Freshwater Biology (2010) 55, 2138–2152
doi:10.1111/j.1365-2427.2010.02474.x
Can filter-feeding Asian carp invade the Laurentian Great
Lakes? A bioenergetic modelling exercise
SANDRA L. COOKE AND WALTER R. HILL
Institute of Natural Resource Sustainability, Illinois Natural History Survey, University of Illinois, Champaign, Illinois, U.S.A.
SU M M A R Y
1. There is much concern that filter-feeding Asian carp will invade the Laurentian Great
Lakes and deplete crucial plankton resources. We developed bioenergetic models, using
parameters from Asian carp and other fish species, to explore the possibility that
planktonic food resources are insufficient to support the growth of silver carp (Hypophthalmichthys molitrix) and bighead carp (H. nobilis) in the Great Lakes.
2. The models estimated basic metabolic requirements of silver and bighead carp under
various body sizes, swimming speeds and reproductive stages. These requirements were
then related to planktonic food resources and environmental temperature to predict when
and where silver and bighead carp may survive in the Great Lakes, and how far they may
travel.
3. Parameter values for respiration functions were derived experimentally in a coordinated
study of silver and bighead carp, while consumption parameters were obtained from
the literature on silver carp. Other model parameters lacking for Asian carp, such as those
for egestion and excretion, were obtained from the literature on other fish species.
4. We found that full-sized bighead carp required 61.0 kJ d)1 just to maintain their
body mass at 20 C, approximately equivalent to feeding in a region with 255 lg L)1
macrozooplankton (dry) or 10.43 lg L)1 chlorophyll a. Silver carp energy requirements
were slightly higher.
5. When applied to various habitats in the Great Lakes, our results suggest that silver and
bighead carp will be unable to colonise most open-water regions because of limited
plankton availability. However, in some circumstances, carp metabolism at lower
temperatures may be low enough to permit positive growth even at very low rations.
Positive growth is even more likely in productive embayments and wetlands, and the
modelled swimming costs in some of these habitats suggest that carp could travel
>1 km d)1 without losing biomass.
6. The simulation (and firmly hypothetical) results from this modelling study suggest
when and where Asian carp could become established in the Great Lakes. Given the
potential consequences to Great Lakes ecosystems if these filter feeders do prove capable
of establishing reproducing populations, efforts to keep Asian carp out of the Great
Lakes must not be lessened. However, we do encourage the use of bioenergetic
modelling in a holistic approach to assessing the risk of Asian carp invasion in the Great
Lakes region.
Keywords: bighead carp, invasive species, planktivore, risk assessment, silver carp
Correspondence: Sandra L. Cooke, Institute of Natural Resource Sustainability, Illinois Natural History Survey, University of Illinois,
1816 South Oak Street, Champaign, Illinois 61820, U.S.A. E-mail: [email protected]
Present Address: Biology Department, Duke University, Box 90025, Durham, North Carolina 27708-0025, U.S.A.
2138
2010 Blackwell Publishing Ltd
Bioenergetics of invasive Asian carp 2139
Introduction
As humans continue to transport species and erode
natural barriers to biological invasions, ecosystems
throughout the world have born the consequences.
The Laurentian Great Lakes have experienced cascading ecological effects from over 180 invasive species
(Holeck et al., 2004), and most scientists and resource
managers agree that it is critically important to
prevent further species introductions to and from this
region (Vander Zanden & Olden, 2008). Two aquatic
invaders of particular concern in the Great Lakes
basin (and in over 30 other countries around the
world) are bighead carp (Hypophthalmichthys nobilis
Richardson) and silver carp (H. molitrix Valenciennes), collectively known as Asian carp. These carp
have invaded the Mississippi River Basin and are now
found in waterways connected to the Laurentian
Great Lakes (Chick & Pegg, 2001). Bighead and silver
carp are fast-growing, high-volume filter feeders with
a generalist diet of both phytoplankton and zooplankton (Kolar et al., 2007). Studies on the mobility of
silver and bighead carp show they can travel up to
64 km d)1, depending on river flow and other variables (DeGrandchamp, Garvey & Colombo, 2008), and
thus they have the potential to enter and invade new
regions rapidly.
Recent studies suggest that Asian carp may
adversely affect native planktivorous fishes including
gizzard shad (Dorosoma cepedianum LeSueur) and
bigmouth buffalo (Ictiobus cyprinellus Valenciennes)
in the Illinois River (Irons et al., 2007). There is
concern that Asian carp in the Illinois River will enter
Lake Michigan via the Chicago Sanitary and Ship
Canal (CSSC) and similarly affect native planktivores,
both invertebrate and vertebrate, through competition
for limited food resources. Other possible modes of
introduction into the Great Lakes include bait-bucket
transfer, movement from other U.S. and Canadian
catchments and release from live fish markets (Herborg et al., 2007; Keller & Lodge, 2007).
Although earlier models of invasion risk predicted
the invasion potential of silver carp in the Great Lakes
to be low (Kolar & Lodge, 2002), more recent ecological niche models predict that most of the Great Lakes
catchments (Chen, Wiley & Mcnyset, 2007), and the
Great Lakes themselves (Herborg et al., 2007), offer
suitable environments for bighead and silver carp to
establish reproducing populations. These models use
2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
variables such as precipitation, river discharge, slope
and per cent tree cover to predict the potential range
of invasive species. While such climatic and hydrological variables are important; biotic variables,
including food availability and energetic constraints,
can be used to predict a more realistic range of
suitable environments. Bioenergetics models are useful tools that allow fisheries ecologists and resource
managers to predict growth and food requirements of
both native and exotic species in aquatic ecosystems.
Developing bioenergetic models of bighead and silver
carp would enable a comparison of their energy
requirements to the energy available in the plankton
of potential invasion sites, such as the Great Lakes,
which are oligotrophic in most locations. An understanding of bighead and silver carp bioenergetics
should also be valuable for managing their populations in ecosystems where they are already established. Food availability has been suggested as an
influence on microhabitat selection of Asian carp in
the Illinois River (DeGrandchamp et al., 2008).
Despite the abundance of Asian carp in both their
native Asian and non-native North American habitats,
the bioenergetic requirements of these fishes have
only been sparsely reported in the mainstream literature (but see Mukhamedova, 1977). Our purpose was
to develop bioenergetics models for bighead and
silver carp using empirically determined respiration
rates and bioenergetic parameters derived from literature on Asian carp and other fish species. We used
these models to assess the theoretical potential of
bighead and silver carp to colonise habitats in the
Laurentian Great Lakes, based on plankton biomass
and surface water temperature data. Our theoretical
analysis also takes into account the possible effects of
thermal stratification and swimming costs on carp
growth and movement estimates. We hypothesised
that most open-water habitats of the Great Lakes will
be much less likely than littoral habitats to support the
establishment of bighead and silver carp, because of
between-habitat differences in plankton biomass and
temperature.
Methods
Model development
We structured bighead carp and silver carp models
following the widely used Wisconsin bioenergetics
2140
S. L. Cooke and W. R. Hill
V ¼ ðCTM TÞ=ðCTM CTOÞ
model (Hanson et al., 1997). The basic energy balance
equation described by the model is:
C ¼ ðR þ A þ SDAÞ þ ðF þ UÞ þ ðDB þ GÞ
ð1Þ
where total consumption of energy (C) is equal to the
sum of metabolism (respiration, R; active metabolism,
A; and specific dynamic action, SDA), wastes (faecal
egestion, F; and urinary excretion, U) and growth
(somatic growth, DB; and gonad production, G). Each
component of this overall equation has different forms
of the temperature dependence and mass dependence
functions that can be used, depending on the physiology of each species.
We used the form of the consumption function
designed for warm-water species (eqn 2 in Fish
Bioenergetics 3.0 software; Kitchell, Stewart & Weininger, 1977; Hanson et al., 1997):
C ¼ CA W CB p V x eðXð1VÞÞ
ð2Þ
where C is the specific consumption rate (g g)1 d)1);
CA and CB are the intercept and slope of the
allometric mass function, respectively; W is fish mass
(g); and p is the proportion of maximum consumption.
The temperature dependence parameters are defined
as follows:
Parameter
2
0:5 2
ð2aÞ
X ¼ ðZ ð1 þ ð1 þ 40=YÞ Þ Þ=400
ð2bÞ
Z ¼ LnðCQÞ ðCTM CTOÞ
ð2cÞ
Y ¼ LnðCQÞ ðCTM CTO þ 2Þ
ð2dÞ
where T is temperature (C), CQ is the temperaturedependent coefficient, CTM is the maximum temperature above which consumption ceases, and CTO is
the optimum temperature.
Bighead and silver carp filtration and consumption
rates are highly variable, being dependent not just
on body size and temperature, but also on particle
size (Kolar et al., 2007). Smith (1989) observed that
juvenile silver carp had maximum filtration rates of
particles >70 lm compared to other particle sizes.
Smith (1989) developed an allometric relationship
that explained 99% of the variance for silver carp
feeding at 20 C on particles >70 lm, and we use
these parameters for our bighead and silver carp
consumption equation (Table 1). For the temperature
dependence parameters of the consumption equation, we calculated mean CTO and CTM from values
reported for Asian carp in the literature (reviewed
by Kolar et al., 2007). We used CQ from tilapia
(Sarotherodon spp. and Oreochromis spp.; Hanson
Description
Value
Consumption
CA
Intercept for maximum consumption
CB
Mass dependence coefficient
CQ
Temperature dependence coefficient
CTO
Optimum temperature (C)
CTM
Maximum lethal temperature (C)
Egestion and excretion
FA
Intercept of the proportion of consumed energy egested
FB
Temperature dependence coefficient for egestion
FG
Ration dependence coefficient for egestion
UA
Intercept of the proportion of consumed energy excreted
UB
Temperature dependence coefficient for excretion
UG
Ration dependence coefficient for excretion
Metabolism
RA
Intercept of mass dependence function
RB
Slope of mass dependence function
RQ
Approximates Q10 over low temperatures
ACT
Activity multiplier for a constant swimming speed
SDA
Proportion of assimilated energy lost to specific dynamic
action
1.54*
)0.287*
2.5†
29, 26‡
43, 38‡
Table 1 Bioenergetics parameters for silver (first value) and bighead carp (second
value). In some cases, the same parameter
was used for both species
0.212§
)0.222§
0.631§
0.031§
0.58§
)0.299§
0.0028, 0.0053
)0.239, )0.299
0.076, 0.048
1.0
0.1†
*
Smith, 1989;
Nitithamyong (in Hanson et al., 1997)
‡
Kolar et al., 2007;
§
Elliott, 1976 (in Hanson et al., 1997)
†
2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
Bioenergetics of invasive Asian carp 2141
et al., 1997) because tilapia are planktivorous filter
feeders with thermal tolerances and feeding characteristics very similar to Asian carp (Table 1). We also
assumed that Asian carp energy density was the
same as adult tilapia (5442 J g)1 wet mass; Hanson
et al., 1997).
In a review of fish bioenergetics studies, Chipps &
Wahl (2008) discuss the importance of not overestimating waste losses when modelling consumption at
low rations. Thus, for modelling egestion (F) and
excretion (U), we used equation set 2 in Fish Bioenergetics, which addresses this overestimation problem
by accounting for fish mass, temperature and ration
(Hanson et al., 1997):
F ¼ FA TFB eFGp C
ð3Þ
U ¼ UA T UB eUGp ðC FÞ
ð4Þ
where FA and UA are intercepts of the proportion of
consumed energy egested and excreted, respectively,
versus temperature and ration; FB and UB are the
coefficients of temperature dependence; FG and UG
are the coefficients for ration dependence; p is ration
(proportion of maximum consumption); and T is
temperature. For these functions, we used parameters
modified for brown trout Salmo trutta Linnaeus
(Hanson et al., 1997; Table 1). This set of parameters
has been used for other species, including yellow
perch Perca flavescens Mitchill (Kitchell et al., 1977) and
lake trout Salvelinus namaycush Walbaum (Stewart
et al., 1983).
We used the form of the respiration function that
allows an input of swimming speed (eqn 1 in Fish
Bioenergetics, Hanson et al., 1997):
R ¼ RA W RB eRQT eRTOVEL
ð5Þ
where R is the specific rate of respiration (g g)1 d)1);
RA and RB are the intercept and slope of the
allometric mass function, respectively; RQ approximates the Q10; RTO is swimming speed in cm s)1; and
VEL is a function that allows swimming speed to vary
with body mass and temperature. When using Fish
Bioenergetics 3.0 software, if swimming speed is a
constant (i.e. not dependent on mass or temperature),
then the activity multiplier is set to 1 and RTO is set to
the desired velocity. To develop our model, we
assumed that average swimming speed was constant
because the swimming respirometer allowed mainte 2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
nance of a more or less constant swimming velocity
for each fish (see below). We also assumed that
specific dynamic action (SDA) for both species was
equal to 0.10 (Table 1), the value developed for tilapia
(Hanson et al., 1997).
Respiration rates of adult and juvenile bighead and
silver carp were taken from Hogue & Pegg (2009),
who measured oxygen consumption with both a static
respirometer and a Brett-style swimming respirometer following the methods of Cech (1990). Respiration
in the Hogue & Pegg (2009) study was measured over
a temperature range of 4.5 C to 26.9 C. Because
those authors had difficulty in getting bighead carp to
swim in the swimming respirometer, only resting data
were used for bighead carp, whereas the silver carp
trials were successfully conducted at 0, 20 and
30 cm s)1.
To obtain values for RA, RB and RQ for silver
carp, we used a Ln-transformed version of eqn. 5, so
that the respiration data could be fitted to the
equation using multiple linear regression (Stewart
et al., 1983).
ln R ¼ RA þ RB lnðWÞ þ RQT þ vU
ð5aÞ
where m is an empirical constant and U is swimming
speed in cm s)1. The parameters we obtained were:
lnR ¼ 5:880:239lnðWÞþ0:076T þ0:0074U
ð5bÞ
The model fitted the data reasonably well (adjusted
R2 = 0.77), and all parameters were significant
(P < 0.0001), with the exception of m (P = 0.12) whose
lack of significance may have resulted from relatively
few observations at different swimming speeds. Thus,
the form of the respiration equation we used for silver
carp in Fish Bioenergetics 3.0 was:
R ¼ 0:00279 W 0:239 e0:076T
ð5cÞ
For bighead carp, multiple linear regression of the
respiration data was used to fit values for RA, RB and
RQ similar to those for silver carp except that a
swimming component was not included. The resulting equation was:
R ¼ 0:00528 W 0:299 e0:048T
ð5dÞ
This model fitted the data reasonably well (adjusted
R2 = 0.74), and all parameters were significant
(P < 0.0002).
2142
S. L. Cooke and W. R. Hill
Sensitivity analysis
We conducted a sensitivity analysis on the parameters
listed in Table 1 following the procedure in Kitchell
et al. (1977) and Stewart et al. (1983). Each parameter
was separately varied by +10% and )10% from its
nominal value, and the resulting output (specific
consumption rate required for metabolic maintenance) was compared to the nominal specific consumption rate (from the standard simulation). This
sensitivity analysis was carried out for a 2400 g
resting adult of each species feeding on zooplankton
prey with an energy density of 2512 J g)1 wet mass
(Cummins & Wuycheck, 1971) at 20 C. Sensitivities
were calculated as follows:
sðpÞ ¼
10DC
C
ð6Þ
where s(p) is sensitivity of parameter p (a value of 1
means that a 10% change in the parameter causes a
10% change in consumption), C is the simulated
required daily consumption rate for metabolic maintenance, and DC is the change in C because of the
change in p. Parameters that were most sensitive
include RA and RB, but no parameter had a sensitivity
value larger than 2.58 (Table 2), and all sensitivity
parameters were within the range of those observed in
other bioenergetics studies (e.g. Kitchell et al., 1977;
Stewart et al., 1983).
Model application
Fish Bioenergetics 3.0 software, which was developed
for the Wisconsin model (Hanson et al., 1997), was
used to predict daily consumption requirements of
bighead and silver carp for basic metabolic maintenance (no growth). We generated simulations for
three different body sizes: 10 cm long (10 g) juveniles; 20 cm long (70 g) sub-adults and 60 cm long
(2400 g) adults. Consumption requirements were
generated for different swimming speeds (0–
4 cm s)1) at 20 C (we kept temperature constant
here because our purpose was to assess the effects of
body size and swimming speed on consumption).
These swimming speeds may seem low, but when
calculated as daily distance travelled (e.g. 4 cm s)1 is
3.5 km d)1) they fall within the range of observed
mean movement rates for both species (0.21–
10.61 km d)1; DeGrandchamp et al., 2008). Consump-
Table 2 Sensitivities of the specific consumption rate required
for routine metabolic maintenance (no growth) to deviations of
each input parameter. Sensitivities were calculated for 2400 g
resting silver carp and bighead carp at 20 C
Input error – silver
Parameter
Consumption
CA
CB
CQ
CTO
CTM
Egestion
FA
FB
FG
Excretion
UA
UB
UG
Metabolism
RA
RB
RQ
SDA
Input error –
bighead
+10%
)10%
+10%
)10%
+0.00
)0.00
+0.01
+0.02
)0.00
+0.00
+0.01
)0.00
)0.00
+0.01
)0.01
)0.01
)0.00
)0.01
)0.01
+0.00
)0.00
)0.00
)0.01
+0.00
+0.14
+0.10
+0.02
)0.13
)0.08
)0.02
+0.12
+0.09
+0.00
)0.12
)0.09
+0.00
+0.21
+0.46
+0.02
)0.25
)0.37
)0.02
+0.21
+0.43
)0.03
)0.26
)0.40
)0.03
+1.84
+2.05
+1.65
+0.14
)0.32
)1.70
)1.42
)0.14
+0.96
+2.58
+0.96
+0.11
)1.04
)2.10
)0.94
)0.17
tion requirements were also estimated for a 2400 g
female of each species spawning 5% of its body
mass, or a gonadosomatic index (IG) of 5. Papoulias,
Chapman & Tillitt (2006) report IG values of 0–9.6 for
bighead and silver carp in the Missouri River.
Simulation outputs were obtained as specific consumption rates (J g)1 d)1) required for metabolic
maintenance (no growth) for resting and swimming
fish. For each size fish, the consumption rate in kJ d)1
was converted to kJ L)1 by taking into account the
filtration rate of the fish. Using the allometric
relationship from Smith (1989), we assumed that 10,
70 and 2400 g Asian carp filter 191, 764 and
9502 L d)1, respectively. To express these energetic
requirements in terms of environmental prey densities, we converted the kJ L)1 values to chlorophyll a
(Chl a) concentrations and zooplankton dry biomass
(both in lg L)1). For zooplankton, we assumed that
all prey had a mean energy density of 2512 J g)1 wet
mass (Cummins & Wuycheck, 1971) and that the
ratio of zooplankton wet mass to dry mass was 10:1
(Dumont, Van de Velde & Dumont, 1975). To obtain
Chl a concentrations, we assumed that all phytoplankton had a mean energy density of 2460 J g)1
2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
Bioenergetics of invasive Asian carp 2143
wet mass (Hambright, Blumenshine & Shapiro, 2002),
the ratio of wet mass to dry mass was 2.5 (Reynolds,
1984), and that the ratio of Chl a to dry mass was 100
(Reynolds, 1984).
To model the growth of carp feeding in different
types of habitats within the five Laurentian Great
Lakes, we compiled data on Chl a, phytoplankton
biomass, zooplankton densities, zooplankton biomass
and water temperature from multiple regions. In cases
where surface water temperatures were not provided
with the plankton data, we approximated the ‘typical’
temperature for a site and season based on the
temperature data available from NOAA’s Great
Lakes Environmental Research Laboratory (http://
www.glerl.noaa.gov/data/) and the EPA’s Great
Lakes Environmental Database (http://www.epa.
gov/greatlakes/monitoring/data_proj/glenda/index.
html). Our goal was to include a selection of recently
sampled sites representative of offshore pelagic
habitats as well as coastal embayments and wetlands
with higher plankton biomass. We also included
plankton data collected at different times of year
across a range of temperatures. This selection of
locations and seasons is far from comprehensive, but
nevertheless represents a broad range of habitats
within the Great Lakes. The data selected include a
recent study of a late winter production pulse in
southern Lake Michigan (Kerfoot et al., 2008); a survey
of Great Lakes wetlands (Lougheed & Chow-Fraser,
2002; open water habitats only); and a comparison of
zooplankton biomass and Chl a in embayment,
nearshore and offshore regions in Lake Ontario (Hall
et al., 2003). We also applied the model to several
riverine sites to demonstrate that the model predicts
positive growth in habitats where Asian carp have
already invaded. We used the bioenergetics models to
estimate expected growth (biomass loss or gain) of
juvenile (10 g) and adult (2400 g) non-swimming
bighead and silver carp in each region over 30 days
(a reasonable amount of time to allow a potential new
invader to establish a ‘foothold’ in the new habitat).
For habitats in which non-swimming Asian carp were
predicted to have positive growth, we determined the
maximum distance that the carp could travel without
losing biomass by setting growth to zero (metabolic
maintenance), solving the bioenergetics model for
mean velocity (RTO in Fish Bioenergetics 3.0), and
then calculating distance travelled over 30 days based
on this mean velocity. These distance calculations are
2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
merely estimates that assume that water flow is not a
factor.
In generating estimates of growth and swimming
costs and we used the filtration rates and prey energy
density stated previously. Most of the zooplankton
data available were densities rather than biomass. To
convert zooplankton densities to dry mass, we
assumed that each taxon exhibited average body
lengths and applied length-weight regressions from
Culver et al. (1985), which were developed for Great
Lakes zooplankton. For rotifers, we used the mean
biomasses presented in Dumont et al. (1975). Not all
zooplankton data sets included rotifers, and we noted
these exceptions. Because most of the phytoplankton
data were in Chl a concentrations rather than phytoplankton biomass, we used the conversion factors
mentioned previously.
To assess the effects of temperature on growth rates,
we selected four open-water habitats that would
normally be thermally stratified during the summer,
for which summertime plankton data are available,
and for which modelled growth at surface temperature was negative. These sites were Lake Michigan’s
southern basin (September), Collingwood Harbour of
Lake Huron, the central basin of Lake Erie, and the
nearshore zone of Sandy Pond (Lake Ontario). We
simply re-ran the model at different temperatures
from 4 to 24 C for 30 days of feeding. We ran
separate simulations at a constant temperature for
each temperature to compare more effectively the
growth of a carp feeding at the chlorophyll maximum
and at other depths (with cool water) with carp
growth in the warmer epilimnion.
Measured respiration rates of any fish species may
overestimate resting metabolic requirements because
of the difficulty in measuring the respiration of
completely inactive fish in a chamber (Cech, 1990;
Hogue & Pegg, 2009). To counter the potential issue
of overestimating energy requirements and underestimating growth, we made several conservative
assumptions. In addition to the assumption of all
particle sizes being consumed at the same maximum
rate, we assumed that all prey were 100% digestible;
all prey were easily captured by passive filter feeding
(no escape by swimming zooplankton); and all prey
had a constant, relatively high energy density. We
also assumed that carp filtration rates did not vary
with swimming speed (when in reality a swimming
fish would filter a higher volume than a resting fish).
2144
S. L. Cooke and W. R. Hill
10 000
However, because we may have overestimated resting filtration rates and because the simulated swimming speeds were so low, the differences in filtration
rates because of swimming speed are probably
negligible.
The specific consumption rate required to maintain a
constant fish mass increased with swimming speed
and decreased with fish size (Fig. 1). At 20 C, silver
carp specific consumption rates were slightly higher
than those of bighead carp: resting silver carp weighing 10 g, 70 g and 2400 g required 1.4, 6.1 and
91 kJ d)1, respectively, while bighead carp of those
masses required 1.3, 5.1 and 61 kJ d)1. A 2400 g
reproducing silver carp (IG = 5) requires 415 kJ d)1,
while a similar bighead required 380 kJ d)1. Consumption requirements of reproducing carp were
higher at all swimming speeds, although the differences between reproducing and non-reproducing
adults were smaller at higher speeds because of the
higher energetic costs of swimming compared to
reproducing (Fig. 1). When the daily requirements
and Asian carp filtration rates are translated into Chl a
currency, resting silver carp weighing 10, 70 and
2400 g require 11.91, 13.08 and 15.50 lg L)1 Chl a to
maintain their mass (Fig. 2). When compared as
environmental densities of zooplankton, resting silver
carp of those masses require 292, 320 and 379 lg L)1
of zooplankton dry mass, and bighead carp require
273, 266 and 255 lg L)1dry mass (Fig. 2). Environmental requirements were similar for non-reproducing Asian carp of different sizes because of the greater
filtration rates of larger carp. The model assumed that
activity was an exponential function of swimming
speed, and thus predicted specific consumption rates
of swimming carp were quite high compared to
resting carp (e.g. Fig. 1).
The projected growth of non-swimming silver and
bighead carp feeding on phytoplankton and zooplankton in different regions of the Great Lakes was
negative in almost all open-water regions of Lakes
Michigan, Superior, Huron and Ontario (Table 3).
However, positive growth was predicted in Green
Bay, western Lake Erie and all of Lake Erie during the
spring, the embayment regions of Sodus Bay and
Sandy Pond (Lake Ontario), and some wetlands.
Modelled growth was positive in the riverine habitats
1000
Specific consumption rate for metabolic maintenance (J g-1 day-1)
Results
(a)
100
10
1
0
10 000
1
2
3
4
5
1
2
3
4
5
(b)
1000
100
10
1
0
Swimming speed (cm s-1)
Fig. 1 Specific energy consumption rates required for basic
metabolic maintenance (no growth) of (a) silver carp and (b)
bighead carp. Values were generated for a 10 g juvenile (triangle), 70 g sub-adult (square), 2400 g non-reproducing adult
(open circle) and 2400 g female spawning 5% of its body mass
(closed circle) at swimming speeds of 0, 1, 2, 3 and 4 cm s)1.
where Asian carp have established reproducing populations (Table 3).
The maximum distance that carp could travel in
different Great Lakes habitats without losing biomass
over 30 days ranged from 0.8 to 33.7 km for 10 g
bighead and silver carp and 2.4–35.0 km for 2400 g
carp (Table 4). The range of maximum movement
predicted in riverine habitats ranged from 9.3 to
38.9 km for 10 g carp and 2.6–39.9 km for 2400 g carp
(Table 4).
2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
Bioenergetics of invasive Asian carp 2145
0.10
150
100
0.06
0.04
50
0.02
0.00
10 g
70 g
2400 g (NR)
2400 g (R)
200
(b)
0.10
150
0.08
0.06
100
0.04
50
0.02
0.00
10 g
70 g
2400 g (NR)
2400 g (R)
Body size and reproductive stage
Growth simulations at different temperatures suggest that carp would generally have higher growth
rates at lower temperatures (Fig. 3). Although carp
were projected to lose biomass at surface temperatures, modelled growth was positive at low temperatures (<8 C) in all four habitats.
Discussion
Our modelling results indicate that the low concentrations of plankton in many open-water regions of
the Laurentian Great Lakes cannot support growth of
silver and bighead carp. The threat of these filterfeeding fish establishing open-water populations and
disrupting the pelagic food web in the oligotrophic
regions of the lakes therefore appears to be small.
However, our results also indicate that more productive regions, such as Green Bay, the western basin of
2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
0
4000
3000
2000
1000
0
5000
4000
3000
2000
1000
0
Required zooplankton biomass (mg L-1)
0.12
0
Required chlorophyll a concentration (mg L-1)
Fig. 2 Estimated environmental energy
density, Chl a concentration and zooplankton dry mass required for (a) silver
carp and (b) bighead carp to meet basic
metabolic demands (no growth). Estimates were generated for a 10 g juvenile,
70 g sub-adult, 2400 g non-reproducing
(NR) adult and 2400 g female spawning
5% of its body mass (R) at swimming
speeds of 0 (black bars), 1 (grey bars) and
2 cm s)1 (white bars).
Required energy density to maintain body mass (kJ L-1)
0.08
5000
Required zooplankton biomass (mg L-1)
(a)
Required chlorophyll a concentration (mg L-1)
200
0.12
Lake Erie and some other embayments and wetlands,
may contain enough plankton to meet energetic
requirements at certain times of year and at certain
temperatures. Furthermore, although modelled energetic costs of swimming were high, the simulations
predict that carp in some of these habitats could still
travel up to 40 km over a 30-day period while
maintaining body mass. Many embayments, wetlands
and other coastal zones are important habitats and
nurseries for larval fishes such as alewives (Alosa
pseudoharengus Wilson; Klumb et al., 2003) and walleye (Sander vitreus Mitchill; Roseman et al., 2005).
Thus, although Asian carp would probably not
become established in most nearshore or offshore
pelagic habitats of Lakes Ontario, Michigan, Superior
and Huron, they might indirectly affect those ecosystems if they became established in adjoining embayments and wetlands. The effect of Asian carp on
2146
S. L. Cooke and W. R. Hill
Table 3 Projected growth, based on bioenergetics models, of juvenile (10 cm, 10 g) and adult (60 cm, 2400 g) non-swimming bighead
carp (BC) and silver carp (SC) foraging on zooplankton (zoop) and phytoplankton (phyto) for 30 days at different times of year
and in different regions of Lakes Michigan, Superior, Huron, Erie and Ontario, and riverine habitats currently invaded by Asian carp
(Spr = spring; Sum = summer)
Location
Lake Michigan
southern basin, nearshore
Time of
year,
water
temperature
(C)
Phyto.
wet
mass
(mg L)1)
Zoop.
wet
mass
(mg L)1)
Predicted % biomass gain or
loss over 30 days
10 g
BC
10 g
SC
2400 g
BC
2400 g
SC
References
May, 8.8
Jul, 19.4
Sep, 20.2
Apr, 3.4
Apr, 3.6
Apr, 13.4
Jun, 20.3
0.69
0.69
0.69
0.52
0.19
5.5
5.5
0.024
0.15
0.79
0.18
0.045
0.16
4.72
)15
)29
)20
)9
)17
+63
+120
)9
)30
)23
)2
)11
+66
+113
)3
)6
)4
)2
)4
+15
+28
)3
)10
)9
)1
)3
+13
+23
C. E. Cáceres unpubl.
data (zoop); Gardner
et al., 2004 (Chl a)
Kerfoot et al., 2008
May, 3.4
Aug, 9.4
Jul, 22.5
Jul, 22.5
Jul, 22.5
0.31
0.32
1.42
1.13
0.07
0.16
0.59
2.52
2.22
3.19
)13
)12
+13
+3
+2
)6
)6
+5
)4
)5
)3
)2
+4
+2
+1
)2
)3
)3
)5
)5
Brown & Branstrator,
2004 (NR)
Lougheed &
Chow-Fraser, 2002;
pers. comm.
Jul, 22.5
1.42
1.83
+2
)5
+1
)5
Jul, 22.5
Jul, 22.5
0.57
0.07
0.056
0.024
)38
)46
)43
)51
)9
)10
)15
)16
Lougheed &
Chow-Fraser, 2002;
pers. comm.
Spr, 6.1
Sum, 21.0
Spr, 6.1
Sum, 21.0
Spr, 6.1
Sum, 21.0
Jun, 22.5
Jul, 22.5
3.31
3.12
0.63
1.21
1.82
1.06
0.14
0.36
0.69
1.74
1.14
0.95
0.29
0.62
0.46
0.40
+46
+31
+8
)12
+13
)20
)38
)36
+50
+25
+14
)16
+20
)23
)43
)41
+10
+8
+2
)2
+3
)2
)9
)8
+9
+2
+2
)7
+3
)9
)15
)14
Conroy et al., 2005 (NR)
Lake Ontario
Sodus Bay embayment
Sodus Bay nearshore
Sandy Pond embayment
Sandy Pond nearshore
Frenchman’s Bay (wet)
Bronte Creek (wet)
Jul, 20.0
Jul, 20.0
Jul, 20.0
Jul, 20.0
Jun, 22.5
Jun, 22.5
1.87
0.29
1.11
0.64
8.94
1.84
5.91
0.81
6.06
0.76
1.57
0.42
+82
)26
+72
)21
+116
)14
+77
)28
+67
)24
+104
)20
+20
)6
+17
)4
+28
)3
+14
)10
+12
)9
+21
)9
Hall et al., 2003; pers.
comm. (NR)
Middle Mississippi River
Chester
Grand Tower
Upper Mississippi River
Missouri River
Aug, 22.0
Oct, 16.0
Sum, 27.0
Sum, 23.0
5.00
10.0
8.77
5.30
0.05
0.01
3.75
1.39
+30
+130
+127
+37
+23
+130
+102
+27
+8
+30
+31
+9
+2
+26
+19
+2
within production pulse
outside production pulse
Green Bay
Lake Superior
western arm
Chippewa Park (wet)
Pine Bay (wet)
Hurkett Cove (wet)
Lake Huron
Collingwood Harbour
(Georgian Bay)
Oliphant Bay (wet)
Baie du Dore (wet)
Lake Erie
West basin
Central basin
East basin
Rondeau Prov. Park (wet)
Long Point Prov. Park (wet)
Fulford et al., 2006;
pers. comm. (zoop,
NR); Qualls et al.,
2007 (Chl a)
Lougheed &
Chow-Fraser, 2002;
pers. Comm.
Lougheed &
Chow-Fraser,2002;
pers. comm.
Williamson & Garvey,
2005 (NR)
A. P. Levchuk unpubl.
K. D. M. Dickerson
unpubl. (zoop);
Bukaveckas pers.
comm. (Chl a)
Open-water habitats near wetlands are indicated after the site name (wet), zooplankton samples excluding rotifers are noted in the
reference column (NR), and negative growth values are highlighted in boldface.
2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
Bioenergetics of invasive Asian carp 2147
Table 4. Maximum distance that can be travelled, based on bioenergetics models, by juvenile (10 cm, 10 g) and adult (60 cm, 2400 g)
bighead carp (BC) and silver carp (SC) over 30 days in different habitats at different times of year (Spr = spring; Sum = summer).
Open-water habitats near wetlands are indicated after the site name (wet)
Location
Lake Michigan
Green Bay
Lake Superior
Chippewa Park (wet)
Pine Bay (wet)
Hurkett Cove (wet)
Lake Huron Collingwood Harbour
Lake Erie
West basin
10 g BC
10 g SC
2400 g BC
2400 g SC
27.0
33.4
29.8
31.4
28.8
35.0
22.8
24.4
5.7
1.6
1.0
0.8
2.1
–
–
–
7.5
2.4
2.9
2.6
–
–
–
–
Spr, 6.1
Sum, 22.0
Spr, 6.1
Spr, 6.1
26.7
13.2
6.5
10.9
33.7
10.6
14.5
18.7
28.5
14.8
8.8
13.0
26.7
3.9
8.0
12.2
Jul 1997
Jul 1997
Jun 1998
26.7
24.9
30.8
25.1
23.1
27.2
28.5
26.4
32.7
18.1
16.3
20.5
Aug, 22.0
Oct, 16.0
Sum, 27.0
Sum, 23.0
12.4
38.1
29.3
14.0
9.3
38.9
22.8
10.1
14.3
39.9
31.1
15.8
2.6
32.1
15.6
3.4
Apr 1999
Jun 1999
Jul
Jul
Jul
Jul
percent growth
Central basin
East basin
Lake Ontario
Sodus Bay embayment
Sandy Pond embayment
Frenchman’s Bay (wet)
Rivers
Middle MS River (Chester)
Middle MS River (Grand Tower)
Upper MS River
Missouri River
Maximum distance of travel over 30 days (km)
Time of year;
water temp. (C)
1998
1998
1998
1998
15
10
5
0
–5
–10
–15
–20
–25
–30
–35
Lake Michigan,
southern basin, Sep.
Lake Huron,
Collingwood
Harbour, Jul.
40
30
20
10
0
–10
0
10
30
20
30
Lake Erie, central
basin, summer
20
10
Fig. 3 Per cent growth of 10 g silver carp
(open triangles), 10 g bighead carp (closed
triangles), 2400 g silver carp (open circles)
and 2400 g bighead carp (closed circles),
modelled over 30 days at a constant temperature. The model was run for multiple
temperatures in each site and
month ⁄ season. The plankton data for
these sites and seasons are in Table 3.
50
0
–10
–20
–30
–40
0
10
2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
20
30
–20
0
10
15
10
5
0
–5
–10
–15
–20
–25
–30
–35
20
30
Lake Ontario,
nearshore Sandy
Pond, Jul.
0
Temperature (oC)
10
20
30
2148
S. L. Cooke and W. R. Hill
native fishes may be similar to that of zebra mussels,
whose invasion in Lake Michigan altered the foraging
patterns of alewives and other species despite having
only partial spatial and diet overlap (Pothoven &
Madenjian, 2008).
Bighead and silver carp mostly inhabit warm,
shallow waterbodies such as rivers and backwater
lakes; and to our knowledge, there is little research
indicating at what depth in a thermally stratified
pelagic zone Asian carp would prefer to feed. They
are not visual feeders, and so temperature and
plankton availability, rather than light, are likely to
determine depth preference. The temperatures of
maximum consumption for bighead and silver carp
are 26 and 29 C, respectively, but at low rations
maximum growth occurs at lower temperatures,
according to the bioenergetic models. This is consistent with bioenergetic simulations by Kitchell et al.
(1977), in which the maximum growth rate of 10 g
perch occurs around 4 C when only feeding at 3% of
their body weight per day, but the CTO is 23 C.
Although carp growth was predicted to be negative in
the four sites shown in Fig. 3, when modelled at
surface water temperatures (20–22.5 C), growth
could be positive if the carp were to feed in deeper
and cooler water where zooplankton tend to reside
during the day.
It should be noted that plankton densities and other
ecological conditions in the Great Lakes can change
because of climate, land use, additional invasive
species and other factors. Habitats invaded by filterfeeding zebra mussels might be less conducive to an
Asian carp invasion, but it is unknown if the veliger
larvae could serve as a substantial food source for
carp. Also, selective herbivory by zebra mussels
promotes cyanobacteria blooms in some habitats
(e.g. Pillsbury et al., 2002), which could benefit carp.
Changing temperature and increased nutrient inputs
could increase plankton biomass or alter zooplankton
and phytoplankton community structure, which
could in turn increase the potential for carp growth
in the Great Lakes. Our analysis provides some
insight into the range of feeding conditions and
temperatures that could facilitate Asian carp invasion
should conditions change.
We emphasise that this study is only a first attempt
at a model for these ecologically important invasive
species. The model’s conclusions are only as robust as
the assumptions and parameters that are part of it. For
this exercise, we were forced to borrow some of the
bioenergetics parameters from studies on other species. While such sharing of parameters is widespread
in the fish bioenergetics literature (e.g. Chipps &
Wahl, 2004; Peterson & Paukert, 2005), we acknowledge that further laboratory evaluations of the parameters could improve the performance of the model
and the accuracy of its predictions. For example, we
assumed that carp had a constant energy density
across body sizes, when in reality larger fish would
have higher energy densities than smaller fish. Thus,
the 5442 J g)1 wet mass value we used from adult
tilapia may be too low for large, 2400 g adult Asian
carp, and may be too high for sub-adults and
juveniles. If this is the case, then adult carp energetic
requirements would be even higher than we predicted, and juvenile carp requirements would be
lower. Additionally, although we used experimentally
derived consumption rates from a study of silver carp
(Smith, 1989), we assumed that all particle sizes
(phytoplankton and zooplankton) could be filtered
at the same maximum rate, despite evidence that carp
filter smaller particles less efficiently (Smith, 1989),
and we assumed bighead and silver carp have similar
consumption rates. The apparent absence of allometry
for the energetic requirements of bighead carp
(Fig. 2b) may indicate that the filtration rates taken
from Smith (1989) were overestimates for sub-adult
and adult bighead carp. Caged bigheads ranging in
weight from 52 g to 139 g had a mean filtration rate of
4.44 L h)1 g)1 when feeding on rotifers (Opuszynski,
Shireman & Cichra, 1991), which is equal to a filtration
rate of 311 L d)1 for a 70 g fish. But we assumed a
70 g carp could filter 764 L d)1. Chipps & Wahl (2008)
have observed that model-predicted consumption
rates are often higher than those observed in the field.
The consequence of making such assumptions and
overestimating filtration rates is that our conclusions
with respect to carp growth are conservative and
more likely to predict higher growth rates than might
actually occur.
A strength of our modelling effort was that we used
allometric- and temperature-dependent respiration
parameters for both bighead and silver carp that were
determined in a coordinated study (Hogue & Pegg,
2009). Although the juvenile and adult life stages of
some fish have different allometric curves for metabolism (Post, 1990), we combined the adult and
juvenile data into one model because Hogue & Pegg
2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
Bioenergetics of invasive Asian carp 2149
(2009) found that life stage did not affect massindependent oxygen consumption rates. The sensitivities of the respiration parameters were higher than
those of most other parameters, but they were
comparable to other published sensitivity values for
metabolism (Stewart et al., 1983). However, the confidence intervals for the respiration parameters were
large because of the low sample size. Many more
respiration trials were conducted, but we only used
those values for which we were confident that the
carp were swimming normally (or exhibiting minimal
swimming in the resting trials).
In modelling the expected growth of Asian carp in
different habitats, we assumed these fishes were
feeding on zooplankton and phytoplankton only, as
most of the published literature on Asian carp feeding
has focussed on these two primary food sources
(reviewed by Kolar et al., 2007). In some cases where
plankton availability is low, both carp species have
been reported to consume large quantities of detritus
(Opuszynski, 1981). It is not uncommon for particulate organic carbon (POC), rather than algae, to
comprise the majority of seston carbon in rivers
(Acharya et al., 2006). Thus, it is likely that Asian
carp in rivers with low plankton availability, such as
portions of the Missouri River, may depend more on
POC than in other habitats. The nutritional quality of
this food source is often low for zooplankton such as
Bosmina (Acharya et al., 2006), so we suspect that POC
is likely to be a poor food for Asian carp as well. Also,
it is unknown if Asian carp would feed in lake benthic
zones where most POC and detritus are found or
consume benthic macroinvertebrates. Bighead carp
may be able to consume these larger organisms, but it
is suggested that a small foregut prevents silver carp
from consuming large food items (Kolar et al., 2007).
Other potential food sources not considered in these
models are protozoans and other microplankton.
Carrick (2005) observed that heterotrophic protozoan
biomass is equivalent to at least 70% of crustacean
biomass in Lake Michigan, and Munawar & Lynn
(2002) observed that mean ciliate biomass ranges from
<1 to >680 mg m)3 in Lakes Superior, Huron, Erie and
Ontario. While even the higher end of this range may
be insignificant compared to the biomass requirements of Asian carp, a refined bioenergetic analysis
that includes these prey sources may be warranted in
certain ecosystems. Another important point is that
the plankton densities in Table 3 are regional whole
2010 Blackwell Publishing Ltd, Freshwater Biology, 55, 2138–2152
water column averages that do not take into account
possible zooplankton swarms and patchiness. In the
Great Lakes, extreme wind, gyres and other physical
phenomena may create patches of zooplankton sufficiently dense to support Asian carp, although such
patches are probably temporary and may not be able
to sustain lasting populations.
Rotifer data were not available for all plankton
datasets with which we applied the models (Table 3).
A recent study in the Mississippi and Illinois rivers
found that the diets of bighead and silver carp were
dominated by rotifers rather than crustaceans (Sampson, Chick & Pegg, 2009). This is at least partially
because of the fact that rotifers were more abundant
than crustacean zooplankton in these habitats, suggesting that the carp modified their diet based on
prey availability, as other studies have shown (Kolar
et al., 2007). Rotifers generally make up a small
percentage (c. 5–20%) of zooplankton biomass in
the Great Lakes (Barbiero & Tuchman, 2002), especially compared to some rivers (Sampson et al., 2009),
but the absence of rotifer data may slightly underestimate potential growth of carp in some Great Lakes
habitats. Potential growth may also be underestimated in the Middle Mississippi River where rotifer
data were unavailable, although modelled growth
was positive in all riverine habitats that we examined
– habitats where Asian carp currently thrive
(Table 3).
Despite the preceding caveats, some important
implications emerge from the bioenergetics modelling. Recent spatially comprehensive studies show
that low plankton biomass is prevalent in both
nearshore and offshore regions of Lake Michigan
(Vanderploeg et al., 2007). If Asian carp were to enter
the ‘plankton desert’ of Lake Michigan via the CSSC,
it seems unlikely (but not impossible) that they would
be able to derive enough energy from the plankton to
support the energetic costs of travelling to Green Bay
or another ‘plankton oasis’. Our analysis suggests that
a greater Asian carp invasion risk may be posed by
the inadvertent use of Asian carp as bait or by
Canadian live fish markets in close proximity to
productive harbours and embayments of Lakes
Ontario and Erie (Herborg et al., 2007; Keller & Lodge,
2007). However, we do not advocate removal of the
existing electric fish barrier in the CSSC to prevent
migration to and from Lake Michigan, as the modelling results suggest that positive growth is indeed
2150
S. L. Cooke and W. R. Hill
possible in this region at cooler temperatures despite
the low plankton rations (Fig. 3a).
Bioenergetics models are only one component of
what should be a more extensive approach to assessing the invasion risk of Asian carp. We advocate
testing model predictions empirically, under as realistic conditions as possible. A recent laboratory
experiment showed negative growth of bighead carp
feeding at mesotrophic plankton densities and positive growth at eutrophic values (Cooke, Hill & Meyer,
2009); however, the plankton composition in this
experiment (primarily Daphnia magna Straus and
Microcystis spp.) did not resemble that of most Great
Lakes habitats. Lakeside growth studies, in which
Lake Michigan water is fed to Asian carp enclosed in
mesocosms, would be preferable in testing our
hypotheses that plankton resources in the Great Lakes
are too sparse to support the growth of filter-feeding
carp. Hitherto, government agencies have been reluctant to approve lakeside studies because of concern
over the potential escape of Asian carp from the
mesocosms. Appropriate design features could be
implemented to eliminate the potential for escape,
however, and given the current public concern about
the invasion threat posed by the fish, additional
information gained through empirical testing should
be welcomed by both environmental managers and
politicians.
Further, while bioenergetic predictions may provide some information on the potential for Asian carp
to grow and reproduce in new habitats, recent
research highlights the importance of river discharge
and temperature in influencing the spawning success
and larval recruitment of bighead and silver carp
(DeGrandchamp, Garvey & Csoboth, 2007; Lohmeyer
& Garvey, 2009). Data from the Upper Mississippi
River System suggest that the reproductive potential
of both species is reduced in slow-flowing water
(DeGrandchamp et al., 2007; Lohmeyer & Garvey,
2009). However, spawning in low-flow conditions has
been observed in isolated cases (Kolar et al., 2007), and
more research is needed on Asian carp spawning and
recruitment.
In conclusion, our results suggest that silver and
bighead carp will be unable to colonise many openwater regions because of limited plankton availability.
However, our results also suggest that in some
habitats plankton resources are sufficient to support
positive growth of bighead and silver carp, even when
taking into account high swimming costs. Furthermore, carp metabolism in cool water is low enough to
support positive growth at very low rations in some
habitats. Because the probability of a successful
invasion increases as more Asian carp individuals
are introduced into the Great Lakes, current efforts to
prevent introductions should at least be maintained if
not expanded. More broadly, we recommend that
aquatic resource managers in other locations threatened by bighead and silver carp incorporate a
bioenergetics approach into more holistic invasion
risk assessments.
Acknowledgments
We thank the following people who provided unpublished data or further information on their published
datasets: Paul Bukaveckas; Carla Cáceres; John Chick
and Alexander Levchuk; Kelli Dickerson and John
Havel; Richard Fulford; Spencer Hall; and Vanessa
Lougheed and Patricia Chow-Fraser. We thank Jennifer Hogue for providing respiration data, Greg Sass
and the staff at the Illinois River Biological Station for
providing facilities, Kevin Meyer for assistance with
respiration experiments, and James Garvey and two
anonymous reviewers for feedback that improved this
paper. This work was supported by an Aquatic
Invasive Species grant from the National Sea Grant
Office of the National Atmospheric and Oceanic
Administration.
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