Download Interactions of multiple predators with different foraging modes in an

Oecologia (2010) 162:443–452
DOI 10.1007/s00442-009-1461-3
COMMUNITY ECOLOGY - ORIGINAL PAPER
Interactions of multiple predators with different foraging modes
in an aquatic food web
Michael P. Carey Æ David H. Wahl
Received: 18 December 2008 / Accepted: 1 September 2009 / Published online: 24 September 2009
Ó Springer-Verlag 2009
Abstract Top predators can have different foraging
modes that may alter their interactions and effects on food
webs. Interactions between predators may be non-additive
resulting from facilitation or interference, whereas their
combined effects on a shared prey may result in emergent
effects that are risk enhanced or risk reduced. To test the
importance of multiple predators with different foraging
modes, we examined the interaction between a cruising
predator (largemouth bass, Micropterus salmoides) and an
ambush predator (muskellunge, Esox masquinongy) foraging on a shared prey (bluegill sunfish, Lepomis macrochirus) with strong anti-predator defense behaviors.
Additive and substitution designs were used to compare
individual to combined predator treatments in experimental
ponds. The multiple predator interaction facilitated growth
of the cruising predator in the combined predator treatments, whereas predator species had substitutable effects
on the growth of the ambush predator. The combined
predator treatments created an emergent effect on the prey;
however, the direction was dependent on the experimental
Communicated by Steven Kohler.
M. P. Carey D. H. Wahl
Sam Parr Biological Station, Illinois Natural History Survey,
6401 Meacham Road, Kinmundy, IL 62854, USA
M. P. Carey D. H. Wahl
Program in Ecology, Evolution, and Conservation Biology,
University of Illinois at Urbana-Champaign,
Urbana, IL 61801, USA
Present Address:
M. P. Carey (&)
NOAA Fisheries, Northwest Fisheries Science Center,
2725 Montlake Boulevard East, Seattle, WA 98112, USA
e-mail: [email protected]
design. The additive design found a risk-reducing effect,
whereas the substitution design found a risk-enhancing
effect for prey fish. Indirect effects from the predators
weakly extended to lower trophic levels (i.e., zooplankton
community). Our results highlight the need to consider
differences in foraging mode of top predators, interactions
between predators, and emergent effects on prey to
understand food webs.
Keywords Multiple predators Risk-enhanced effect Additive design Substitution design
Introduction
Predation is a key factor structuring communities and
drives food web dynamics. Ecological theory often
assumes predator species have similar effects; however,
this assumption potentially obscures important differences
and interactions (Luttbeg et al. 2003; Sokol-Hessner
and Schmitz 2002; Eklov and VanKooten 2001; VanceChalcraft et al. 2004). Natural communities often have
multiple predators and the critical question becomes: do
multiple predator interactions and effects have an influence
on food web dynamics (Sih et al. 1998; Siddon and Witman
2004)? Predators with different foraging modes are likely
to have the largest differential impact on food webs
determining the nature of predator combinations, the success of anti-predator behavior, and the indirect effects on
other components of the food web (Schmitz and Suttle
2001; Schmitz 2007).
Interactions between multiple predators can result in
facilitation, interference, or neutral relationships and the
nature of predator combinations is determined by how
foraging modes interact (Crowder et al. 1997; Siddon and
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Witman 2004; Schmitz 2007). Predators that have complementary foraging activities facilitate capture success
and increase predator growth rates (Soluk 1993; Soluk
and Richardson 1997; Losey and Denno 1998; Eklov
and VanKooten 2001). Conflicting foraging activities and
intraguild predation create interference between predators
reducing capture success (Sih et al. 1998; Siddon and
Witman 2004; Griswold and Lounibos 2006; Schmitz
2007). Neutral interactions between predators can occur
if predator species are substitutable in that interspecific interactions are similar to intraspecific interactions
(Schmitz 2007). The outcome for a shared prey to multiple
predators is also influenced by the foraging mode of the
predators and habitat use of both predators and prey (Schmitz 2007). When a prey species is able to compensate for
different predator species a neutral interaction will result
(Schmitz and Sokol-Hessner 2002). Prey species experience
a risk reduction if predator species interfere with each other
or if a prey response to one predator reduces the risk to
another predator species (Griswold and Lounibos 2006;
Crowder et al. 1997; Vance-Chalcraft and Soluk 2005).
Multiple predators that impose conflicting demands on the
anti-predator defenses of their shared prey create an effect
that is risk enhanced (Soluk and Richardson 1997). Antipredator behaviors of the prey, such as habitat shifts or
maneuvering defenses, are traits that can have a large effect
on the outcome of multiple predators (Matsuda et al. 1993;
Crowder et al. 1997; Siddon and Witman 2004; VanceChalcraft et al. 2004; Preisser et al. 2007).
Most studies have not examined the effects of multiple
predators on their prey to lower trophic levels and those
that have show different influences on food web structure.
Studies have shown strong cascading effects from predators by density effects or due to behavior changes of
intermediate consumers in aquatic food webs (Werner et al.
1983; Turner and Mittelbach 1990; Peacor and Werner
1997; Eklov and VanKooten 2001). In contrast, the
strength of trophic cascades is weakened by intraguild
predation of multiple predators in a terrestrial food web
(Finke and Denno 2004). Thus, direct and indirect behavioral interactions can overwhelm trophic effects generating
dynamics different from what is expected by following
energy flow (Soluk and Richardson 1997; Luttbeg et al.
2003; Vance-Chalcraft and Soluk 2005).
Additive and substitution designs are the most common
approaches used to explore multiple predator interactions
and effects (Sih et al. 1998; Griffen 2006; Schmitz 2007).
In an additive design, a set quantity is established for
individual predators and maintained in both single-species
and multiple-species treatments to keep levels of intraspecifc interactions constant (Goldberg and Scheiner 1993)
and determine if predator effects are independent (Sih et al.
1998; Vance-Chalcraft et al. 2004; Griffen 2006). Additive
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designs are limited in that changes in predator species are
confounded with changes in predator amounts and therefore cannot resolve if predator species are functionally
substitutable (Sih et al. 1998; Griffen 2006). A substitution
design holds predators constant across multiple predator
treatments to determine if predators are functionally substitutable by comparing mean per capita effects of individual predators to mean per capita effects of multiple
predators (Siddon and Witman 2004; Griffen 2006). Substitution designs are limited in that variation in intra- and
interspecific interactions are confounded with predator
treatments (Inouye 2001; Griffen 2006). Few studies have
simultaneously used both additive and substitution designs
in multiple predator studies (e.g., Vance-Chalcraft et al.
2004; Vance-Chalcraft and Soluk 2005); however, both
experimental designs in combination are necessary to
determine the influence of multiple predators on food webs
(Relyea 2003; Griffen 2006; Schmitz 2007).
Within aquatic food webs, foraging mode differences
amongst top predators may be particularly important due to
the frequently strong effect of trophic cascades (Hairston
and Hairston 1993; Elser et al. 2000). Cruising, e.g.,
largemouth bass (Micropterus salmoides; Savino and Stein
1989), versus ambush tactics, e.g., muskellunge (Esox
masquinongy; New et al. 2001), may alter food web
dynamics. Bluegill sunfish (Lepomis macrochirus) are
commonly found in the diets of predators in freshwater
lakes. Bluegills utilize habitat shifts to avoid predation, a
common response for fish (Crowder et al. 1997), but also
have strong maneuvering defenses (Wahl and Stein 1988;
Einfalt and Wahl 1997). Combining the characteristics of
these predator and prey species will determine how foraging mode influences the nature of predator combinations
and the ability of anti-predator behavior to compensate for
conflicting demands from different predator species.
Multiple predator interactions were examined by comparing treatments of cruising predator alone, ambush
predator alone, and combined predators foraging on bluegill prey in both an additive and substitution design. Species of predators may differ in a number of characteristics.
To allow the assessment of different foraging modes of the
predator species we made the foraging abilities similar
between species by matching predators that select similar
prey sizes. We hypothesized that the multiple predator
interaction would result in facilitation between the predator
species, because the foraging modes of these predators are
complementary. Cruising predators force prey towards
the ambush predator increasing encounters, whereas the
ambush predator limits the habitat refuge of prey from the
cruising predator. Similarly, we predicted an emergent
effect that is risk enhanced for the prey, because multiple
predator species will impose conflicting demands on the
anti-predator defenses of the prey. The predator effects
Oecologia (2010) 162:443–452
were expected to cascade to lower trophic levels (zooplankton) by altering richness and density from prey fish
foraging in different habitats. To explore these predictions,
we asked these specific questions:
1. What effect does the combination of cruising and
ambush predators have on species-specific growth
rates of the predators?
2. What is the effect (risk enhanced, risk reduction, or
substitutable) of multiple predators on prey mortality
and growth?
3. How do the richness, density, and biomass of lower
trophic levels (zooplankton and benthic macroinvertebrates) vary across multiple predators?
Materials and methods
Predator treatments of the cruising predator alone (cruising
only, largemouth bass), the ambush predator alone (ambush
only, muskellunge), and the combination of cruising and
ambush predators (combined predators) were replicated
in experimental ponds (16 9 25 m2) at the Sam Parr Biological Station, Illinois Natural History Survey, Kinmundy,
Illinois. Ponds had vegetation extending out 2–3 m from the
edges creating a structured and open-water (10 9 20 m2)
habitat. Muskellunge were obtained from the Jake Wolfe
Memorial Fish Hatchery, Illinois Department of Natural
Resources, Manito, Illinois. Largemouth bass, and the
shared prey species, bluegill sunfish were collected from
local lake populations. To focus on comparing different
foraging modes of predator species and avoid confounding
morphological constraints (e.g., gape size, body form), we
selected the body size of the two predators such that each
species preferred prey of the same size (Hoyle and Keast
1987; Hambright 1991; Gillen et al. 1981; Wahl and Stein
1988). Predators preferred a similar prey size when largemouth bass total length (TL) was 50% of muskellunge TL.
The ratio of predator sizes to their preferred prey sizes has
been found to be constant across the sizes used in this
experiment for both muskellunge [86–310 mm TL (Gillen
et al. 1981); 150–225 mm TL (Wahl and Stein 1988, 1993)]
and largemouth bass [70–285 mm TL (Hoyle and Keast
1987)]. Ratios of predator to prey body sizes used ensured
that prey were vulnerable to both predators.
Experimental designs
Multiple predator interactions and the response of the
shared prey were examined with both an additive and
substitution design (Goldberg and Scheiner 1993; Griffen
2006). Predator density, biomass, and sizes could not all be
held constant within each design. Predator density is most
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often manipulated in additive designs (e.g., Eklov and
VanKooten 2001); we used biomass to standardize predator
treatments to be consistent with previous food web studies
(e.g., Carpenter et al. 1985). In the additive design, multiple predator treatments of largemouth alone (mean ± SD;
total predator biomass = 809 ± 49.9 g), muskellunge
alone (total predator biomass = 823.7 ± 10.7 g), and
combined predators (total predator biomass = 1,540.3 ±
96.1 g) foraging on bluegill were tested in experimental
ponds (n = 3 for each treatment) from mid May to July
2004 (6 weeks). The ratio of largemouth bass TL (mean
TL ± SD; 199 ± 14 mm) to muskellunge TL (441 ±
26 mm) was constant within ponds across treatments. To
create uniform initial conditions, ponds were left dry for
2 weeks and then filled with filtered lake water from a
common source 2 weeks prior to the start of the experiment. Predators were individually marked with passive
integrated transponder tags (12 mm 9 2.1 mm; TX1400
ISO 134.2 kHz; Biomark, Boise, Id.). Bluegill (36 ±
5 mm) were measured and added to each pond in mid May
at a constant density (n = 150/pond).
Two trials were conducted with a substitution design in
the same experimental ponds. Similar biomass (245 ± 77
g/pond) of predators was maintained between trials by using
different densities, because two sizes of fish were available
at different times of year. Within each trial, predator density
was kept constant across treatments to eliminate the confounding effect of density-dependent predation. The first
trial was run from early May to late June 2003 (7 weeks)
with age-1 predator treatments of largemouth bass
alone (n = 2/pond), muskellunge alone (n = 2/pond),
and combined predators (n = 1 largemouth bass ? 1
muskellunge = 2/pond) foraging on bluegill (39 ± 5 mm;
n = 105/pond). The ratio of largemouth bass TL
(185 ± 10 mm) to muskellunge TL (354 ± 16 mm) was
constant within ponds across treatments. The second trial
was conducted from early August to mid September
(6 weeks) with smaller young-of-year largemouth bass
alone (n = 20/pond), muskellunge alone (n = 20/pond),
and combined predators (n = 10 largemouth bass ? 10
muskellunge = 20/pond). Bluegills (29 ± 3 mm) were
added to the ponds at similar densities as the first trial. In
addition, fathead minnows (Pimephales promelas) were
added to all of the ponds as alternative prey (42 ± 5 mm;
n = 105/pond) to ensure predator survival. All fathead
minnows were consumed during the trial. Largemouth bass
TL (89 ± 6 mm) relative to muskellunge TL (163 ±
10 mm) was also constant within ponds for the second trial.
For both trials, treatments were replicated 3 times for
largemouth bass alone, muskellunge alone, and combined
predators; however, a combined predator pond was dropped
from each trial for the analysis because of predator
mortality.
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Data collection
At the end of the experiment, ponds were drained and TL
and mass were recorded for all fish. Instantaneous growth
[ln(final biomass/initial biomass)/elapsed time] was
determined by averaging across ponds for both predators
and prey. Change in biomass was calculated for individually marked predators in the additive design and averaged across ponds. For the additive and second
substitution trial, zooplankton were sampled at the
beginning, middle, and end with a 70-mm-diameter 9
0.5-m-long vertical tube sampler (DeVries and Stein
1992). Four samples of the water column (7.6 l) were
taken per sample date, combined, and then preserved with
Lugols solution (Wallace 2001). Simultaneously, benthic
invertebrates were sampled with a stovepipe sampler
(0.017 m2; Merritt et al. 1996) in the littoral/vegetated
zone (one sample per pond; 0.3–0.5 m depth) and preserved with a solution of 0.1% rose Bengal stain and 90%
ethanol.
In the laboratory, zooplankton were identified under a
dissecting scope into taxonomic groups of Daphnia, other
cladocerans, calanoids, cyclopoids, and nauplii (Welker
et al. 1994). All benthic macroinvertebrates were identified to family and enumerated. For both the zooplankton
and benthic macroinvertebrates, taxa-specific body
dimensions were measured from each sample and used as
input in length–weight regression equations to estimate
individual mass (Dumont et al. 1975; Smock 1980;
Culver et al. 1985; Sample et al. 1993; Benke et al.
1999). Mean individual mass was then extrapolated by
volume (zooplankton) and area (benthic macroinvertebrates) to obtain estimates for each pond and sampling
date combination.
Analysis
In the additive design, growth rates were compared with
an ANOVA between the individual treatment of a predator species and the growth rates of that species in the
combined-predator treatment. To test for an emergent
effect from multiple predators on prey and the direction
of the effect (risk enhanced or risk reduction), an
ANOVA compared the predicted values of the combinedpredator treatment to observed values for prey mortality.
A multiplicative risk model was used to predict the
combined-predator effect from the individual predators.
The multiplicative risk model predicts the expected proportion of prey consumed (PC?A) based on the observed
prey mortality in the individual predator treatments as
PC?A = PC?PA - PCPA (Sih et al. 1998; Eklov and
VanKooten 2001; Vance-Chalcraft et al. 2004). PC is the
observed proportion of prey consumed in the cruising-
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only treatment and PA is the observed proportion of prey
consumed in the ambush-only treatment. PCPA accounts
for prey that are removed by one predator and are no
longer available to the other predator (Vance-Chalcraft
et al. 2004; Vance-Chalcraft and Soluk 2005). For additive designs, the advantage of this approach is that the
number of predicted prey consumed by the predator
cannot exceed the total number of prey available (Sih
et al. 1998). Prey responses were further explored by
testing growth across multiple predator treatments
(cruising only, ambush only, and combined predators)
with an ANOVA.
For the substitution design, ratios of TL between
predator species were maintained between trials, thus
trials were simultaneously analyzed to increase the number of replicates. Growth rates were compared with an
analysis of covariance (ANCOVA) between the individual
treatment of a predator species and the growth rates of
that species in the combined-predator treatment. Initial TL
of the predators was used as the covariate to account for
differences in predator sizes within and between trials.
Prey responses were analyzed with an ANOVA comparing predicted against observed combined-predator effects
for prey mortality (n) and growth to determine if predators are functionally substitutable and the nature (neutral,
risk reducing, or risk enhancing) of the multiple predator
effects. A block was used to simultaneously analyze both
trials. Mortality was arcsine square root transformed to
satisfy the homogeneity of variance assumption for normality. For the substitution design, the predicted multiple
predator effects (P) were calculated as P = (OA 9 OC)0.5,
where OA is the observed prey response in the presence of
the ambush predator and OC is in the presence of the
cruising predator (Griffen 2006). If predator species have
identical effects on prey then the combined predator
effects will be equivalent to the individual effects suggesting species are functionally substitutable (SokolHessner and Schmitz 2002). In addition, for both the
additive and substitution design, intraspecific interactions
within the prey were examined by correlation analysis
between prey growth and biomass.
A repeated measures ANOVA tested the effects of the
multiple-predator treatments on richness, density, and
biomass of the zooplankton and benthic invertebrate
communities in both experiments. Initial samples were
homogenized by standardizing the pond set up and
were not included in the analysis. All response variables
were log transformed to satisfy the homogeneity of variance assumption for normality. When a significant time
interaction was detected, we used the SLICE option in SAS
to partition the effect of time and tested for treatment
effects (Littell et al. 2002). All statistical analyses were
conducted in SAS 8.2 (SAS, Cary, N.C.).
Oecologia (2010) 162:443–452
Results
Predator growth
The cruising predators had higher growth rates than ambush
predators in both experiments. In the additive design,
growth of the cruising predator was not different between
the cruising-only treatment and combined-predator treatment (ANOVA multiple predator treatment F1,4 = 2.11,
P = 0.22; Fig. 1a). In the substitution design, no interaction
was found between the covariate of initial TL and the
predator treatment for the cruising predator (P = 0.55).
Across all predator lengths, growth of the cruising predator
was higher in the combined-predator treatment than the
cruising-only treatment (ANCOVA multiple predator
treatment F1,7 = 5.03, P = 0.059; Fig. 1b). Smaller cruising predators benefitted more from the combined-predator
(a)
447
treatment than larger predators (predator TL F1,7 = 54.20,
P = 0.0002). Growth of the ambush predator was not different between the ambush-only treatment and combinedpredator treatment in either the additive design (ANOVA
multiple predator treatment F1,4 = 3.37, P = 0.14; Fig. 1a)
or in the substitution design (ANCOVA multiple predator
treatment F1,7 = 0.64, P = 0.45; predator TL F1,7 = 2.25,
P = 0.18; Fig. 1b). No interaction was found between initial TL and the predator treatment for the ambush predator
(P = 0.69).
Prey mortality and growth
Prey mortality was lower in the combined-predator treatments than predicted by the individual treatments in the
additive design (ANOVA F1,4 = 8.47, P = 0.04; Fig. 2a).
The significant difference between observed and predicted
effects of multiple predators suggests that predators are not
independent and create an effect that is risk reducing for
prey mortality. In contrast, prey mortality was higher in
the combined-predator treatments than predicted by the
(a)
(b)
(b)
Fig. 1 Instantaneous growth rate [ln(final biomass/initial biomass)/
elapsed time)] for cruising (CP; Micropterus salmoides, open bars)
and ambush (AP; Esox masquinongy, black bars) predators in the
pond experiment using a additive and b substitution designs.
Experiments were conducted at the Sam Parr Biological Station,
Illinois Natural History Survey, Kinmundy, Illinois in the summer of
2003 and 2004. Predator growth is compared between single species
treatments (CP or AP) and combined predator treatments (CP ? AP
or AP ? CP) foraging on bluegill sunfish (Lepomis macrochirus).
Different letters indicate significant treatment effects within each
design compared with ANOVA at a 0.05 level. d-1 Day-1
Fig. 2 Prey mortality (%) in individual (CP, white bars; AP, black
bars) and combined predator (grey bars) treatments for the a additive
and b substitution designs. Prey mortality in predicted (Predicted
CP ? AP) and observed (CP ? AP) combined predator treatments
are compared in both designs. Mortality was arcsine square root
transformed to satisfy the homogeneity of variance assumption for
normality. Different letters indicate significant treatment effects
within each design at a 0.05 level. For abbreviations, see Fig. 1
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Oecologia (2010) 162:443–452
individual treatments in the substitution design (ANOVA
predators F1,7 = 9.52, P = 0.02; Fig. 2b). Higher mortality of prey in the combined treatment indicates predators
are not functionally substitutable and create an effect that is
risk enhanced for the prey. No differences were detected
across predator treatments for prey growth in either the
additive or substitution design (P [ 0.12). Furthermore, no
evidence was found for density-dependent growth in either
experimental design and a positive relationship was found
between prey growth and total biomass at the end of the
experiment for both the additive (R2 = 0.74, P = 0.02)
and substitution (R2 = 0.91, P = 0.002) design.
Zooplankton and benthic invertebrates
Multiple predator treatments did not have a strong affect
on the invertebrate community. In both experiments, zooplankton were dominated by calanoid copepods with
large numbers of Ceriodaphnia. In the additive design, a
marginally significant interaction was found between the
multiple predator treatments and time for zooplankton
richness (multiple predator treatment F2,6 = 0.40, P =
0.69; time F1,6 = 10.31, P = 0.02; interaction F2,6 = 4.70,
P = 0.06); however, the least squares multiple comparison
test (SLICE option) did not find a significant treatment
effect in either time period (P [ 0.10). The ambush predator treatment had the lowest zooplankton richness, but no
effect was found on zooplankton density or biomass
(P [ 0.20). In the substitution design, zooplankton richness
changed through time (time F1,5 = 16.99, P = 0.01), but
no differences were found between the predator treatments
Fig. 3 a Zooplankton richness,
b benthic richness c
zooplankton density, and d
benthic density (mean ? SE)
across predator treatments in the
substitution design at both the
mid-point (Middle) and end of
the experiment. Treatments are
CP only, AP only, and
combined predators (CP ? AP).
For abbreviations, see Fig. 1
123
(multiple predator treatment F2,5 = 1.18, P = 0.38; interaction F2,5 = 1.99, P = 0.23; Fig. 3a). Zooplankton density was affected by the predator treatments (multiple
predator treatment F2,5 = 6.36, P = 0.04; time F1,4 =
0.91, P = 0.38; interaction F2,4 = 0.46, P = 0.65;
Fig. 3b). Ambush-only predator treatments had significantly lower zooplankton density than the cruising-only and
combined-predator treatments at the middle and end of the
experiment (P \ 0.04). The cruising-only treatment had
large numbers of Daphnia at the end of the experiment,
whereas very few Daphnia were found in the ambush-only
treatments. Similar to density, a significant interaction was
found between predator treatment and time for total zooplankton biomass (multiple predator treatment F2,5 = 5.6,
P = 0.05; time F1,5 = 0.96, P = 0.37; interaction F2,5 =
5.0, P = 0.06) with a significant treatment effect at the
midpoint (least significant multiple comparison test, SLICE
option; P = 0.003).
Benthic macroinvertebrates were dominated by Diptera
in both experimental designs. No effect from the multiple
predator treatment was found in the additive design on
benthic macroinvertebrate richness, density, or biomass
(P [ 0.2). In the substitution design, a significant interaction
between predator treatments and time was found for benthic
macroinvertebrate richness (multiple predator treatment
F2,5 = 2.40, P = 0.19; time F1,4 = 9.14, P = 0.04; interaction F2,4 = 6.22, P = 0.06; Fig. 3c). A significant treatment effect was found at the midpoint (least significant
multiple comparison test, SLICE option; P = 0.01), but not
at the end point of the experiment. Lower benthic macroinvertebrate richness was found in the ambush-only
(a)
(b)
(c)
(d)
Oecologia (2010) 162:443–452
treatment than in the combined-predator treatment. A significant time by treatment interaction was also found for
benthic macroinvertebrate density (multiple predator treatment F2,5 = 4.72, P = 0.07, time F1,4 = 13.22, P = 0.01,
interaction F2,4 = 5.91, P = 0.05; Fig. 3d). Similar to
benthic richness, a significant treatment effect was found for
density at the midpoint (P = 0.003), but not at the end point
of this experiment. The midpoint differences were driven by
lower density in the ambush-only treatment relative to the
combined treatment. Benthic macroinvertebrate biomass
was not affected by the multiple predator treatments
(P [ 0.13).
Discussion
Predator growth in our study was influenced by both
predator treatments and the experimental design. As a
result, both species interactions and density-dependent
effects need to be considered when evaluating the effects of
top predators in food webs. In the additive design, no
differences were found between the combined predators
relative to the individuals for either the cruising or ambush
predator suggesting the effects are independent. However,
the increase in density in the combined-predator treatment
did not reduce growth as would be expected from combining independent species. In the substitution design,
ambush predator growth was also unaffected by predator
species confirming a neutral interaction for the ambush
predator. In contrast, the cruising predator had higher
growth with combined predators in the substitution design
suggesting a benefit of interspecific interactions over
intraspecific interactions. The benefit of the combined
predators was greater for smaller individuals and these
relationships were consistent between individual and
combined treatments. A positive effect for the cruising
predator in the combined-predator treatments with the
substitution design and a neutral effect in the additive
design despite higher predator density support our
hypothesis of predator facilitation. Facilitation has now
been found to lead to more captures, increased individual
and population growth rates, and higher survival for a
number of predator species in both terrestrial and aquatic
systems and with both vertebrates and invertebrates (Soluk
1993; Soluk and Richardson 1997; Losey and Denno 1998;
Eklov and VanKooten 2001; this study). To further
understand the interaction of multiple predators, experimental designs are needed that also directly test the
strength of intra- and interspecific interference for both
predators (Griffen 2006).
Determining when facilitation occurs between predators
is necessary to advance our understanding of food web
dynamics (Swisher et al. 1998). Our study found a positive
449
effect for the cruising predator and neutral effect for the
ambush predator. In another study examining fishes a
positive effect was found for an ambush species, while a
cruising species was unaffected by the multiple predator
interaction (Eklov and VanKooten 2001). Key differences
between studies were use of a less evasive prey fish with
different habitat preferences in the earlier study. Prey
without a strong maneuvering defense were forced from
the open water towards the vegetated habitat of the ambush
predator (Eklov and VanKooten 2001). In contrast, bluegill
in addition to habitat shifts are adept at utilizing structured
habitat in avoiding predators with a maneuvering antipredator defense (Wahl and Stein 1988; Einfalt and Wahl
1997). The cruising predator may have benefitted from a
higher encounter frequency in the combined treatment
when prey were forced into the open water habitat. In
contrast, the ambush predator was not more successful in
the structured habitat as the maneuvering anti-predator
defenses of the bluegill were equally effective between the
combined and individual treatments. Understanding how
combinations of foraging modes of predators and antipredator defenses of prey interact along with habitat use of
both predators and prey is necessary to predict facilitation
between predators.
Interactions between predators can affect the distribution, population size, and growth rate of prey species and
ultimately influence the stability of predator–prey interactions (Soluk and Richardson 1997; Losey and Denno
1998). We found predator effects on prey cannot be predicted by individual species and the combination of
cruising and ambush predators had an emergent effect;
however, the additive and substitution designs did not
agree on the nature of the combined predator effect.
Mortality was lower in the combined-predator treatment
than was predicted by the individual predator effects in
the additive design. In contrast, mortality was higher
in the combined-predator treatment than was predicted by
the individual predator effects in the substitution design.
Finding different conclusions between the additive and
substitution design is not uncommon, because they ask
complimentary, but different questions (Griffen 2006;
Schmitz 2007). Additive designs determine if combined
predator effects are independent, whereas a substitution
designs compares the effect of intra- to inter-specific predators. These designs combine predators differently, thus
different outcomes indicate total biomass and density of the
predators alters the emergent effect (Griffen 2006). Additive designs are biased towards finding a risk-reducing
effect (Sih et al. 1998) further justifying the simultaneous
use of designs.
Interference between predators due to the high level of
predator biomass in the combined-predator treatment of the
additive design likely created a risk reduction for bluegill.
123
450
Conflicting demands on the anti-predator defenses of the
prey from predators with different foraging modes (Losey
and Denno 1998; Eklov and VanKooten 2001) likely
resulted in the risk enhancement in the substitution design.
Other studies where designs can be compared have also
detected a risk reduction in the additive design and risk
enhancement in the substitutive design (review in Griffen
2006). However, a limitation to these conclusions is that
these designs do not compare the strength of intra- and
interspecific interference, thus risk enhancement for the
prey may have resulted from weaker interference among
heterospecific predators than between conspecifics (Griffen
2006). Future studies need to test the strength of intraspecific interactions simultaneously while testing the effect of
multiple predators. Furthermore, studies need to examine
how prey may modify their behavior relative to the threat
of predation (Gilliam and Frasier 1987; Griffen 2006).
Prey responses to multiple predators have included
habitat shifts, changed activity levels, or the amount of
aggregation (Crowder et al. 1997; Eklov and VanKooten
2001; Vance-Chalcraft and Soluk 2005). Habitat shifts
would likely be ineffective with a cruising predator in the
open water and an ambush predator waiting in the structured habitat. Aggregation or maneuvering anti-predator
defenses exhibited by the shared prey, bluegill (Wahl and
Stein 1988; Einfalt and Wahl 1997), were evidently not
able to reduce capture efficiency of the predators enough to
overcome multiple predator pressures. Reducing activity
may be effective, but would lower consumption rates and
growth and multiple predators did not affect bluegill
growth. The counteracting effect of combined predators
may have reduced bluegill density and increased individual
growth. Teasing apart the effect of changing intraspecific
interactions from anti-predator behaviors would determine
the specific mechanism involved.
The different foraging strategies of the predators were
expected to cascade to the invertebrate communities. The
expectation that the prey fish would forage more in the
open water habitat with ambush predators and be more
confined to the vegetation with a cruising predator was
supported by the zooplankton responses; however, the
patterns were inconsistent between experimental designs.
The ambush-only treatment had the lowest zooplankton
richness in the additive design and lowest zooplankton
density in the substitution design. The diversity and density
responses of zooplankton likely resulted from indirect
predator effects that alter the foraging of the prey fish.
Zooplankton composition can be as important as density or
biomass changes as different zooplankton species alter the
transfer efficiency between trophic levels in pelagic food
webs (Brooks and Dodson 1965; Elser et al. 2000). Other
studies that have observed stronger effects on invertebrate
communities used higher densities of bluegill in
123
Oecologia (2010) 162:443–452
mesocosms (Knowlin and Drenner 2000; Aday et al. 2005)
and ponds (Hall et al. 1970; Hambright et al. 1986; Turner
and Mittelbach 1990); however, the bluegill density in our
experiments was within the range of natural communities
(Hackney 1979; Johnson et al. 1988). In both the additive
and substitution designs, the multiple predator treatments
had little effect on benthic macroinvertebrate richness,
density, or biomass. Results for macroinvertebrates are
difficult to interpret, because predators may be supplementing their diets with these invertebrates, leading to
direct interactions between the predators and lower trophic
levels (Vander Zanden et al. 2006). Although not primary
prey, diets of both predators have been found to contain
macroinvertebrate prey in other systems [largemouth bass
(Liao et al. 2002); Esocids (Venturelli and Tonn 2006)].
The effects of the multiple predators on the benthic
macroinvertebrate communities were weak and the relative
influence of both direct and indirect effects need to be
further explored. Adding alternative fish prey to ensure
predator survival in later summer trial did not influence the
relationship between individual and combined predator
treatments. The alternative prey was added at constant
density to all ponds with minimal survival (B4 individuals/
pond) suggesting no relative difference between multiple
predator treatments for the bluegill and no influence on
relative differences between treatments for predator
growth.
Our study highlights the need to address multiple
predator interactions and effects along with species traits
of both predators and prey to understand food web interactions. Both additive and substitution designs were
required to tease apart the nature of multiple predator
interactions and their influence on a shared prey. With this
approach, questions regarding the independence of predator effects, importance of predator quantities, and the
relative influence of intra- and inter-specific interactions
can be addressed simultaneously. To further generalize
multiple predator interactions and effects among fishes,
other biotic and abiotic factors that influence predator–
prey interactions need to be considered (Scharf et al.
2006; Schmitz 2007). Prey density (Vance-Chalcraft and
Soluk 2005; Griffen 2006), ontogenetic niche shifts (Frank
and Leggett 1985; Olson 1996; Griswold and Lounibos
2006), and structural complexity (Swisher et al. 1998;
Siddon and Witman 2004; Vance-Chalcraft and Soluk
2005) are potential factors that could modify the influence
of multiple top predators. Furthermore, temperature and
turbidity could be particularly relevant in aquatic food
webs as top predator species have ranges that encompass
large thermal gradients and water clarities, factors that can
have a strong influence on ectotherms that are visual
predators (Garvey et al. 2004; Van de Meutter et al.
2005).
Oecologia (2010) 162:443–452
Acknowledgments We thank the staff at the Kaskaskia and Sam
Parr Biological Stations, Illinois Natural History Survey, especially
K. Schnake, K. Ostrand, M. Diana, C. Wagner, E. Smolik, K. Atkins,
J. Clark, and J. Wisher for help in the field and with sample processing. All procedures conformed to the University of Illinois
Institutional Animal Care and Use Committee and comply with the
current laws of the U.S. Reviews by C. Cáceres, J. Brawn, and K.
Paige substantially improved the manuscript. Support was provided
by the Illinois Natural History Survey.
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