Behavioral Ecology
doi:10.1093/beheco/arq100
Advance Access publication 15 July 2010
Attack or call for help? Rapid individual
decisions in a group-hunting ant
Volker Witte,a Daniel Schliessmann,b and Rosli Hashimc
Department Biologie II, Ludwig-Maximilians Universität München, Großhaderner Str. 2,
82152 Planegg, Germany, bDepartment of Animal Evolutionary Ecology, Universität Tübingen, Auf der
Morgenstelle 28, 72076 Tübingen, Germany, and cInstitute of Biological Sciences, Faculty of Science,
University of Malaya, 50603 Kuala Lumpur, Malaysia
a
Adaptive decision making is an important trait of many animals, especially in the context of foraging. Social animals are able to
optimize their foraging behavior individually or on a collective level. In the predatory ant Leptogenys diminuta, scout ants search
individually for prey and then decide within seconds whether to attack directly or to recruit a large raiding group for a collective
attack. Both strategies have inherent costs and benefits, and the information collected by the scout during prey assessment is
crucial for an appropriate reaction. We studied how differences in prey type and size are taken into account by experienced and
inexperienced scout ants. Although decisions are made under time pressure and frequently without disturbing the prey, experienced scouts adjusted their raiding strategies in accordance with predicted hypotheses. In contrast, inexperienced scouts
preferred a risk-averse strategy by recruiting large raiding groups. After a 4-week learning phase, inexperienced scouts developed
raiding strategies equal to experienced scouts, independent of hunting success treatments, suggesting a predetermined behavioral repertoire. Using gas chromatography and mass spectrometry, we studied furthermore whether prey items could be
discriminated by chemical cues. Natural prey was distinguishable on a high taxonomic level. In raids on chemically treated
dummies, however, responses were not equal to those elicited by real prey. Thus, the ants probably integrate additional information, such as visual or tactile cues, into their decision-making process. Overall, L. diminuta exhibits a remarkably cautious,
quick, and adaptive decision-making system in which prey cuticular chemicals are incorporated as informational cues.
Key words: optimality, predator–prey interactions, risk sensitive foraging, speed versus accuracy trade-off. [Behav Ecol 21:1040–
1047 (2010)]
nimals face situations in which they may react differently,
and their decisions can have varying consequences. If these
consequences affect fitness, selection should favor optimal
decisions. Selection is likely to act in the context of food acquisition because nutritional input strongly affects growth and reproduction (Charnov 1973; Pyke et al. 1977). Selection acts on
the individual in solitary animals, whereas in social animals,
the group represents an important level of selection (Reeve
and Hölldobler 2007; West et al. 2007). Consequently, decision-making processes in social animals frequently involve cooperation between individuals as well as collective decisions
(Conradt and Roper 2003, 2005). Foraging social insects communicate information about valuable resources to colony
mates mainly through pheromones, leading to efficient resource exploitation (Jaffe 1980; Detrain and Deneubourg
2002; Costa-Leonardo et al. 2009). House-hunting ants and
bees use a quorum consensus mechanism to select appropriate nest sites for their colonies (Pratt et al. 2002; Visscher
2007). These collective systems are based primarily on individual level decisions that can accumulate and lead to a secondary
colony-level response through positive and negative feedback
loops (Bonabeau 1998; Couzin 2009). In such collective systems, individual errors can be balanced out, resulting in low
negative consequences as long as decisions are not made
under strong time pressure (Franks et al. 2003; Chittka
et al. 2009). However, although collective mechanisms are
widespread, not all social insects rely on self-organization to
A
Address correspondence to V. Witte. E-mail: [email protected].
Received 2 February 2010; revised 27 May 2010; accepted 29
May 2010.
The Author 2010. Published by Oxford University Press on behalf of
the International Society for Behavioral Ecology. All rights reserved.
For permissions, please e-mail: [email protected]
equal extent. The predatory ant Leptogenys diminuta exhibits
an extraordinary group-raiding behavior, where individual
decisions evoke significant colony reactions. Leptogenys diminuta
is a generalist predatory ant that inhabits Southeast-Asian rainforests and includes a broad spectrum of different invertebrate
taxa in its diet (Steghaus-Kovac 1994; Steghaus-Kovac and
Maschwitz 1998). Prey organisms show great variation in size,
ranging from few millimeters to more than 2 cm, as well as in
mobility, ranging from slow-moving animals such as insect larvae or mollusks to highly mobile animals such as grasshoppers,
crickets, or spiders (Steghaus-Kovac 1994). The inclusion of
large and mobile prey in the dietary spectrum is enabled by
the application of a sophisticated scout-induced group-raiding
strategy, where single ants trigger raids that can comprise up to
almost 50% of the worker force of a colony (colony size median: 435 workers) (Maschwitz and Steghaus-Kovac 1991; Steghaus-Kovac 1994). We used this system to study individual
decision making during foraging. Foragers always search for
prey individually (scouts) and then follow 1 of 2 different raiding strategies after encountering prey. First, a scout may attack directly, attempting to subdue the prey alone. The
second option is not to attack but to return to the nest in
order to recruit a raiding party, which can then overwhelm
the prey in a collective attack (Steghaus-Kovac 1994; Witte
2001). Independent of the attack strategy, the prey is typically retrieved by a recruited group, unless the item is very
small. In terms of optimal foraging, we hypothesize that the
2 different attack strategies have inherent costs and benefits
that depend greatly on the prey type. The individual strategy should work best for small prey objects, which can be
handled by individual ants and/or for prey objects with
a small escape probability. If the target object is small and
Witte et al.
•
Decision making in group-hunting ants
weak enough to be subdued by a single ant, a direct attack
bears low risk for a scout and has a good chance of success.
Contrarily, a scout may risk injury during an individual attack on large and strong prey as well as have a lower chance
of success. Consequently, for such situations, a collective
strategy should have a better payoff. If the escape capabilities of the prey are low in terms of mobility, the scout may
have a chance of success using a direct attack, but this
comes with an increased risk. The collective strategy is not
assumed to be optimal in all cases because of its inherent
costs. First, the energy investment is higher; second, the
worker force is absent and unavailable for other raids;
and third, perhaps most importantly, there is a permanent
risk of losing the unattended prey because the process of
recruitment takes time, and the focal objects might escape
or be preyed upon by other animals. In this context, the
actual movement of a prey item at the time of encounter is
another crucial factor to be considered independent of its
potential mobility. Once a target object is moving, it has
a high likelihood of leaving the range of the approaching
raiding party. Under such circumstances, an individual attack of the scout may pay off better, despite an increased
individual risk.
A critical limitation in optimal foraging is the availability of
information (Pyke 1984). If knowledge of the environment is
incomplete, only suboptimal decisions can be made. This is
particularly evident in the system studied here. For the collective strategy to work on prey with high potential mobility,
L. diminuta scouts must gather information on the prey type
without disturbing it. The longer and closer an L. diminuta
scout inspects an animal, such as a spider, the more likely it
becomes that the prey may become aware of the predator and
attempt to escape, leading to a potential loss of prey. Furthermore, prey animals may even attempt to attack, potentially
harming or killing the scout. Scouts, thus, face a trade-off between information gathering and interacting with the prey animal. Because the time a scout spends investigating prey before
recruiting a raiding party is frequently as short as a second
(Steghaus-Kovac 1994), we assume that there is selection on
scouts to react appropriately by gathering as much information
about the prey as possible in a minimal amount of time. The
response can be adjusted adaptively only if sufficient information can be collected in a short time frame. Thus, we ask which
prey properties are assessed by scouts, which cues are involved,
and whether an adaptive foraging strategy follows.
Visual cues presumably play a minor role for these diurnal
and nocturnal foragers, at least in the darkness of the rainforest’s leaf-littered floor during the night. Because social insects
are generally known to rely predominantly on chemical cues
(Wilson 1990; Jackson and Morgan 1993; Morgan 2008) and
because they are capable of learning foreign odors (Helmy
and Jander 2003; Chaline et al. 2005; Choe and Rust 2006;
Dupuy et al. 2006), a chemical channel of identification can
be presumed in L. diminuta. Most arthropods carry a hydrocarbon layer on their cuticle, and social insects are well known to
use these cuticular hydrocarbons (CHCs) as intra- and interspecific recognition cues (Vander Meer and Morel 1998;
Howard and Blomquist 2005; Lucas et al. 2005; Hefetz
2007). However, to our knowledge, the role of CHCs in the
identification of prey animals has not been studied before.
Finally, an important aspect associated with decision making
is the role of learning. In a predictable environment, decision
rules could be fixed; however, in a highly variable environment, the capacity of learning is more adaptive (Dukas
2008). Learning plays an important role for many animals,
including social insects (Dornhaus and Franks 2008; Dukas,
forthcoming). Thus, we address whether scouts follow inherent decision rules or acquire experience through learning
1041
trials in which they are exposed to successes and errors. If
learning plays a significant role in the decision-making process
of L. diminuta, we would expect that inexperienced foragers
come to less adaptive decisions than experienced foragers.
In this study, we examined whether individual decisions of
scouts follow adaptive patterns. Specifically, we addressed
3 main questions. First, whether the short amount of time
for prey assessment is sufficient for a scout to react with an
adaptive decision according to the hypotheses established
above. To study this question, we performed a prey type, a prey
size, and a prey movement experiment. We expected an
increase in recruitment of large raiding groups with prey
size (within a given prey type) as well as with potential prey
mobility (between prey types and within a size class). Furthermore, once prey is already moving, we expected an increase in
individual attacks on every prey type. Second, we asked which
cues are involved in prey assessment. To examine potential
chemical discrimination among prey taxa, we analyzed the
cuticular chemistry of 3 abundant prey taxon groups of
L. diminuta, and we tested the effects of chemical prey cues
using dummy experiments. Our third question addressed
whether experience is necessary to come to an appropriate
decision. We conducted a reward experiment in which colonies were treated with prey-specific success or failure treatments, and we tested whether they exhibit different raiding
strategies according to treatments.
MATERIALS AND METHODS
Leptogenys diminuta colonies were collected at the field
studies center of the University Malaya (Kuala Lumpur,
Malaysia), located in Ulu Gombak (lat 0319.4796#N,
long 10145.1630#E, 230 m elevation). Colonies were
maintained at the field station for controlled laboratory
experiments (on prey type and size) and later brought to
the Ludwig-Maximilians Universität München (Munich,
Germany) for further experiments (on prey movement
and learning). In Germany, the ants were kept in a climatized room at 12:12 h light:dark, 26 C, and 70% humidity.
The colonies were housed in plastic containers (45 3 30 3
12 cm) and allowed to nest in their natural leaf litter on
a moistened sand floor. They were provided with water ad
libitum and fed after each experimental period with small
amounts of various freshly killed insects (ca. 2 mm3), excluding the prey species that were used in the experiments.
All raiding experiments were performed according to the
following protocol.
Prey items were offered in a foraging arena that was connected to the nest-box with a wooden bridge of 2 m length
(in Malaysia) or 50 cm length (in Germany). At the field station, we worked at night and in the laboratory in a darkened
room using headlamps set to a low level. To study individual
decisions exclusively, scout behavior and subsequent recruitment events were observed only after prey contact by a single
scout. A contact was defined as a scout coming closer than
5 mm with its antennae but did not necessarily include physical
contact. We recorded the scouts’ ‘‘contact time’’ at the prey (in
seconds, using a stopwatch), its decision to ‘‘attack’’ (yes or no),
and the size of the recruited ‘‘raiding party,’’ that is, the number of recruited nest mates (using a hand counter). A raiding
party is either recruited by a scout that did not attack itself (for
a subsequent collective attack) or by a scout after its initial attack (to finally kill and retrieve the prey). An attack was defined
as biting and/or stinging the prey object. Although numerous
scouts were active, a slight possibility of repeated observations
existed because individuals were not marked. The prey objects
were only used once and removed from the foraging arena after the scout had left and started a recruitment runback to the
Behavioral Ecology
1042
nest. Raiding experiments were carried out under the following treatments to test specific hypotheses.
Prey type experiment
The question whether L. diminuta scouts distinguish between
prey organisms and react with different raiding strategies was
tested using crickets (Gryllus sp.) as a defensive and highly
mobile prey and beetle larvae (Zophoba sp.) as a less defensive
and slow-moving prey. The 2 taxa were similar in weight
(crickets: mean 0.55 g, standard deviation [SD] 0.15, N ¼ 50
and larvae: mean 0.46 g, SD 0.15, N ¼ 51) but not in length
due to their respective shapes. The prey items were purchased
and do not occur in the natural environment of L. diminuta.
Fifty-one experiments were conducted with living prey animals and 50 with freshly killed animals to study the effect of
movement. The latter were killed in a headspace of hexane,
which was then evaporated for 5 min before testing the animal. Series of 10 (one time 11) raids in a row were conducted
on the same colony using both prey species alternately.
Alive and dead prey were tested on separate days. The experiments were conducted using 5 captive colonies, resulting in
101 raids.
Prey size experiment
Prey sizes in the prey type experiment were at the upper limit
of L. diminuta’s diet, and there was little variation in size.
Therefore, a separate experimental series was performed with
more pronounced size differences within one prey type only,
that is, crickets. Series of 10 raids in a row were conducted on
a colony with either a freshly killed entire cricket or only
a hind leg offered alternately. The legs were placed with the
wound in the soil of the foraging arena to prevent the perception of hemolymph. Five colonies were tested, resulting in
50 raids.
Movement experiment
The effect of prey movement on the scouts’ decision making
was tested within one prey type, that is, crickets. Freshly killed
animals were either not moved or moved using forceps in a
defined manner by one experimenter. The movements started
tangentially toward a scout’s antennae and, after the scout
reacted to the prey, turned into an 8-shaped path of twice
2.5-cm diameter. The speed of movement was about 2 s per
round. Fifty repetitions of each treatment were performed,
resulting in 100 experiments (using 5 colonies). These experiments were conducted after the reward experiment (see
below) with overall reduced raiding activities.
Chemical recognition cues
A preliminary analysis of the surface chemicals of natural prey
animals was performed to study the possibility of a chemical
recognition. Ten leaf litter animals of similar size from 3 typical
prey taxa (crickets, roaches, and spiders) were collected at
the field site and extracted with hexane and methanol. The
animals were collected randomly and comprised different species within each taxon. They were killed in a hexane headspace
and then placed into a vial containing 200 ll of hexane for
15 min. After removal, the solvent was evaporated for 1 min,
and the animals were subsequently extracted with 200 ll methanol in the same way. Finally, the samples were completely
evaporated and dissolved in 20 ll of the respective solvent containing an internal standard (8.64 mg/l methyl tridecanoate).
One microliter was injected into a gas chromatograph (Agilent
6890N) that was equipped with an Agilent HP-5 column (30 m
length, 0.25-mm inner diameter, and 0.25-lm film thickness)
and coupled to a mass spectrometer (Agilent 5975 MSD).
Injections were performed splitless over 1.0 min at 280 C, followed by automatic flow control at 1.0 ml/min with helium as
the carrier gas. The oven program began isothermally at 120 C
for 2 min and then increased at a rate of 25 C/min until 200 C
was reached, followed by a temperature ramp of 4 C/min until
the final temperature of 300 C was reached. The transfer line
was held constantly at 310 C. A range of 50–500 amu was
scanned after an initial solvent delay of 3.8 min.
Raiding experiments were also carried out using dummies
(6-mm glass beads), which were brought in direct contact with
Zophoba sp. and Gryllus sp. in order to transfer surface chemicals. After rubbing the glass surface approximately 2 min
from all sides gently over a freshly killed prey animal, raiding
experiments were performed as described above. Clean untreated dummies were tested additionally as a control. Dummies were removed, and the respective trials were not counted
if no scout contact occurred within 5 min.
Reward experiment
In contrast to the other experiments in which the prey was removed after scout contact, the raiding groups were now provided with rewards. Six colonies were used, 3 of which were
rewarded with a small piece of cricket (diameter 1 mm) after
each raid on crickets and the other 3 were rewarded with an
equal amount of larvae after each raid on larvae. All colonies
experienced 2 raids per day, 3 times a week, on both prey types.
Only the reward differed. The intention was to provide different experiences to the scouts either that only crickets are catchable but not larvae or vice versa. If learning had an effect, we
would expect specific responses to prey type according to the
treatments. Either more effort would be invested in catching
difficult prey or a stronger preference for easily catchable prey
would occur. In both cases, an effect of treatment must become
apparent if learning plays a role. We can imagine 3 modes of
learning: one among the scouts that initiated the raids, one
among the recruited participants of the raid party, and one
among the ants in the nest based on the type of prey they
get to feed on. To reduce the number of experienced scouts,
we removed all scouting ants in the foraging arena of all 6 colonies over the course of 1 day, leaving mostly inexperienced
ants behind. The training phase, consisting of 2 raids per colony per day, was conducted for 4 weeks and then a testing
phase followed during which each colony was tested intensely
over 1 day with a series of 26–29 raids (including the reward
treatments used previously). Two colonies had to be excluded
because they did not show sufficient activity for analysis. Thus,
108 raids of 4 colonies (2 with cricket and 2 with larvae treatments) remained. The overall raiding activity decreased to
about half of the original activity during this experimental
series (see ‘‘RESULTS’’).
Data analysis
Frequencies of attack versus non–attack decisions were analyzed between prey types using Fisher’s Exact tests (XlStat
2009, version 6.02, Addinsoft). Two response variables were
studied in detail, the scout’s contact time (log transformed),
representing an individual strategy, and the raiding party
size, representing a collective strategy. Explanatory variables
were the respective focal treatment of each experiment, the
scout’s decision to attack (yes/no) and the experimental colony (as a random factor). For clarity, we do not report significant differences between colonies because they are not
among the focal questions. Prey weight was included as
Witte et al.
•
Decision making in group-hunting ants
a covariate only in the prey type experiment. All raids belonging to the same treatment were performed on 1 day using the
same colony, except for the learning phase of the reward experiment, where colonies were treated repeatedly. There
were, however, not sufficient repetitions per day to perform
calculations between prey types so that, as a compromise,
weeks instead of days were used as the level of repetition
in time. The data was evaluated with nonparametric (NP)
analysis of variance (ANOVA), with 9999 permutations on Euclidean distances. In our experience, NP-ANOVA is a sensitive
and robust method that is free from assumptions about data
distribution, except for the covariates, which must be linear
(Anderson 2001; Anderson et al. 2008). The analyses were
performed with the software PRIMER 6 (version 6.1.11) with
the PERMANOVA1 add-in (version 1.0.1; PRIMER-E Ltd.,
Ivybridge, UK). Graphs were produced with the SSC-Stat Excel
add-in (version 2.18; University of Reading).
To process the chemical data, peak areas were integrated
with Agilent Chemstation (version E.02.00.493). Contaminants
were identified by mass spectra and excluded from the analysis.
Four samples had to be excluded due to an overall lack of concentration. Peak areas of the remaining samples were fourth
root transformed and standardized using each samples total.
A canonical analysis of principle coordinates (CAP) was performed on a resemblance matrix based on Bray–Curtis similarities
using the software Primer 6. CAP is a NP constrained ordination
method, comparable with the parametric discriminant analysis,
that explicitly seeks differences between predefined groups
(Anderson and Willis 2003). To assess differences, it performs
cross-validation tests between groups. In addition, we used an
analysis of similarities (ANOSIM) as a NP (permutation) test for
differences between predefined groups.
RESULTS
Prey type experiment
As expected for an individual strategy, scouts stayed in contact
longer with beetle larvae (low mobility) than with crickets
(high mobility) (NP-ANOVA, Pprey , 0.001; Figure 1A, right
side). Not surprisingly, the contact times also depended on
the scouts’ decision to attack (P , 0.001; Figure 1B, right
side). Recruited raid parties comprised, on average, 100 workers (SD 38, N ¼ 101). As expected, the effect of prey type on
1043
recruited group sizes had the opposite effect of contact time,
that is, raiding groups were larger for crickets, the more mobile prey (NP-ANOVA, P ¼ 0.012; Figure 1A). These effects
indicate a trade-off for scouts between individual prey
handling and recruiting helpers. As expected for a collective
strategy, raiding groups were larger when the prey was not
attacked by the scout (NP-ANOVA, P ¼ 0.007). The state of
prey animals (dead or alive) had an additional unexpected
effect on the size of raiding groups (NP-ANOVA, P ¼ 0.023),
and this interacted with the decision to attack (NP-ANOVA,
P , 0.001), that is, raiding group sizes differed between attack
and non–attack decisions but only for dead prey (Figure 2).
The sizes of recruited raiding groups decreased only when
dead prey was ‘‘attacked’’ (accompanied by increasing contact
times) (Figure 2). Finally, prey weight had, as expected, a positive effect on raiding groups sizes (P ¼ 0.013) and a negative
effect on contact time (P ¼ 0.002).
Prey size experiment
As expected for an individual strategy, there were significantly
more attacks on the smaller prey (cricket leg) in the prey size
experiment (Table 1) and attacks caused the scouts to stay
longer at the prey (NP-ANOVA, P , 0.001). Scouts that did
not attack stayed a median of 1 s in contact with the prey
(same for both prey types). The recruited raid parties comprised 103 workers on average (SD 55, N ¼ 50). Larger groups
were recruited to entire crickets compared with cricket legs,
as expected for a collective strategy (NP-ANOVA, P ¼ 0.007;
Figure 1C, left side). This happened as well for shorter
contact durations, but this was only visible as a trend (NPANOVA, P ¼ 0.067; Figure 1C, right side) because most of
the variation in contact time is explained by attack (see
above). In summary, the findings were similar to those between
prey types, with respect to individual versus collective strategies
(Figure 1A) but, in this case, they depended on size differences
within the same prey type (Figure 1C).
Movement experiment
Attack frequencies increased with movement, as predicted,
that is, moving prey was attacked significantly more frequently than non–moving prey (Table 1), and contact times
Figure 1
Size of recruited raid party (left) and contact time of the scout (right) of L. diminuta dependent on (A) prey type, (B) individual attack of the
scout in the prey type experiment, and (C) prey size. Outliers are depicted as closed diamonds (.1.5 times) or asterisks (.3 times the
interquartile range). Significance levels are indicated with Tr (trend) , 0.10, *P , 0.05, **P , 0.01, and ***P , 0.001 (NP-ANOVA).
Behavioral Ecology
1044
In raiding experiments with chemically treated dummies,
24 out of 30 encounters (80%) resulted in subsequent raids,
whereas no raids were initiated on control dummies (crickets:
13 out of 15; larvae: 11 out of 15 and control: 0 out of 15). The
reaction to chemically treated dummies differed significantly
from control dummies (Fisher’s Exact test: P , 0.001 each
for larvae and cricket).
180
160
Raind party size
140
120
100
80
Reward experiment
60
Interestingly, after removing most of the experienced scouts at
the beginning of the learning phase, the colonies failed to perform raids during the first week. The inexperienced scouts either lost their orientation and a few even died in the foraging
arena or they reacted with flight after prey encounter and did
not recruit raiding parties. Therefore, we evaluated only scouts
that did recruit. From the second week on, raiding activity
started again at low level; however, the proportion of attacks
decreased dramatically (Table 1). The attack frequencies
across both prey types in the reward experiment were significantly smaller compared with the prey type experiment (Fisher’s test, P , 0.001). Nevertheless, the decision to attack still
had an influence on contact times (NP-ANOVA, P ¼ 0.046).
The recruited raid parties comprised 48 workers on average
(SD 23, N ¼ 109). In the NP-ANOVAs on the number of
recruited nest mates and the contact times of scouts, there
were no differences between the learning treatments (cricket
or larvae) and prey types. The sizes of the raiding parties decreased significantly during the last 3 weeks of the learning
phase (NP-ANOVA, Pweek ¼ 0.005). Furthermore, there was an
interaction between prey type and time (in weeks) on contact
times (NP analysis of covariance, Pprey 3 week ¼ 0.011). This
means that contact times increased for beetle larvae and decreased for crickets over time (Figure 4A), resulting in an
effect similar to that observed in the unmanipulated colonies
of the prey type experiment.
In the test phase, which followed the learning phase, the
original strategies were restored (Figure 4B). Differences between prey types were found for both raid party size
(NP-ANOVA, P ¼ 0.003) and contact time (NP-ANOVA,
P , 0.001), with the directions observed before in the prey
type experiment. As before, contact time depended also on
attack (NP-ANOVA, P , 0.001). The recruited raid parties
comprised 55 workers on average (SD 31, N ¼ 108).
40
20
0
0
0.5
1
1.5
2
2.5
Contact time (log)
Figure 2
Size of recruited raid party of L. diminuta scouts dependent on
contact time, attack decision, and prey state (dead/alive). Open
symbols depict raids without individual attack of the scout, and filled
symbols represent raids after individual attack of the scout. Triangles
(solid lines) depict dead prey, and rectangles (dashed lines) depict
living prey.
with moving prey were significantly longer (NP-ANOVA,
P ¼ 0.015). The number of recruited nest mates did not
depend on movement or attack and was low overall (mean
45, SD 27, N ¼ 100).
Chemical recognition cues
The 3 taxa investigated were well separated by CAP analysis
according to their cuticular chemistry (Figure 3). Crossvalidation tests assigned 20 of 26 samples (76.9%) correctly
into their respective group (100% for crickets, 75% for
roaches, and 60% for spiders). All pairwise comparisons
between groups were significantly different (ANOSIM, all
P , 0.01). Roaches and crickets carried higher concentrations of cuticular chemicals and showed lower within group
variation in chemical profiles than spiders.
Table 1
Comparison of attack frequencies of L. diminuta scouts dependent
on different treatments
Experiment
Treatment
Attack
No
attack
Prey type (alive)
Cricket
Larvae
Cricket
Larvae
Cricket
Cricket leg
Cricket
Larvae
Cricket
Larvae
No
Yes
12
15
10
15
9
17
6
4
7
8
22
39
13
11
15
10
16
8
52
55
46
47
28
11
Prey type (dead)
Prey size (cricket)
Reward
(learning phase)
Reward (test phase)
Movement (cricket)
Attack
ratio
0.5
0.6
0.4
0.6
0.4
0.7
0.1
0.1
0.1
0.1
0.4
0.8
P value
0.579
0.259
0.045
0.529
1.000
,0.001
Cricket: adult Gryllus sp. and Larvae: Zophoba sp. larva. P values of
Fisher’s Exact tests are given. Uncorrected P values are reported
because they result from independent experiments. Sample sizes
result from ‘‘attack’’ and ‘‘no attack’’ frequencies.
DISCUSSION
Our results demonstrate a clear trade-off between collective
and individual hunting in L. diminuta that follows the predictions of a flexible adaptive foraging strategy. On the one
hand, when scouts chose an individual strategy and decided
to attack prey directly, they naturally invested a longer handling time, and subsequently they recruited fewer helpers. On
the other hand, when they followed a collective strategy, they
spent less time at the prey but recruited a larger raiding
group. This trade-off was obvious both with respect to different prey types (mobile versus non-mobile) and with respect to
different sizes of the same prey type.
As mentioned in the introduction, it is important to consider
that the actual size of a raiding group depends on a 2-level process. Leptogenys diminuta communicates mainly chemically
(Attygalle et al. 1988; Attygalle et al. 1991; Steghaus-Kovac
et al. 1992), and ants generally have the ability to adjust their
signals on an individual level by the frequency or amount of
chemical cues they release (Detrain et al. 1999; Jackson and
Chaline 2007). Moreover, the colony response to a given signal depends on internal response thresholds of other ants
Witte et al.
•
Decision making in group-hunting ants
1045
Figure 3
Left: CAP of cuticular chemicals in 3 abundant groups of
L. diminuta prey arthropods.
‘‘Total’’ indicates the direction
of increased total concentrations of all cuticular chemicals
in the plot. Right: L. diminuta
raid on a 6-mm glass dummy
treated with cricket cuticular
chemicals.
that may vary 1) between individuals due to caste or age or 2)
overall in the colony according to external factors (such
as nutritional input) (Detrain and Pasteels 1991; Robinson
1992; Theraulaz et al. 1998; de Biseau and Pasteels 2000).
Our data analysis considered the second level by incorporating variance between colonies as a random factor but focused
on the reactions of individual scouts.
Adjustments of foraging strategies according to prey quantity, quality, and distribution are common in ants (e.g., Schatz
et al. 1997; Bonser et al. 1998; Mailleux et al. 2000; Cerda et al.
2009); however, the circumstances under which decisions are
made vary greatly due to different food sources and communication systems. For predatory ants, it should be more difficult to gather information about the target due to potential
interactions with their prey as well as the risk of losing it or
being attacked themselves. For these reasons, we conclude
that L. diminuta attempts to interact as little as possible with
large and mobile prey. Scouts decide between individual or
collective strategies within seconds, and, if they follow a collective strategy, they avoid direct contact with the prey. Thus,
scouts can lower their own risk and avoid disturbing the prey,
(B)
(A)
Raid party
Contact time (s)
Contact time
(number of ants) (of scout in sec.)
20
140
18
**
***
14
120
12
100
10
16
14
12
80
8
8
60
6
6
40
4
20
2
10
4
2
0
0
0
5
10
15
20
25
0
Larvae Cricket Larvae Cricket
Day
Figure 4
Raiding behavior of L. diminuta after removal of experienced scouts.
(A) Changes in contact durations of scouts over a learning phase of
3 weeks dependent on prey type (cricket ¼ open diamonds and
dashed line and larvae ¼ open rectangles and solid line). Due to
scale adjustment of the y axis, 2 outliers for larva are not visible (day
17, 61 s, and day 19, 126 s). (B) Size of recruited party (left) and
contact time of the scouts (right) after the learning phase dependent
on prey type. Outliers are depicted as closed diamonds (.1.5 times-)
or asterisks (.3 times the interquartile range). Significance levels are
indicated with **P , 0.01 and ***P , 0.001 (NP-ANOVA).
thereby minimizing the likelihood of losing it. Risk-averse foraging became particularly evident in the reward experiment
that was conducted with inexperienced scouts. Only 10% of
prey encounters resulted in an attack, independent of the
prey object. Most ant species show a temporal polyethism,
and younger workers usually perform safer tasks inside the
nest, whereas older workers tend to perform more risky tasks,
such as foraging or defense (Hölldobler and Wilson 1990;
Chapuisat and Keller 2002). In L. diminuta, the experienced
(and presumably older) workers appear to be the ones that
decide more frequently to attack.
In contrast to the risk-averse behavior of inexperienced
scouts, the attack frequencies measured in our raiding experiments with nonmanipulated colonies were surprisingly high
(.50%), and in the case of the prey type experiment, they
did not show as clear of a pattern as expected. We presume that
a lack of information could be responsible for this tendency
to more risk-prone behavior. There are probably limits to gathering the necessary information about prey type and size within
a few seconds and without interfering with the target. When
there is a lack of information, experienced scouts apparently
tend to attack, whereas inexperienced scouts do not. Although
this is a more risky strategy, additional information about the
prey can be collected during an attack, and the subsequent
group recruitment can be better adjusted to the prey size,
for example, for the transport back into the nest. Presumably
for this reason, the groups recruited by a scout that had previously attacked were smaller compared with those that had
not attacked in the prey type experiment because fewer ants
are necessary for transport than for a successful attack. This
trend was particularly evident for dead prey because in this
case, scouts faced no limitation in gathering information. Live
prey, on the other hand, attempts to escape or fight back so
that larger raiding groups are required. In the movement experiment, if prey objects were moving at the time of encounter,
a risk-prone strategy of attack was preferred by the experienced
scouts. As an adaptive strategy, this behavior was expected. The
question remains how scouting ants assess prey identity, even
partially, within seconds without disturbing the prey. Characteristic prey chemical cues provide a conclusive answer. Because mobility as well as defensive or aggressive abilities are
rather conserved within taxonomical groups, the ants would
not need to adjust their behavior on a species level if broader
groups can be distinguished. Our chemical analysis of natural
prey animals revealed that the potential for a distinction of
broad taxonomic groups is given by their surface chemistry.
Furthermore, chemicals appear to play a role in prey recognition by L. diminuta because raiding groups were recruited to
1046
dummies that lacked all characteristic prey cues except for
chemicals. However, in 20% of the trials, the ants did not
recruit at all, suggesting that either chemical cues were not
fully transferred or that other stimuli (such as tactile or visual)
play additional roles. Even if prey types can be recognized
chemically, this is probably not the case for the size of an
animal. To assess size, tactile or visual cues are most likely
required. This is still under investigation.
Whatever cues are involved, the question remains whether
scouts develop their strategies during repeated experiences
with prey. We found no evidence for learning a specific strategy
depending on success or failure with particular prey types in
the reward experiment; however, due to the experimental procedure, which included 6 colonies, the learning trials per colony and especially per individual scout were very limited.
Under natural conditions, a median of 10 scouts per colony
is permanently active (Steghaus-Kovac 1994), and each individual has many chances to interact repeatedly with potential
prey. Thus, our laboratory experiments did not provide a comparable learning environment to natural conditions, and we
cannot rule out learning per se. Nevertheless, the results of
our experiment suggest an innate behavioral repertoire that
becomes activated by experience (or age) because the original
strategy was restored equally, independent of treatment. An
innate ability to differentiate between broad taxonomical
(and functional) groups of prey explains our findings best.
Such ability would also explain the fact that distinct raiding
strategies were exhibited on prey species that the ants never
encounter in their natural environment (commercially available crickets and beetle larvae).
Overall, L. diminuta exhibits a remarkable decision-making
system that enables these ants to come to very quick adaptive
decisions. To achieve this, they probably make use of various
information channels, including chemical cues. However,
when there is a lack of information, scouts behave differently
according to experience (or age). Although the inexperienced ants choose a safer collective strategy relying on the
help of nest mates, the experienced (presumably older) ants
tend to follow a risk-prone strategy of attack.
FUNDING
Deutscher Akademischer Austausch Dienst, project D/08/
45978 (travel and research fund for graduation).
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