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Behavioral Types of Predator and Prey Jointly Determine Prey Survival: Potential
Implications for the Maintenance of Within-Species Behavioral Variation.
Author(s): Jonathan N. Pruitt, John J. Stachowicz, Andrew Sih
Reviewed work(s):
Source: The American Naturalist, Vol. 179, No. 2 (February 2012), pp. 217-227
Published by: The University of Chicago Press for The American Society of Naturalists
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vol. 179, no. 2
the american naturalist
february 2012
Behavioral Types of Predator and Prey Jointly Determine Prey
Survival: Potential Implications for the Maintenance of
Within-Species Behavioral Variation
Jonathan N. Pruitt,1,2,* John J. Stachowicz,1,3 and Andrew Sih1,4
1. Center for Population Biology, University of California, Davis, California 95616; 2. Department of Biological Sciences, University of
Pittsburgh, Pittsburgh, Pennsylvania 15260; 3. Department of Evolution and Ecology, University of California, Davis, California 95616;
4. Department of Environmental Science and Policy, University of California, Davis, California 95616
Submitted May 20, 2011; Accepted September 29, 2011; Electronically published December 21, 2011
Dryad data: http://dx.doi.org/10.5061/dryad.190pk253.
abstract: Recent studies in animal behavior have emphasized the
ecological importance of individual variation in behavioral types (e.g.,
boldness, activity). Such studies have emphasized how variation in
one species affects its interaction with other species. But few (if any)
studies simultaneously examine variation in multiple interacting species, despite the potential for coevolutionary responses to work to
either maintain or eliminate variation in interacting populations.
Here, we investigate how individual differences in behavioral types
of both predators (ocher sea stars, Pisaster ochraceus) and prey (black
turban snails, Chlorostoma funebralis) interact to mediate predation
rates. We assessed activity level, degree of predator avoidance behavior, and maximum shell diameter of individual C. funebralis and
activity levels of individual P. ochraceus. We then placed 46 individually marked C. funebralis into outdoor mesocosms with a single P.
ochraceus and allowed them to interact for 14 days. Overall, predator
avoidance behavior and maximum shell diameter were positively
associated with survival for C. funebralis. However, the effects of
these traits depended on the predator’s behavioral type: greater predator avoidance behavior was favored with active P. ochraceus, and
low predator avoidance behavior was favored with inactive P. ochraceus. We argue that, even in two-species interactions, trait variation
in heterospecifics could be an important factor maintaining trait
variation within populations.
Keywords: behavioral type, behavioral syndrome, frequencydependent selection, personality, predator-prey interactions.
Introduction
Identifying the mechanisms maintaining trait diversity
within populations is a perennial goal in ecology and evolutionary biology. Within behavioral ecology, a surge of
recent literature has focused on consistent individual differences in behavior (e.g., in boldness or aggressiveness),
* Corresponding author; e-mail: [email protected].
Am. Nat. 2012. Vol. 179, pp. 217–227. 䉷 2011 by The University of Chicago.
0003-0147/2012/17902-53048$15.00. All rights reserved.
DOI: 10.1086/663680
over time or across contexts, that are commonly referred
to as behavioral syndromes, temperament, and/or personality (see reviews in Dall et al. 2004; Sih et al. 2004; Bell
2007; Sih and Bell 2008). Here we refer to consistent behavioral variants as behavioral types (BTs) and correlations
in behavior across trait types (e.g., activity, aggression) as
behavioral syndromes. Although a large number of recent
studies have quantified BTs and examined their proximate
correlates (e.g., neuroendocrine correlates) or effects on
components of fitness (e.g., effects of boldness on survival), to date, few studies have demonstrated how individual variation in BTs of multiple species influences interspecific interactions (but see Webster et al. 2009).
Instead, evolutionary ecology studies typically consider intraspecific variation in only a single focal species and regard individuals of the other species as functionally identical to one another (e.g., Yoshida et al. 2003; Hairston et
al. 2005; Meyer et al. 2006; Bell and Sih 2007; but see
Smith and Blumstein 2010). However, we argue that
within-species variation in two or more interacting species
could be a general mechanism maintaining trait diversity
within populations because variation in one interactor
could maintain variation in another and vice versa via
frequency-dependent selection (Roughgarden 1976; Tellier
and Brown 2009).
In particular, we focus on predator-prey interactions. A
large number of studies test how BTs influence predatorprey interactions (Sih et al. 2003; Biro et al. 2004, 2006;
Bell and Sih 2007; Dingemanse et al. 2007; Carter et al.
2010; Smith and Blumstein 2010). For instance, in some
prey species, bold BTs commonly enjoy higher growth rates
but suffer greater susceptibility to predation (Biro et al.
2004; Pruitt and Krauel 2010; but see Réale and FestaBianchet 2003; Smith and Blumstein 2010). This trend
stems from bold individuals’ tendency to exploit high-risk
foraging opportunities, whereas other individuals forgo
218 The American Naturalist
these opportunities in favor of safety. In predators, variation in aggressiveness is known to influence the kinds of
prey attacked (Riechert 1991; Maupin and Riechert 2001;
Costantini et al. 2005), the tactics used to detect and subdue prey (Coleman and Wilson 1998; Wilson 1998; Pruitt
et al. 2008), and the amount of food consumed during
foraging bouts (Pruitt 2010; Pruitt and Krauel 2010; Smith
and Blumstein 2010). However, to date, no study has simultaneously evaluated the effects of BTs in both predators
and prey to test their overall impacts on the outcome of
the interaction. Interestingly, this deficit persists despite
recent data indicating that the performance effects of BTs
likely depend on the individual traits of heterospecific interactants (Smith and Blumstein 2010).
We propose that BT by BT interactions are of general
interest because they could maintain trait variation within
populations through context-dependent performance
trade-offs, where the fitness effects of different BTs in one
species depend on the frequency of BTs in another interacting species. Frequency-dependent selection has been
broadly appreciated for its role in the maintenance of genetic diversity (e.g., Carius et al. 2001; Kassen 2002; Roulin
2004), as well as species diversity (e.g., Chesson 2000).
Here, we examine the possibility that joint frequency dependence might contribute to maintenance of variation in
both predator and prey levels. In essence, we suggest that
intraspecific variation in predator BTs represents a dynamic form of environmental heterogeneity for prey that
can help to explain the maintenance of functional variation
(e.g., in behavioral types). Specifically, if the prey BT that
results in highest fitness depends on the predator’s BT,
then variation in predator BT can help maintain variation
in prey BTs. By parallel logic, variation in BTs in prey can
help maintain variation in predator BTs. In essence, even
in two-species interactions, diversity in one trophic level
may help maintain it in another, and vice versa.
We use the black turban snail, Chlorostoma funebralis
(formerly Tegula funebralis, Turbinidae, Vetigastropoda)
and its predator Pisaster ochraceus (Asteriidae, Forcipulatida) as models for our investigation. Chlorostoma funebralis is an abundant herbivore in the rocky intertidal
from Vancouver Island to Baja California (occasionally
exceeding 400 individuals/m2; Morris et al. 1980). Chlorostoma funebralis is preyed on by sea otters (Enhydra lutris), red rock crabs (Cancer antennarius), predatory snails,
and, most prominently, the ocher sea star (P. ochraceus;
Paine 1969; Morris et al. 1980). Chlorostoma funebralis
readily responds to predators by climbing up rock walls
out of the water or, if on a slope, releasing its grip from
the rock surface and rolling downhill (Doering and Phillips
1983; Fawcett 1984). Though not a preferred prey item of
P. ochraceus, it is estimated that P. ochraceus consumes
25%–28% of adult C. funebralis each year where the two
species co-occur (Paine 1969). Thus, predation by P. ochraceus can be a major selective force for mature C. funebralis.
We ask the following questions. (1) Do C. funebralis and
P. ochraceus exhibit consistent individual differences in behavior? (2) For C. funebralis, what BTs are associated with
survival in staged mesocosm predation trials? (3) Are the
survival consequences of various BTs in C. funebralis affected by the BTs of their predators (P. ochraceus)? (4) Are
BTs in P. ochraceus associated with foraging success?
Methods
Collection and Laboratory Maintenance
Chlorostoma funebralis (N p 2,638 ) were haphazardly collected from mid-intertidal pools near Bodega Bay, California, from August to October 2010. Snails were transported to the laboratory and housed in a recirculating
seawater system for the duration of their behavioral assays
(!2 weeks). The salinity of the system ranged from 32 to
35 ppt, temperatures ranged from 17.1⬚ to 18.5⬚C, and the
system was maintained on a 12L : 12D photoperiod. Snails
were individually marked by painting their shells with a
unique series of colored dots using high-gloss, metalliccolored nail polish. We measured snails’ maximum shell
diameter before conducting our behavioral assays.
We opportunistically collected 62 size-matched (Ⳳ12%
average arm length) Pisaster ochraceus from the midintertidal pools near Bodega Bay from September to October 2010. Pisaster ochraceus were housed individually in
outdoor flow-through seawater systems (1-m diameter, 0.5
m deep, 400 L) and provided an ad lib. diet of California
mussels (Mytilus californianus).
Snail Behavioral Type
Before exposure to predators, the BT of individual C. funebralis was characterized by measuring activity level in
the absence of predators and snail response to predator
threat (termed their “predator avoidance response”). To
determine activity level, we placed each snail (mean p
17.46 mm, SD p 3.12) in a 490-mL cylindrical container
(width radius p 7 cm) in a table of recirculating seawater
and allowed it to acclimate for 1 h. To allow us to plot
the position of the snails at regular time intervals, containers were protracted every 45⬚ with lines extending up
the walls of the enclosures. After the acclimation period,
the position of the snail was plotted every 15 min for 2
h. Snail activity level was estimated by summing their distance traveled over the 2-h period, assuming linear movement between positions. To assess repeatability of our
activity-level measurement, 120 individuals were retested
1 week after their initial assay. During the week between
Context-Dependent Selection on Behavior 219
measurements, snails were housed individually in similar
490-mL containers in a table of recirculating seawater
(17.1⬚–18.5⬚C). Snails used to estimate repeatability were
excluded from subsequent assays.
Snail predator avoidance behavior was measured as the
distance snails crawled out of the water in response to sea
star presence (Markowitz 1980; Doering and Phillips
1983). Distance above the waterline represents a natural
trade-off between safety from marine predators and risk
of desiccation; our model predator, P. ochraceus, does not
willingly emerge from the water to forage but can be observed above the waterline during low tides (Morris et al.
1980). Thus, the farther out of the water a snail is, the
less likely it is to be encountered by a sea star as the tide
rises in the field. Circular arenas (45-cm diameter, 43 cm
tall) filled with 15 L of seawater were marked every 3 cm
up the side of the enclosure, which allowed us to estimate
the distance out of the water traveled by each snail during
counts with and without predators. Sets of these markings
were placed every 45⬚ around the arena. Observations were
taken outdoors, at ambient air temperatures (20⬚–22⬚C)
during daylight hours (1100–1600 hours). Before the start
of the trial, the arena was filled with seawater to the 6-cm
mark.
Groups of 12 individually marked, unsexed snails were
placed in a ring (10-cm radius) within the enclosure and
allowed 30 s to acclimate before a single P. ochraceus was
placed centrally into the arena. We assayed snails in small
groups because C. funebralis naturally occurs in clusters
around suitable microhabitat in the field. Thus, although
this species is known to respond to conspecific alarm cues
and this doubtlessly affects their behavior (Jacobsen and
Stabell 2004; Magnhagen and Bunnefeld 2009), our assay
conditions mirror the social context snails experience both
under natural conditions and in our subsequent mesocosm
predation trials (i.e., conspecifics present). We recorded
the height each snail traveled out of the water every 5 min
for 30 min. Snails that failed to breach the water surface
were given a score of zero. As a control, all individuals
were run through a second trial without a predator. Chronological sequence of assays with predators present or absent was alternated among cohorts, and we failed to detect
an association between trial sequence and individuals’
flight response (P 1 .20). These two measurements were
separated by no more than 2 days. Our estimate of each
individual’s predator avoidance response was the difference between the maximum height obtained during the
predator-present and no-predator control treatments. To
assess repeatability of our predator avoidance measure, a
cohort of 101 individuals was retested with a predator 1
week after their initial assays. Snails used to estimate repeatability were excluded from our predation trials.
Sea Star Behavioral Type
Sea star activity level was assessed by measuring distance
traveled for individual sea stars (arm length: mean p
15.18 cm, SD p 1.44) in standardized solitary enclosures
(54 cm # 34 cm # 29 cm). Sea stars were allowed 3 days
to acclimate before being provided an ad lib. diet of M.
californianus for 3 days. Sea stars were allotted 3 days of
acclimation time because preliminary observations indicated that sea stars expressed a heightened activity level
and reduced tendency to accept food when first transported to laboratory. We assessed sea star activity level
twice: 1 and 14 days after their ad lib. meal. Sea star activity
levels were assessed during daylight hours (1100–1600
hours; from September to October 2010) by placing their
enclosures on grids with 2 cm # 2 cm demarcations and
plotting the position of the sea star every 15 min for 3 h.
We estimated activity level as the distance traveled by each
sea star assuming linear movement among plotted positions. Although for the remainder of our article we will
refer to our two measures (i.e., 1 and 14 days) as “time
since an ad lib. meal,” this period represents both time
without food and time acclimating in a novel environment.
These measurements were repeated for a group of 17 sea
stars to assess repeatability. Sea stars used to obtain repeatability estimates were excluded from other assays.
To further characterize sea star BT, we estimated the
ability of individual P. ochraceus to orchestrate movements
across irregular landscapes (e.g., up the sides of enclosures
or around rock faces) by measuring sea stars’ latency to
right themselves once overturned. We adopted this measure because sea stars must orchestrate the movement of
multiple arms, engage their tube feet, and exhibit considerable flexibility in order to overturn their bodies, providing an integrated measure of many activities. Additionally, this behavior is commonly assessed in interspecific
comparisons (e.g., Ohshima 1940; Pollis and Gonor 1975).
Sea stars were placed upside down in the center of a circular flow-through seawater system (1-m diameter, 0.5 m
deep, 400 L). Using a stopwatch, we timed sea stars’ latency
to right themselves. Individuals were deemed “righted”
when tube feet from all five arms were in contact with the
substrate and their ventral side faced downward. To assess
the repeatability of P. ochraceus’s latency to right, 15 sea
stars were assayed three times on consecutive days. Sea
stars used to obtain repeatability were excluded from all
other behavioral assays.
Mesocosm Predation Trials
To test whether sea star and snail BT affected the outcome
of predator-prey interactions, we staged encounters between snails and sea stars whose BT was characterized in
220 The American Naturalist
the above assays. Randomly selected, individually marked
snails (37–46 individuals) were placed within each of 18
rectangular mesocosms (54 cm # 34 cm # 29 cm) and
allowed 15 min to acclimate before a randomly selected
P. ochraceus was placed in the enclosure. Post hoc analyses
confirmed there was no significant association between BTs
of P. ochraceus and the mean (P 1 .70) or variance (P 1
.25) of BTs in their randomly selected pools of prey. Pisaster
ochraceus were starved 5 days before the start of our mesocosm experiments. Lids to the mesocosms were then
sealed and left undisturbed for 14 days. At the end of this
period, we recorded the number of snails consumed and
noted their IDs. A snail was considered “consumed” if all
that remained of it was its empty shell (i.e., no soft tissue).
Mesocosm experiments were run outside under ambient
lighting conditions from late September to November
2010. Mesocosms were connected to an outdoor flowthrough seawater system at Bodega Bay Marine Laboratory. A hole was drilled in the top of each mesocosm,
which allowed a steady flow of cool (16.1⬚–17.5⬚C) seawater to cascade into the enclosures. Eight holes (1.5-cm
diameter) were drilled 15 cm above the base of the mesocosm on all sides, which allowed water to fill the bottom
of the chamber and flow out all sides. This design permitted snails an approximately 14-cm refuge above the
waterline to escape predation. Within a few days, diatoms
were observed growing on the surface of our mesocosms,
and grazing by snails near refuges was common.
To obtain repeated estimates of the selective foraging
effects of individual P. ochraceus, we replicated this experiment three times with each sea star (N p 18). To avoid
confounding effects of mesocosms’ placement, the positions of sea stars were randomized among temporal replicates. Mesocosms were scrubbed clean between replicates
and rinsed thoroughly with seawater.
Statistical Methods
We used ANOVA and partitioning of variances to estimate
repeatability (after Boake 1989) and nonparametric Spearman’s correlations to test for associations among behavioral traits (i.e., behavioral syndromes) in both the snails
and sea stars. To assess the traits associated with survival
in C. funebralis, we calculated selection gradients by transforming trait values to mean zero and unit variance, and
survival scores (1, 0) were transformed into relative fitness
(individuals’ fitness/average fitness of their cohort). Selection gradients (i.e., the change in expected fitness per standard deviation of trait value) were calculated for predator
avoidance response (cm), maximum shell diameter, and a
correlated selection term (i.e., their interaction term) for
each mesocosm independently. We used logistic regression
for our significance tests (after Janzen and Stern 1998) and
multiple linear regression to estimate selection gradients
(after Calsbeek and Irschick 2007). We did not include
nonlinear selection terms in our models owing to limited
degrees of freedom, but visual inspection of the data indicated no nonlinearity. From our selection analyses we
obtained a selection gradient estimate for each P. ochraceus
based on the average of their three repeated mesocosm
predation trials.
To estimate the effects of predator BT and body size on
sea star foraging effects, we used multiple regression with
two response variables: (1) the percentage of snails captured and (2) the average selection gradients imposed. We
included the following predictor variables in our models:
sea star activity level (1 day since an ad lib. meal), sea star
activity level (14 days since an ad lib. meal), sea star’s
latency to right, and average arm length. Because of the
limited number of sea stars in our selection experiments
(N p 18), we lacked the degrees of freedom to include
interaction terms in our models. All of our statistics were
run using JMP 8.0.
Results
Behavioral Types of Snails and Sea Stars
We found considerable variability in behaviors among individuals of both snails and sea stars (fig. 1), and an individual’s behavior was generally consistent across repeated trials. We detected a significant difference in the
maximum height obtained by snails in the presence and
absence of a predator (Wilcoxon sign rank Z p 31.58,
df p 2,146, P ! .0001; fig. 2A), and predator avoidance
responses were consistent across trials with the same individual (F1, 100 p 4.75, P p .002, r p 0.66; fig. 2B). However, we failed to detect a significant repeatability for our
estimate of snail activity level (F1, 119 p 1.27, P p .09,
r p 0.13), and thus, we exclude these measures from our
selection analyses. In contrast, we detected significant repeatability of sea star activity level both 1 day (F16, 33 p
10.04, P ! .001, r p 0.71) and 14 days (F16, 33 p 5.61,
P ! .001, r p 0.59) after an ad lib. meal, and sea star activity levels were correlated across repeated measures (table
1). Sea stars’ latency to right themselves was also repeatable
(F14, 44 p 6.89, P ! .001, r p 0.45). None of our measures
of sea star BTs were associated with body size (i.e., their
average arm length; activity level 1 day: r p ⫺0.13,
df p 18, P p .62; activity level 14 days: r p ⫺0.01,
df p 18, P p .97; latency to right: r p 0.05, df p 18,
P p .85), and we detected only a weak positive association
between snails’ maximum shell diameter and their predator avoidance response (r p 0.07, df p 1, 823, P p
.003).
Context-Dependent Selection on Behavior 221
Figure 1: Histograms depicting the distribution of behavioral types for Pisaster ochraceus (A–C) and Chlorostoma funebralis (D, E).
Effects of BT on Outcome of Predator-Prey Interactions
A summary of our selection analyses for each mesocosm
is provided in table 2. From observing table 2, we see both
positive and negative selection gradients on snails’ predator avoidance behavior and maximum shell diameter in
different mesocosms. To test whether variation in selection
gradients is associated with sea star attributes, we averaged
the gradients across the three replicates for each sea star
and used these averages in our subsequent analyses.
Before testing for associations between sea star phe-
notypes and their effects on prey populations, we first
tested whether the percentage of snails consumed and selection gradients imposed by each sea star were repeatable
among replicates. We detected significant repeatabilities for
both the percent of prey consumed (F17, 36 p 3.99, P !
.001, r p 0.67, 5%–85% mortality, mean p 41%) and the
selection gradients imposed (predator avoidance response:
F17, 36 p 7.51, P ! .0001, r p 0.71; maximum shell diameter: F17, 36 p 3.23, P p .002, r p 0.65) by individual sea
stars.
We next tested whether sea star attributes were asso-
222 The American Naturalist
model predicting selection on predator avoidance response
included sea star activity level after 14 days without food
and no other terms (fig. 3A; appendix); active sea stars
tended to capture prey with low predator avoidance responses, whereas inactive sea stars tended to capture snails
exhibiting high predator avoidance responses. In a sideby-side comparison against the null model, the model containing activity level after 14 days and no additional terms
boasted an Akaike weight closely resembling one (Wi 1
0.99). In a side-by-side comparison against the second
most informative model, the model containing activity
level after 14 days and no additional terms possessed an
Akaike weight three times that of the alternative model
(Wi p 0.78).
Finally, we tested whether the percent of prey consumed
by sea stars was associated with the selection gradients
they impose on their prey (table 3). We detected a significant positive association between the average percent
of prey consumed by individual P. ochraceus and the selection gradient they impose on maximum shell diameter
(table 3; fig. 3B); however, this trend was differentially
influenced by one highly voracious sea star, and, when
removed, the trend was nonsignificant (r p 0.42, df p
17, P p .09). We detected no significant association between selection imposed on predator avoidance behavior
and the percent of prey consumed by individual sea stars
(table 3).
Discussion
Figure 2: A, Box plots depicting the distribution of the maximum
heights obtained by Chlorostoma funebralis in our no-predator control and predator-present treatments. Heights obtained differed significantly among treatments (Wilcoxon sign rank Z p 31.58, df p
2, 146, P ! .0001). B, Positive covariance between repeated measures
of individual predator avoidance responses by C. funebralis
(F1, 100 p 4.75, P p .002, r p 0.66). Point size is scaled to the number
of co-occurring data points.
ciated with either the average percent of prey consumed
or the selection gradients they impose on their prey. Our
full models predicting the percentage of prey items killed
(F4, 17 p 0.89, P p .50, r 2 p 0.22) and the selection gradient imposed on maximum shell diameter (F4, 17 p 0.82,
P p .54, r 2 p 0.20) were nonsignificant. In contrast, our
full model predicting selection gradients on snails’ predator avoidance response was significant (F4, 17 p 5.46,
P p .008, r 2 p 0.51). Using Akaike Information Criterion
(AIC) model selection criterion (Akaike 1987), the best
Identifying the mechanisms maintaining trait variation
within populations is a core goal in ecology and evolutionary biology; one commonly proposed variance-sustaining mechanism is context-dependent trait performance, where the performance of a trait depends on the
environment in which it is expressed. Here, we document
a pattern in which the performance of BTs in one species
is dependent on the BTs of heterospecific interactors. Specifically, we provide evidence that (1) the BTs associated
Table 1: Spearman’s correlation coefficients and
P values for repeated measures of sea star activity
levels
M1D1
P
M2D1
P
M1D14
P
M2D1
M1D14
M2D14
.69
.008
.79
!.001
.61
.009
.31
.226
.68
.002
.56
.018
Note: Measurements were taken 1 and 14 days after an
ad lib. feeding bout. M p measurement, D p day (e.g.,
M1D1 p measurement 1 at day 1).
Context-Dependent Selection on Behavior 223
Table 2: Estimated selection gradients Ⳳ SE on snails’ predator avoidance behavior, maximum shell diameter, and their interaction
for each sea star (1–18) in each of three replicate mesocosm predation trials (A–C)
Predator avoidance
Sea
star
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
A
⫺.28
⫺.19
.03
⫺.15
.01
.07
.13
.14
⫺.01
.18
.13
.28
.28
⫺.18
.14
.13
⫺.26
.04
Ⳳ.10*
Ⳳ.08*
Ⳳ.05
Ⳳ.08
Ⳳ.04
Ⳳ.09
Ⳳ.09
Ⳳ.08
Ⳳ.08
Ⳳ.08*
Ⳳ.09
Ⳳ.09*
Ⳳ.08*
Ⳳ.05*
Ⳳ.11
Ⳳ.04*
Ⳳ.06*
Ⳳ.19
B
.16
⫺.35
.06
⫺.21
⫺.10
.07
.08
.24
⫺.38
.13
.28
.07
.13
⫺.14
.03
.12
⫺.26
.11
Ⳳ.07*
Ⳳ.07*
Ⳳ.08
Ⳳ.09*
Ⳳ.08
Ⳳ.07
Ⳳ.10
Ⳳ.08
Ⳳ.10*
Ⳳ.06*
Ⳳ.09*
Ⳳ.05
Ⳳ.06*
Ⳳ.06*
Ⳳ.10
Ⳳ.07
Ⳳ.10*
Ⳳ.08
C
⫺.22
⫺.22
.10
⫺.25
⫺.05
.29
.21
.13
⫺.13
.23
.03
.14
.29
⫺.27
⫺.14
.19
⫺.12
.10
Predator avoidance # maximum
shell diameter
Maximum shell diameter
Ⳳ.09*
Ⳳ.06*
Ⳳ.09
Ⳳ.08*
Ⳳ.08
Ⳳ.06*
Ⳳ.06*
Ⳳ.06*
Ⳳ.07
Ⳳ.07*
Ⳳ.08
Ⳳ.07
Ⳳ.07*
Ⳳ.07*
Ⳳ.09
Ⳳ.05*
Ⳳ.04*
Ⳳ.10
A
⫺.08
.17
.01
⫺.07
⫺.05
.27
.11
.12
.01
.07
.08
⫺.06
.09
.22
.06
.16
.08
.42
Ⳳ.09
Ⳳ.11
Ⳳ.07
Ⳳ.08
Ⳳ.06
Ⳳ.09*
Ⳳ.12
Ⳳ.08
Ⳳ.06
Ⳳ.08
Ⳳ.09
Ⳳ.06
Ⳳ.07
Ⳳ.05*
Ⳳ.11
Ⳳ.05*
Ⳳ.07
Ⳳ.08*
B
⫺.06
⫺.12
⫺.01
.03
.04
.01
.14
.01
.05
.22
.08
⫺.13
.08
⫺.09
⫺.17
.20
⫺.14
.01
Ⳳ.07
Ⳳ.09
Ⳳ.08
Ⳳ.08
Ⳳ.06
Ⳳ.09
Ⳳ.10
Ⳳ.09
Ⳳ.05
Ⳳ.11*
Ⳳ.09
Ⳳ.05
Ⳳ.10
Ⳳ.07
Ⳳ.09
Ⳳ.06*
Ⳳ.12
Ⳳ.14
C
.06
.08
.09
⫺.19
⫺.15
⫺.01
.30
⫺.14
⫺.12
.11
.06
⫺.18
⫺.02
⫺.09
⫺.07
.24
⫺.09
.17
Ⳳ.07
Ⳳ.09
Ⳳ.12
Ⳳ.13
Ⳳ.05*
Ⳳ.07
Ⳳ.06*
Ⳳ.06*
Ⳳ.15
Ⳳ.10
Ⳳ.06
Ⳳ.08*
Ⳳ.04
Ⳳ.07
Ⳳ.10
Ⳳ.05*
Ⳳ.06
Ⳳ.08*
A
.05
.07
⫺.05
⫺.04
.05
⫺.05
⫺.11
.02
⫺.05
⫺.07
⫺.01
.12
.01
.07
.03
.02
⫺.03
⫺.06
Ⳳ.06
Ⳳ.06
Ⳳ.06
Ⳳ.13
Ⳳ.08
Ⳳ.07
Ⳳ.10
Ⳳ.02
Ⳳ.06
Ⳳ.09
Ⳳ.08
Ⳳ.08
Ⳳ.09
Ⳳ.06
Ⳳ.14
Ⳳ.06
Ⳳ.05
Ⳳ.15
B
.01
.02
⫺.03
.07
.10
.06
⫺.01
⫺.05
.01
⫺.09
.04
.06
.02
.02
⫺.05
.13
.34
.22
Ⳳ.06
Ⳳ.06
Ⳳ.07
Ⳳ.07
Ⳳ.07
Ⳳ.09
Ⳳ.13
Ⳳ.10
Ⳳ.07
Ⳳ.06
Ⳳ.12
Ⳳ.05
Ⳳ.06
Ⳳ.05
Ⳳ.08
Ⳳ.07
Ⳳ.21
Ⳳ.26
C
⫺.01
⫺.06
.13
.24
⫺.06
.03
⫺.03
.16
⫺.02
.10
.23
.08
⫺.04
.04
.10
⫺.08
.02
⫺.05
Ⳳ.06
Ⳳ.07
Ⳳ.10
Ⳳ.16
Ⳳ.09
Ⳳ.09
Ⳳ.06
Ⳳ.11
Ⳳ.16
Ⳳ.10
Ⳳ.08*
Ⳳ.11
Ⳳ.06
Ⳳ.05
Ⳳ.13
Ⳳ.05
Ⳳ.08
Ⳳ.09
* Significant correlation coefficient at a p 0.05.
with survival in Chlorostoma funebralis vary depending on
the BTs of its predator, Pisaster ochraceus: snails exhibiting
greater predator avoidance responses experience higher
survivorship with active sea stars while snails with low
predator avoidance responses experience higher survivorship with inactive sea stars (fig. 3A). (2) Although the
survival consequences of snails’ maximum shell diameter
also differed among individual sea stars (table 2), we failed
to detect an association between selection on maximum
shell diameter and any sea star attributes. Finally, (3) we
provide evidence that the Pisaster-Chlorostoma system
meets the necessary preconditions for multispecies frequency-dependent selection, where the fitness consequences of BTs in one species depend on the frequency
of BTs in another. We discuss each of these points in more
detail below.
As in many other systems, we found evidence for behavioral types in C. funebralis and P. ochraceus. Chlorostoma funebralis exhibited repeatable differences in their
tendency to flee from P. ochraceus, and P. ochraceus exhibited consistent individual differences in activity level
across repeated measures separated by more than 30 days
(table 2). More interestingly, individual differences in behavior in C. funebralis were associated with survival in
staged encounters with P. ochraceus, and, if predator avoidance behavior is heritable, differential survivorship could
lead to evolution in snails’ antipredator response. Al-
though at present we lack data on the heritability of antipredator behavior in C. funebralis, two lines of evidence
suggest among-individual differences in response to predators have some genetic basis. First, we detected strongly
repeatable individual differences in flight response, and in
species with long generation times (e.g., C. funebralis take
15 years to reach maturity; Paine 1969), repeatabilities are
often used as rough proxies for narrow-sense heritability
(i.e., because repeatability sets an upper limit to heritability; Boake 1994). Second, previous data comparing flight
responses among populations of C. funebralis revealed that
populations with more predators exhibit greater predator
avoidance responses (Fawcett 1984), and these behavioral
differences are maintained following reciprocal transplants. Fawcett (1984) argues that population differences
in predator avoidance behavior are likely the result of local
adaptation, because in field selection experiments, greater
predator avoidance responses were associated with higher
survivorship in localities with more predators. However,
several studies have documented tremendous within-population variation in predator avoidance behavior (Markowitz 1980; Doering and Phillips 1983; Fawcett 1984),
and little is known about how this variation is maintained.
Although C. funebralis BT affected its survival, the BTs
favored differed among individual sea stars. When paired
with active P. ochraceus, C. funebralis expressing greater
predator avoidance responses enjoyed higher survivorship;
224 The American Naturalist
adopt a sit-and-wait foraging strategy, tend to capture prey
with greater predator avoidance responses, perhaps because fleeing snails are more likely to make contact with
the inactive predator. Interestingly, we failed to detect an
association between sea star foraging success (i.e., total
number of prey killed) and the selection gradients P. ochraceus imposed on snails’ predator avoidance response, and
this suggests that foraging strategy does not influence the
number of prey consumed by individual P. ochraceus. In
other words, whether P. ochraceus are active or inactive,
they are able to capture a similar number of snails, provided there is a diversity of prey phenotypes present. This
finding is important because if any BT consistently experienced higher foraging rates, we would expect rapid
selection and fixation of that variant within the population.
Synthesis and Future Directions
Figure 3: A, Positive relationship between sea star activity levels after
14 days without food and the selection gradients they impose on
predator avoidance behavior in their prey (Chlorostoma funebralis;
F1, 17 p 23.42, P ! .001, r2 p 0.41). B, Positive relationship between
the average percent of prey consumed by individual sea stars averaged
across three replicates and the selection gradient they impose on
maximum shell diameter in their prey (C. funebralis). Positive values
indicate greater predator avoidance responses or larger C. funebralis
experienced higher survivorship. Negative values indicate unresponsive or smaller individuals experienced higher survivorship.
however, predator avoidance behavior was disfavored in
encounters with inactive P. ochraceus. Instead, unresponsive individuals were more likely to survive encounters
with inactive P. ochraceus (fig. 3A). Although the mechanism behind this trend is unresolved, the data resemble
those from classic literature on foraging mode (Huey and
Pianka 1981; Scharf et al. 2006): active-foraging species
tend to capture sedentary prey and sit-and-wait predators
tend to capture active prey. Similarly, active P. ochraceus
are perhaps more likely to make contact with unresponsive
C. funebralis, while inactive P. ochraceus, which appear to
A familiar idea in evolutionary ecology is that negative
frequency dependence, a rare type advantage, can be important in maintaining variation within or among species
(Chesson 2000; Sinervo and Calsbeek 2006). However,
here we identify the preconditions for multispecies frequency-dependent selection in a predator-prey system,
whereby the mechanism of frequency-dependent selection
on BTs in each species depends on BTs of the other species,
which are themselves under frequency-dependent selection. We propose this scenario can result in “joint frequency-dependent selection” in overall predator-prey interactions via the following feedback sequence: (1) if a
system has mostly active predators that primarily eat unresponsive prey, this favors prey that actively avoid predators; (2) selection then favors more responsive prey, and
the prey population gradually expresses greater predator
avoidance behavior; (3) responsive, fearful prey populations then favor inactive predators that can catch more
prey without absorbing the costs of high activity levels;
however, (4) when inactive predators become more common, this favors unresponsive prey, which in turn favors
active predators. It is important to note that although we
outline this feedback in terms of intraspecific trait variants,
the sequence could as easily be illustrated with suites of
predator and prey species (Huey and Pianka 1981). Thematically similar cycles have been outlined in models on
gene-for-gene coevolution in host-parasite interactions
(Frank 1992), in which multispecies frequency-dependent
cycles can have either stabilizing or destabilizing effects
depending on a multitude of factors (Tellier and Brown
2007, 2009).
In nature, the Pisaster-Chlorostoma system is probably
usually too complex for a simple, two-species, joint frequency-dependent selection scenario to hold. Although
Chlorostoma funebralis experiences intense predation by
Context-Dependent Selection on Behavior 225
Table 3: Spearman’s correlations between the average percent of prey consumed by individual
sea stars and the selection gradients they impose on their prey
Selection on predator
avoidance response
Selection on maximum
shell diameter
.17
.497
.51
.029
.23
.356
Percent of prey consumed
P
Selection on predator avoidance response
P
Pisaster ochraceus, C. funebralis constitutes a relatively minor portion of P. ochraceus’s diet (i.e., the interaction is
highly asymmetrical; Paine 1969). However, our study successfully illustrates the potential for such feedbacks to occur, and many of the necessary preconditions identified
here are met in other predator-prey systems (e.g., Smith
and Blumstein 2010); thus, similar feedback mechanisms
could be quite general. We propose the reason such mechanisms have not been characterized previously is that most
evolutionary ecologists (behavioral or otherwise) tend to
focus on traits in only a single species and regard heterospecifics as passive, nonevolving selective agents (Yoshida
et al. 2003; Biro et al. 2004; Hairston et al. 2005; Meyer
et al. 2006; Bell and Sih 2007; Smith and Blumstein 2010).
Further work is required to determine the possible im-
portance of our joint frequency-dependent selection hypothesis in other test systems that (1) exhibit a more symmetrical predator-prey interaction and (2) have shorter
generation times.
Acknowledgments
We are indebted to K. Demes, S. Kamel, and two anonymous
reviewers for their helpful comments on previous versions
of this manuscript. Funding for our work was provided by
the Center for Population Biology at the University of California, Davis, and a grant from the National Science Foundation Biological Oceanography Program to J.J.S.
APPENDIX
Table A1: Summary of model statistics predicting selection gradients sea stars impose on snail predator avoidance
behavior
Model
Activity level 14 days
Latency to right
Arm length
Activity 1 day
Arm length, activity level 14 days
Activity 1 day, activity level 14 days
Latency to right, activity level 14 days
Arm length, latency to right
Latency to right, activity 1 day
Arm length, activity 1 day
Arm length, activity 1 day, activity level 14 days
Arm length, latency to right, activity level 14 days
Latency to right, activity 1 day, activity level 14 days
Arm length, latency to right, activity 1 day
Arm length, latency to right, activity 1 day, activity level 14 days
No.
parameters
r2
AIC
DiAIC
1
1
1
1
2
2
2
2
2
2
3
3
3
3
4
.411
.1085
.102
.0025
.5109
.4223
.4202
.2218
.1247
.1052
.5237
.5164
.4279
.241
.5263
⫺14.108
⫺6.6489
⫺6.5173
⫺4.6259
⫺12.091
⫺11.096
⫺11.03
⫺5.7314
⫺3.6158
⫺3.2196
⫺10.648
⫺10.372
⫺7.3474
⫺2.2598
⫺6.1077
0
7.4591
7.5907
9.4821
2.017
3.012
3.078
8.3766
10.4922
10.8884
3.46
3.736
6.7606
11.8482
8.0003
226 The American Naturalist
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Associate Editor: Thomas N. Sherratt
Editor: Mark A. McPeek
White-lipped snail or Helix albolabris. “That the sense of smell is enjoyed by the snail has long been known, since they will oftentimes
travel some distance in quest of food for which they have a particular fondness.” From “The Land Snails of New England,” by E. S. Morse
(American Naturalist, 1867, 1:5–16).