Collective anti-predatory behaviour in animals groups
Gregory M. Kohn
Utrecht University, Neuroscience and Cognition Masters, Track: Beahvioural
Neuroscience
Supervisor:
Claudio Carere
Dipartimento di Scienze Ambientali
Università degli Studi della Tuscia
Largo dell'Università s.n.c.
01100 Viterbo
Italy
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Summary
The collective behaviour of animal groups serves to reduce the risk of predation
to individuals. By joining a group individuals remain in close proximity to others which
reduces the risk of predation. Groups can also afford benefits by allowing for early
detection of predators. During predatory attacks groups may confuse or deter predators
by making it difficult for single individuals to be targeted. The mechanisms underlying
many aspects of collective behaviour in response to predation are not well known. Here
we review the models and studies of collective responses to predation and propose some
underlying mechanisms for collective detection, evasion and communication about
predators. In foraging flocks collective detection benefits individuals by providing them
earlier detection of predators then when alone. Vigilance behaviour of neighboring
individuals is copied. The amount of individuals displaying vigilant behaviour reaches a
threshold level where the group initiates escape behaviors. Therefore predators raise
vigilance levels and allow individuals to detect and escape predation earlier. Predators
also attack free flying or free swimming groups. Here information about the location fo
the predator may be spread through agitation wave. These waves of changing density
have been shown the orient individual group members towards the location of the
predator. These waves may also serve to confuse a predation attempt by making it harder
for a predator to single out an individual within the group. Often prey species possess
highly reflective feather or scale which reflect waves of light during agitation wave
propagation, which may in turn further the confusion effect. In addition to performing
waves free flying / swimming groups also exhibit consistent flocking patterns. These
patterns have been shown reflect the level of predation risk experienced at certain areas.
It is possible that flocking patterns represent honest signals of environmental conditions
and may therefore serve as communication becons to other groups. Findings that
neighboring groups tend to copy flocking patterns lends some support for this, albeit its
mechanisms are unknown. However all aspects of collective behaviour involve groups
moving and making decisions as a coordinated whole. Collective anti-predatory
behaviour could be caused through individual threshold responses leading feeding back
to collective group level behavior. In all situations individual responses to the presence or
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attack of a predator reaches a certain level when positive feedback , through coping
neighboring behaviors, spreads this behaviour through the entire group. This process
allows groups to make informed and accurate decision when detecting, evading and
communicating about predators.
1. Introduction
From the synchrony of a flying flock of starlings (Sturnus vulgaris), to the vast
schools of herring (Clupea harengus) in the open ocean, to the migration of wildebeest
(Connochaetes taurinus) herds across the Serengeti, the collective behaviour of animals
has always had the power to captivate man’s imagination. So compelling was the
movement of bird flocks that the ancient Romans once saw it as proclaiming the will of
the gods (Zimmer 2007). Until very recently it was also thought that flocking and
schooling patterns were the result of some underlying psychic abilities of animals, not yet
comprehensible to man (Long 2005). Although long misunderstood in antiquity, today
collective animal behaviour has become a serious field of scientific investigation.
Researchers are now beginning to delve into the mysteries which surround the collective
movement of animal groups. Studies have shown that it is inter-individual interactions,
and not psychic ability, which determines and guides collective behavior. While research
into collective behaviour has yielded impressive results about the mechanisms involved
in collective decision making and movement, it has remained somewhat distinct from
other areas of behavioral biology. The incorporation of empirical studies and models of
collective behaviour with other well studied areas of behavioral ecology and ethology,
such as predator avoidance, will help enrich our knowledge of how social animals
respond to environmental obstacles. This paper will review the mechanisms which
animals employ in order to detect, evade and communicate about predators collectively.
In order for any collective behaviour to occur animals must form and maintain
groups. Being part of a group itself poses certain advantages and disadvantages in
contrast to being solitary. It is widely assumed that the main benefit for being in a group
is protection from predation (Hamilton 1971) which is the central focus of this review.
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There are many different theories about the advantages which groups provide in reducing
the risk of predation. The first and most intuitive reason to join a group is to increase the
number of potential targets surrounding you, therefore decreasing the individual
probability of being taken by predator. This is know as the dilution effect, and is seen as
the basic factor moving most animals into groups (Wrona and Dixon 1991). Arranging
into groups may also decrease the probability of encountering predators as more
individuals will inhabit a limited spatial area then if individuals were more widespread
and solitary (Zoratto et al., 2009). One example of a species utilizing the dilution effect
can be seen in the parental care behaviour of ostriches (Struthio camelus). Ostriches have
been know to actively adopt other juveniles into there brood. For a long time this
apparently altruistic act was not well understood. A study by (Bertram 1992) found that
raising precotial ostrich chicks was nearly cost free for the adults, and adoption therefore
benefited parents own offspring by decreasing the predation risk. It was also found that
individuals who adopted more offspring enjoyed a higher reproductive success. The
dilution effect can also be seen in the mass breeding swarms of certain insects. Cicadas
(genus Magicicada) for instance often have a biological cycle of about 17 years where all
individuals in the population will hatch and breed synchronously. Other species such as
wildebeest form huge annual aggregations when breeding and migrating. Therefore, the
dilution effect can also be applied temporally as well as spatially to avoid predation. In
order for the dilution effect to be functional individuals must maintain group cohesion in
response to a predator in many situations.
While simply being part of a group confers some advantages in reducing the
predation risk not all individuals share these benefits equally. Spatial position within the
group may also determine the level of risk individuals experience. Individuals at the
periphery of the group are likely to experience a higher predation risk then individuals
who are within the center of the group. The “selfish heard” theory posits that there will be
individual competition within the group to gain a favorable position. Therefore as
Hamilton (1971) put it is the, “selfish avoidance of a predator that can lead to
aggregation”. Many predators will try to single out an individual at the periphery of a
group to direct their attack. Groups arise as individual try to obtain a more central
position in response to an attack. Thus in the “selfish heard” theory individuals try to
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maximize the risk-dilution effect with larger groups offering bigger advantages However
large groups have also been shown to increase the attention of predators (Pulliam 1973).
One potential difficulty of the selfish herd theory is that individuals at the margins of the
group may experience greater risk while in a group (because of the increased attention
from predators) then when outside the group (Pulliam 1973). Therefore groups may be
very unstable and may break apart easily. While the selfish heard theory may be a large
factor in motivating individuals to form groups other benefits may be necessary in order
to maintain group cohesion. Models of the selfish herd theory often do not include these
other potential benefits such as the early detection of predators.
Living in a group may confer an advantage in detecting predators. The “manyeyes” theory posits that the presence of many individuals increases the probability of
detecting a predator earlier. Many studies have provided examples that groups tend to
detect and evade predators sooner then singular individuals. For instance Kenward (1978)
used trained goshawks (Accipiter gentilis) to attack groups of pigeons (Columba livia) (of
differing sizes) as well as single individuals. It was shown that risk of mortality was
greatest in singular doves and increased as group size decreased. Within larger groups the
probability of an individual detecting a predator in close proximity is much higher then in
smaller groups or when single. Therefore by joining a group, individuals will decrease
the chances of becoming a victim of predation, as they are more likely to respond to the
presence of a predator earlier. The ability for groups to detect predators earlier could be
factor maintaining group integrity even when a predator is not immediately present. In
order for the many-eyes theory to be effective however individuals in the group need to
share information and coordinate escape response together. Later we look at the
mechanisms which animal groups utilize in collective detection, mainly how information
of the predator spreads throughout the group.
The collective behaviour of animal groups may also serve as a means of actively
deterring predatory attacks. Many studies have shown that predators are attracted to
larger groups but actually experience a lower success rate in comparison to attacking
singular individuals. This apparent contradiction may be explained by the groups
deterring predation attempts through coordinated movements. The ability of groups to
deter or “confuse” predators when attacking has been called the confusion effect. The
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confusion effect is based on the assumption that it is easier for a predator to target a
single individual when it is not surrounded by conspecifics. Cresswell (1994) looked at
the success of predatory attacks after the predator had targeted a specific individual
within the group (called “open attacks). These open attacks predators were seen as more
vulnerable to the confusion effect. Surprise attacks also occurred where predators did not
target a single individual within the group and would be less vulnerable to the confusion
effect. As group size increased though both attacks elicited less successful captures then
when attacking smaller flocks. This suggests that the presence of more individuals can
somehow defect or deter predatory attacks. Krause and Godin looked at the preferences
of Acara cichlid fish (Aequiden pulcher) when attacking shoals of guppies (Poecilia
reticulate) of different sizes. Groups of different size were presented to the Acara cichlid
which demonstrated a preference for attacking larger groups, but only if they exhibited
more movement then smaller groups. Consequently, it seems that larger groups are more
conspicuous, and it was this that caused the increased attraction. If smaller groups were
experimentally manipulated to increase movement they were more also attractive to
predator. Despite the increased attraction to larger groups predation success decreased as
the size of the shoal increased. This also suggests that fish have some collective
mechanism for deterring predation attempts. When large flocks of birds or schools of fish
initiate escape maneuvers in response to a predator it can be difficult for a predator to
maintain its focus on a single individual. Later we considers the mechanisms which
groups use in order to deter predatory attacks through coordinated group movements
(especially through cascading waves of changing density within a group). Information
about the presence of a predator must be transferred throughout the group in order to
initiate evasive maneuvers. The mechanisms which information about predators spreads
in free flying/swimming groups, and its relation to deterring predation success, is
discussed in detail later.
Here we outlined the basic theories looking at the benefits groups confer in order
to protect individuals from predation. For every theory presented groups must maintain
cohesion and behave collectively in order to garner the benefits of group living. This
means that individuals must be able to spread information between individuals and
coordinate behaviour appropriately as a group. Here we review the mechanisms which
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groups utilize in detecting, evading and communicating about predation. In order to get a
bottom up picture of these mechanisms you must be able to measure and predict the
movement of the individual group members. Previously this has been constrained to
computer models which create hypothetical groups. These models have attempted to
uncover the mechanisms behind collective behaviour from the level of the individual
interactions (Conradt and Roper 2005). Here individuals within a group are given
(programmed) with certain rules that determine their interactions with other individuals.
These inter-individual interactions then have cascading influences into the collective
behaviour of the group. Changing the rules of social interaction may lead to changes in
the overall group behavior. While few of these models have specifically dealt with group
response to predation their assumptions on group behaviour are may help in
understanding collective responses to predation. Bird flocks and fish schools are some of
the most studied model system in collective and behaviour and exhibit a coordinated and
synchronous response to the behaviour of a predatory agent. The difficulty in capturing
films of animal groups in three dimensions was a large impediment to looking at group
behaviour in the field. Recently though techniques have become available that allow for
tracking whole groups in three dimensions, as well as each individual within the group
(Cavagna et al 2008). These techniques involve taking fast sequential images of a moving
group in three dimensions, and using computer analysis to look at interactions between
individuals. These procedures allow for a real time reconstruction of actual flocking
patterns within a virtual environment where they can be explored in greater detail for the
causal inter-individual mechanisms behind flocking behavior. Ballernini et al (2008) was
able to capture the movement of starlings engaging in aerial displays and then analyze the
basic movement of the flock, along with each individual.
Here we seek to review the empirical studies and theoretical models of collective
behavior, and integrate it within the frame work of predator detection, avoidance and
communication. We also clarify and uncover some mechanisms operating within
collective anti-predatory behaviour. This review will follow by investigating: (1) The
mechanisms of collective predator detection, or how information about the presence of a
predator spreads throughout the group initiating evasive action. (2) The mechanisms of
predator evasion, or how groups actively avoid or deter a predator from attacking. (3) The
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mechanisms of collective communication between animal groups about the presence of a
predator. (4) The common mechanisms which groups utilize to be able to make decisions
together in response to a predator. Here we will integrate empirical research looking at
the actual behaviour of animal groups with computer models to infer for common
mechanism in collective detection, response and communication of predators.
Collective predator detection: Vigilance and social information
Many studies have tried to quantify the amount of time which individuals spend
looking out for predators, or being vigilant, in contrast to time spent in other activities
such as foraging. Individuals within a group will likely face a tradeoff between
maximizing foraging benefits and maintaining vigilance (Bednekoff and Lima 1998).
Time spent feeding may leave an individual more vulnerable to predation, yet time spent
looking out for predators will take away from time spent feeding. In field studies on bird
flocks individuals are said to be foraging when their head is oriented towards the ground
and vigilant (scanning) when the head is raised and the bird in an upright posture.
Vigilance has been much harder to quantify in fish schools (Lima and Bednekoff 1999),
but some studies have shown that fish tend to feed more when the perceived risk of
predation is lower (Ryer & Olla 1991). This suggests that vigilance, in the form of
scanning, may also be present in fish but much harder to quantify. Some of the earliest
efforts to look at group protection from predation assumed that individuals joined groups
to place individuals physically in-between themselves and a predatory attack, creating a
selfish herd (Williams 1966). Models that tried to document the mechanisms of this
selfish herd found that they were not stable (Pulliam 1973). Individuals at the group
margins tended to have higher predation levels and were more inclined to depart. A large
group would also likely attract the attention of more predators, and these marginal
individuals would face less predation by foraging alone then on the periphery of the
group. In order for groups to be stable other factors needed to be considered then just
obstructing a predatory attack, like the early detection of predators. Pulliam (1973)
created a model that looked at the dynamics of predator detection in bird flocks. His
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model incorporated ideas from the “many-eyes” theory and assumed that when a predator
is detected this information would spread throughout the group. This would in turn cause
individuals to coordinate evasive action with larger groups better at detecting predators
then smaller groups. Within the model only a single individual was needed to spot the
predator in order to move the group to collective evasion. Pulliam did not consider the
costs of foraging together and the dilution effect in his model which led it to some
criticism. The collective vigilance behaviour of groups is highly unpredictable, and likely
influenced by a multitude of confounding factors (Bedenkoff & Lima 1998). For instance
Pulliams model assumes that the spread of information about a predator and evasive
action is instantaneous and perfect. However, it has been shown that the individual who
detects the predator may gain an advantage in avoiding predation over neighboring
conspecifics (Lima 1995). While detectors can initiate evasive behaviour almost
instantaneously, others have to interpret and respond to the behaviour of neighbors before
taking evasive action. This leaves them at a disadvantage because it takes longer for them
to initiate evasive action in contrast to neighbors who originally detected the predator.
The dilution effect is thus likely to interact (and potentially conflict) with collective
detection and influence the vigilance levels in the group (Bednekoff & Lima 1998).
Group living also carries costs as individual may compete for resources which will in turn
influence the levels of vigilance. Scramble competition with neighboring conspecifics
will be intensified if food levels on a foraging patch are low. The levels of vigilance are
likely to be a result of the relative differences in the costs and benefits. They will also be
influenced by environmental conditions, group composition and individual dispositions.
Despite the potential costs it is certainly advantageous to form foraging flocks in many
situations as they are relatively common in numerous species. In these situations the
benefits from the dilution effect and collective predator detection likely outweigh the
costs of foraging alone in many circumstances.
In order to understand the benefits of early predator detection there must be some
understanding of the mechanisms underlying it. One common assumption of antipredatory vigilance models is that once a predator has been detected this information will
spread throughout the group with other individuals responding appropriately. Social
information, or information gathered by observing others interacting with the
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environment, is thus key to understanding predator detection in groups of animals. There
have been numerous theoretical attempts to investigate the mechanisms and factors
influencing the amount of time spent scanning. Sirot (2006) for instance modeled the
influence of social information on vigilance behaviour in flocks. She found that the
perception of predatory risk was determined by the levels of vigilance within the group.
Initially individual vigilance is a rather stochastic process with birds raising there heads
and scanning at seemingly random intervals. Flocks with initially low levels of vigilance
will tend to move to a more relaxed feeding behaviour whereas groups with higher initial
vigilance levels will slowly rise in vigilance until a threshold is reached where the group
takes off. A potential cost of this strategy is that flocks may create “imaginary” predators
when vigilance levels reach a threshold, causing birds to exhibit evasive behaviour in
absence of any real threat. These models show a high similarity to the quorum decision
making seen in many species of fish (Ward et al. 2008). Vigilance levels tends to reach a
threshold capacity which then creates a positive feedback response where the group takes
evasive action by leaving the forging patch. Application of models of self-organization
could further research on predatory vigilance. For instance, studies on the emergence of
leadership often document that knowledgeable individuals, or ‘leaders’ often coordinate
there behaviour more then other and thus could lower the threshold needed for evasive
action. Birds with more knowledge about a certain area could thus serve as initiations of
appropriate responses to predation threat. In areas where the predation threat is high
knowledgeable individuals may display more scanning making the group more likely to
take evasive behaviour then in areas where predation is low and individuals are more
relaxed.
Attention to the behaviour of others is an import determinant of group level
vigilance. Empirical studies have also explored the social influences and transmission of
vigilance within a group. Bekoff (1995) investigated flocks of evening grosbeaks
(Coccothraustes uespertinus) and found that they maintained flock positions which
facilitated information gathering between individuals. When groups were arranged in a
line, where neighboring individual blocks visual inspection of other conspecifics, they
were characterized by being more vigilant and less coordination in scanning behaviour
then when arranged in a circular pattern. The assumption is that a circular pattern
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facilitates social information transfer within the group because there is less visual
obstruction then in a linear group patter. Fernández-Juricic and Kacelnik (2008)
investigated the mechanisms of information transfer in small flock of three starlings.
Three birds were lined up in a field with each bird placed in a bottomless cage (to be
allowed to forage in the grass). The middle bird was designated as the ‘receiver’ which
gained social information from the two distal birds or ‘senders’. It was shown that
receiving birds tended to copy the scanning and foraging behaviour of conspecifics when
they were in close proximity. Receivers also directed there scanning toward the senders
more often when their behaviour differed from previously determined baseline levels.
Increasing the distance between individuals decreased the fidelity of social information
transfer. ‘Receivers’ coordinated their behaviour less with the ‘senders’ with increased
distance All these studies suggest that information regarding the presence of a predator
could be spread throughout a group by monitoring the vigilance of conspecifics. Higher
levels of vigilance also tend to be reinforcing moving neighboring individuals to become
more vigilant as well. When a predator is spotted information initially flows to near
neighbors from the detector and quickly expands from the epicenter until threshold is
reached and group flies away. By integrating and testing the assumptions of vigilance
models in relation to the transmission of social information we can better understand the
mechanisms of collective detection (Lima 1995). This may also help explain some
ambiguities seen in some models. For instance some models predict that detection of
predator by single individual may increase the predation risk of neighboring individuals,
who must interpret the cues and respond to ‘detectors’, before initializing evasive action
(Bedenkoff & Lima 1998). Through investigating the benefits of collective detection and
social information use in contrast to the costs of increased predation risk associated with
‘detectors’, you may better predict the circumstances when social foraging is
advantageous. However predators can also pose risks to groups of animals while they are
in flight. In the next section we look at how flocks and school avoid predatory attacks
once the decision to take evasion action is implemented.
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Collective predator evasion: Waves of Agitation
Tinbergen (1951) was among the first to describe the twisting and turning
movement of starling flocks above their roosting areas. Since then many studies have
looked at both the mechanisms involved in creating these intriguing collective displays
(Couzin and Krause 2003). Comparatively fewer studies have investigated collective
behaviour when groups are under direct predation However the minority of studies
investigating collective responses to predation have documented certain group behaviors
which may serve to inform groups on the position of the predator and deter predation
through utilizing the confusion effect. For instance Michaelsen & Byrkjedal (2001)
looked at the flocking patterns in groups of shorebirds in response to different predatory
attacks. Predatory attacks were classifed as dives, pursuits or surprise-attacks. Flocks of
Dunlins (Calidris alpina) and Common Ringed Plovers (Charadrius hiaticula) formed
highly cohesive flocks when a predator was detected. The shape, pattern, and group
composition were measured from video recordings to create a “collective” ethogram.
Flocks exhibited a characteristic structure of flying low over the water in response to the
presence of a predator in a cohesive ‘magic carpet’ like fashion. Their shape tended to be
elongate with only a single layer of birds, thus giving the appearance of a carpet when in
flight. The main predatory species of these flocks were Peregrine Falcons (Falco
peregrinus), which often engage in diving attacks. The group formation served to prevent
these attacks as they would not allow a falcon enough stalling time in order to avoid
contact with the water. Because the falcon risks becoming waterlogged it often had to
employ different hunting techniques, such as pursuing prey horizontally, which have a
lower success rate then dives. The density of the group was higher in the anterior then in
the posterior where a large amount of attacks were directed. Descriptions of group flight
maneuvers under predation are sparse, despite their apparent relevance to evading
predation attempts. The descriptions that exist though suggest some common
mechanisms which groups use to coordinate their movement in order confuse the
predator..
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While many studies and models have addressed predation threat in foraging
aggregations comparatively fewer studies have addressed interactions with predators in
free flying or swimming groups. In the previous section we documented that flocks
initiate evasive action once a certain number of individuals exhibit vigilant behavior.
While foraging on the ground it has been shown that certain group configurations lower
the amount of visual obstruction that neighboring individuals impose and facilitate
information flow between conspecifics (Bekoff 1995). Being able to interact with
multiple individuals in three dimensions could help better coordinate movements and
collective decisions then when on ground where more visual obstructions and limited
interactions (Ballerini, et al. 2008). Evasive maneuvers in response to predation also
often occur in three dimensions. Nonetheless, this makes it quantitatively much harder to
look at the local interactions governing evasive behaviour in large flocks and schools. In
three dimensions there are more avenues for interaction to occur then when foraging on
the ground. This also means that different mechanisms may apply when social
information is transferred throughout the group. For instance in foraging groups the
quality of information received is a function of the metric distance of conspecifics
(Fernández-Juricic and Kacelnik 2008). Increased distance from neighbors decreases the
quality of information being transferred between individuals. In free flying groups the
relationship may be much different. Ballerini et al (2008) filmed and reconstructed flocks
in three dimensions to look at the local rules governing collective behavior. They found
that individual birds tend to consistently align themselves with around six to seven birds
at a time [other experiments looking at numerical abilities of birds often suggests that
many species can accurately distinguish up to seven units (Pepperberg 2006) ]. This
alignment was also not entirely dependent on the metric distance of neighboring
individuals. A focal individual would orient him/herself in a way that the closest nearest
neighbors would be located at the sides of the individuals. This could be to free up flying
space ahead of the bird, or it could be that birds have anisotrophic vision (visual system
with eyes located on the sides of the head). Therefore topological orientation, or how
many individuals you keep within your visual field, may be more important then the
distance between neighboring individual. While it is not been explicitly demonstrated,
this orientation style could have many implications for the flow of information in free
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flying and swimming groups. Flocks often change shape, size and density very rapidly in
the presence of a predator. Topological orientation, which is not dependent on metric
distance, allows for changes of density to flow throughout the flock while still
maintaining flock integrity. Changes in density and metric distance between individuals
may serve as a means which information is transmitted thorough the group. Waves of
changing densities often propagate throughout a group (Carere et al. 2009) in a similar
fashion to ripples in a puddle, and may carry with them information about a predator,
such as its location. Within bird flocks and fish schools waves are exemplified as
propagating an epicenter of a few individuals [usually in closest proximity to the predator
(Happer, 1997)]. Carere et al (2009) quantified the flocking behaviour of starlings in
relation to the predation risk in certain roosting areas. They observed consistent agitation
waves within flocks engaging in aerial displays. Waves in response to a predator have
been observed and investigated more extensively within fish schools. Sonar is utilized to
measure the changes in shape and density within large schools of fish in response to
predation. For instance Gerlotto (2006) looked at the ‘waves of agitation’ in fish schools
disturbed by predatory sea lions (Callorhinus ursinus). Waves perpetuated throughout a
group just as a sea lion attacked. Before an attack group internal structure was
characterized by patterns of ‘vacuoles’ or empty spaces and ‘nucleus’ or areas of high
densities within the shoal. Following an attack and progression of wave of agitation the
group exhibited a more homogenous density with individuals tending to orient
themselves in a certain direction. Radkov (1973) also documented changes in internal
organization of captive schools in response to a wave. At the distal end of the school a
few individuals were given a fright stimulus which initiated a wave of agitation across the
group. After the progression of the wave individuals in the school consistently oriented
themselves in the direction of the fright stimulus (get figure). This suggests that waves
could relay information about the location of the predator quickly throughout the whole
group.
These ‘social waves’ may also be a means which flocks and schools can deter
attacks by utilizing the confusion effect (Kastberger 2008). The collective movement of
group members may make it hard for a predator to target a specific individual within the
group. Predators are also preferentially attracted to larger groups but enjoy a lower
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suiccess then when attacking smaller groups. Zheng et al (2005) modeled the interactions
between the confusion effect and predation. In his model fish could respond to predation
using three component behaviour patterns: (1) move in the coordination with neighbors,
(2) avoid collisions and (3) escape singly without regard for the movement of near
neighbors. Manipulating the weight of these three heuristics when making decision in
virtual predator-prey scenarios influenced the group behaviour and success rate of
predators. By coordinating movement with neighbors schools were able to use the
confusion effect to deter virtual predators from successful attacking the group. Agitation
waves, while potentially serving as a means to spread information about the location of
the predator (Gerlotto 2006) may even deter predation. Giant honeybees (Apis dorsata)
swarms form coordinated waves across their hive in response to the threat of predation.
By flipping there abdomen over and displaying their shinny underside individuals
collectively propagate a shimmering wave of reflected light across the group. Giant
honeybees are sting-less and live in open hives that are not surrounded by a protective
layer as in many temperate species. Kastberger (2008) found that these shimmering
waves effectively deterred predatory wasps from attacking within a set area around the
nest site. Wave strength and rate corresponded with the strength and closeness of the
predatory hornet. Hornets responded to these waves by avoiding areas within close
proximity to the hive, and foraging on isolated bees away from the hive. Consequently,
the shimmering waves served to create a “safe haven” around the nest where predation
was prevented. Cohesive flocks of starlings engaging in aerial displays were more
common in areas of high predation (Carere et al 2008). Similarly, predation attempts
directed at these cohesive flocks were less successful then attempts directed at less
cohesive flocks. Starlings possess a glossy black plumage which is excellent at reflecting
light, and waves often correspond with bright flashes of light. Other flocking species such
as dunlins also exhibit bight flashes of light as waves disseminate throughout the group
(Parrish and Hamner 1997). Wave propagation through fish schools is also often
associated with flashes of light (Gerlotto et al. 2006). Fish scales can be highly reflective
and wave propagation in schools often coincides with a rolling motion by the fish which
reflects sunlight outward. These shimmering flashes may aid the confusion effect by
visually making the group a coordinated whole, and therefore also making it harder for
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predators to single out individuals. Agitation waves which cause flashes of light may
therefore aid in deterring predation thorough the confusion effect. Because data regarding
the effects of agitation waves in response to predation is sparse follow up experiments
need to be conducted in order to validate these assumptions.
Although it warrants significantly more study, agitation waves could be an
important component in the spread of social information about the presence of the
predators and a potential mechanism for predatory deterrence. Due to the increasingly
sophisticated techniques used to measure animal groups in three dimensions it is now
possible to look at the dissemination of waves from the level of the individual
interactions. These studies could help elucidate the anti-predatory function of waves. For
instance experiments could investigate if predators have lower success rate when
attacking a group engaging in a wave then they are not. Fish tend to orient towards the
attack stimulus after wave propagation (Radakov 1973). This suggests that waves carry
basic information about the position of the predation in relation the group as a whole.
Other evasive techniques such as the twist and turns of flocks and schools may rely on
information provided by waves as a framework. Therefore in order to understand the
complex flocking or schooling patterns in response to predation you may need to
understand first the interactions within and subsequent reactions to an agitation wave.
The next section investigates if the shapes which flocks form can also be utilized as
“communication beacons” to other flocks or single individuals about predation.
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From (Heppner 1997). A propagation of an agitation wave in a flock of birds. This photo
also shows the reflected flash of light seen also seen in wave propagation in both fish
schools and bees.
Information Transfer between groups
The behaviour of groups themselves may serve as a form of communication to
other groups about the presence of a predator. Feare (1984) hypothesized that the shapes
formed during flocking displays served to inform other individuals about the location of
the roosting site. Species typical flocking behaviour has been documented in some
species, such as starlings, and has been used to identify species from afar where
individuals cannot be discerned. Animal aggregations have been known to be important
cues used by individuals when assessing and choosing between foraging patches, but
there is no evidence that individuals utilize specific patterns of aggregation when making
decisions. Empirical investigations of information transfer between flocks have yet to be
17
conducted and therefore its mechanisms (if it occurs) are unknown. However flocks do
often exhibit consistent patterns in certain situations. If these patterns are consistent
enough to convey accurate information to other flocks evolution might favor inter-flock
communication. Therefore one of the first steps to investigating inter-flock or school
communication is to see if flocking / schooling patterns represent honest signals about
environmental conditions which others can utilize.
Starlings often forage during the day in the countryside and return to roosting
areas during the evening. When arriving at roosting areas starlings will form vast flocks
with hundreds or thousands of individuals. Flocks often engage in complex aerial
displays above the roosting site before settling in for the evening. The purpose of these
aerial displays is not entirely known (as they often occur without predation as well).
Carere at al (2008) classified different starling flocking patterns in relation to the level of
predator threat in certain areas. Two roosting sites in Rome were monitored and the
flocking patterns recorded. From these recordings a flocking ethogram was developed
with twelve distinct flocking patterns. It was also noted how abundant the main predator ,
the peregrine falcon (Falco peregrinus) was at each location and the number of falcon
attacks upon starling flocks (either successful or unsuccessful). This information could be
used to deduce the predation risk at each site. Large cohesive flocks were found at higher
proportions in areas with higher predation risk, whereas in areas with lower predation risk
smaller and less cohesive flocks were more apparent. Consequently different flocking
patterns accurately correlated with the level of predation risk. This suggests that specific
patterns could potentially function as communication beacons by transmitting accurate
information about predation risk to other flocks. Moreover, Carere (2008) found that antipredatory displays by flocks outside but still in view of the roosting area influenced the
probability of observing similar flocking patterns on the roosting site. This suggests that
flocking patterns may served as a form of communication between groups with
neighboring groups copying patterns from each other. Predation tactics are often
restricted and can influence the shape of fish schools in predictable ways (Parrish 1992).
Pitcher and Wyche (1983) were able to classify different schooling patterns based on the
predation tactics used by predatory sand eels. Nottestad and Axelsen (1999) looked at
the response of schools of herring to predation by killer whales (Orcinus orca) and found
18
that groups increased in density and displayed consistent evasion patterns when under
attack.
These examples show that flocking and schooling formation often correlate with
risks of predation, types of predators, and types of predatory attack behavior. As far as we
know there are no studies which have explicitly documented or provided direct evidence
for inter-flock communication. The pre-requisites for inter-group communication, mainly
that flocking patterns represent honest signals regarding predation are well founded. It is
possible that instances of inter-flock communication individuals may simply be simply
reacting to similar or even the same stimuli and therefore matching flocking patterns.
Artificial or trained predators could be used to elicit a response a single flocks and then
quickly removed from view. Changes in flocking patterns of neighboring flocks could
then be observed to see if they tend to match each other. This study may suggest that
flocks do indeed match other flocks patterns and do not simply respond to the same
predatory agent. Further research should now be conduced to (1) develop large scale
ethogams for flocking and schooling patterns in relation to contextual and environmental
variables (2) document copying of flocking patterns between groups..
In order for inter-group communication to take place it individuals should be able
to discriminate between different flocking patterns. Numerous studies have shown that
birds can categorize different visual stimuli. Pigeons have been a classic model for visual
categorization and can learn to recognize pictures based on the presence of human
figures, shapes and even weather conditions (Dittrich et al 1998). Similar studies could be
conducted by exposing individual birds to videos of different flocking patterns. Birds can
first learn to peck at a button or light to receive a food reward when videos of flocking
behaviour are played. Over training periods only certain flocking patterns come to deliver
rewards. Individuals could then be tested to see if they can differentiate between patterns
by presenting them with novel videos of different flocking patterns and record there
response. Inter-group communication is a potentially exciting field of research that
deserves in depth investigation and documentation.
19
Figure 2 From (Carere et al. 2009), a collective ethogram of different starling
flocking patterns.
Self-organization from foraging flocks to intra-group communication
Group living allows individuals to reduce their risk of being taken by a predator.
However in order for individuals to garner protection from group living they must
coordinate their behaviour with surrounding individuals. The evolution of social
behavior, or being able to respond appropriately to the behaviour of conspecifics, laid the
ground work for the development of collective group level behaviors. For example
Alberts (2007) found that rat (Rattus rattus) pups began coordinating group movements
only when they developed the ability to respond to conspecifics (sociality), beforehand
individual movements were random. Moreover, rats also developed coordinated
responses to the presence of the mother which were absent before sociality developed.
One way of investigating the mechanisms within collective behaviour is through the lens
20
of self organization (Sumpter 2006). Self organization is when the group behaviour is
defined by the interaction of lower level components within the system. Interactions
between these components create larger scale structures, which can then feedback and
influence the behaviour of the components accordingly. Within animal groups this means
that the collective group behaviour is determined by the simple interaction rules between
individuals. Self organizing systems can be seen in a wide scale of natural phenomenon
from the movement of people crossing a city street to the migration of birds and the
fluctuation of the stock market (Couzin and Krause 2003). Traditionally self organizing
phenomenon have been investigated using mathematical models, although techniques are
becoming available that allow for accurate measurement of self organizing groups in the
laboratory and field.
The key to understanding self-organization in groups is positive feedback. A
positive feedback system is where the behaviour of the group feeds-back into the
interactions of the components in order to maintain and amplify the group behaviour
(Couzin and Krause 2003). In order for this to occur individuals must be able to copy the
behaviour of neighboring individuals. An example of a positive feedback system can be
seen in the creation of game trails by many ungulate species (Couzin and Krause 2003).
Considering a uniform environment many models have shown that individuals will
initially choose to travel at random leaving a slight path behind them. Once a path is
created though it is easier for other individuals to use this already partially made path.
Therefore, the initial creation of a path feeds-back into other individuals using this path
until a permanent trail system is created. Trail systems can thus be said to be a selforganizing system. Within predator detection, evasion and communication positive
feedback systems may be operating to ensure that individuals collectively coordinate
their behavior. During predator detection positive feedback enables vigilant behaviour
(and thus information about the presence of a predator) to spread throughout the group.
During predator evasion positive feedback propagate and agiation wave throughout the
group.
Utilizing positive feedback is one mechanism which groups may use to
collectively decide on a course of action, or reach a consensus. Reaching a consensus is
crucial for collective predator detection and evasion. There are many different routes
21
which individuals within a group can utilize in order to reach consensus between
mutually exclusive decisions. Some of these include individual group members averaging
there information together in what is called “information pooling” (Conradt and Roper
2005). A classic example of this is the popular fair game where individuals must guess
the weight of the ox or other livestock and then receive prizes for the best guess. In 1906
Francis Galton obtained all the individual guesses from a local fair and averaged them to
see if they matches the weight of the ox. While individual guesses were rarely close to
the average weight of the ox the average of all the guesses was within one pound of the
actual weight. Information pooling thus generates accurate predictions about
environmental conditions but has no mechanism for coordinating collective action.
Animals groups are often not capable of global communication. For instance an
individual herring at the periphery of a large herring school may not be able to directly
communicate with an individual at the center of the school. Starlings for instance are only
able to maintain contact with seven individuals while flying (Fernández-Juricic and
Kacelnik 2004).This potentially makes averaging information over large groups quite
difficult and slow/ because interactions are limited to neighboring individuals. In flocks
and schools that need to respond to predatory attacks information transfer and consensus
need to be reached quickly and accurately. By utilizing reaction thresholds and positivefeedback systems animal groups may be able to respond to predation without
“information pooling”. Here a certain number of individuals within a group display a
specific behaviour together (threshold value) which subsequently initiates a positive
feedback response that spreads and amplifies this behaviour (and associated information)
throughout the group. Once the behaviour and information has spread throughout the
group it can collectively move towards a decision together (consensus). This is a
parsimonious hypothesis for how groups can reach a consensus without resorting to
cogntivley sophisticated behaviours. Understanding the mechanisms within antipredatory behaviour from on the ground foraging flocks to inter-flock communication
may be furthered by looking at threshold values and positive feedback responses.
Being in a group confers benefits to individuals by diluting the predation risk.
Therefore, maintaining group integrity and coordinating group behaviour might confer
benefits upon individuals when responding to predation. In order to respond appropriately
22
to the presence of a predator it must first be detected. Individuals within foraging groups
alternate between being vigilant and foraging. The key to understanding collective
predator detection and response is threshold and feedback of vigilant behaviour. Once
vigilance levels reach a threshold value all individuals become aware of the danger and
collectively respond by flying away from the foraging area. This requires rapid spread of
information throughout the group which initiates a collective response (Sumpter et al
2008). Feedback ensured that vigilance levels rise to the point of initiating evasive action.
Once the group is airborne the threat of predation dose not always vanish, and often the
group must respond to pursuit or further attacks. Information transfer throughout the
flock here must be very fast and efficient. Agitation waves may serve to transfer
information about the location of the predator quickly throughout the group in order to
initiate appropriate evasive techniques (Radakov 1973). As in collective detection
information must be spread rapidly throughout free flying flocks and schools in order to
initiate collective maneuvers. Threshold values may also be important in initiating an
agitation wave. A certain number of individuals may respond to the presence /attack of a
predator by moving in towards the center of the group This movement may then be
copied by surrounding individuals. When a certain threshold number of individuals
responds to a predator by moving in unison an agitation wave is instigated. The threshold
values that initiate wave propagation will likely be low because the speed which groups
must respond to a predatory attack. Waves then advance as individuals copy the
responses of neighboring individuals by moving closer to each other with positive
feedback perpetuating the wave throughout the group.
One common way for groups to deal with the threat of predation is to form large,
dense flocks. In flocks of starlings denser flocking arrangements were observed in areas
that had a higher risk of predation (Carere et al. 2009). Forming dense arrangements may
facilitate information transfer through positive feedback. For instance models looking at
the collective behaviour of self-propelled particles have showcased the influence of
density in determining group coordination (Sumpter et al 2008, Vicsek et al 1989).
Particles within a virtual environment can move in two ways, either by coordinating the
movement in alignment with another particle or by moving randomly. At low densities
particles behave stochastically, often randomly exploring the environment with little
23
coordination with other individuals. At medium densities particles tend to coordinate
their movement with others or employ random exploration. The group as a whole exhibits
a fluctuating pattern of mass coordination with mass un-coordination. Particles at high
densities tend to exhibit consistent coordinated motion in a single direction on both the
individual and group level. To summarize, once a threshold density is reached it becomes
easier for the group to coordinate actions together. In studies of collective behaviour you
can observe that denser groups are be able to coordinate evasive maneuvers better then
groups with lower densities. Denser flock arrangements may also increase the utility of
positive feedback by allowing for quicker copying of neighboring conspecifics. Waves of
agitation for instance may propagate information throughout a group by locally
increasing the density of individuals. This can be seen most clearly when groups adopt a
more homogenous and oriented internal structure after wave propagation. The
significance of forming dense group patterns in response to predation may therefore
increase the utility of positive feedback and the spread of information throughout the
group.
A largely unexplored question is how the self organizing characteristics of
flocks and schools influence inter-group communication. The presence of a predator is
often a very palpable stimuli which individuals need to respond. Flocking and schooling
patterns represent a more ambiguous stimulus because of there dynamic and continually
changing structures. However flocks and schools do exhibit clear patterns in response to
predation (such as creating dense flocking and schooling arrangements). This means that
specific patterns could be co-opted as signals to other groups about the risk of predation
in a specific area. If it is documented that individual birds can recognize and classify
flocking patterns we can then start to look at the mechanisms by which inter-group
communication proceeds. Hypothetically individuals could classify different flocking
patterns and respond to patterns indicative of predation as they would if a predator was
present. When a threshold number of individuals copies the patterns of a neighboring
group positive feedback is initiated and the behaviour spreads throughout the entire group
Therefore through threshold mediated positive feedback interactions groups may adopt
similar flocking patterns. Inter-group communication is an unknown area of study with
many potentially exciting findings for how animal groups respond to predation
24
Models of collective behaviour have focused either on the benefits of forming and
maintaining groups (in response to predation) or on the self-organized mechanisms
underlying group behavior. Integrating self–organization models with theories of the antipredatory advantages of groups will help further our understanding of how animal groups
reduce the risk of predation. Here we saw how the self organizing process of threshold
and positive feedback could help uncover potential mechanisms that groups use when
detecting, evading and communicating about predators. However this still needs to be
validated experimentally. Confounding environmental factors not included in our
discussion may influence the grouping arrangements and flocking patterns seen in the
wild. For instance similar environmental conditions, such as the size of roosting areas,,
may induce similar flocking patterns and also attract predators. This might lead to a
correlation between specific patterns and predation risk. The mechanisms underlying
group behaviour could also be confounded by individual differences and propensities.
Further studies that take into account confounding factors will give us a better picture of
the advantages and mechanisms underlying collective anti-predatory behaviours.
Index
Acara cichlid fish, 6
Cicadas, 4
Common Ringed Plovers, 12
confusion effect, 2, 5, 12, 14
dilution effect, 3, 4, 9
Dunlins, 12
flocking patterns, 2, 7, 12, 17, 18, 19, 20,
24
Giant honeybees, 15
goshawks, 5
herring, 2, 18, 21
information pooling, 21
ostriches, 3
Pigeons, 19
positive feedback, 2, 10, 20, 21, 23, 24
predatory sand eels, 18
rat, 20
Romans, 3
Self organization, 20
selfish heard, 4
self-organization, 10, 20
starling, 11, 17, 20
starlings, 2, 7, 11, 14, 15, 17, 23
vigilance, 2, 8, 9, 10, 22
wildebeest, 2, 4
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