Behavioral Ecology doi:10.1093/beheco/arj024 Advance Access publication 7 December 2005
Collective detection in escape responses of temporary groups of Iberian green frogs Jose´ Martı´n,a Juan Jose´ Luque-Larena,b and Pilar Lo´peza Departamento de Ecologı´a Evolutiva, Museo Nacional de Ciencias Naturales, CSIC, Jose´ Gutie´rrez ´ rea de Zoologı´a, Departamento de Ciencias Agroforestales, Abascal 2, 28006 Madrid, Spain, and bA ETS Ingenierı´as Agrarias, Universidad de Valladolid, Campus La Yutera (Edificio E), Avda. de Madrid 44, 34004 Palencia, Spain
a
When confronted with a predator, prey are often in close proximity to conspecifics. This situation has generated several hypotheses regarding antipredator strategies adopted by individuals within groups of gregarious species, such as the ‘‘risk dilution,’’ ‘‘early detection,’’ or ‘‘collective detection’’ effects. However, whether short-term temporary aggregations of nongregarious animals are also influenced in their escape decisions by nearby conspecifics remains little explored. We simulated predator approaches to green frogs (Rana perezi) in the field while they were foraging at the edge of water, either alone or spatially aggregated in temporary clusters. ‘‘Flight initiation distances’’ of frogs (i.e., the distance between the simulated predator and the frog at the time it jumped) that escaped by jumping into the water were influenced by microhabitat variables (vegetation at the edge and in water and the initial distance of the frog to the closest water edge) and also by the responses of nearby individuals. In clusters, risk dilution did not influence the first individual to respond to the predator simulation or the average response of all frogs in the cluster as the frog’s responses were independent of group size. Also, flight initiation distances of individuals that first responded to the predator within clusters did not differ from those of solitary individuals, which is contrary to the predictions of the early detection hypothesis. However, the remaining frogs in the cluster had longer flight initiation distances than expected from the comparison with solitary individuals. We suggest that this pattern originated because the response of the first frog within a cluster triggered the sequential response of the remaining frogs in the cluster, which agrees with the expectations from the collective detection hypothesis. Our findings give insight into an early stage in the evolution of grouping as they suggest that individual frogs may benefit from being part of a cluster, even for short periods of time. Key words: antipredator behavior, collective detection, escape behavior, frogs, group-size effect. [Behav Ecol 17:222–226 (2006)]
heoretical models and empirical evidence suggest that prey should not flee immediately upon detecting an approaching predator but instead should adjust their escape response to minimize the costs of flight (Lima and Dill, 1990; Ydenberg and Dill, 1986). Predators do not always pose an immediate threat, and environmental variables may also affect risk perception (for a review see Stankowich and Blumstein, 2005). Consequently, the distance at which an animal starts to flee (flight initiation distance) should be the point where the costs of staying (i.e., predation risk) exceed the costs of fleeing (Ydenberg and Dill, 1986). In addition, when facing a predator, prey are often in close proximity of conspecifics that are also potential prey. In these circumstances, the escape decisions of a single individual may be strongly influenced by the behavior of other individuals. Escape responses of individuals within a group may differ from those of solitary individuals because of the risk dilution effect of a group (Hamilton, 1971; Roberts, 1996). When group size increases, individual risk decreases, and thus, individuals should delay escape behavior (e.g., Ferna´ndez-Juricic et al., 2002). Also, animals may rely on collective detection of a threat via other wary animals in the group (Creswell et al., 2000; Hilton et al., 1999; Lima, 1994). Furthermore, all group members may be alerted earlier to the presence of a predator by the response of the individual in the group that first detects the
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Address correspondence to J. Martı´n. E-mail: jose.martin@ mncn.csic.es. Received 6 July 2005; revised 25 October 2005; accepted 6 November 2005. The Author 2005. Published by Oxford University Press on behalf of the International Society for Behavioral Ecology. All rights reserved. For permissions, please e-mail:
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predator (early detection effect) (Pulliam, 1973; Vine, 1971). Although there are studies examining escape tactics of diverse prey types in groups, additional tests are needed to ascertain the generality of the responses to a wider range of prey species of different taxa. Also, it is useful to consider a larger variety of environmental conditions and social contexts. For example, the effect of being in a group on vigilance and other antipredator behaviors has been widely examined in social groups of gregarious birds and mammals (e.g., Beauchamp, 2003; Elgar, 1989; Quenette, 1990; Roberts, 1996). Yet, whether individuals participating in short-term temporary aggregations of nongregarious animals are also influenced in their escape behavior by nearby conspecifics, for example, when individuals are temporarily aggregated at locations favorable for foraging, remains little explored. We hypothesized that in such temporary aggregations, group size may have little effect because individuals might not be able to assess the number of group members easily, as this number may be changing continuously, or individuals might not be aware of the presence of nearby conspecifics. However, temporary group membership could still benefit individuals from early detection or collective detection effects. Many frogs and toads are predominantly aquatic but come to the water’s edge to forage on terrestrial invertebrates (e.g., Taigen and Pough, 1983). On land they are potential prey of many predators, such as birds, mammals, or snakes (Marchisin and Anderson, 1978; Martı´n and Lo´pez, 1990). Cryptic coloration, immobility, and crouching serve as primary defenses by helping prevent detection, but an active escape behavior is often needed (Gomes et al., 2002; Hayes, 1990; Licht, 1986; Marchisin and Anderson, 1978), particularly in species without toxic skin secretions (Williams et al., 2000). Many frog
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species have evolved morphological structures that allow them to escape by jumping into the water when a terrestrial predator approaches (Gans and Parsons, 1966). Some studies have compared the escape behavior of several species of frogs in relation to differences in morphology or habitat preference (Choi and Park, 1996; Hayes, 1990; Licht, 1986). However, factors that may cause intraspecific variation in the escape response remain largely unexplored (but see Rodrı´guezPrieto and Ferna´ndez-Juricic, 2005). Moreover, frogs are often found in short-term temporary foraging aggregations (clusters hereafter) at the edge of water bodies, but social or permanent cohesive bonds within these groups do not exist. Such clusters arise as a potentially fortuitous consequence of individuals foraging at the same favorable locations. This provides a good opportunity to test whether being in a temporary cluster still affects the escape behavior of frogs. In this paper, we examined the variation in the escape response of free-living green frogs (Rana perezi) foraging on land at the water shore to an approaching predator. By means of simulated predatory attacks, we compared the escape response of solitary individual frogs with the response of frogs when they were aggregated within clusters. We suggest that the decision to stop foraging and jump into the water should be affected by environmental factors that affect predation risk and also by the presence or the response of other individuals in a cluster. Thus, we specifically examined whether there was any group-size effect on escape decisions (risk dilution hypothesis) and/or whether the response of the first responding frog within a cluster affected the response of other members of the cluster (early detection and collective detection hypotheses). We predicted that the escape of the first individual might elicit a quicker escape response in other individuals (e.g., Cresswell, 1994; Hilton et al., 1999), even if they were further away from the predator, than would be expected if individuals were solitary. METHODS Study area The study area was located in ‘‘Campo Aza´lvaro’’ (Segovia and ´ vila provinces, Central Spain). The habitat consists of a mixA ture of grazed pastures, open grasslands, cultivated plots, and loose oak woodlands. The area is intersected by the Voltoya River, which has a large population of R . perezi. The diet of R . perezi includes mainly Diptera and other insects, which are caught by ambush foraging either floating on the water surface or on aquatic vegetation or sitting at the water’s edge (Hodar et al., 1990). Throughout this study, we recorded the presence of a relatively large number of potential predators of R. perezi in the area, including fish such as barbels (Barbus bocagei), two aquatic snakes (Natrix natrix, Natrix maura), mustelids such as otters (Lutra lutra) and polecats (Mustela putorius), and birds that often forage at the water edge and heavily prey on frogs, such as white storks (Ciconia ciconia), grey herons (Ardea cinerea), and black kites (Milvus migrans) (Martı´n and Lo´pez, 1990). Sampling procedure We recorded the escape responses of R . perezi to an approaching human simulating a predator throughout June 2002. In this month, weather conditions, including air temperature (about 25C on average), wind speed (15–20 km/h), solar radiation, and relative humidity (60% on average) were consistent over the study period and were optimal for green frogs’ activity. Thus, we avoided the potential effects of different environmental factors, such as temperature, on antipredator
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behavior of frogs (Gomes et al., 2002). Flowing water occurred in the study area at all times, although river broadness and depth varied slightly at a local level. Sampling was based on a continuous data collection procedure which involved the nonstop recording of frog responses for 2–3 h between 1100 and 1600 h, which corresponded with a daily period of high foraging activity of R . perezi (unpublished data), during consecutive days. We simulated predator approaches by walking slowly (approximately 45 m/min) parallel to river banks at 1 m from the water edge. This is comparable to the behavior of birds such as storks or herons that forage by moving slowly along the river bank. Because an approaching predator either real or, as in this case, simulated would stimulate a number of the prey’s sensory modalities (i.e., vision, hearing, vibration), it was not possible to determine the physiological mechanisms that prompt an escape response. Nevertheless, the structure of the river banks and environmental conditions were similar throughout the study period so that all frogs should be subjected to a similar combination of sensory stimuli. Moreover, our aim in this study was only to determine how behavioral responses varied among solitary individuals and clusters. The experimenter who simulated the predator recorded frog behavior using a video camera (Panasonic G100 NV-6100) with a wide-angle lens (Bower solarvision-super-wide AF 0.423, S. Bower, Inc., Long Island City, NY). We devised a strap system attached to the experimenter’s shoulders in order to maintain a constant height and orientation of the camera during video recording. This method allowed a wide vision of the river during sampling, while recording all fleeing animals from 300–350 cm perpendicular to the water’s edge up to 20 m in front of the observer. Pilot trials showed that the area covered by the camera was well beyond the range of distances at which R . perezi reacted to the approach. Both walking speed and orientation of the camera were constantly maintained, and all recordings were performed by the same person to reduce variation in the context surrounding data collection. To reduce pseudoreplication, we did not repeat sampling on the same river transects. At the end of the study a total of approximately 3.2 km of river bank containing frogs had been sampled. Given the high abundance of frogs, the probability of repeatedly sampling the same individual was low. We therefore treated all measurements as independent. We analyzed frog behavior from videotapes using a 25-inch monitor. To accurately measure the spatial scale of the recordings, we marked out a detailed grid of coordinates (5-cm divisions) on the surface of a wide flat area (approximately 6 m wide 3 35 m long) made of black concrete. We then recorded the grid following the same procedures (i.e., camera height and orientation) as during frog sampling. From still frames of the grid, we made an accurate template of scale references onto an acetate sheet fixed to the front of the monitor. We used this template to measure distances from the videotapes. During the analysis of videotapes, every time a single escaping frog was detected, we recorded the flight initiation distance (i.e., the distance between the simulated predator and the frog at the time it jumped). Escape decisions of prey have been shown to be affected by microhabitat structure (Cooper, 1998; Lima, 1990; Martı´n and Lo´pez, 2000) and distance to refuges (e.g., Bonenfant and Kramer, 1996; Dill and Houtman, 1989). Thus, we also determined (1) the initial distance of the fleeing individual to the closest water edge (considered as a refuge from a terrestrial predator) and (2) the presence or absence of vegetation cover on land at the water edge (which may affect the probability of being detected by the predator as well as the probability of detecting the predator) and/or in the water (which may affect how safe the refuge is). Vegetation found along the river banks showed a constant type and structure, consisting of one or two types of the
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commonest monocots in the area (Poa sp. and Bromus sp.) of approximately 10- to 15-cm height. This contrasted highly with areas without vegetation, which were composed of loose soil or highly grazed pastureland. Vegetation in the water consisted mainly of compact submerged and floating aquatic macrophyte Ranunculus sp. that covered large areas of water. We also extracted from the videotapes data relating to the escape response of individual frogs within foraging clusters. A ‘‘cluster’’ was considered to be at least three individuals, in close proximity (average distance between spatially consecutive frogs within a cluster, X 6 SE ¼ 140 6 17 cm, range ¼ 15–475 cm, n ¼ 67 pairs; maximum distance between individuals within a cluster, X 6 SE ¼ 326 6 45 cm, n ¼ 29 clusters). In contrast, solitary frogs were typically spaced at least 15–20 m to the nearest frog. Frogs within temporal clusters shared no social or cohesive bonds but were temporally aggregated at favorable locations. Thus, in defining clusters, we made no assumptions regarding whether individuals within a cluster interacted directly or were even aware of each other’s presence. We recorded the same set of variables for each cluster individual as recorded for solitary individuals (see above). Additionally, we recorded the number of individuals in the cluster, the duration of the complete cluster’s fleeing sequence, the distances between the individuals of the cluster, and the fleeing order of the individuals. After recording the fleeing responses, we ensured that all frogs within a cluster were detected by continuing the approach until reaching and passing the area where the cluster was originally located. Thus, we would have elicited the escape of any further frog that had not responded before. We also ensured that there were no additional frogs present for the next 15–20 m after the last frog of a given cluster. Data analyses To analyze the effects of group size on flight initiation distance, we used general linear modeling (GLM) (Crawley, 1993), including group size as a categorical variable (i.e., the number of frogs that formed a group, ranging from three to five frogs) and microhabitat characteristics (vegetation at the edge and in water and the initial distance of the frog to the closest water edge) as continuous variables. We also used GLM to analyze the relationships between flight initiation distances, microhabitat variables, and the effect of being in a cluster as a categorical variable (alone versus cluster). To determine whether the effects of microhabitat differed as a function of being in a cluster, we included in the GLM the interactions between cluster effect and microhabitat variables. We also used GLM to compare the responses of individuals within a cluster (within factor). To determine whether the effect of microhabitat variables (between factors) differed as a function of order of response, we included in these models the two-way interactions between order and each microhabitat variable. Previous analyses showed that in all cases three-way interactions were not significant, and thus, we did not include them in the final models. Data were log transformed to ensure normality (Shapiro-Wilk tests). Tests of homogeneity of variance (Levene’s test) showed that in all cases variances were not significantly heterogeneous (all p . .15) after transformation. All statistical tests were two tailed, and we used p , .05 as the significance criterion.
Table 1 Results of GLM comparing flight initiation distances of solitary frogs versus that of the first responding frog in a cluster, or versus the average response of all individuals in a cluster, and considering the effects of the presence of vegetation cover on land at the water edge and in the water body and the distance from the initial position of the frog to the water edge Solitary versus first frog in cluster
Solitary versus cluster average
Factor
F
p
F
p
Solitary versus cluster Vegetation on land Vegetation in water Distance to water Cluster 3 vegetation on land Cluster 3 vegetation in water Cluster 3 distance
0.82 30.40 50.95 27.62 0.34 3.76 0.86
.36 .0001 .0001 .0001 .56 .05 .35
17.54 15.76 52.13 32.20 4.86 3.31 0.69
.0001 .0001 .0001 .0001 .029 .071 .41
Degrees of freedom are 1,151 in all cases.
initiation distance of the first responding frog (group-size effect: F2,23 ¼ 0.43, p ¼ .65) or the average flight initiation distance of all the frogs in the cluster (F2,23 ¼ 0.61, p ¼ .55). When comparing the responses of solitary individuals with that of the first responding frog in a cluster, we found that variability in the flight initiation distance allowed by frogs was explained by several microhabitat variables (GLM, R2 ¼ .75, F7,151 ¼ 64.59, p , .0001; Table 1). Thus, flight initiation distance was significantly and positively related to the initial distance of the frog to the closest water edge, and frogs allowed significantly closer flight initiation distances when they were sitting at the water edge with abundant vegetation or when there was submerged and floating vegetation in the water. However, flight initiation distances of the first frogs responding in the clusters were not significantly different from those of solitary individuals (Figure 1). The interactions of habitat factors with the effects of being solitary or in clusters were not significant, although the interaction between
RESULTS Contrary to expectations from the risk dilution effect hypothesis, the number of frogs found within a cluster, after removing the effects of variation due to microhabitat variables (GLM, p , .01 in all cases), did not influence either the flight
Figure 1 Flight initiation distances (X 6 1 SE) of solitary individual green frogs and individuals in clusters depending on the temporal order of their fleeing response within the cluster.
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Figure 2 Effects of the presence of vegetation cover on land at the water edge on flight initiation distances (X 6 1 SE) of solitary green frogs and on average response of all individuals within a cluster.
cluster effect and aquatic vegetation approached significance (Table 1). In contrast, when comparing the response of solitary individuals with the average flight initiation distances of all individuals in a cluster, variability in flight initiation distances was explained by several microhabitat variables as above (GLM, R2 ¼ .76, F7,151 ¼ 66.95, p , .0001; Table 1), but average flight initiation distances of frogs in a cluster were significantly longer than those of solitary individuals (Figure 1). In addition, there was a significant interaction between being in a cluster and the presence of vegetation on land (Figure 2). Thus, solitary frogs decreased significantly flight initiation distances when there was no vegetation on land (Tukey’s test, p , .0001), but this effect only approached significance in clusters (p ¼ .07). Similarly, the interaction between the cluster effect and aquatic vegetation presence approached significance. Moreover, the effect of being in a cluster on the escape response was also supported by the results of a GLM comparing the first four frogs responding within a cluster. Thus, after removing the effect of distance to the edge (F1,25 ¼ 11.62, p ¼ .002), flight initiation distances of the successive frogs responding within a cluster increased successively (within factor: F3,75 ¼ 41.77, p , .0001) (Figure 1). Also, although vegetation at the edge did not affect overall flight initiation distances of the cluster (F1,25 ¼ 0.21, p ¼ .65), its influence depended on the response order within the cluster (interaction effect: F3,75 ¼ 2.97, p ¼ .04). Thus, the first responding frogs allowed significantly shorter flight initiation distances when there was vegetation at the water edge compared to when vegetation was absent (Tukey’s test, p ¼ .02). In contrast, for successive responding frogs, vegetation at the water’s edge did not significantly affect their responses (p . .60 in all cases). Vegetation in the water, however, resulted in significantly shorter flight initiation distances for all individuals (F1,25 ¼ 18.40, p ¼ .0002), independently of order of jumping (interaction: F3,75 ¼ 1.63, p ¼ .19). DISCUSSION This study shows that the escape responses of frogs are not fixed but are influenced by microhabitat variables and also by the response of other individuals when in clusters. This variability suggests that frogs may assess the risks associated with different situations and respond accordingly. This risk assessment would allow frogs to adjust their escape response, min-
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imizing costs of flight, such as interruption of foraging (Cooper, 2000; Ydenberg and Dill, 1986). Microhabitat characteristics, especially microhabitat cover, have been identified as important factors determining risk assessment by prey. Generally, more cover is associated with greater protection against detection by predators, although in some cases cover is obstructive when it may hide predators (Blumstein and Daniel, 2002; Lima and Dill, 1990). Prey that forage in covered microhabitats tend to respond to a predator later than prey that forage in the open (Ferna´ndez-Juricic et al., 2002; Martı´n and Lo´pez, 2000). In our study, frogs sitting in vegetated edges escaped later as they were probably using a sit-and-wait strategy, remaining for long periods immobile and cryptic, due to their green or brown skin coloration. A similar situation has been found in other animals that rely initially on crypsis to elude predators, such as other frog species (Marchisin and Anderson, 1978) or chameleons (Cuadrado et al., 2001). Water could be considered as a relatively safe refuge to frogs, at least against most terrestrial and aerial predators, which is supported by the positive relationship between the distance of frogs to the water edge and the flight initiation distance. As the risk of capture is higher for prey that are farther from a refuge, the flight initiation distance should increase with the distance to the refuge. A similar relationship has been found in many terrestrial animals that use safe refuges (Bonenfant and Kramer, 1996; Dill and Houtman, 1989). However, water may not be a completely safe refuge against all predators, and the effect of aquatic vegetation on escape behavior suggests that it provides a more effective refuge than water alone. Vegetation in water may enable frogs to hide more effectively after jumping into the water, if pursued by a predator. In other animals, foraging in groups may reduce predation due to the risk dilution effect (Hamilton, 1971; Roberts, 1996). This may affect the escape decisions of animals within a group, which should tolerate closer predator approaches, as individual risk is reduced with increasing size of the group (Ferna´ndez-Juricic et al., 2002). However, in our study cluster size did not influence the flight initiation distance of green frogs within the cluster, and the escape response of the first frog responding in a cluster did not differ from the response of solitary individuals. Moreover, other frogs in the cluster escaped at greater flight initiation distances when compared to solitary individuals. Thus, frogs did not seem to perceive that the presence of nearby conspecifics could decrease predation risk, or, perhaps, frogs were not aware of the presence of conspecifics. However, our results do suggest that the escape response of frogs within clusters may be affected by the decisions of other frogs. After the first frog escaped, the other nearby frogs escaped at greater flight initiation distances than expected if they were alone. This was probably because the escape response of the first frog triggered the escape response of other frogs in the cluster. The possibility of cooperative collective detection of the approaching predator (Hilton et al., 1999; Lima, 1994) seems unlikely in these loosely cohesive and temporary clusters of foraging frogs. The consequences for the frogs in temporary clusters may be, however, similar to those for other animals forming long-term groups. The changes in the escape response of frogs may be explained by the sound or sight of a nearby frog entering the water. This may represent a sudden increase in risk to other frogs, which would be required to increase their own flight initiation distance (i.e., decreasing their own response delay). Therefore, individuals in clusters may benefit by being alerted to prospective risk by the escape response of the first individual, which would be similar to what is observed in more stable groups (Creswell et al., 2000; Hilton et al., 1999; Lima and Bednekoff, 1999).
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The occurrence of this collective detection effect in frogs may also be supported by the low effect of vegetation at the water edge and distance to water on the average flight initiation distance allowed by frogs in clusters, in contrast to the strong effect of vegetation and distance on escape decisions of the first responding frog within a cluster or solitary individuals. If risk, or the knowledge of actual risk level, increases after the first frog has jumped (i.e., the predator has already detected a hidden frog), then the potential advantages of relying on immobility and/or crypsis to remain undetected would be reduced. After the predator has already detected a frog, the probability that other nearby frogs have also been detected, or a magnification of the predator’s searching behavior, may also increase, which would require a quicker escape response than for a solitary frog. Similarly, the distance to a safe refuge would not be important after risk has increased over the potential benefits of remaining without escaping. In contrast, we found no evidence to support an early detection effect. The model of Pulliam (1973) predicts that a predator will be detected earlier in larger groups because the probability that any one individual will be vigilant or paying attention at any one time increases with group size. Therefore, a solitary frog should have a shorter escape initiation distance than the first frog to respond in a group. However, we found that the first frog to jump in a group had a flight initiation distance similar to that of a solitary frog. We conclude that green frogs adjust their escape response to microhabitat conditions but also seem to be affected by the escape responses of other nearby individuals, when deciding their own escape responses. Being in clusters, although in many cases is just a fortuitous consequence of short-term temporary aggregations, may still benefit individuals because the escape response of one individual alerts others in the cluster to the presence of a predator, which agrees with the collective detection hypothesis. Therefore, this study may give us an insight into an early stage in the evolution of grouping. There will be initial selection for collective detection, but animals at an early stage of grouping may not have evolved the means to assess the implications of group size. Only as the system becomes more efficient can early detection benefits accrue, and selection can operate on individuals to perceive this and to start trade-offs that can occur because of the risk dilution effect. We thank D. Blumstein and J. Hare for helpful comments, A. Bauer for kindly providing useful bibliography on frog’s behavior, and A. Douglas for improving the English. We also thank ‘‘El Ventorrillo’’ Museo Nacional de Ciencias Naturales Field Station for the use of their facilities. Financial support was provided to J.M. and P.L. by the Ministerio de Ciencia y Technologia project BOS 2002-00547. The experiments complied with current Spanish law.
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