Attack or call for help? rapid individual decisions in a group-hunting ant

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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 Hashim

^c

a

Department Biologie II, Ludwig-Maximilians Universita¨t Mu¨nchen, Großhaderner Str. 2,

82152 Planegg, Germany,

^b

Department of Animal Evolutionary Ecology, Universita¨t Tu¨bingen, Auf der Morgenstelle 28, 72076 Tu ¨ bingen, Germany, and

^c

Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia

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 antLeptogenys 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. diminutaexhibits 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)]

A

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 acqui- sition because nutritional input strongly affects growth and re- production (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 Ho¨lldobler 2007; West et al. 2007). Consequently, decision-making processes in social animals frequently involve co- operation between individuals as well as collective decisions (Conradt and Roper 2003, 2005). Foraging social insects com- municate information about valuable resources to colony mates mainly through pheromones, leading to efficient re- source 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

equal extent. The predatory antLeptogenys 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 rain- forests 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; Steg- haus-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 typi- cally 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 Address correspondence to V. Witte. E-mail: [email protected].

Received 2 February 2010; revised 27 May 2010; accepted 29 May 2010.

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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 capabil- ities 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. diminutascouts 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. Further- more, 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 rainfor- est’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 inL. 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 inter- specific 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

trials in which they are exposed to successes and errors. If learning plays a significant role in the decision-making process ofL. 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). Further- more, 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 Universita¨t Mu¨nchen (Munich, Germany) for further experiments (on prey movement and learning). In Germany, the ants were kept in a climat- ized room at 12:12 h light:dark, 26 C, and 70% humidity.

The colonies were housed in plastic containers (453303 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), ex- cluding 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 con- nected 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

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nest. Raiding experiments were carried out under the following treatments to test specific hypotheses.

Prey type experiment

The question whetherL. diminutascouts 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 (Zophobasp.) 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,N¼50 and larvae: mean 0.46 g, SD 0.15,N¼51) but not in length due to their respective shapes. The prey items were purchased and do not occur in the natural environment ofL. 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 per- ception 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 200ll of hexane for 15 min. After removal, the solvent was evaporated for 1 min, and the animals were subsequently extracted with 200ll methanol in the same way. Finally, the samples were completely evaporated and dissolved in 20ll 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 280C, followed by automatic flow control at 1.0 ml/min with helium as the carrier gas. The oven program began isothermally at 120C for 2 min and then increased at a rate of 25C/min until 200C was reached, followed by a temperature ramp of 4C/min until the final temperature of 300C 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 Zophobasp. andGryllussp. 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 un- treated dummies were tested additionally as a control. Dum- mies 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

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a covariate only in the prey type experiment. All raids belong- ing 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 Eu- clidean 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 con- centration. 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,N¼101). As expected, the effect of prey type on

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 ¼0.012; 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,P¼ 0.007). The state of prey animals (dead or alive) had an additional unexpected effect on the size of raiding groups (NP-ANOVA,P¼0.023), 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 (P¼0.013) and a negative effect on contact time (P¼0.002).

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,N¼50). Larger groups were recruited to entire crickets compared with cricket legs, as expected for a collective strategy (NP-ANOVA,P¼0.007;

Figure 1C, left side). This happened as well for shorter contact durations, but this was only visible as a trend (NP- ANOVA, 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) ofL. diminutadependent 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).

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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,N¼100).

Chemical recognition cues

The 3 taxa investigated were well separated by CAP analysis according to their cuticular chemistry (Figure 3). Cross- validation 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 concentra- tions of cuticular chemicals and showed lower within group variation in chemical profiles than spiders.

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).

Reward experiment

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 (Fish- er’s test,P,0.001). Nevertheless, the decision to attack still had an influence on contact times (NP-ANOVA,P¼0.046).

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,Pweek¼0.005). Furthermore, there was an interaction between prey type and time (in weeks) on contact times (NP analysis of covariance,Pprey 3week¼ 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,N¼108).

DISCUSSION

Our results demonstrate a clear trade-off between collective and individual hunting inL. diminutathat follows the predic- tions 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 sig- nal depends on internal response thresholds of other ants Table 1

Comparison of attack frequencies ofL. diminutascouts dependent on different treatments

Experiment Treatment Attack No attack

Attack

ratio Pvalue

Prey type (alive) Cricket 12 13 0.5 0.579

Larvae 15 11 0.6

Prey type (dead) Cricket 10 15 0.4 0.259

Larvae 15 10 0.6

Prey size (cricket) Cricket 9 16 0.4 0.045

Cricket leg 17 8 0.7

Reward (learning phase)

Cricket 6 52 0.1 0.529

Larvae 4 55 0.1

Reward (test phase) Cricket 7 46 0.1 1.000

Larvae 8 47 0.1

Movement (cricket) No 22 28 0.4 ,0.001

Yes 39 11 0.8

Cricket: adultGryllussp. and Larvae:Zophobasp. larva.Pvalues of Fisher’s Exact tests are given. UncorrectedPvalues are reported because they result from independent experiments. Sample sizes result from ‘‘attack’’ and ‘‘no attack’’ frequencies.

0 0 2 40 60 80 100 120 140 160 180

2.5 2

1.5 1

0.5 0

Contact time (log)

Raindparty size

Figure 2

Size of recruited raid party ofL. diminutascouts 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.

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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 incorporat- ing variance between colonies as a random factor but focused on the reactions of individual scouts.

Adjustments of foraging strategies according to prey quan- tity, 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 thatL. 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,

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 (Ho¨lldobler 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. Charac- teristic prey chemical cues provide a conclusive answer. Be- cause 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 byL. diminutabecause raiding groups were recruited to

0 2 4 6 8 10 12 14

Larvae Cricket 0

20 40 60 80 100 120 140

Larvae Cricket Raid party (number of ants)

Contact time (of scout in sec.)

*

* (B)

25 Contact time (s)

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0 2 4 6 8 10 12 14 16 18 20

20 15 10 5 0

Day

Figure 4

Raiding behavior ofL. diminutaafter removal of experienced scouts.

(A) Changes in contact durations of scouts over a learning phase of 3 weeks dependent on prey type (cricket¼open diamonds and dashed line and larvae¼open rectangles and solid line). Due to scale adjustment of theyaxis, 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).

Figure 3

Left: CAP of cuticular chemicals in 3 abundant groups of L. diminuta prey arthropods.

‘‘Total’’ indicates the direction of increased total concentra- tions of all cuticular chemicals in the plot. Right:L. diminuta raid on a 6-mm glass dummy treated with cricket cuticular chemicals.

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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 pro- cedure, 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 avail- able crickets and beetle larvae).

Overall,L. diminutaexhibits 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).

REFERENCES

Anderson MJ. 2001. Permutation tests for univariate or multivariate analysis of variance and regression. Can J Fish Aquat Sci. 58:

626–639.

Anderson MJ, Gorley RN, Clarke KR. 2008. PERMANOVA1 for PRIMER: guide to software and statistical methods. Plymouth (UK):

PRIMER-E.

Anderson MJ, Willis TJ. 2003. Canonical analysis of principal coordinates: a useful method of constrained ordination for ecology. Ecol- ogy. 84:511–525.

Attygalle AB, Steghauskovac S, Ahmad VU, Maschwitz U, Vostrowsky O, Bestmann HJ. 1991. Cis-isogeraniol, a recruitment pheromone of the antLeptogenys diminuta. Naturwissenschaften. 78:90–92.

Attygalle AB, Vostrowsky O, Bestmann HJ, Steghaus-Kovac S, Maschwitz U. 1988. (3R,4S)-4-Methyl-3-heptanol, the trail pheromone of the ant Leptogenys diminuta. Naturwissenschaften. 75:

315–317.

de Biseau JC, Pasteels JM. 2000. Response thresholds to recruitment signals and the regulation of foraging intensity in the antMyrmica sabuleti(Hymenoptera: Formicidae). Behav Processes. 48:137–148.

Bonabeau E. 1998. Social insect colonies as complex adaptive systems.

Ecosystems. 1:437–443.

Bonser R, Wright PJ, Bament S, Chukwu UO. 1998. Optimal patch use by foraging workers ofLasius fuliginosus, L. nigerandMyrmica rugi- nodis. Ecol Entomol. 23:15–21.

Cerda X, Angulo E, Boulay R, Lenoir A. 2009. Individual and collective foraging decisions: a field study of worker recruitment in the gypsy antAphaenogaster senilis. Behav Ecol Sociobiol. 63:551–562.

Chaline N, Sandoz JC, Martin SJ, Ratnieks FLW, Jones GR. 2005.

Learning and discrimination of individual cuticular hydrocarbons by honeybees (Apis mellifera). Chem Senses. 30:327–335.

Chapuisat M, Keller L. 2002. Division of labour influences the rate of ageing in weaver ant workers. Proc R Soc Lond B Biol Sci. 269:

909–913.

Charnov EL. 1973. Optimal foraging: some theoretical explorations [PhD thesis]. [Seattle (WA)]: University of Washington.

Chittka L, Skorupski P, Raine NE. 2009. Speed–accuracy tradeoffs in animal decision making. Trends Ecol Evol. 24:400–407.

Choe D-H, Rust MK. 2006. Homopteran chemical signatures reduce aggression of tending ants. Oecologia. 16:175–178.

Conradt L, Roper TJ. 2003. Group decision-making in animals. Nature 421:155–158.

Conradt L, Roper TJ. 2005. Consensus decision making in animals.

Trends Ecol Evol. 20:449–456.

Costa-Leonardo AM, Casarin FE, Lima JT. 2009. Chemical communication in Isoptera. Neotrop Entomol. 38:1–6.

Couzin ID. 2009. Collective cognition in animal groups. Trends Cogn Sci. 13:36–43.

Detrain C, Deneubourg JL. 2002. Complexity of environment and parsimony of decision rules in insect societies. Biol Bull. 202:

268–274.

Detrain C, Deneubourg J-L, Pasteels JM. 1999. Decision-making in foraging by social insects. In: Detrain C, Deneubourg JL, Pasteels J, editors. Information processing in social insects. Basel (Switzerland): Birkhauser Verlag. p. 331–354.

Detrain C, Pasteels JM. 1991. Caste differences in behavioral thresholds as a basis for polyethism during food recruitment in the ant, Pheidole pallidula(Nyl.) (Hymenoptera: Myrmicinae). J Insect Behav.

4:157–176.

Dornhaus A, Franks NR. 2008. Individual and collective cognition in ants and other insects. Myrmecol News. 11:215–226.

Dukas R. 2008. Evolutionary biology of insect learning. Annu Rev Entomol. 53:145–160.

Dukas R. Forthcoming 2010. Social learning in insects. In: Breed MD, Moore J, editors. Encyclopedia of Animal Behavior. Elsevier.

Dupuy F, Sandoz JC, Giurfa M, Josens R. 2006. Individual olfactory learning inCamponotusants. Anim Behav. 72:1081–1091.

Franks NR, Dornhaus A, Fitzsimmons JP, Stevens M. 2003. Speed versus accuracy in collective decision making. Proc R Soc Lond B Biol Sci. 270:2457–2463.

Hefetz A. 2007. The evolution of hydrocarbon pheromone parsimony in ants (Hymenoptera: Formicidae)—interplay of colony odor uni- formity and odor idiosyncrasy. Myrmecol News. 10:59–68.

Helmy O, Jander R. 2003. Topochemical learning in black carpenter ants (Camponotus pennsylvanicus). Insectes Soc. 50:32–37.

Ho¨lldobler B, Wilson EO. 1990. The ants. Cambridge (MA): Belknap Press of Harvard University Press.

Howard RW, Blomquist GJ. 2005. Ecological, behavioral, and bio- chemical aspects of insect hydrocarbons. Annu Rev Entomol. 50:

371–393.

Jackson BD, Morgan ED. 1993. Insect chemical communication: pheromones and exocrine glands of ants. Chemoecology. 4:125–144.

Jackson DE, Chaline N. 2007. Modulation of pheromone trail strength with food quality in Pharaoh’s ant,Monomorium pharaonis. Anim Behav. 74:463–470.

Jaffe K. 1980. Theoretical analysis of the communication system for chemical mass recruitment in ants. J Theor Biol. 84:589–609.

Lucas C, Pho DB, Jallon JM, Fresneau D. 2005. Role of cuticular hydrocarbons in the chemical recognition between ant species in the Pachycondyla villosaspecies complex. J Insect Physiol. 51:1148–1157.

Mailleux AC, Deneubourg JL, Detrain C. 2000. How do ants assess food volume? Anim Behav. 59:1061–1069.

Maschwitz U, Steghaus-Kovac S. 1991. Individualismus versus Kooperation—Gegensa¨tzliche Jagd- und Rekrutierungsstrategien bei tropischen Ponerinen (Hymenoptera: Formicidae). Naturwis- senschaften. 78:103–113.

Morgan ED. 2008. Chemical sorcery for sociality: exocrine secretions of ants (Hymenotera: Formicidae). Myrmecol News. 11:79–90.

Pratt SC, Mallon EB, Sumpter DJT, Franks NR. 2002. Quorum sensing, recruitment, and collective decision-making during colony

(8)

emigration by the antLeptothorax albipennis. Behav Ecol Sociobiol. 52:

117–127.

Pyke GH. 1984. Optimal foraging theory: a critical review. Annu Rev Ecol Syst. 15:523–575.

Pyke GH, Pulliam HR, Charnov E. 1977. Optimal foraging: a selective review of theory and tests. Q Rev Biol. 52:137–154.

Reeve HK, Ho¨lldobler B. 2007. The emergence of a superorganism through intergroup competition. Proc Natl Acad Sci U S A. 104:

9736–9740.

Robinson GE. 1992. Regulation of division of labor in insect societies.

Annu Rev Entomol. 37:637–665.

Schatz B, Lachaud JP, Beugnon G. 1997. Graded recruitment and hunting strategies linked to prey weight and size in the ponerine antEctatomma ruidum. Behav Ecol Sociobiol. 40:337–349.

Steghaus-Kovac S. 1994. Wanderja¨ger im Regenwald—Lebensstrate- gien im Vergleich. O¨ kologie und Verhalten su¨dostasiatischer Amei- senarten der Gattung Leptogenys (Hymenoptera: Formicidae:

Ponerinae. [PhD dissertation]. [Frankfurt am Main (Germany)]:

J.W. Goethe—Universita¨t.

Steghaus-Kovac S, Maschwitz U. 1998. Niche differentiation in Malayan Leptogenys species (Formicidae: Ponerinae). Mittlg BFH.

190:135–138.

Steghaus-Kovac S, Maschwitz U, Attygalle AB, Frighetto RTS, Frighetto N, Vostrowsky O, Bestmann HJ. 1992. Trail-following responses of Leptogenys diminutato stereoisomers of 4-methyl-3-heptanol. Experi- entia. 48:690–694.

Theraulaz G, Bonabeau E, Deneubourg JL. 1998. Response threshold reinforcement and division of labour in insect societies. Proc R Soc Lond B Biol Sci. 265:327–332.

Vander Meer RK, Morel L. 1998. Nestmate recognition in ants. In: Vander Meer RK, Breed M, Winston M, Espelie KE, editors. Pheromone communication in social insects. Boulder (CO): Westview Press.

p. 79–103.

Visscher PK. 2007. Group decision making in nest-site selection among social insects. Annu Rev Entomol. 52:255–275.

West SA, Griffin AS, Gardner A. 2007. Social semantics: altruism, co- operation, mutualism, strong reciprocity and group selection. J Evol Biol. 20:415–432.

Wilson EO. 1990. Success and dominance in ecosystems: the case of the social insects. Excellence in ecology, 2. Oldendorf/Luhe (Germany): Ecology Institute.

Witte V. 2001. Organisation und steuerung des treiberameisenverhal- tens bei Su¨ dostasiatischen Ponerinen der GattungLeptogenys[PhD dissertation]. [Frankfurt/Main (Germany)]: J.W. Goethe-Universita¨t.