Download DiVerential habitat use and antipredator response of juvenile roach

Oecologia (2010) 162:893–902
DOI 10.1007/s00442-010-1564-x
BEHAVIORAL ECOLOGY - ORIGINAL PAPER
DiVerential habitat use and antipredator response of juvenile
roach (Rutilus rutilus) to olfactory and visual cues from multiple
predators
Charles W. Martin · F. Joel Fodrie ·
Kenneth L. Heck Jr. · Johanna Mattila
Received: 16 June 2009 / Accepted: 6 January 2010 / Published online: 3 February 2010
© Springer-Verlag 2010
Abstract The indirect, behavioral eVects of predation and
predator–predator interactions can signiWcantly alter the
trophic ecology of many communities. In numerous
instances, the strength of these eVects may be determined
by the ability of prey to identify predation risk through
predator-speciWc cues and respond accordingly to avoid
capture. We exposed juvenile roach (Rutilus rutilus), a
common forage Wsh in many brackish and freshwater environments, to vision and/or olfactory cues from two predators with diVerent hunting methods: northern pike (Esox
lucius, an ambush predator) and European perch (Perca
Xuviatilis, a roving predator). Our results demonstrated that
responses of roach to perceived risk (as evidenced by their
selection of structured or open-water habitats) were highly
dependent on cue type and predator identity. For instance,
roach responded to olfactory cues of pike by entering
Communicated by Anssi Laurila.
C. W. Martin (&) · K. L. Heck Jr.
Dauphin Island Sea Lab, 101 Bienville Boulevard,
Dauphin Island, AL 36528-0369, USA
e-mail: [email protected]
C. W. Martin · K. L. Heck Jr.
University of South Alabama,
307 University Boulevard N, Mobile,
AL 36688-0002, USA
F. J. Fodrie
Department of Marine Sciences,
Institute of Marine Sciences,
University of North Carolina at Chapel Hill,
3431 Arendell Street, Morehead City, NC 28557, USA
J. Mattila
Husö Biological Station, Åbo Akademi University,
Tykistökatu 6, 20520 Turku, Finland
open-water habitat, but entered structured habitat when
presented with a vision cue of this predator. Opposite
responses were elicited from roach for both olfactory and
visual cues of perch. Interestingly, roach defaulted to selection
of structured habitat when presented with vision + olfaction
cues of either predator. Moreover, when presented individual cues of both predators together, roach responded by
choosing open-water habitat. Upon being presented with
vision + olfaction cues of both predators, however, roach
strongly favored structured habitat. DiVerences in habitat
selection of roach were likely in response to the alternative
foraging strategies of the two predators, and suggest that
prey species may not always use structured habitats as protection. This appears particularly true when a threat is perceived, but cannot immediately be located. These results
provide insight to the complex and variable nature by
which prey respond to various cues and predators, and oVer
a mechanistic guide for how behaviorally mediated and
predator–predator interactions act as structuring processes
in aquatic systems.
Keywords Antipredator behavior · Predator–prey
interactions · Olfaction · Vision · Multiple predator eVects ·
Non-consumptive eVects
Introduction
The non-consumptive eVects of predation (also referred to
as trait or behaviorally mediated indirect interactions) are
increasingly recognized to be an important, yet understudied, component of predator–prey interactions and food-web
dynamics (Dill et al. 2003; Grabowski 2004). Recent metaanalyses have indicated that the mere threat of predation
can have impacts that are as strong, if not stronger, than
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direct consumption (Dill et al. 2003; Werner and Peacor
2003; Pressier et al. 2005). For instance, indirect interactions that alter the foraging behavior of mid-trophic-level
species can initiate trophic cascades (Trussell et al. 2002;
Schmitz et al. 2004). A key element of these non-lethal
predator–prey exchanges is the ability of prey to recognize
and evade risk once a threat is perceived through visual,
olfactory, mechanoreception, electroreception, or social
cues. Thus, separating the behavioral responses of prey to
various cue types should lead to a better understanding of
the circumstances in which trait-mediated interactions will
dominate trophic exchanges and regulate energy Xow
through food webs.
Although the roles of all antipredator sensory cues have
been evaluated in aquatic systems [e.g., mechanoreception
via lateral line sensitivity (Montgomery and MacDonald
1987) and social cues via schooling (Hager and Helfman
1991; Brown et al. 2009)], many experiments have focused
on the role of vision (Mathis et al. 1993; Heithaus et al.
2002, 2006; Wirsing et al. 2007) and olfactory cues in
mediating predator–prey exchanges (Smith 1992; Kats and
Dill 1998; Chivers and Smith 1998; Brown 2003; Amo
et al. 2004; Kusch et al. 2004; Ylönen et al. 2007). Within
aquatic environments, we still know little about the relative
roles of each in governing predator–prey interactions
(Wahle 1992; Mathis and Vincent 2000; Hickman et al.
2004; Kim et al. 2009), even though it could be expected
that prey rely heavily on olfaction within relatively turbid
environments. In the future, eutrophication (Utne-Palm
2002; Engström-Öst and Mattila 2008) and the loss of sediment-stabilizing foundation species such as submerged
aquatic vegetation (Waycott et al. 2009) should lead to
increasingly turbid conditions. This may force prey to rely
even more heavily on olfaction for guiding defensive
responses to predator detection (Lehtiniemi et al. 2005).
Therefore, data are needed to evaluate the relative eVects of
vision and olfaction, which are recognized as the most
important sensory cues used by prey within shallow-water
environments (Mikheev et al. 2006), on the predator-avoidance responses of prey. Moreover, quantifying the magnitude and direction of prey responses elicited by these cues,
both individually and in combination, has the potential to
reveal new insights for predicting how food webs will
respond to anthropogenic stressors aVecting water quality
(sensu Lindquist and Bachmann 1982; Shivik 1998).
Since omnivory is common in natural systems (Pimm
and Lawton 1978), most species at lower and intermediate
positions in food webs (i.e., forage Wsh in estuarine environments) not only receive multiple cues from single predators, but also simultaneous threat stimuli from multiple
predator species. Therefore, prey must respond to an amalgam of risk cues. Where predator species diVer in foraging
behaviors, there is growing interest in quantifying multiple
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Oecologia (2010) 162:893–902
predator eVects on shared prey, especially relative to the
impacts of predator species operating alone (Sih et al.
1998). In some cases, multiple predators can operate synergistically, resulting in enhanced risk for their shared prey
(Fodrie et al. 2008). Nearly all reports of predator facilitation that result in enhanced risk for a shared prey are based
on two elements: one predator alters the habitat selection of
prey, and this makes prey highly vulnerable to attacks from
another predator (Sih et al. 1998). In other scenarios, predators interfere with one another resulting in reduced risk for
prey (Crowder et al. 1997). Often, this occurs if prey are
capable of rapidly switching between predator-speciWc
defense behaviors/mechanisms (Sih et al. 1998). Regardless of the outcome, the ability of prey to receive, process,
and act upon multiple cues is put to a stern test in instances
when there is more that one threatening predator species.
Although tests of multiple predator eVects have thus far
focused on prey mortality as the response variable, multiple
predator eVects should be equally important determinants
of non-consumptive eVects. To our knowledge, the speciWc
cues used by prey in multiple predator scenarios and
subsequent eVects on habitat selection have not been
evaluated.
To investigate cue-mediated predator–prey interactions,
we designed an experiment to address the following questions: (1) what are the relative roles of olfactory and visual
cues from two common predators on the habitat selection of
a widespread prey species, and (2) do interspeciWc combinations of predator cues induce responses in prey habitat
selection that could be predicted by averaging the responses
of prey to each predator individually?
Materials and methods
Study organisms
We explored cue-driven predator–prey interactions using
commonly encountered species in brackish and freshwater
habitats throughout Europe. Juvenile roach (Rutilus rutilus), a numerically dominant forage Wsh that inhabits both
open-water and structured habitats [e.g., emergent reeds
(Phragmites australis) as well as numerous species of submerged aquatic vegetation], were used as prey. While roach
are known to school, especially under threat of predation
(Christensen and Persson 1993; Eklöv and Persson 1995),
we used individual roach in this experiment to tease apart
their responses to various cue inputs as a starting point to
understanding their behavior. We selected northern pike
(Esox lucius) and European perch (Perca Xuviatilis), two of
the most commonly encountered piscivores in this region
(BonsdorV and Blomqvist 1993; Ådjers et al. 2006) as predators. These two species have diVerent foraging strategies:
Oecologia (2010) 162:893–902
northern pike hide in vegetation and ambush prey (Savino
and Stein 1989), while perch forage by continually roving
among habitats (Eklöv and Persson 1995). Despite these
divergent foraging strategies, pike and perch are both capable predators of roach and could be deWned by qualitatively
similar interaction coeYcients. Furthermore, these predators are known to elicit strong antipredator responses in
other species of prey (Christensen and Persson 1993;
Mathis and Smith 1993; Mathis et al. 1993).
Experimental design and procedures
Our experiment was conducted during 14 August–7 September 2008 at Husö Biological Station in the Åland archipelago. We collected roach, pike, and perch by seining or
dip netting in Husö Bay adjacent to Husö Biological Station, in the Åland archipelago (60°04’N, 20°48’E). Following collection, Wshes were held in 75-l holding tanks
(654 cm long £ 29 cm wide £ 9.5 cm tall) until their use in
experimental trials (each species in separate tanks). Holding tanks were devoid of structure and completely surrounded with plastic dividers to minimize Wsh stress. We
exchanged water daily in holding tanks and provided aeration with a single airstone in each tank. Predators (pike and
perch) were fed two roach (31.6 § 5 mm) each day until
needed for experiments. Roach were always collected the
day before their use in experimental trials and therefore not
fed while in the holding tank. Individual prey were used
once and then released in Husö Bay.
Experimental trials were conducted within six 17-l
experimental aquaria (33 cm long £ 24.5 cm wide £ 21 cm
tall). In each aquarium, we placed artiWcial seagrass units
(ASUs) over half of the bottom (16.5 cm long £ 24.5 cm
wide £ 21 cm tall) to provide structured habitat. The other
half of the aquarium remained unstructured, open-water
habitat. ASUs were assembled by tying green ribbon to
Vexar mesh to mimic the morphology of many common
aquatic plants [e.g., eelgrass (Zostera marina)] at a density
of approximately 1,000 shoots m¡2, a value within the
range of typical eelgrass beds in the Baltic Sea (Baden and
Boström 2001). During each experimental run, Wltered
water (180 m) from Husö Bay was used to Wll each aquarium. Although predator olfactory cues could be present in
the incoming water, we assumed these to be at trace levels
and equally introduced among all experimental aquaria and
holding tanks. Since chemical cues were involved in these
experiments, we did not circulate water in aquaria during
these trials, but did use an airstone to ensure the aquaria
were well aerated. The airstone was placed in the ASU section of each aquarium to prevent the introduction of structure to the open half of the aquaria. A pilot study veriWed
that prey were neither attracted nor deterred by the presence
of the airstone. Between trials, experimental aquaria were
895
drained, rinsed thoroughly, and reWlled with Wltered water
to eliminate any lingering olfactory cues from previous
trials. Salinity and temperature were checked periodically
throughout the experiment and found to range between
4.7–5.0 and 15.5–18.5°C. Fluorescent lighting, placed
approximately 20 cm above each aquarium, was used for
illumination.
The behavioral responses of roach [95% conWdence
interval (CI): 31.6 § 5 mm; n = 162] to pike (95% CI:
157.8 § 13 mm; n = 10) and/or perch (95% CI:
144.2 § 14 mm; n = 6) cues were investigated by examining habitat selection (open water vs. structured) in a twoway experimental manipulation within experimental
aquaria. First, we allowed individual roach to select
between habitats during exposure to three diVerent cue
types: olfaction, vision, and vision + olfaction. Second, we
manipulated the predator Weld that generated each of our
three cue types: no predator (control), one pike, one perch,
one pike + one perch, two pike, two perch. This resulted in
a 6 £ 3 orthogonal design with 16 unique treatments (we
were unable to include the one-pike and one-perch treatments during trials made with just olfactory cues because of
predator availability). We conducted six replicates of each
unique treatment combination, resulting in 96 trials in
which we observed the behavioral response of roach. Runs
of cue type were blocked by time for logistic reasons (number of available pike and perch to generate olfactory or
visual cues), while the six predator Welds were completely
randomized among aquaria and experimental cycles.
Including six levels of predator Weld allowed us to evaluate
if multiple predator eVects (i.e., do pike and perch foraging
together aVect the behavior of prey diVerently than the
additive eVects of single predators?) inXuenced the habitat
selection of roach using both substitutive (comparing
results from the one pike + one perch treatment with results
of the two-pike and two-perch treatments) and additive
(comparing results from the one-pike and one-perch treatments against the one pike + one perch treatment) designs
(GriVen 2006). Both methods have advantages. The substitution design allows for the teasing apart of total density
and species richness eVects (e.g., Schmitz and Sokol-Hessner 2002; Vance-Chalcraft et al. 2004). The additive design
acknowledges the reality that species richness and overall
density usually scale together, and does not alter the
strength of intraspeciWc interactions among treatments
(e.g., Finke and Denno 2002; Lang 2003; Warfe and
Barmuta 2004).
We designated six additional holding tanks (also without
structure and with opaque partitions) for generating and
recovering olfaction cues from each level of predator Weld.
Water from nearby Husö Bay was Wltered through a 180m sieve and used to Wll tanks (24.5 cm long £ 16.5 cm
wide £ 21 cm tall; Wlled to »3–1), and then we added one
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of the six combinations of predators to each tank. To
recover predator-derived olfactory cues, we kept predators
inside these tanks for 24 h to standardize scent accumulation. Between trials, we rinsed tanks thoroughly. This
procedure was completed each time an experimental cycle
was run.
We also placed six additional aquaria immediately
behind our six experimental aquaria (devoid of any structure, and with an airstone). In treatments requiring vision or
vision + olfaction cues from predators, we randomly placed
one of the six combinations of predators in these aquaria
(moving pike and perch out of the holding tanks as needed).
Thus, roach were able to see these predators but not receive
olfactory cues (unless separately added, see below).
For each trial, we Wrst allowed a single roach to acclimate to the experimental aquarium for 1 h. In treatments
that included olfactory cues, we sampled a 100-ml aliquot
from each of the six tanks in which predators had been
soaking for 24 h. These aliquots were immediately poured
into the center of the appropriate experimental aquaria. In
trials that employed visual cues, we placed predators in the
tanks adjacent to the experimental aquaria at the same time
roach were added. To allow acclimation for both predator
and prey, we placed an opaque divider between the two
aquaria and then removed it after 1 h. In vision + olfaction
cue trials, we combined the steps from the olfaction and
vision treatments.
To observe the behavioral response of roach to cues and
minimize handling artifacts, we recorded Wsh movements in
the aquaria using a Sony digital video camera (model DCRH36). Video recordings were initiated following the acclimation period (immediately after the addition of predator
cues) and the experiment then ran for 1 h. Pairs of roach/
predator aquaria were placed immediately beside each
other so we could capture all six in the video recording, and
therefore opaque dividers were placed between the six pairs
to avoid transmission of visual cues among aquaria and
achieve independent replicates. Using a white background
behind the aquaria pairs, the silhouettes of roach were
highly visible in all videos, making it easy to determine if
each individual was in the structured or open-water half of
each of the six aquaria. After the experiment, all aquaria
and holding tanks were reset as described above. During
the Wrst six trials, roach occupancy was recorded every
minute and compared at intervals of 1, 2, or 3 min. No statistical diVerence was detected among sampling regimes
(two-way ANOVA with trial number and time interval as
factors; F1,16 = 39.350, P = 0.125; Tukey’s post hoc: 1 versus 2 min, P = 0.985; 1 versus 3 min, P = 0.932; 2 versus
3 min, P = 0.979), thus 3-min intervals were used to quantify roach occupancy. The frequency of ASU selection by
roach was used as the response variable in all subsequent
analyses.
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Statistical analyses
We used a series of one-way ANOVAs to determine if
diVerent cue types and predator treatments aVected the
roach’s selection of ASU habitat (not having olfactory
treatments from the one-pike or one-perch treatments precluded the use of a two-way analysis). First, three separate
ANOVAs were conducted to determine if predator Weld
generated diVerences in roach habitat selection. For these
analyses, we considered the data from each cue treatment
(i.e., olfaction, vision, or vision + olfaction) individually.
Similarly, we conducted six additional ANOVAs to assess
how cue type aVected roach habitat selection. This required
parsing the data among the individual predator treatments
[i.e., no predator (control), one pike, one perch, one
pike + one perch, two pike, two perch]. In cases with signiWcant ANOVA results ( = 0.05), Tukey’s post hoc tests
were performed to make pairwise comparisons between
treatments.
The presence of multiple predator eVects on the habitat
selection of roach for both the additive and substitutive
designs was evaluated by comparing “expected” habitat
selection of roach (based on single-predator species
treatments) to observed habitat selection of roach in the
mixed-predator treatment. If predator cues aVected roach
independently in the one pike + one perch treatment,
expected habitat selection of prey in the mixed-predator
aquaria for the additive experimental design can be predicted by averaging ASU selection (%) by roach in the
separate one-pike and one-perch treatments. A similar
approach was true for the substitution design: expected
habitat selection of roach in the 1 pike + 1 perch treatment
was calculated by averaging results from the individual
two-pike and two-perch treatments. We averaged the
results of separate predator treatments to calculate expected
habitat selection, rather than using the additive or multiplicative models suggested in Sih et al. (1998) or GriVen
(2006), because we measured a non-consumptive variable
and our measured response could be bi-directional. For
example, roach could shift away from one habitat for one
predator, and toward that habitat for the other, relative to
our controls, with the expectation that in combined predator
treatments these two eVects should cancel one another.
Thus, the methods proscribed in consumptive multiple
predator eVect experiments were not logically or quantitatively appropriate and had to be amended. For both the
additive and substitution designs, we used two-sample
unpaired t-tests to compare observed outcomes in multiple
predator treatments (one pike + one perch) to calculated,
expected outcomes as prescribed above. Using this statistical approach, a signiWcant diVerence ( · 0.05) between
observed and expected values would indicate that the combined eVects of pike and perch on the habitat selection
Oecologia (2010) 162:893–902
897
Parametric assumptions were satisWed in all instances
and therefore data transformations were not required.
Because each statistical test applied to separate and easily
distinguishable hypotheses, we also made no corrections to
experiment-wise during this study (Moran 2003).
Table 1 Results of one-way ANOVAs testing for the eVects of either
cue type or predator Weld on selection of structured habitat by roach
Source
df
Predator Weld (olfaction
only treatments)
3
Error
Predator Weld (vision
only treatments)
Error
Predator Weld (vision +
olfaction treatments)
Error
Cue type (control)
18,404.2
2,939.2
35
27,448.6
5
10,007.1
36
11,107.1
1
Error
Cue type (one perch)
Error
Error
Cue type (two perch)
Error
Cue type (one pike +
one perch)
Error
21.3
P
4.10
0.020
7.50
<0.001
6.49
<0.001
0.01
0.989
0.03
0.872
12.92
<0.001
13.95
<0.001
12.76
<0.001
8.49
0.003
Results
Juvenile roach responded strongly to the cues of pike and
perch, but the speciWc responses (i.e., habitat selection) of
roach varied based on the predator Weld and cue type.
Within all levels of predator Weld except the control and
one-pike treatment, the eVect of cue type on roach habitat
selection was highly signiWcant (Table 1). Likewise, predator Weld had a signiWcant eVect on the response of roach
during trials run with the three cue combinations (Table 1).
For instance, roach were observed in structured habitat only
»30% of the time when provided olfactory cues from two
pike (we did not have a one-pike treatment with olfactory
cues). In contrast, in both the one-pike and two-pike treatments, vision and vision + olfaction cues drove roach into
the structured habitat more than 80% of the time (Fig. 1).
For the treatments that included only perch as predators,
olfaction (two perch) and vision + olfaction (one and two
perch) cues resulted in roach selecting structured habitat
nearly 80% of the time. However, roach only utilized structured habitat 25–30% of the time when presented with just
a visual cue of one or two perch (Fig. 1). If roach were presented with only olfactory or visual cues from one
pike + one perch together, the prey selected structured habitat 20–25% of the time. Conversely, when roach were
introduced to the vision + olfaction cues of one pike + one
15,970.8
7
12
3,186
1
10,314
12
Cue type (two pike)
11,319.8
5
16
Cue type (one pike)
F
20
2
Error
SS
9,579
2
12,686.1
17
7,732.5
2
13,570.9
17
9,042.9
2
11,430.6
17
11,449.4
SigniWcant values (P · 0.05) are shown in bold
(behavioral response) of roach were not independent. For
the additive design, separate analyses were conducted
for the trials run with vision and vision + olfaction cues. For
the substitution design, separate analyses were run for all
three cue types.
2 p ik e
1 p ik e
2 perch
1 perch
Time in structured habitat (%)
100
A,2
B,1
1 pi ke +1 p e r ch
contr ol
A,1
A ,2
A,1
80
AB
A, 2
AB
60
40
A,2
A, 1
B
B ,1
A ,1
A,1
B,2
B,1
20
0
No
Data
No
Data
Olfaction
Vision
Vision + olfaction
Cue type
Fig. 1 Frequency of roach (Rutilus rutilus) selection of artiWcial seagrass habitat (ASU; mean + 1 SE) when exposed to diVerent cue types
(olfaction, vision, and vision + olfaction) and predator Welds (no predator, one pike, one perch, one pike + one perch, two pike, two perch).
DiVerent letters indicate diVerences at P · 0.05 among predator treatments within each cue treatment and numbers indicate diVerences at
P · 0.05 among each cue treatment within each predator Weld (ANOVA results provided in Table 1)
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Oecologia (2010) 162:893–902
100
Expected (additive)
Expected (substitutive)
Observed
Time in structured habitat (%)
perch they selected the ASU half of the aquaria 70% of the
time (Fig. 1). Notably, no diVerences in prey response were
found between single predator species treatments regardless if cues from one or two individuals were used (i.e.,
vision or vision + olfaction cues from either one pike and
two pike or one perch and two perch), suggesting that cue
saturation was achieved with the addition of a single predatory Wsh (Fig. 1).
Statistical support for the occurrence of multiple predator eVects was highly dependent on the cue type presented
to roach (Table 2). For olfactory cues, only the substitutive
design was used to evaluate if pike and perch together generated non-linear behavioral responses from the roach.
Based on the separate two-pike and two-perch treatments,
we estimated that roach should select structured habitat
»55% of the time in the one pike + one perch treatment.
Interestingly, observed roach selection of ASU habitat
was signiWcantly less than what we expected (»25%;
P = 0.036; Fig. 2).
When roach were presented with visual cues of one
pike + one perch, both the additive and substitutive designs
demonstrated that the roach again used structured habitat
less than would be predicted based on the separate pikeprey and perch-prey interactions. We expected roach to
select structured habitat »60% and »55% of the time in the
one pike + one perch treatment based on the additive and
substitutive designs, respectively. However, we observed
that roach selected structured habitat in the mixed-predator
treatment only »25% of the time, which was unambiguously diVerent from our expectations (additive, P = 0.017;
substitutive, P = 0.024).
When roach were presented with vision + olfaction cues,
both the additive and substitutive experimental approaches
revealed that the behavioral response of roach to multiple
predators could be predicted by averaging individual predator–prey interactions. Using the additive and substitutive
80
60
40
20
0
Olfaction
Vision
Vision +
olfaction
Cue Type
Fig. 2 “Expected” and observed results for roach habitat selection in
one pike + one perch treatments. Both additive (black bars) and substitutive (gray bars) approaches were employed to calculate expected and
assess multiple predator eVects on the frequency of ASU habitat selection by roach (mean + 1 SE)
designs, we expected that roach would select structured
habitat »90% and »85% of the time in the mixed-predator
treatment, respectively. Ultimately, we observed that roach
selected ASU habitat »75% of the time, which was not a
signiWcantly diVerent result (additive, P = 0.118; substitutive, P = 0.362). We did note that in all Wve analyses,
observed selection of structured habitat in mixed-predator
treatments was less than expected by averaging the separate
pike-roach and perch-roach results.
Discussion
Table 2 Results of t-tests for the diVerences in “expected” and observed habitat selection of roach using both the additive and substitutive designs
Source
df
t
P
Vision
12
2.77
0.017
Vision + olfaction
12
1.68
0.118
Olfaction
10
2.43
0.036
Vision
12
2.57
0.024
Vision + olfaction
12
0.95
0.362
Additive
Substitutive
SigniWcant values (P · 0.05) are shown in bold and are indicative of
non-linear multiple predator eVects
123
Juvenile roach responded strongly to the cues of the pike
and perch predators, but the speciWc responses (habitat
selection) of roach were varied and partially counter-intuitive (Fig. 3). While fear is known to inXuence the behavior
of prey (Brown 2003; Wirsing et al. 2007), our pike-perchroach data indicate that fear-driven responses are contextspeciWc. SpeciWcally, our results suggest that roach are not
only able to distinguish between species-speciWc predator
cues, but also demonstrate unique responses based on the
type of cue that is detected. For instance, roach responded
to the olfactory cues of pike by entering open-water habitat,
but entered structured habitat when presented with a visual
cue of this predator. When presented with visual or olfactory cues of perch, the opposite responses were elicited
from roach. Interestingly, roach defaulted to selection of
Oecologia (2010) 162:893–902
Fig. 3 Conceptual diagram illustrating the strength of habitat preference for open or structured habitat by roach with olfactory and/or visual cues from pike and/or perch. The length of the arrow scales with
the magnitude of observed preference for either habitat type during trials with each combination of cue type and predator Weld (calculated in
comparison to the average of all control treatments in which no predator cues were included)
structured habitat when presented with vision + olfaction
cues of either predator. Moreover, when roach were presented with olfactory cues of both predators, the roach
behaved as though they were ignoring the perch, and
responded just as they did during the pike-only treatments
(choosing open-water habitat). When visual cues of both
predators were presented to the prey, roach responded as
they did in the perch-only treatments (again selecting
open-water habitat). Upon being presented with
vision + olfaction cues of both predators, however, roach
strongly favored structured habitat; consistent with their
responses to detecting pike visually or perch through olfaction. Our results indicating increased use of structured habitat by roach when presented with vision + olfaction cues
agree with previous studies that have examined the foraging eYciency of roach predators (i.e., both visual and olfactory stimuli are available to roach; Nelson and BonsdorV
1990; Mattila 1992), but also highlight the more detailed,
cue- and predator-speciWc responses of this common forage
Wsh.
The speciWc antipredator responses of roach likely reXect two interacting factors: the foraging strategies of predatory pike and perch and the diVerence between only
perceiving a predation threat versus perceiving and locating
that threat. Northern pike forage primarily by occupying
structured habitats and ambushing prey (Savino and Stein
1989). We hypothesize that roach may escape structured
habitat when a pike is detected through only olfactory cues,
because, although roach are aware of threat, they may not
899
be able to determine the direction from which a camouXaged, stationary pike will attack. As a result, they seek
open habitat to increase their opportunity to locate pike
visually (sensu Horinouchi et al. 2009; Schultz et al. 2009).
Conversely, once a stationary pike is located visually (alone
or in combination with olfaction), roach can use structured
habitat for the mechanical defense it provides against
directed pike attacks (Fig. 3). Alternatively, perch move
continuously while foraging in structured and unstructured
habitats (Eklöv and Persson 1995). As a result, olfactory
cues may be received by roach as an unambiguous signal
that perch have entered the immediate vicinity, and therefore present a pressing, short-term threat. In this circumstance, our data suggest that roach prefer structured habitat
as refuge. Within structured habitats, visual encounters
with perch are informative but potentially less reliable than
with ambush predators since roving predators will likely
move in and out of the visual Weld routinely. Therefore,
once a perch has been visually detected, roach may be conditioned to seek open habitats in an attempt to maintain
more constant visual contact with this roving predator
(unless the immediate threat associated with perch scent
cues is also perceived). In fact, we frequently encountered
roach in open habitats adjacent to structured habitats while
capturing organisms for our trials. The emergent theme of
our results is that structured habitat serves as optimal refuge
habitat only if roach are able to detect the speciWc location
(direction) from which a predation threat will come from
(Horinouchi et al. 2009; Schultz et al. 2009).
Although aquatic vegetated habitats can decrease the
foraging eYciency of predators (Nelson and BonsdorV
1990; Mattila 1992), our results suggest that prey may not
always perceive structure as optimal refuge space: a pattern
previously documented in terrestrial studies. For example,
Valeix et al. (2009) found that lions utilized tall grass as
cover during the day while stalking/ambushing prey. In
instances that prey (multiple ungulate species) became
aware of threatening lions, they spent more time during the
day in open habitat away from grasslands. In this case, tall
grass did serve as the preferred refuge for these prey species at night, when lions were able to stalk/ambush prey
equally well in open habitat (FischhoV et al. 2007).
Recently, several marine studies have identiWed speciWc
predator–prey scenarios that can result in prey beneWting
from less-structured habitats. Notably, these studies and our
own experiment all suggest that if structure increases
uncertainty for prey in locating predation threats, prey species do not necessarily associate complex habitats with suitable refuge. Studies on gobies under pressure from cryptic
ambush predators (sculpin) have shown that prey can experience elevated mortality while occupying dense seagrass
patches (Horinouchi et al. 2009). Similarly, James and
Heck (1994) showed that increasing density of artiWcial
123
900
vegetation had no impact on the foraging eYciency of
another well-camouXaged ambush predator, the seahorse.
In tropical environments, the Weld of vision for damselWsh
can be limited by complex coral reefs. Subsequently, the
behavior of damselWsh is altered such that mating and feeding opportunities are lost, negatively aVecting individual
Wtness (Rilov et al. 2007).
While behaviors can be observed, determining the decision rules that produce those behaviors is extremely diYcult. With this in mind, we are left to speculate on the role
of uncertainty in mitigating the defensive responses of
roach to evaluate behavior-related multiple predator eVects.
In both olfaction- and vision-only treatments, we observed
a non-linear response by roach to the simultaneous detection of one pike + one perch. In each instance, we suspect
this occurred because roach eVectively ignored the predator
for which the introduced cue should reveal the predator’s
position (perch in olfaction trials, pike in vision trials).
Rather, the roach behaved as if only the predator that could
be detected but not consistently located determined the
response that should minimize overall risk (Table 2;
Fig. 3). Conversely, when vision + olfaction cue combinations of both predators were presented to roach, thereby
providing the prey with information to detect and locate
both species, roach responded as expected by balancing its
response to account for two equally capable predators
(Table 2; Fig. 3). Thus, it is not only the fear of predators
that aVects the behavior of prey (Pressier et al. 2005), but
also the fear of ambiguity in knowing where attacks will
come from.
More broadly, our data contribute to a growing literature
that indicates community dynamics cannot be predicted by
simply summing or averaging all pairwise predator–prey
interactions. Although previous studies have mostly
focused on changes in prey abundance (e.g., Fodrie et al.
2008), quantifying non-consumptive eVects in scenarios
with multiple predators should also elucidate important trophic dynamics. First, several studies have demonstrated
distinct and complex behavioral responses to visual and
olfactory cues that are known to aid prey in escaping single
predators (e.g., Brown and Cowan 2000; Vincent et al.
2005; Brown et al. 2006). Second, emergent multiple predator eVects typically follow from the behavioral response(s)
of a shared prey after detecting one or more predators (Sih
et al. 1998). Ultimately, quantifying these non-consumptive
eVects are valuable because: (1) a shift in prey activity can
have impacts that propagate through the food web
(Grabowski 2004), and (2) understanding the defensive
responses (habitat selection) of prey against predators
provides a framework for predicting whether multiple
predators should have independent, risk-reducing, or riskenhancing eVects. For instance, our results strongly suggest
that, for all of the sensory cues we investigated, roach
123
Oecologia (2010) 162:893–902
responded to multiple predators by shifting toward open
water. However, we also noted anecdotally that individual
roach switched between unstructured and structured habitats more often when simultaneously presented with cues
from both pike and perch. Such behavior has been previously documented with roach under predation threat (Christensen and Persson 1993). We propose that this increase in
emergence rates would increase their risk of being captured
(Sih 1997). As a result, we predict that multiple predator
scenarios will result in enhanced mortality for roach despite
its Wne-tuned defensive behaviors.
While GriVen (2006) has demonstrated that additive and
substitutive experimental approaches can lead to quantitatively and qualitatively diVerent results, we found that these
approaches supported one another in investigating the antipredator responses of roach (Table 2). Although these
approaches diVer in the way predator density and identity
are manipulated, roach responded similarly whether we
included one or two pike, or one or two perch in singlepredator treatments (Fig. 1). Essentially, the presence of a
single individual pike or perch was suYcient to induce
roach to demonstrate their full antipredator response. This
is not surprising given the relative size of our experimental
mesocosms and that of predators/prey in these systems, but
it may also suggest that roach do not respond as though
there is intraspeciWc facilitation or interference among pike
or perch. As a result, there was little diVerence in expected
habitat use for the one pike + one perch treatment regardless of whether we employed the additive or substitutive
design.
Ultimately, this study should be a gateway to further
experiments of roach-pike-perch interactions. We conducted our experiments on single roach, ignoring the social
cues that might be relied on by this schooling species to
avoid predators (Magurran and Seghers 1994). Schooling,
for example, should increase the awareness of each individual roach to the presence and location of predators by the
increased probability of detecting predator olfactory and/or
visual cues when multiple prey species are present. While
collecting roach for our experiments, we routinely observed
individuals swimming together in open water near emergent or submerged vegetation. Thus, additional tests are
needed to determine whether schooling and solitary roach
respond diVerently to threats perceived though olfactory
and visual cues. Also, a future experiment should examine
if multiple predators (pike and perch) interact to generate
enhanced or reduced mortality risk for juvenile roach in
landscape mosaics of open and structured habitats.
Lastly, we recognize that the habitat selection of roach
may be the result of instinctual responses or learned antipredator behaviors (Ferrari et al. 2005; Brown and Chivers
2006; Leduc et al. 2007) prompted by earlier attacks. Thus,
conditioning experiments could investigate if the responses
Oecologia (2010) 162:893–902
we observed are plastic, and therefore capable of evolving
to meet the demands of temporally and spatially varying
predator Welds and changing environmental conditions
(e.g., increasing turbidity or loss of vegetated habitats). For
instance, as turbidity increases, roach are likely to demonstrate a bias for olfactory cues to sense predators. In
instances with nearby multiple predators, this bias should
lead to greater pike-avoidance behaviors by roach
(Table 2), regardless of the distribution of perch. As a
result, roach-perch encounters may increase (ultimately,
predation rates will also be aVected by other co-occurring
changes in submerged aquatic vegetation cover and capture
eYciency in turbid water). Clearly, there is considerable
opportunity to further explore the complexity of predator–
prey interactions and the non-intuitive outcomes that can
result from defensive behaviors of prey beyond simple habitat preference (although this likely represents one of the
foremost antipredator defenses). Although applied to a
freshwater and estuarine ecosystem here, our results may be
broadly applicable to many other environments.
Acknowledgments Support for this project was provided through
general funds from the University of South Alabama’s Department of
Marine Science, as well as Husö Biological Station, Åbo Akademi
University. We thank S. Scyphers, M. Scheinin, M. Ajemian, and M.
Kenworthy for assistance in collecting Wsh and running trials, as well
as the staV and students at Husö Biological Station for their logistical
support throughout our visit. We also thank J. Valentine, M. Ajemian,
B. Toscano, and two anonymous reviewers for their constructive criticism and improvements to this manuscript. All experiments were in
compliance with the laws of Finland.
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