Lake (open squares; standardized fall
gillnetting surveys) and in a spawning stream, Clear Creek (solid circles). Yellowstone cutthroat trout abundance recently
declined due to lake trout introduction (in 1985), whirling disease (discovered in 1998), and drought. Figure is modified from
Koel et al. (2005b). Discharge from the Yellowstone Lake outlet (black line) is also shown (U.S. Geological Survey, http://
waterdata.usgs.gov/nwis/rt).
loge GRS ¼ 10:7ð6 0:5Þ þ 1:8ð6 0:1Þ 3 loge TL
ð6Þ
2
(r ¼ 0.70, df ¼ 153, P , 0.0001; 695% CIs), showing
that larger fish had larger GRSs and could filter only
large zooplankton (Figure 2A). Zooplankton sizes
significantly differed among the species. Diacyclops,
Leptodiaptomus, and nauplii were smaller than 0.4 mm
in width, with nauplii being significantly smaller than
the two other groups. Hesperodiaptomus and Daphnia
schødleri were between 0.5 and 1.0 mm in width,
whereas Daphnia pulicaria were significantly larger,
with mean width exceeding 1.3 mm. Therefore, a 200mm TL Yellowstone cutthroat trout with a mean GRS
of 0.32 mm could filter individual zooplankton of all
species in Yellowstone Lake except Diacyclops and
nauplii, but a 400-mm TL fish with a mean GRS of
1.11 mm could only filter Daphnia pulicaria.
The number of Yellowstone cutthroat trout that
could potentially consume zooplankton was lower in
2004 than in 1977–1980 due to decreased abundance
and increased size of Yellowstone cutthroat trout
(Figure 2B). Yellowstone cutthroat trout abundance
declined after the introduction of lake trout (Figure 3).
Thus, there were fewer Yellowstone cutthroat trout to
consume zooplankton in 2004 than in 1977–1980.
Additionally, the size structure of adult Yellowstone
cutthroat trout shifted to longer individuals, changing
the ability of these fish to consume zooplankton.
Larger Yellowstone cutthroat trout have larger GRSs
and can consume only the largest zooplankton species
(Figure 2A). After the introduction of lake trout, fewer
Yellowstone cutthroat trout had the potential to
consume zooplankton of all species present in Yellowstone Lake (Figure 2C).
Zooplankton in Yellowstone Lake
The zooplankton assemblage in 1977–1980 differed
from the 2004 assemblage in terms of both individual
size and species composition. Zooplankton shifted
from an assemblage dominated by small copepods in
1977–1980 (large species comprised 24% of biomass)
to an assemblage with higher abundance and biomass
of large species in 2004 (large species comprised 51%
of biomass; bootstrapped 95% CI for the mean change
¼ 55.1 to 34.7 mg DM/m3; Figure 4A). Total
biomass was two times higher in 2004 compared with
1977–1980 (bootstrapped 95% CI for the mean change
¼65.6 to 26.1 mg DM/m3), probably because of the
increase in the proportion of large species.
Length of individual zooplankton and the assemblage changed between 1977–1980 and 2004. The
length of individual zooplankton species averaged 17%
greater in 2004 (Figure 4B). Because the zooplankton
assemblage shifted to larger species in 2004, the mean
length of an individual zooplankter in the assemblage
TROPHIC CASCADE IN YELLOWSTONE LAKE
1543
FIGURE 4.—(A) Biomass (lg dry mass [DM]/L) of zooplankton (three copepod taxa plus copepod nauplii; two cladoceran
taxa: Daphnia schødleri and Daphnia pulicaria) collected from four areas of Yellowstone Lake in 1977–1980 (before lake trout
introduction) and 2004 (postintroduction). (B) The mean individual length (mm) of each zooplankton species was larger in 2004
than in 1977–1980, and (C) the zooplankton size distribution was also larger in 2004 than in 1977–1980. (D) Zooplankton
secondary production (lg DM L1 d1) was similar between the two periods.
increased from 0.40 mm in 1977–1980 to 0.55 mm in
2004 (t-test: t ¼ 2.62, df ¼ 33, P ¼ 0.01), and the
frequency of individuals in each size-class changed
between the two time periods (Kolmogorov–Smirnov
test: dmax ¼ 13.3, k ¼ 20, P , 0.05, where dmax is the
test statistic and k is the number of categories; Figure
4C).
Production of small zooplankton was 45% higher in
1977–1980 than in 2004. Production of large zooplankton was 150% higher in 2004 than in 1977–1980
(Figure 4D). However, total zooplankton production
was similar between the two periods. The b for
Daphnia schødleri was higher in 2004 (0.04 per day)
than in 1977–1980 (0.01 per day). For Daphnia
pulicaria, b was similar between periods (0.12 per
day). Zooplankton daily production : biomass ratio
(turnover rate) was slightly higher in 1977–1980 (0.055
per day) than in 2004 (0.046 per day).
Phytoplankton in Yellowstone Lake
Phytoplankton biomass in Yellowstone Lake was
lower after the introduction of lake trout. Chlorophyll-a
concentration, an indicator of phytoplankton biomass,
was twice as high in 1972 (Knight 1975) compared
with 2004 and 2005 (t-test: t ¼ 4.8, df ¼ 16, P ¼ 0.0002;
Figure 5A) in the West Thumb. The total density of
phytoplankton in Yellowstone Lake during 2004 was
intermediate to the densities in 1996 and 1997 (Figure
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TRONSTAD ET AL.
FIGURE 5.—(A) Chlorophyll-a concentrations (Chl a; lg/L) in the West Thumb of Yellowstone Lake were twice as high during
the ice-free season of 1972 (Knight 1975; before lake trout introduction) compared with 2004 and 2005 (postintroduction). (B)
Total phytoplankton density (cells/mL; þ95% confidence interval [CI]) was similar in 1996, 1997, and 2004, but the diatom
density was greater in 2004 than in 1996–1997. (C) Total phytoplankton biovolume (mm3/m3; 695% CI) was three times higher
in 1972 and 1996 and nearly seven times higher in 1997 than in 2004. (D) Taxon-specific changes to phytoplankton biovolume
depended on the species (not all phytoplankton species are shown). Biovolume of Asterionella was higher in 2004 than in 1972;
biovolumes of Anabaena, Stephanodiscus yellowstonensis, Aulacoseira, and Rhodomonas were lower in 2004 than in 1972; and
biovolumes of S. jamsranii and S. minutus were similar between the pre- and postintroduction periods.
5B). Conversely, total phytoplankton biovolume in
Yellowstone Lake was three times higher in 1972
(sequential differences, 95% CI of change ¼ 58.7–
222.0 mm3/m3; Knight 1975), three times higher in
1996 (sequential differences, 95% CI of change ¼ 124–
186 mm3/m3; Interlandi and Kilham 2001), and 6.5
times higher in 1997 (sequential differences, 95% CI of
change ¼ 356–449 mm3/m3) compared with 2004
(Figure 5C).
Differences in the phytoplankton assemblages were
taxon specific. Total density of diatoms was 2.5 times
higher in 2004 (sequential differences, 95% CI of
change ¼740 to 175 cells/mL for 1996 and 733 to
223 cells/mL for 1997) compared with 1996 and
1997 because of higher densities of Stephanodiscus,
Synedra, and Cyclotella; there was no difference
between 1996 and 1997 (sequential differences, 95%
CI of change ¼141 to 162 cells/mL; Figure 5B). The
differences were mainly driven by the density of small
phytoplankton (greatest axial linear dimension , 30
TROPHIC CASCADE IN YELLOWSTONE LAKE
1545
FIGURE 6.—(A) Secchi depths (m) in Yellowstone Lake have become deeper through time between 1976 (before lake trout
introduction) and 2006 (postintroduction). The plotted line shows the fit for year and Secchi depth only (variation explained by
Julian day was not included). Inset illustrates that log(Secchi depth) was negatively related to log(chlorophyll a).
lm). Biovolumes of the taxa Stephanodiscus yellowstonensis, Anabaena, Aulacoseira, and Rhodomonas
were higher in 1972, whereas Asterionella had higher
biovolume in 2004 (Figure 5D).
Water clarity increased between 1976 and 2006 (15
July–15 September; Figure 6). Secchi depths showed
little first-order (DW test statistic ¼ 1.84) or higherorder autocorrelation. Year (df ¼ 84, P ¼ 0.0033) and
Julian day (df ¼ 84, P , 0.0001) explained 26% of the
variation in Secchi depth. According to the relationship, Secchi depth increased by 0.053 m each year
(695% CI):
Secchi depth ¼ ½0:053ð6 0:03Þ 3 year
þ ½0:045ð6 0:02Þ 3 day
105ð6 68Þ:
ð7Þ
Secchi depths were 1.6 m (0.7–2.5 m) deeper in 2006
compared with 1976. Deeper Secchi depths indicated a
decrease in phytoplankton biomass:
loge ðSecchi depthÞ ¼ 0:44ð6 0:09Þ 3 loge C
þ 1:7ð6 0:07Þ
ð8Þ
(df ¼ 29, R2 ¼ 0.44, P , 0.0001), where C is
chlorophyll-a concentration (lg/L; Figure 6 inset).
Discussion
Evidence of a Trophic Cascade in Yellowstone Lake
Reduced abundance and increased mean body size
of Yellowstone cutthroat trout altered the assemblage
of zooplankton in Yellowstone Lake through consumption. Yellowstone cutthroat trout size structure
likely affected the removal of zooplankton because the
number of large fish increased, simultaneously increasing GRS. Similarly, Post et al. (2008) showed that two
subpopulations of alewives Alosa pseudoharengus
filtered different sizes of zooplankton, which resulted
1546
TRONSTAD ET AL.
in trophic cascades of different strengths. Additionally,
reduced Yellowstone cutthroat trout abundance produced changes in the Yellowstone cutthroat trout diet,
thereby altering the zooplankton assemblage. Tronstad,
Hall, and Koel (unpublished data) observed that in
years when Yellowstone cutthroat trout were abundant
in Yellowstone Lake, their diet was largely composed
of zooplankton, whereas in the years after their decline
they consumed more benthic invertebrates. Similarly,
Hodgson and Kitchell (1987) observed that zooplankton constituted a larger fraction of the diet for adult
largemouth bass Micropterus salmoides when these
fish were more abundant.
The introduction of lake trout into Yellowstone Lake
had a small effect on zooplankton production. We
calculated that zooplankton production was only 13%
higher when Yellowstone cutthroat trout dominated
Yellowstone Lake. Using modeling, Scavia et al.
(1988) calculated that zooplankton production was
five times higher in Lake Michigan when the
abundance of planktivorous alewives was high than
when alewife abundance was low. We expected higher
zooplankton production in 1977–1980 because turnover rates of smaller individuals are faster (Gillooly
2000; Huryn and Benke 2007). However, trophic
cascade theory does not predict changes in zooplankton
secondary production.
Phytoplankton biomass was lower after lake trout
introduction into Yellowstone Lake. Whole-lake experiments demonstrated that phytoplankton biovolume
(Carpenter et al. 1987; Findlay et al. 2005) and
chlorophyll a (Carpenter et al. 2001) were about three
times higher when planktivores dominated. Similarly,
biovolumes of phytoplankton in Yellowstone Lake
were 3.0–6.5 times higher and chlorophyll-a concentrations were two times higher prior to the invasion of
lake trout. Although interannual variability of total
phytoplankton biovolume was large and varied with
local climate (Kilham et al. 1996), phytoplankton
biovolume after the introduction of lake trout was
significantly lower than all pre-introduction estimates.
Furthermore, the density of small phytoplankton taxa
increased in Yellowstone Lake after the introduction of
lake trout. Similarly, the density of small phytoplankton increased in Bighorn Lake, Banff National Park,
Alberta, after the removal of planktivorous fish (i.e.,
number of trophic levels was reduced from three to
two; Parker and Schindler 2006). Large phytoplankton
taxa were also lost from the assemblage after the
addition of largemouth bass and removal of minnows
(northern redbelly dace Phoxinus eos, finescale dace P.
neogaeus, and central mudminnow Umbra limi) in
Tuesday Lake, Michigan (Carpenter et al. 1987).
Smaller individual biovolumes or a larger proportion
of smaller phytoplankton taxa may explain why total
phytoplankton biovolume in Yellowstone Lake was
lower but density was similar in 2004.
A sparser phytoplankton assemblage after the
introduction of lake trout into Yellowstone Lake
(number of trophic levels was increased to four)
increased water clarity by 1.6 m. Similarly, lakes
dominated by Daphnia pulicaria, a large zooplankton
species that often predominates in lakes with an even
number of trophic levels, had deeper water clarity than
lakes dominated by smaller zooplankton (Kasprzak et
al. 1999). Eliminating fish in a Norwegian lake (two
trophic levels after fish removal) also increased water
clarity by 3 m (Reinertsen et al. 1990).
Multiple lines of evidence suggested that the
Yellowstone Lake food web changed from three to
four trophic levels, ultimately lowering phytoplankton
biomass. Individually, each measurement contained
low inference because any one data point is likely to be
unreliable. However, the support of multiple hypotheses can indicate lake trout-induced change. Together,
90% of the hypotheses (Figure 1) were in the predicted
direction based on trophic cascade theory and only
10% were inconclusive, providing strong evidence that
the food web of Yellowstone Lake effectively changed
to four trophic levels (Table 1). The calculated effect
size of zooplankton and phytoplankton in Yellowstone
Lake (2.2 times difference between the pre- and
postintroduction periods) were within the range
reported for herbivores (1.4–17.3 times) and primary
producers (1.1–18.0 times) from multiple ecosystem
types (Schmitz et al. 2000; Shurin et al. 2002).
Furthermore, Polis and Strong (1996) suggested that
when the ratio of direct to indirect effects of predators
is greater than 1, the effects of predation attenuate
down the food chain. Conversely, when the ratio is less
than 1, predator effects intensify down the food chain.
The ratio of direct effects (2.0; Yellowstone cutthroat
trout) to indirect effects (mean ¼ 2.2; zooplankton and
phytoplankton) in Yellowstone Lake suggests that
predation by lake trout was nearly equally transmitted
down the food chain, indicating strong interactions at
each trophic level. Lake trout are specialist piscivores
that tend to be apex predators with the longest food
chains (Post et al. 2000). The strength of the cascading
trophic interactions in Yellowstone Lake may be
attributable to the lake’s biota, including ectothermic
predators, invertebrate herbivores, and small primary
producers, which can facilitate a trophic cascade (Borer
et al. 2005; Shurin and Seabloom 2005; Shurin et al.
2006). Compared with many lakes inhabited by lake
trout, Yellowstone Lake contains few other fish species
and lacks nonnative mysid shrimp Mysis relicta. Thus,
the observed interactions may have been stronger
1547
TROPHIC CASCADE IN YELLOWSTONE LAKE
TABLE 1.—Responses of Yellowstone cutthroat trout (YCT), zooplankton, and phytoplankton to the introduction of lake trout
into Yellowstone Lake. Based on trophic cascade theory, we predicted the response of variables to the addition of lake trout.
Means and 95% confidence intervals (MoE ¼ margin of error) of the response variables are reported. The mean and MoE of
zooplankton biomass were bootstrapped, and phytoplankton biovolume was calculated from sequential differences. We
calculated significant differences in zooplankton and phytoplankton based on changes between the pre- and postintroduction
periods (see Methods). We compared the response variables for the past (before 1998) and present (after 2003) using a log
response ratio of means (log10(Xpresent/Xpast)). Lake trout enhanced the variable when the ratio was positive and reduced the
variable when the ratio was negative; ratios near zero indicate that the variable was similar between the two time periods. The
conclusion column states whether the data fit the prediction (yes), produced the opposite finding as expected (no), or were
inconclusive (?). Asterisks indicate that the two time periods were significantly different and agreed with the hypothesis (after
Hebblewhite et al. 2005).
Past
Variable
a
YCT abundance (fish/net) *
Zooplankton individual length (mm; Daphnia pulicaria)*
Zooplankton assemblage length (mm)*
Zooplankton biomass (mg dry mass [DM]/m3)*
Large zooplankton biomass (mg DM/m3)*
Cladoceran biomass (mg DM/m3)*
Zooplankton production (mg DM m3 d1)b
Phytoplankton biovolume (mm3/m3)c*
Chlorophyll a (lg/L)*
Secchi depth (m)d*
Present
Prediction
Mean
MoE
Mean
MoE
P-value
Log ratio
Conclusion
þ
þ
þ
þ
þ
þ
15.5
1.88
0.40
49.7
16.6
13.9
5.4
214
1.9
10.0
1.9
0.088
0.04
10.4
4.6
3.9
6.2
2.24
0.55
97.8
63.3
46.9
4.8
74
0.8
11.6
1.2
0.076
0.01
2.97
2.3
2.3
,0.0001
,0.0001
0.0095
0.40
0.08
0.20
0.30
0.58
0.53
0.05
0.47
0.38
0.003
Yes
Yes
Yes
Yes
Yes
Yes
?
Yes
Yes
Yes
40
0.2
9
0.4
0.0002
0.0033
a
Index of YCT abundance from fall gillnetting surveys (Figure 3) in 1977 and 2006.
Confidence intervals were not calculated for secondary production estimates.
Past phytoplankton biovolume was from 1972 (Knight 1975).
d
Secchi depth was calculated using the model in Figure 6 based on a date of 15 August (Julian day 228) in 1976 and 2006.
b
c
because there are few fish to replace the role of
Yellowstone cutthroat trout in the food web of
Yellowstone Lake.
Alternative Hypotheses
Other factors besides the introduction of lake trout
may have altered the trophic structure of Yellowstone
Lake. For example, surface water temperatures increased by 0.298C per decade in Yellowstone Lake
during the past 30 years (i.e., 1976–2006; Tronstad,
Hall, and Koel, unpublished data). Such temperature
increases could directly influence the zooplankton and
phytoplankton of the lake. Similar to Yellowstone
Lake, March–June water temperatures in Lake Washington, Washington, increased by 0.358C per decade
during the past 40 years (i.e., 1962–2002; Winder and
Schindler 2004). The altered thermal regime in Lake
Washington caused asynchrony in Daphnia and
phytoplankton blooms. As a result, densities of
Daphnia declined, but there were no increases in adult
size (Winder and Schindler 2004). In addition, Winder
and Schindler (2004) observed higher juvenile Daphnia mortality with increasing temperatures, suggesting
low food availability. In contrast with Lake Washington, Daphnia in Yellowstone Lake have become
both more abundant and larger, suggesting reduced
predation pressure rather than responses to water
temperatures and low food availability (e.g., Brooks
and Dodson 1965). We suggest that the observed
changes in the Yellowstone Lake zooplankton assemblage are more likely due to the introduction of lake
trout and loss of Yellowstone cutthroat trout than to
increased temperature.
Climate change may also affect the phytoplankton
assemblage in Yellowstone Lake by altering precipitation and nutrient availability. Using experiments and
observations, Interlandi and Kilham (1998) predicted
that increasing atmospheric nitrogen deposition would
shift the phytoplankton assemblage from diatoms to
green and blue-green algae. Despite increasing atmospheric nitrogen deposition at Tower, Yellowstone
National Park (NADP 2007; http://nadp.sws.uiuc.edu/),
we observed higher diatom densities in 2004 compared
with those observed in 1996–1997. However, a
zooplankton assemblage dominated by large individuals (four trophic levels) decreased the biovolume of
large phytoplankton (Carpenter et al. 1987) because of
an increased capacity to handle and consume larger
phytoplankton taxa (Bergquist et al. 1985). Similarly,
the decrease in Stephanodiscus yellowstonensis, a large
centric diatom (mean biovolume ¼ 2,480 lm3/individual), was probably caused by altered zooplankton
grazing. Conversely, the colonial diatom Asterionella
increased when the zooplankton assemblage was
dominated by cladocerans (four trophic levels; Bergquist et al. 1985), similar to our observations in
1548
TRONSTAD ET AL.
Yellowstone Lake. Finally, we did not observe the
Anabaena sp. (blue-green algae) bloom in Yellowstone
Lake during 2004 (0 mm3/m3 on 26 August 2004),
whereas such blooms were observed prior to the
introduction of lake trout (360 mm3/m3 on 25 August
1972; Knight 1975). Likewise, Scavia et al. (1988)
noted a high biomass of blue-green algae under three
trophic levels and extremely low biomass under two
trophic levels. Our data suggest that the decreases in
phytoplankton biomass and biovolume were more
likely due to increased grazing pressure of a zooplankton assemblage dominated by large cladocerans than to
climate change or increasing nitrogen deposition.
Drought may reduce Yellowstone cutthroat trout
abundance and alter the trophic structure of Yellowstone Lake. During drought years, low water levels in
small spawning streams can kill juvenile Yellowstone
cutthroat trout (Koel et al. 2005). To estimate the
degree to which drought caused the Yellowstone
cutthroat trout decline, we compared discharge of the
Yellowstone Lake outlet with indices of Yellowstone
cutthroat trout abundance over time (Figure 3).
Abundance decreased during both wet and dry years;
thus, we attribute most of the loss of Yellowstone
cutthroat trout to lake trout predation.
Management Implications
The ecosystem consequences of introducing predators are more easily understood when a single
perturbation occurs, such as the loss of an apex oceanic
predator as occurred in the Scotian Shelf ecosystem
(Frank et al. 2005). The effects of numerous invasive
predators and perturbations can be difficult to untangle,
such as in the Great Lakes (e.g., Scavia et al. 1988;
Kitchell et al. 2000; Mills et al. 2003). However,
studying the effects of an invasive predator in an
otherwise relatively undisturbed ecosystem is opportune. We demonstrated that lake trout likely induced a
four-level trophic cascade and decreased primary
producer biomass. Lake trout have been introduced
into over 200 lakes and reservoirs in the western
United States (Martinez et al. 2009), and these
piscivores may induce trophic cascades and change
energy flow in water bodies with native salmonids.
In Yellowstone Lake, the impacts of lake trout
predation have resulted in a population decline from
which the Yellowstone cutthroat trout may be unable to
fully recover. The effects of lake trout predation were
transmitted down the food web, indicating strong
interactions at each trophic level. However, the
interaction between humans and lake trout is weak.
Even with intensive lake trout suppression efforts by
the NPS, evidence suggests that lake trout continue to
regulate Yellowstone cutthroat trout and maintain an
altered trophic structure within Yellowstone Lake.
Future research should address how much lake trout
removal is needed to allow recovery of Yellowstone
cutthroat trout and reversion of the Yellowstone Lake
food web to its historic configuration.
Acknowledgments
Thanks to Christine Fisher, Heather Thon, Jessie
Julien, Liz O’Connor, Don Alzner, Lusha Alzner,
Bryan Tronstad, and Lisa Kunza for helping with
sample collection and processing. Jeff Arnold, Pat
Bigelow, Brian Ertel, Dan Mahony, Phil Doepke,
Christie Hendrix, Christine Smith, and the seasonal
fisheries staff (2003–2006) in Yellowstone National
Park made this research possible. Christine Fisher
created the line drawings. Historical data from Edward
Theriot, Sebastian Interlandi, Susan Kilham, and the
Fisheries and Aquatic Sciences Program of Yellowstone National Park were very helpful for making
comparisons with past conditions. Thanks to Merav
Ben-David, Wayne Hubert, Bill Reiners, Richard
Beamish, and three anonymous reviewers for comments that improved the manuscript. Financial support
to L.M.T. and R.O.H. was provided by the Environmental Protection Agency’s Experimental Program to
Stimulate Competitive Research (R-82942601–0),
University of Wyoming–NPS, and Jackson Hole One
Fly Foundation–National Fish and Wildlife Federation.
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