ArticlePDF AvailableLiterature Review

Individual versus Social Complexity, with Particular Reference to Ant Colonies


Abstract and Figures

Insect societies – colonies of ants, bees, wasps and termites – vary enormously in their social complexity. Social complexity is a broadly used term that encompasses many individual and colony-level traits and characteristics such as colony size, polymorphism and foraging strategy. A number of earlier studies have considered the relationships among various correlates of social complexity in insect societies; in this review, we build upon those studies by proposing additional correlates and show how all correlates can be integrated in a common explanatory framework. The various correlates are divided among four broad categories (sections). Under ‘polyphenism ’ we consider the differences among individuals, in particular focusing upon ‘caste ’ and specialization of individuals. This is followed by a section on ‘totipotency’ in which we consider the autonomy and subjugation of individuals. Under this heading we consider various aspects such as intracolony conflict, worker reproductive potential and physiological or morphological restrictions which limit individuals ’ capacities to perform a range of tasks or functions. A section entitled ‘organization of work’ considers a variety of aspects, e.g. the ability to tackle group, team or partitioned tasks, foraging strategies and colony reliability and efficiency. A final section, ‘communication and functional integration’, considers how individual activity is coordinated to produce an integrated and adaptive colony. Within each
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Biol.Rev. (2001), 76,pp. 211237 Printed in the United Kingdom #Cambridge Philosophical Society 211
Individual versus social complexity, with
particular reference to ant colonies
Department of Biology,Duke University,Durham,NC 277080338, USA
(Received 6April 2000, revised 14 November 2000; accepted 14 November 2000)
Insect societies – colonies of ants, bees, wasps and termites – vary enormously in their social complexity.
Social complexity is a broadly used term that encompasses many individual and colony-level traits and
characteristics such as colony size, polymorphism and foraging strategy. A number of earlier studies have
considered the relationships among various correlates of social complexity in insect societies ; in this review,
we build upon those studies by proposing additional correlates and show how all correlates can be
integrated in a common explanatory framework. The various correlates are divided among four broad
categories (sections). Under ‘polyphenism’ we consider the differences among individuals, in particular
focusing upon ‘caste’ and specialization of individuals. This is followed by a section on ‘ totipotency ’ in which
we consider the autonomy and subjugation of individuals. Under this heading we consider various aspects
such as intracolony conflict, worker reproductive potential and physiological or morphological restrictions
which limit individuals’ capacities to perform a range of tasks or functions. A section entitled ‘organization
of work’ considers a variety of aspects, e.g. the ability to tackle group, team or partitioned tasks, foraging
strategies and colony reliability and efficiency. A final section, ‘ communication and functional integration ’,
considers how individual activity is coordinated to produce an integrated and adaptive colony. Within each
section we use illustrative examples drawn from the social insect literature (mostly from ants, for which there
is the best data) to illustrate concepts or trends and make a number of predictions concerning how a
particular trait is expected to correlate with other aspects of social complexity. Within each section we also
expand the scope of the arguments to consider these relationships in a much broader sense of ‘sociality’ by
drawing parallels with other ‘social ’ entities such as multicellular individuals, which can be understood as
societies’ of cells. The aim is to draw out any parallels and common causal relationships among the
correlates. Two themes run through the study. The first is the role of colony size as an important factor
affecting social complexity. The second is the complexity of individual workers in relation to the complexity
of the colony. Consequently, this is an ideal opportunity to test a previously proposed hypothesis that
individuals of highly social ant species are less complex than individuals from simple ant species’ in light
of numerous social correlates. Our findings support this hypothesis. In summary, we conclude that, in
general, complex societies are characterized by large colony size, worker polymorphism, strong behavioural
specialization and loss of totipotency in its workers, low individual complexity, decentralized colony control
and high system redundancy, low individual competence, a high degree of worker cooperation when tackling
tasks, group foraging strategies, high tempo, multi-chambered tailor-made nests, high functional integration,
relatively greater use of cues and modulatory signals to coordinate individuals and heterogeneous patterns
of worker-worker interaction.
Key words: Ants, insect societies, individual complexity, social complexity, polyphenism, totitpotency, work
organization, functional integration, sociality.
* Current address: LS Biologie I, Universita
$t Regensburg, Universita
$tsstrasse 31, D-93040 Regensburg, Germany.
Correspondence: C. Anderson, LS Biologie I, Universita
$t Regensburg, Universita
$tsstrasse 31, D-93040 Regensburg,
Tel: j49 (0)941 943 3293;
Fax: j49 (0)941 943 3304.
E-mail: carl.anderson!
212 Carl Anderson and Daniel W. McShea
I. Introduction ............................................................................................................................ 211
II. Polyphenism............................................................................................................................. 214
(1) Polymorphism ................................................................................................................... 214
(2) A continuum of specialization........................................................................................... 216
(3) Differentiation................................................................................................................... 216
III. Totipotency ............................................................................................................................. 217
(1) Totipotency, morphological skew and intracolony conflict............................................... 217
(2) Physiological and morphological constraint...................................................................... 218
(3) Individual complexity ....................................................................................................... 218
IV. Organization of work............................................................................................................... 219
(1) Groups and teams ............................................................................................................. 220
(2) Task partitioning............................................................................................................... 221
(3) Nest complexity................................................................................................................. 221
(4) Defence.............................................................................................................................. 222
(5) Foraging strategies ............................................................................................................ 223
(6) Tempo, reliability and efficiency....................................................................................... 223
(7) Intermediate-level parts .................................................................................................... 226
V. Communication and functional integration............................................................................. 227
(1) Signal range and system connectedness ............................................................................ 227
(2) Signals versus cues.............................................................................................................. 228
(3) Modulatory signals............................................................................................................ 229
(4)Integration and connectedness............................................................................................ 229
VI. Discussion ................................................................................................................................ 230
VII. Conclusions.............................................................................................................................. 232
VIII. Acknowledgements .................................................................................................................. 232
IX. Appendix ................................................................................................................................. 233
X. References................................................................................................................................ 233
In insect societies – colonies of ants, bees, wasps and
termites – significant correlations exist among cer-
tain properties of the colony and of the individuals
that comprise it. For example, the degree of
behavioural specialization and intracolony colony
conflict among the workers both correlate with
colony size and colonies in which the nest is simple in
structure also tend to have simple communication
systems. In the most recent review of the subject,
Bourke (1999) used the term ‘simple ’ to describe
colonies with ‘few or no morphological differences
between reproductive individuals and workers, no
physical caste polymorphism among the workers
and relatively simple nests and communication
systems’. (The converse characteristics apply for
complex ’ colonies.) Here, we initially adopt his
view of complexity as a small cluster of correlates.
However, as we proceed through the various sections
we extend the investigation and consequently ex-
pand Bourke’s (1999) cluster to include aspects of
colony life not previously considered.
The above usage of complexity is generally
consistent with that elsewhere in the social insect
literature, where the term been used to refer to a
number of variables, such as mean size of behav-
ioural repertoire (Cole, 1985), body size and per
capita productivity (Karsai & Wenzel, 1998), num-
ber of castes (Oster & Wilson, 1978), negentropy of
nestmate recognition signals (Jaffe, 1987 ; Jaffe &
Perez, 1989), degree of cooperation and coordination
among workers (Beckers et al., 1989; C. Anderson,
N. R. Franks & D. W. McShea, in preparation),
reproductive dimorphism (Peeters, 1997; Bourke,
1999) and colony size (Wilson, 1971; Peeters, 1997 ;
Karsai & Wenzel, 1998; Bourke, 1999). This study
expands the scope of certain related treatments of
social insects (e.g. the above references and
Michener, 1974; Bonner, 1988; Alexander, Noonan
& Crespi, 1991; Seeley, 1995) and our usage of the
term ‘social complexity’ is more inclusive ; indeed,
our hope is to develop a common scheme that shows
how many of these variables, along with others, are
related to each other.
Our usage also suggests a connection with the
broader literature on hierarchy in biology, where
there has been considerable interest in the factors
affecting degree of emergence, or individuation, of
entities at various hierarchical levels, such as the
213Individual versus social complexity
Table 1. Social correlates of individual and social complexity in insect societies.The correlates are intended to illustrate
general trends only and not to encompass the behaviour of every social insect species.All of these trends are discussed in
the text.Numbers in parentheses refer to the subsections of the sections (in bold)where the particular trait or correlate is
primarily discussed.(0)refers to the introduction of a section
Simple societies 4Complex societies
I. Introduction
(0) Colony size Low High
II. Polyphenism
(1) Worker polymorphism Low High
(2) Individual specialization None 4behavioural 4physiological 4morphological
(2) Type of specialization Temporary Permanent
III. Totipotency
(1) Functionality of ovaries High Low
(1) Morphological skew Low High
(1) Worker policing Absent Present
(1) Intracolony conflict High Low
(2) Physiological constraint Low High
(3) Individual complexity High Low
IV. Organization of work
(0) Colony control Centralised Decentralised
(0) System redundancy Low High
(0) Homeostasis Low High
(1) Groups and teams Absent Present
(2) Task partitioning Absent Present
(3) Nest complexity Low High
(3) Colony-constructed nest No Yes
(3) Number of chambers One Many
(4) Foraging strategy Individual 4tandem running 4mass 4trunk trail 4group hunting
(5) Defence Generalist non-sacrificial workers Specialist sacrificial defenders
(6) Tempo Low (‘cool’) High (‘hot’)
(6) Individual competence High Low
(6) Most complex task type Individual 4group 4team & partitioned
(6) Efficiency High Low
V. Communication and functional integration
(1) Average system connectedness High Low
(2) Use of cues Low High
(3) Use of modulatory signals Low High
(4) Heterogeneity of interaction Low High
eukaryotic cell and multicellular organisms as well as
entities at the colony level [e.g. Spencer, 1904 ;
Beklemishev, 1969; Pattee, 1970 ; Boardman &
Cheetham, 1973; Leigh, 1983; Salthe, 1985, 1993 ;
Buss, 1987; Bonner, 1988, 1998; Wimsatt, 1994 ;
Maynard Smith & Szathma
!ry, 1995; Simon, 1962 ;
Keller, 1999; Michod, 1999; Wilson, 1999 ; McShea,
in press b; see also supplement issue to American
Naturalist (1997) 150(1)]. In present terms, a
eukaryotic cell can be understood as a ‘ complex
society’ of prokaryotic cells and a highly individu-
ated multicellular organism as a complex society of
eukaryotic cells. Here, we explore this connection
further, raising the possibility that at least some of
the same principles governing colony complexity in
the social insects apply and that a similar cluster of
correlates will be found across the hierarchical
We divide the whole suite of correlates considered
in this study among four major sections. Section II,
polyphenism ’, considers the differences among
individuals and in particular considers the concept
of caste. Section III, ‘ totipotency ’, considers the
complexity of individuals within a colony (as
opposed to the complexity of the colony itself),
especially their totipotency with respect to behav-
ioural and reproductive capacities. Section IV,
organization of work’, considers how the nature of
214 Carl Anderson and Daniel W. McShea
work itself may change with increasing colony
complexity and the important changes observed in
the way that individuals cooperate in order to tackle
colony tasks. Lastly, Section V, ‘communication ’,
considers how individuals communicate with each
other and coordinate their activities. These cate-
gories are by no means exclusive and the fact that
many of the different characters and traits are
correlated means that there is some overlap across
the sections. Within each section, we identify a
number of new correlates of interest and, with
examples, expand Bourke’s (1999) cluster. Wherever
possible we attempt to identify any causal relation-
ships and put these correlations or causal mech-
anisms in a broad context of ‘sociality’ with
comparisons to other ‘social systems ’ such as
multicellular organisms. The principal concepts,
trends and predictions are summarized in Table 1.
Two major themes are found linking all these
sections. The first is the influence of colony size, one
of the most important correlates when considering
social complexity (e.g. Wilson, 1971; Peeters, 1997 ;
Karsai & Wenzel, 1998; Bourke, 1999). The second
is the relationship between the complexity of the
individual and that of the colony. This presents an
ideal opportunity to test Jaffe & Hebling-Beraldo’s
(1990) hypothesis that ‘ individuals of highly social
ant species are less complex than individuals from
simple ant societies’, in a much broader context, i.e.
set of correlates, than was previously possible. We
suggest that, generally speaking, as social complexity
increases, there is indeed a correlated decrease in
individual complexity. In other words, there is a
decline in independence or autonomy of the in-
dividual and in its ability to function on its own.
Some explanatory notes are required before
proceeding. First, describing the many pair-wise
relationships within even a moderate-sized group of
correlates in an orderly way is difficult. We have
taken an approach in which we begin with a small
number of basic correlates in the first section (e.g.
colony size and differentiation) and build up
incrementally, in each section adding a small suite of
additional variables and discussing their relations-
hips to those in previous (sub)sections. Importantly,
the order in which variables are discussed does not
reflect causal primacy.
Second, ideally we would like to be able to map
some of the social correlates onto a phylogeny. This
would enable us for instance to evaluate whether
simple’ maps onto ‘ primitive ’ insect societies and
complex ’ maps onto more derived and ‘ advanced
societies. A phylogeny could also be used to assess
whether complexity has any tendency to increase
in evolution, a tendency that is widely acknow-
ledged but for which little empirical evidence exists
(McShea, 1996 and references therein). Unfortu-
nately, at the present time a suitable phylogeny does
not exist and as such thus we shall avoid the two
value-laden, yet often-used, terms ‘primitive’ and
advanced ’ (see Sherman et al., 1995). Third, our
treatment of complexity in social insects is restricted
mainly to ant societies, where the best data seem
to be available.
Fourth, implicit in our understanding is our view
of social complexity as a continuum running from
simple to complex. However, occasionally, it will be
convenient to frame the discussion solely as a contrast
of these two extremes without discussing the whole
suite of intermediates.
The following section considers differentiation
among individuals, i.e. temporary and permanent
differences in morphology (polymorphism), physi-
ology and behaviour among individuals.
(1) Polymorphism
Simple societies are composed of monomorphic
individuals whereas complex societies contain a
polymorphic workforce (Michener, 1974; Wheeler,
1986; Ho
$lldobler & Wilson, 1990; Peeters, 1997 ;
Bourke, 1999). Polymorphism has evolved inde-
pendently at least eight times (Ho
$lldobler & Wilson,
1990) but only 15% (44\297) of all ant genera ex-
hibit some degree of worker polymorphism (Oster
& Wilson, 1978: p. 4). Importantly, polymorphism
tends only to be associated with species that have
large colonies (Bourke, 1999: Table 1). Analyzing
Jaffe’s (1987: Table 1) data (although not taking
into account phylogenetic relationships) we found a
highly significant relationship between log"!(colony
size) and log#(variation of worker size), specifically :
log"!(colony size) l1.11ilog#(variation of worker
size) – 1.85 (Fl19.78, P0.0002 ; solid line in Fig.
1A). Jaffe (1987) did not specify how he quantified
this worker size variation. Non-linear regressions
give better fits to the data and the linear fit is still
significant when the two obvious outliers are
removed (Fl8.15, d.f. l22, P0.01 ; dashed line
in Fig. 1A).
It is unfortunate that the analysis cannot easily be
extended to quantify the degree of polymorphism
215Individual versus social complexity
Log10 (colony size)
Log2 (variation in worker size)
12345 67
Log10 (colony size)
Proportion (%)
123456 7
Log10 (colony size)
Foraging strategy
Log10 (colony size)
Running speed (cm/s)
Acts self-grooming:
Time inactive:
Fig. 1. (A) Log#(variation in worker size) versus log"!(colony size) (data from Jaffe, 1987 : Table 1). A small amount
of scatter has been added to the data to separate points. The solid line is the least-squares fit to the data while the
dashed line is the least-squares fit when the two obvious outliers have been removed. (B) Foraging strategy changes
from individual foraging (I) to group hunting (GH) as colony size increases (data from Beckers et al., 1989). Other
foraging strategies: TR, tandem running; GM, group\mass foraging; M, mass foraging; TT, trunk trail. (C) Prop-
ortion of time spent inactive and proportion of acts spent self-grooming both decrease with increasing colony size
(data from Schmid-Hempel, 1990). Reprinted by permission !University of Chicago Press. (D) Running speed
increases with log"!(colony size). Running speed data are listed in the Appendix.
more precisely. In ants, morphological castes are
produced developmentally by altering the relative
growth rates of different body parts (see Bourke &
Franks, 1995 and references therein). The relation-
ship between just two body parts may be isometric,
di- or tri-phasic allometric, or even completely
dimorphic (Wilson, 1953; Wheeler, 1991) and it is
not even always possible to distinguish different
castes in a supposedly multi-modal species (e.g.
Daceton armigerum, Moffett & Tobin, 1991). In
addition, within a species different relationships may
exist between many pairs of body parts (including
internal organs such as brains : see Jaffe & Perez,
1989) may exist between many pairs of body parts
making any overall measure of ‘ degree of poly-
morphism’ a challenging, but not necessarily in-
tractable, multidimensional concept.
Only very recently have researchers begun to
appreciate that polymorphism does not necessarily
mean a difference in size among individuals : size
may be similar but shape may differ. This is clearly
the case when considering winged queens versus
wingless workers of similar size (A. F. G. Bourke,
personal communication). However, shape may also
vary among individuals in which both queens and
workers are winged. This was recently shown to be
the case in Apoica pallens, a polistine wasp in which
the overall size of queens and workers does not differ,
but queens are smaller than workers anteriorly yet
significantly larger posteriorly (Jeanne, Graf &
Yandell, 1995). Importantly, this research suggests
that morphological castes may evolve without a
divergence in body size. Such studies may show that
morphological differences and ‘caste ’ in insect
societies may be greater and more widespread than
previously thought. We predict that the greatest
differences among individuals – not just in size
(including isometric allometry) but also in shape –
216 Carl Anderson and Daniel W. McShea
will be found in the species with the largest colony
size and suggest that polymorphism is a significant
facet of social complexity (contra Wilson, 1953 : p.
(2) A continuum of specialization
An additional facet of polyphenism is worker
specialization. We suggest that simple societies are
composed of generalist workers whereas complex
societies contain workers that are specialized in a
variety of ways, i.e. behaviourally, physiologically,
or morphologically (Oster & Wilson, 1978;
Anderson, 1998), to allow a certain amount of
division of labour. Consequently, the ant Amblyopone
pallipes, which completely lacks division of labour
(Traniello, 1978), excepting reproductive division of
labour, must class as one of the simplest societies
from this aspect. We suggest that the various forms of
specialization form a continuum (Table 1). At the
lower extreme are true generalists, species such as
Amblyopone pallipes, in which the probability of
performing a task is independent of age. In other
species, however, individuals concentrate their ac-
tivities on a subset of the colony’s repertoire and thus
exhibit temporal specialization and division of
labour. This temporal specialization may only be
temporary – age or temporal polyethism may occur
in which individuals tend to pass through an
average’ sequence of tasks over time, or individuals
may switch tasks through recruitment when the need
arises – but we still consider them specialists.
We suggest that a greater degree of specialization
occurs when physiology imposes temporary behav-
ioural specialization by making individuals par-
ticularly well adapted to certain tasks. For instance,
between the 6th and 14th day of their lives, honey
bee workers produce royal jelly (Manning, 1975)
which effectively forces them to specialize in feeding
queen larvae. As the workers age, special cells in
their abdomens start to secrete wax and thus these
individuals become naturally suited to a comb-
building role. Finally, the extreme of this continuum
is associated with morphological castes. In this
situation, individuals are not subject to temporary
changes in their abilities to perform certain tasks but
to permanent differences in skills and abilities. For
instance, a morphologically specialized soldier is
likely to be inherently better at defence than other
activities (e.g. brood care) throughout its life. In
Crematogaster smithi ants there are two worker castes :
large ’ and ‘ small ’. Large workers appear to be
specialized in the production of trophic eggs, i.e.
unfertilized worker-laid eggs used as food. Effect-
ively, these workers specialize in turning protein
from perishable food such as insect prey into
internally stored eggs that they may store for several
weeks (Heinze, Cover & Ho
$lldobler, 1995; Heinze,
Foitzig & Oberstadt, 1999).
(3) Differentiation
Three main arguments support the notion that
differentiation should be correlated with colony size.
As will be seen, they are quite general applying in
principle to complex societies of prokaryotic cells
(i.e. eukaryotic cells) and of eukaryotic cells (i.e.
multicellular organisms) as well as to colonies of
multicellular individuals. First, in a large aggregate
of generalist individuals, performance can often be
improved if individuals differentiate in order to
specialize on particular tasks. In particular, dif-
ferentiation is expected when individual specialists
are able to perform functions more efficiently than
non-specialists (Smith, 1776; Bonner, 1988) or when
synergistic interactions among specialists improve
performance (Corning, 1983). A requirement is that
it must be possible for individuals to share resources
(Harvell, 1994) and for tasks to be coordinated
(Oster & Wilson, 1978; Corning, 1983 ; Bell, 1985).
What factors control the degree of differentiation or
number of specialist types? One possible constraint
follows from a model developed by Oster & Wilson
(1978) relating numbers of castes and tasks in social
insects. Generalizing their result, selection is ex-
pected to favour differentiation of types until the
number of types equals the number of tasks to be
performed; it follows that the number of types could
be limited by the number of tasks. However, the
number of tasks doubtless reflects the number of
selection pressures, including the number of selective
opportunities and we have no reason think that these
are sufficiently limited so as to impose a significant
constraint, especially considering that tasks can often
be readily subdivided into subtasks (see below).
Another possibility is that the number of types is
limited by the number of individuals available to
differentiate, so that each individual is specialized
for a unique function. In this case, the number of
types would be expected to increase directly with the
number of individuals and therefore with colony
size. However, other constraints tend to reduce the
rate of increase. For example, in large aggregates, a
specialized type is rarely a single individual, possibly
because single individuals are often too small to
217Individual versus social complexity
make a significant contribution to the whole (Bell &
Mooers, 1997). Also, in small aggregates, fluct-
uations in demand for specialized tasks on the
aggregate as a whole are often severe, in relative
terms and as a result, specialized individuals will
sometimes be left idle. Thus, differentiation is not
expected even to begin until colonies reach at least a
moderate size (Bell & Mooers, 1997). Consistent
with this, in volvocacean algae (e.g. Volvox), dif-
ferentiation of cells (into somatic and germ cells) is
evident only in species with colony sizes of 64 or
greater (e.g. Eudorina, Bell, 1985). Differentiation
may also be limited by constraints imposed by
development (Oster & Wilson, 1978), environment
(Schopf, 1973), life history, etc.
A second argument is that differentiation may
actually be required at large group sizes. Bonner
(1988) proposed that increased size reduces surface-
area-to-volume ratios, which changes the perform-
ance requirements of certain tasks, which in turn
favours the evolution of specialized devices composed
of differentiated lower-level individuals. For ex-
ample, single-celled organisms can obtain food and
oxygen by diffusion alone but larger multicelled
organisms have cells differentiated to function in
specialized devices, circulatory systems, for food and
oxygen delivery.
Also, a connection between differentiation and
group size is a prediction of Spencer’s (1904)
metaphysic, in particular of what he calls ‘ the
instability of the homogeneous’. Spencer argues that
in an aggregate, the component elements are subject
to different forces by virtue of their differing locations
within the aggregate – internal versus external, for
example – and these differences in forces produce
differences in structure. The greater the size of the
aggregate, the greater the range of variation of
environments within it and therefore also of the
forces producing differentiation. Thus, even in the
absence of selection, larger systems are expected to
become more differentiated.
The relationship between aggregate size and
differentiation has been studied in multicellular
organisms and the results are consistent with
expectations. In particular, Bell & Mooers (1997)
have demonstrated a significant correlation between
body size and number of cell types (see also Bonner,
1988). They further found that the number of cell
types increased very slowly with body size; assuming
a log-linear relationship, they estimated an exponent
of 0.056, much less than 1.
So far we have discussed the complexity of the
colony in the sense of degree of differentiation among
individuals within it. We now turn to the question of
the complexity of the individuals themselves.
Workers in complex societies tend to be less
totipotent (Crespi & Yanega, 1995 ; Bourke, 1999).
Crespi & Yanega (1995 : p. 110) define totipotency
as ‘the potential, throughout life, to express the full
behavioural repertoire of the population (even if
never actually expressed) and the ability to produce
offspring like oneself, exhibiting the full behavioural
repertoire of the population without help’. Thus,
reduction in totipotency includes not only loss of
reproductive potential but also of behavioural
repertoire. A distinction must be made between two
types of reduction in repertoire. First, individuals
may be subject to socially mediated and temporary
behavioural specialization in which they retain their
behavioural flexibility and can potentially switch to
other tasks (see Section II). Second, an individual’s
repertoire may be reduced due to physiological and
morphological constraint. That is, differentiation, in
terms of morphology or physiology, causes a dif-
ference in abilities to perform certain tasks. Here,
only the latter is part of totipotency.
(1) Totipotency, morphological skew and
intracolony conflict
One of the most significant losses of totipotency is the
loss of functional ovaries – and in some cases,
complete loss – in workers of some complex societies.
Oster & Wilson (1978: p. 101; see also Noll, 1999)
demonstrated a positive relationship between mono-
morphism of the colony and possession of ovaries by
workers concluding that ‘to develop into an extreme
caste is to surrender reproductive potential ’. Thus, it
appears there is a correlation between different-
iation, specifically polymorphism (Section II) and
totipotency, in the sense of worker reproductive
Bourke (1999) studied morphological skew in
insect societies. Morphological skew is the degree of
morphological dimorphism, usually external, be-
tween reproductives and workers. It is a consequence
of specialization of queen and worker roles and
reduced worker reproductive potential. For instance,
workers lacking ovaries, a form of extreme skew,
have been reported in the genera Solenopsis,Pheidole,
Monomorium,Tetramorium and Eciton and in the
218 Carl Anderson and Daniel W. McShea
subfamilies Myrmicinae and Ecitoninae (see Villet,
Crewe & Duncan, 1991). Bourke (1999) showed that
species with large colonies had a high degree of
morphological skew. Alexander et al. (1991) pro-
posed a causal relationship between colony size,
worker reproductive potential and morphological
skew. Briefly, in large colonies, due to competition
from the many other workers, any particular
individual has a small chance of replacing the queen
and thus selection maintaining reproductive po-
tential will be weak. Bourke (1999) extended these
ideas to consider the relationship between colony
size and one aspect of intra-colony conflict: worker
policing. Worker policing is the set of behaviours in
which workers search for and eat eggs laid by other
workers (Ratnieks, 1988; Ratnieks & Reeve, 1992 ;
Keller & Reeve, 1999). Worker policing is a
component of totipotency because it prevents work-
ers from reproducing. Bourke (1999) argued that
independent of mating frequency (which affects
average worker-worker relatedness), it is easier for
worker policing to invade large colonies. That is, in
small colonies it is easier for an individual to
monopolise reproduction and so there is greater
conflict among individuals fighting for reproduction
(Ratnieks & Reeve, 1992). However, in large
colonies, in which each individual has a small chance
of personal reproduction, individuals are more likely
to favour worker-policing and fitness gains through
inclusive fitness from the queen(s) than personal
reproduction. Bourke & Ratnieks (1999) consider
additional conflict in insect societies: worker sup-
pression of new queen production, which is predicted
to increase with a reduction in reproductive skew.
(2) Physiological and morphological
Other forms of physiological differentiation, in
addition to loss of ovaries, can impose behavioural
specialization. So, honey bees producing royal jelly
should specialize upon feeding queen larvae and
honey bee workers producing wax should specialize
on comb building. It is conceivable that non wax-
producing workers could remove the wax from the
wax-producing bees and use it themselves to build
the comb. [This is the situation with propolis, a
sticky tree resin, used by honey bees. Propolis
foragers cannot unload themselves and require other
bees to unload them. These unloaders and not the
foragers, use the material to mend cracks in the nest
(Ratnieks & Anderson, 1999a).] However, it is likely
to be far more efficient if the wax-producing bees –
who can remove the wax themselves – remove and
build with the material themselves. In effect, as an
individual becomes physiologically specialized, it
becomes more ‘subjugated ’ and thus less of an
independent individual. This is more so with
morphological differentiation. In this situation,
individuals are subject to permanent restrictions in
their abilities. One of the more extreme examples of
reduction of individuality of workers occurs when
soldiers physically cannot feed themselves and must
rely on trophallaxis for survival (e.g. Daceton arm-
igerum majors; Wilson, 1962).
The greatest loss of individuality must surely be
that associated with suicidal and sacrificial de-
fenders. These traits are only expected to occur in
complex societies. Sting autotomy – self-amputation
of a sting (usually barbed) – is found in various
social insect taxa among the ants, bees and wasps
(Hermann, 1971, 1981). ‘ One predicts that barbed
stings will be used in defence only in species that
form new colonies in swarms such as honey bees and
some tropical wasps [i.e. complex societies]. In very
small colonies [simple societies] workers are too
valuable for suicidal attacks to be beneficial
(Alexander et al., 1991: p. 31). However, alternative
sacrificial and suicidal behaviour does occur in ants
such as in the ‘ walking bombs ’ (Oster & Wilson,
1978: p. 226) of Globitermes sulfureus and Camponotus
saundersi ants who literally explode in front of their
attackers. These ants use hydrostatic pressure to
burst their gaster and mandibular glands releasing
stick fluids, a process termed ‘ autothysis ’ by
Maschwitz & Maschwitz (1974). Although these
adaptations, such as barbed stings and specially
adapted mandibular glands, may be morphological
and physiological adaptations, they are present in
the whole workforce and therefore are not part of
differentiation (Section II). Our point is that the
possession and use of these adaptations constitutes a
reduction in individual autonomy and that these
adaptations are expected only in complex societies.
(3) Individual complexity
Reduction of totipotency has a number of possible
correlates, which we predict will be manifest at all
hierarchical levels. First, there is a direct correlation
with colony size. In small colonies, each individual
in the colony is a scarce and valuable resource and
therefore remains totipotent. Second and more
generally, we expect a correlation between loss of
behavioural and reproductive capacities on the one
hand and loss of morphological structures and
219Individual versus social complexity
physiological capacities on the other. Further, all of
these should be correlated with colony size. As size
increases and individuals specialize, they become
dependent on others, or more precisely on the colony
as a whole, for the performance of various survival-
related functions. An individual that is specialized
for defence, for example, relies on other specialists for
foraging, colony-homeostatic activities and so on. As
a result, the number of different functional demands
on specialist individuals is reduced, along with the
selection pressures maintaining the morphological
structures, behaviours and physiological mechanisms
associated with these activities. [An underlying
assumption is that functions tend to be localized in
such structures and mechanisms (McShea, 2000).]
Indeed, selection is expected to favour the loss of
these structures, behaviours and mechanisms in the
interest of economy (McShea, in press a).
Third, the emergence of function at the level of the
colony requires the loss of some degrees of freedom at
the level of individuals (Guttman, 1969; Pattee,
1973; Bar-Yam, 1997). Buss (1987 ; see also
Maynard Smith & Szathma
!ry, 1995) has pointed
out that selection on the colony favours loss of
reproductive capacities in some individuals, as
discussed above in ants. But more generally, selection
should act to reduce individuals’ degrees of freedom
in order to limit their interference with the co-
ordinated function of the whole. Thus, individuals
specialized for metabolism must not reproduce;
likewise, reproductive specialists should not have
metabolic capability, as their metabolic processes
are unlikely to be coordinated with and indeed are
likely to interfere with, those of the specialists. The
loss of degrees of freedom may be achieved either by
policing (Michod, 1999) self-policing or totali-
tarian control – or, more effectively, by the loss of
morphological structures, behaviours and physio-
logical mechanisms associated with superfluous
In addition to the findings in social insects
discussed above, a number of observations in colonial
marine invertebrates are consistent with these ex-
pectations. For example, Wood, Zhuravlev &
Debrenne (1992) noted that individuals in colonies
are often smaller and less complex than related
solitary individuals and Beklemishev (1969) noted
that zooids in colonial forms are simpler compared
those in related free-living species. At the cellular
level, metazoan and land plant cells contain fewer
macroscopic morphological structures than free-
living eukaryotic cells (McShea, in press a). Extreme
examples include mature human haemocytes, which
contain almost no macroscopic structures and free-
living Euglena, which have a variety of structures
(e.g. nucleus, mitochondria, plastids, a flagellum,
contractile vacuoles and so on). These extreme cases
aside, even the more typical metazoan cells are, at
least impressionistically, less complex in this sense,
on average, than typical free-living cells (Gerhart &
Kirschner, 1997: p. 242).
These observations are based on comparisons
between extreme cases of social complexity, between
free-living forms in which social complexity is
essentially zero and individuals in colonies, in which
it is present to some degree. There has been no
demonstration yet that losses of structure accompany
incremental increases in social complexity. In other
words, it has not been established that the two are
correlated as continuous variables, or that such losses
are connected with any of the various correlates of
social complexity, such as degree of differentiation.
Also, most of the evidence for losses is based on
morphology (e.g. ovaries in ants, parts in cells, etc.),
but the expectation of loss at the level of the
individual extends to behaviours and physiological
mechanisms as well. Individual zooids in marine
invertebrate colonies and cells in metazoans and
land plants show little motor behaviour, but possible
losses of physiological mechanisms could be investi-
gated. Finally, in social insects, we predict that
individuals in complex colonies should have fewer
behaviours, on average, than those in simple col-
onies. Methods for counting behaviours have been
developed (e.g. Wilson & Fagen, 1974; Fagen &
Goldman, 1977) and thus testing could be straight-
The complexity of the colony also has consequences
for the organization of work within the colony. In
addition to worker policing (see Section III),
reduced intracolony conflict in complex societies has
another important consequence: the type of social
control. In small simple societies, as in the ponerine
ant Dinoponera quadriceps (Monnin & Peeters, 1999),
there is much aggression and direct control of colony
activity by the queen or ‘ gamergate ’. [Gamergates
are mated reproductive workers in queenless ants
(Peeters, 1997).] In effect, the reproductives cen-
trally control simple conflict-ridden societies. How-
ever, in the relatively harmonious larger societies,
colony control and decision-making tends to be
decentralized. That is, workers react to local in-
220 Carl Anderson and Daniel W. McShea
formation and configurations and so are ‘ self-
organized’ (e.g. The
!raulaz & Bonabeau, 1995;
Bonabeau et al., 1997; Bonabeau, Dorigo &
!raulaz, 1999; Camazine et al., in press). Cen-
tralized control would be difficult or impossible in
large colonies. However, decentralized control can
be very adaptive at the colony level, even with very
large colony sizes and importantly does not necess-
arily require complexity at the individual level (e.g.
Bonabeau, 1998; Bonabeau et al., 1999 ; Anderson &
Bartholdi, 2000).
Interestingly, there are theoretical reasons to
suppose that a large decentralized colony can be
both efficient and reliable (high probability that
tasks are completed) even when the individuals
tackling the tasks are simple and not especially
competent. Specifically, when activity is concurrent
and individual competence is low, efficiency and
reliability can be achieved by having redundancy –
replication of parts – at the subunit level rather than
the system level (Barlow & Proschan, 1975 ; Oster &
Wilson, 1978; Herbers, 1981; see below). Thus, we
expect many (spare) individuals in the vicinity of a
task who are able to tackle that task. Even though all
the individuals may not be fruitfully employed, at
least the task will be completed.
It has been noted that complex societies tend to
have a perennial cycle and in wasps and bees are
swarm-founded rather than independent-founded
(Bourke, 1999) and so do not go through a bottleneck
of small colony size. Not only is colony size less
variable through the year in more complex societies
but larger systems are inherently more homeostatic
(Wilson, 1971). For instance, there are automatic
benefits to group foraging such as reduced variation
in food influx rate (Wenzel & Pickering, 1991) and
a greater potential for food storage to supply the
colony during forage dearths (Jeanne, 1991). In
summary, complex societies have a more constant
colony size and structure, have less intracolony
conflict, are inherently more homeostatic and rely
more on decentralized control. This has huge
implications in the organization of work as shown
(1) Groups and teams
One very apparent aspect of work organization in
complex societies is the degree of cooperation among
individuals when tackling some tasks. We suggest
that in complex societies tasks may be completed by
groups and teams rather than by individuals.
Anderson & Franks (2001) suggest that there are
four types of task in insect societies: individual,
group, team and partitioned tasks. The first three
types are defined and reviewed in Anderson &
Franks (2001). The fourth task type, partitioned
tasks, are considered in the next subsection. All four
task types are summarized in Table 2 and are further
explored in C. Anderson, N. R. Franks & D. W.
McShea (in preparation).
Briefly, individual tasks are tasks that can sat-
isfactorily be performed by an individual, e.g.
feeding a larva within a cell. Group tasks require
many individuals working together for successful
task completion. In a group task, there is no division
of labour and the behaviour of the individual is the
same as that of the group. For instance, group
ambush and bivouac construction in army ants
(Schneirla, 1971; Gotwald, 1995), intimidation of
competitors in Myrmecocystus mimicus ants (Ho
1976, 1979), and ‘ stigmergic ’ nest construction in
termites (Deneubourg, 1977; Bonabeau et al., 1998 b;
see also Karsai, 1999) are all examples of group
tasks. By contrast, Anderson & Franks (2001)
propose that a team task requires different subtasks
to be performed concurrently, i.e. there is division of
labour. They propose that a task is ‘ an item of work
that potentially makes a positive contribution,
however small, to inclusive fitness (i.e. direct and
indirect fitness)’. However, sometimes a subset of the
behaviours required to complete a task may appear
as a unit in themselves but cannot contribute to
inclusive fitness when performed in isolation. This
unit is a subtask.
Under the above definition of a team task, one
such example is nest construction in Oecophylla spp.
(weaver) ants. To construct the nest, leaves must be
glued with silk while pulled together (subtask 1).
The silk is produced by larvae (subtask 2) who are
held above the seam by other workers (subtask 3)
(Anderson & Franks, 2001). Anderson & Franks
(2001) are careful to point out that team tasks do not
require that individuals in a team must be members
of different castes (contra Oster & Wilson, 1978: p.
151). However, they do highlight that polymorphism
and thus presumed inherent differences in abilities
among individuals to perform different activities,
may favour specialization of castes upon certain
subtasks thus enhancing team task performance.
A team task requires more cooperation than a
group task. This is because in a team workers must
coordinate their different work contributions. In
turn, a group task requires more cooperation and
coordination than an individual task because a
group task requires the concurrent activity of
multiple individuals (Table 2). These concepts are
221Individual versus social complexity
Table 2. Characteristics of various task types.This table defines the various task types.For instance,a team task
requires a number of different individuals (column 2)performing multiple subtasks (column 3)concurrently (column 4).
[From Anderson &Franks (2001).]
Number of
Divided into
Organization of
Individual task Single No
Group task Multiple No*
Partitioned task Multiple Yes Sequential
Team task Multiple Yes Concurrent
* But concurrency is required.
explored in depth in C. Anderson, N. R. Franks &
D. W. McShea (in preparation). We hypothesize
that in simple societies, the most coordinated tasks
observed will generally be individual tasks. High
intracolony conflict, monomorphism and small col-
ony size will disfavour more coordinated activity in
such colonies. In more complex societies we also
expect to observe individual tasks but additionally
we expect the most coordinated activity to be group
tasks. For instance, we may observe group foraging
or group nest construction activity. These group
tasks will be favoured by large colony size in that
many individuals may be available in the immediate
vicinity for recruitment to the task. In even more
complex societies we expect to observe team tasks.
These too will be favoured by large colony size.
However, they are more likely to be favoured by
differences in performance efficiency among individ-
uals arising from polymorphism (e.g. N. R. Franks,
A. Sendova-Franks & C. Anderson, in preparation)
and also from the increased potential for behavioural
specialization due to increased colony homeostasis.
(2) Task partitioning
Task partitioning (Jeanne, 1986; reviewed in
Ratnieks & Anderson, 1999a), in addition to groups
and teams, is another task type that is only tenable
in relatively complex societies. A task is said to be
partitioned when it is split into a number of
sequential stages and material is passed from one
worker to another. In short, the task is split into a
number of sequential subtasks (Table 2) which are
explicitly linked by the act of material transfer. For
instance, in the obligate termite-hunting ant
Megaponera foetans minor workers enter the termite
nest, hunt for termites and deposit them in a pile
outside the termite nest. Major workers then trans-
port the termite prey back to the ants’ nest
(Longhurst & Howse, 1979). Like group and team
tasks, partitioned tasks require the coordination of a
number of individuals for successful task completion
(Table 2).
Partitioning a task may involve a number of
advantages and disadvantages, which are reviewed
in Ratnieks & Anderson (1999 a). The most relevant
to social complexity are as follows. First, task
partitioning usually occurs when there is a difference
in abilities of individuals to perform different parts of
the task. For instance, small Oecophylla longinoda
workers are better at milking scale insects than are
larger workers. Small workers collect the honeydew
and pass it onto larger workers who are better able
to transport it back to the nest (Ho
$lldobler, 1984b).
Thus, division of labour enhances task partitioning
and is most likely to occur when the worker
population is polymorphic, i.e. in complex societies.
Second, when direct transfer occurs searching for a
transfer partner takes time (a cost) and average
search duration decreases exponentially as the
number of individuals in the working group in-
creases. Consequently, when the group is large, these
queueing and search delays are negligible (Anderson
& Ratnieks, 1999a,b). Third, when group size is
large, workers are significantly better able to assess
the status of the system and make correct recruitment
decisions to optimize worker allocation and efficiency
(Ratnieks & Anderson, 1999b). However, because
work demands are inherently more stable in a
complex society anyway, there is less need for
individuals to switch tasks and this increases ef-
ficiency (e.g. Gordon, 1989, 1999b; Karsai &
Wenzel, 1998). Overall, task partitioning has the
potential to greatly enhance task performance
efficiency but mostly so in complex societies.
(3) Nest complexity
Individual ability to cooperate as groups and teams
and partition tasks in complex societies may have
implications for where they live. We suggest that
complex ant societies tend to construct nests for
222 Carl Anderson and Daniel W. McShea
themselves rather than utilizing existing crevices and
that these nests are relatively complex. One possible
reason is that suitable natural nest cavities are more
limiting for large colonies than for small ; unfortun-
ately, testing this is not straightforward. Alter-
natively, complex colonies have greater potential for
tackling tasks that are beyond the abilities of an
individual, such as the construction of tailor-made
nests (e.g. Bonabeau et al., 1999; Anderson & Franks,
What constitutes a complex nest? There are many
features associated with increased nest complexity.
Foremost, we see partitioning of the nest into two or
more chambers. This is usually associated with some
spatial specialization of colony activity. For instance,
in Atta leaf cutter ants some chambers contain the
fungal garden and brood whilst others solely contain
refuse material (e.g. Weber, 1972). In many ant
species, brood is piled in specific areas of the nest and
in termites the queen is physically entombed in one
chamber and the eggs that she lays are taken to other
chambers (e.g. Wilson, 1971). In the seed harvester
ant Pogonomyrmex barbatus (Gordon, 1999a), piles of
seeds accrue only in certain parts of the nest.
In addition to the points made above, this physical
segregation of workers in a multi-chambered nest
has an important implication in the degree of control
a queen has over a complex society. In a multi-
chambered nest, any regulatory pheromones the
queen releases are unlikely to diffuse rapidly through-
out the nest and so her ability to control colony
activity will be greatly reduced. In addition, more
complex societies exhibit a greater degree of mor-
phological skew. Thus, workers could potentially
very easily exclude the queen(s) from certain areas of
the nest by restricting the size of entrances to
particular chambers (Howse, 1970), in the extreme,
completely entombing the queen in a single cham-
ber. Not only will the diffusion of any of the queen’s
pheromones be restricted but this could also be true
of alarm pheromone: recruitment of additional
defenders when the colony is attacked could be
limited by the layout of the nest. Thus, in complex
societies we expect some localisation of specialized
defenders near the nest entrance(s) as in Camponotus
(Colobopsis)fraxinicola ants discussed in Section IV.4.
Complex nests may contain additional adaptive
structural features not found in simple nests. Starr
(1991: p. 523) lists a number of nest features that are
believed to have originated to serve secondary
functions. In ant societies, these include fungus
gardens (leaf cutter ants), auxiliary silk bowers used
as shelters for homopterans (e.g. weaver ants) and
windows or tunnels used for the escape of sexuals for
mating flights (fire ants). Here, we also include the
specialized repletes who act as living storage vessels
in the honey pot ants (Myrmecocystus mimicus,
$lldobler & Wilson, 1990) and ‘turrets ’ at the nest
entrance of Acromymrex landolti nests which may
prevent inundation during sheet flooding (Navarro
& Jaffe, 1985). Despite the apparent complexity of
some nests, it should be stressed that it is not
necessary to invoke complexity at the individual
level during their construction: the complexity may
be an emergent property of a collection of interacting
simple builders (e.g. The
!raulaz & Bonabeau, 1995;
!raulaz, Bonabeau & Denubourg, 1998; Karsai,
Specific testing of our prediction – that complex
societies construct their own nests and that these
nests are more complex – may be difficult. First, the
three-dimensional aspect of an excavated nest will
probably be difficult to preserve. Second, to under-
stand how features of the nest impact on colony
activity requires observation of undisturbed colonies
and the attempt to observe will probably affect its
behaviour. Third, an insect society may move into
an existing crevice but modify it specifically for their
needs. Consider a honey bee colony, a complex
society, whose swarms move into natural tree cavities
but add their own wax combs. In the case of the
honey bee, these modifications may be easy to
detect, but in other instances they may not; an
enlarged natural chamber in a log may be in-
distinguishable from an unenlarged one.
(4) Defence
We suggest that simple ant societies with few workers
react to intruders, usually by stinging, as and when
the need arises. Stinging is presumably the major
ancestral ant defence mechanism as ants evolved
from wasps (Ho
$lldobler & Wilson, 1990) and
stinging is the main, but by no means only, defence
in wasps (e.g. Hermann, 1981). By contrast, in more
complex societies, which have many individuals, the
colonies can afford to allocate workers to specific
defensive roles and defence mechanisms are more
likely to be varied. For instance, they may post
workers at entrances to check ‘colony membership
of individuals going into the nest [e.g. Camponotus
(Colobopsis)fraxinicola ants; Wilson, 1974]. Altern-
atively, they may employ workers to patrol around
the nest looking for intruders. For instance, Pseudo-
myrmex ferruginea ants patrol the foliage around the
Acacia thorns in which they live (Janzen, 1983).
223Individual versus social complexity
Polymorphism, a complex-society trait, opens up the
possibility of producing workers morphologically
specialized for defence. Defence is one of the three
main proposed roles of majors in ants, the other two
being seed milling and food storage (Ho
$lldobler &
Wilson, 1990). In many polymorphic species majors
possess particularly large and strong mandibles (e.g.
Pheidole pallidula majors who decapitate intruders;
Detrain & Pasteels, 1992). Some species, such as
Camponotus truncatus and C.ephippium, possess specially
shaped ‘phragmotic ’ which can plug nest entrances,
either individually or working with others to function
as a living door (Hermann, 1981; Fig. 8–33 of
$lldobler & Wilson, 1990). In this situation, nest
complexity itself also plays its part in colony defence
by only having nest entrances that are just one
individual wide. Similar behaviour is also known in
some social wasps, such as in Chartergus chartarius
(Jeanne, 1991), in which the passages between
combs can be blocked by a single individual.
(5) Foraging strategies
As well as the existence of group, team and
partitioned tasks in complex societies, another facet
of higher-level functionality is a shift from individual
to group foraging strategies. Beckers et al. (1989)
identified six foraging strategies in ant colonies : (1)
individual foraging foraging without cooperation
and communication with others ; (2) ‘ tandem run-
ning’ – a scout guides one recruit to the food source
with or without trail laying; (3) ‘ group\mass
recruitment’ – the scout guides a group of recruits to
the source, usually laying a trail to the nest ; (4)
mass recruitment ’ – the scout lays a trail while
returning to the nest which guides recruits to the
food source; (5) ‘ trunk trail ’ – semi-permanent trails
guide foragers to long-lasting food sources; and (6)
group hunting a group leaves the nest and
forages collectively in a swarm along a well-defined
trail system. It is reasonable to assume that the order
of strategies above (1–6) represents an increase in
reliance on chemical communication between work-
ers; assuming that this ordering is correct, then a
trend of increasing use of chemical communication
with increasing colony size is unmistakable (Beckers
et al., 1989; Fig. 1B). (See also Ruano, Tinaut &
Jose Soler, 2000 for effects of temperature upon
foraging strategy.) In addition, these strategies also
appear to be correlated with a decrease in the
autonomy of the individual foragers themselves (cf.
Jaffe & Hebling-Beraldo, 1990 and also see Section
IV.6). That is, there is a shift from information
processing by individuals to emergent properties of a
set of essentially probabilistically behaving individ-
uals mediated through signals, i.e. a set of trail
pheromones. For instance, in an individual foraging
strategy the worker must rely on its own information,
navigating back to the nest using the sun or other
landmarks (e.g. the desert ant Cataglyphis bicolor). In
tandem running, a successful returning forager can
recruit just one individual and passes on information
of where the food source is by physically leading the
recruit to the source (e.g. Leptothorax spp.). However,
with more complex strategies trail pheromones can
pass the information not just to one other recruit but
to many. There is no need for an individual to be
able to navigate back to the nest using the sun or a
prominent rock but can simply orient (‘ smell ’) their
way along a chemical trail (e.g. Atta spp.). Despite
the apparent simplicity of this task, foragers ex-
perience a constant probability per unit distance of
losing the trail. Seemingly counterintuitive, this
apparently errant behaviour has been shown to be
very adaptive at the group-level (Deneubourg,
Pasteels & Verhaeghe, 1983; Deneubourg et al.,
1987; Fletcher, Blackwell & Cannings, 1995). Once
lost, these workers become scouts who can search for
new sites. However, it appears that the error rate is
sufficiently tuned so that enough foragers do not lose
the trail and thus can exploit the source whilst
enough become scouts enabling a constant supply of
new sources. [Parallel behaviour is known in honey
bee foraging in which the directional information in
waggle dances is imprecise (Weidenmu
$ller & Seeley,
1999).] It seems that the complexity emerges at the
level of the trail network (or group) which can
adaptively adjust to fluctuating food dispersion or
density (e.g. Bernstein, 1975). Thus, the foragers are
a ‘group-level adaptive unit ’ (sensu Seeley, 1995,
1997; see also Bonabeau, 1998).
(6) Tempo, reliability and efficiency
There are some interesting relationships between
colony ‘tempo’, individual reliability, foraging strat-
egy, metabolic rate and social complexity, in
particular, colony size. Oster & Wilson (1978),
without supporting data, suggested that colony
tempo increases with colony size. Tempo was defined
simply as ‘activity level’ and thus is presumed to
incorporate both amount of activity, e.g. proportion
of time spent inactive and the speed and efficiency of
task completion when active. Oster & Wilson (1978)
suggested that workers of ‘ cool ’ species, such as
many ponerine, dacetine and basicerotine ants –
224 Carl Anderson and Daniel W. McShea
which we suggest are simple societies – are slow and
deliberate and conservative in their use of energy.
Hot’ species, on the other hand, such as army ants,
fire ants and members of the genera Conomyrma,
Forelius and Iridomyrmex – which we suggest are
complex societies – bustle with activity, ‘ seethe with
rapid motion’ and ‘ waste substantial amounts of
time canceling out another’s actions ’ (Oster &
Wilson, 1978 : p. 282). On this basis, we can
formulate two non-exclusive hypotheses. First, the
amount of inactivity decreases with increasing
colony size (hypothesis 1). Second, running speed
increases with colony size (hypothesis 2).
Hypothesis 1 was examined by Schmid-Hempel
(1990). He demonstrated a highly significant de-
crease in the proportion of time spent inactive and
the proportion of acts of self-grooming (a low-energy
activity), with increase in colony size for a variety of
ant species. See Fig. 1 C. Running speed was shown
to increase with colony size in Aphaenogaster rudis and
Myrmica punctiventris by Leonard & Herbers (1986)
and in colony fragments of Pheidole dentata by
Burkhardt (1998). Thus, there are limited data
supporting the hypothesis that within a species,
running speed is correlated with colony size. We
compared running speed among 26 taxonomically
diverse ant species (from 11 genera) and found a
highly significant relationship between running
speed (cm\s) and log"!(colony size) (Fl5.03, r#l
0.326, Nl26, P0.02) thus confirming hypothesis
2 (Fig. 1D). In response to Tschinkel’s (1991) plea
for publication of sociometric data, the raw data
appear in the Appendix. (Two desert-dwelling
species, Cataglyphis bicolor and Ocymyrmex barbiger,
which live in very hot climates and run fast to
minimize time spent outside in the intense heat, were
not included in the analysis. Their running speeds
are an order of magnitude greater than most of the
other species studied.) Thus, the available data –
although uncorrected for body size, phylogenetic
relationships and ambient temperature – appear to
support Oster & Wilson’s (1978) assertions.
Why should tempo and colony size be correlated ?
There are at least three main hypotheses. The first
considers foraging strategy and reliability theory
(Barlow & Proschan, 1975; Oster & Wilson, 1978 ;
Herbers, 1981). The second considers thermo-
dynamics of far-from-equilibrium systems (Jaffe &
Hebling-Beraldo, 1990, 1993). The third considers
pheromone concentration.
The first argument is based upon Oster & Wilson’s
(1978) proposal that the correlation between tempo
and colony size can be explained by diet. Their
argument, now backed with more recent research
(Herbers, 1981), goes as follows: in Section IV.5 we
explained that there is a correlation between colony
size and the type of foraging strategy, ranging from
individual foraging in species with small colonies to
group hunting in species with very large colonies.
Herbers (1981) used reliability theory to consider
selection pressures upon individual competence for
five ant foraging strategies. She demonstrated that
strategies associated with larger colonies – strategies
in which foragers have a high rate of encounter with
their prey (high tempo) – result in high system
reliability, even if individual competence is low. So,
species with large colonies, which are catholic in
their selection of prey (i.e. broad diet; Oster &
Wilson, 1978), can afford some inefficiency at the
individual level. Even though retrieval rate per
encounter is relatively low because of poor individual
competence, the net energy influx is high because of
the sheer numbers of workers involved (Oster &
Wilson, 1978). Herbers (1981 : p. 185) even argues
that colony selection will itself result in workers with
low competence (see also Karsai & Wenzel, 1998).
Her argument is based on the assumption that
selection maximizes benefit minus cost, where ‘ bene-
fit’ is the system reliability and the ‘ cost ’ is
individual competence in which it is assumed that
more reliable individuals are more costly to produce.
Species with few foragers on the other hand, tend to
have a more restricted diet and rely on stealth to
catch their prey; Peeters (1997: p. 377) states that
All ‘‘primitive ’’ ants are armed with a sting and
hunt arthropods’. The loss of one forager in a small
colony will have a large effect upon the colony’s
foraging success and so they are selected to have high
individual competence. In short, species with few
foragers have to be relatively reliable whereas
foragers in large colonies tend to be less reliable
because they are able to exploit such a strategy. It
could be argued, although little data exist, that less
reliable foragers, such as blind army ants who follow
chemical trails and overcome prey by sheer weight of
numbers (e.g. Schneirla, 1971 ; Franks, 1989) may
be cheaper to produce than highly competent
individuals who stealthily track down and overcome
prey individually. However, incompetent workers
can only ‘pay their way’ if they are especially active,
i.e. are high tempo, so that their rate of encounters,
despite their incompetence during an encounter,
generates a sufficient supply of prey items.
A second explanation for the correlation between
tempo and colony size can be formulated, without
reference to diet, by considering (neg)entropy and
225Individual versus social complexity
far-from-equilibrium thermodynamics. The more
ordered and complex a system is, the further it is
from equilibrium (disorder) and the higher the
amount of energy required to maintain the system in
that ordered state (e.g. Nicolis & Prigogine, 1977).
In a static equilibrium, such as a wood ant colony’s
nest – the equilibrium state being disordered pine
needles lying on the ground – the energy required to
order the system is normally only a one-time
investment: the effort to construct the nest. How-
ever, with a dynamic equilibrium, such as the far-
from-equilibrium order of an ant society (i.e. the
workers themselves) – the disordered state being
anarchic activity, each individual operating in-
dependently and without cooperating with others –
a constant stream of energy is required to maintain
that state. Jaffe & Hebling-Beraldo (1990, 1993 and
references therein) argue that this should be reflected
in a higher metabolic rate and greater energy
consumption per unit mass. In short, they argue that
a correlation should exist between social complexity
and (1) the colony’s overall energy content and (2)
the rate of energy use by workers, which may be
reflected in tempo. They found that basal metabolic
rate increased with colony size and the number of
morphological castes in eight attine species from four
genera (Jaffe & Hebling-Beraldo, 1993). However,
these results hold for the genus level but not when
comparing castes within a species. That is, complex
colonies as a whole should have a higher metabolic
rate with increasing colony size, but there may be
variation in the partitioning of energy within the
colony. For instance, colonies may contain minims
who have a high metabolic rate and large soldiers
with a low metabolic rate. Karsai & Wenzel (1998)
point out that one way of increasing the ‘tempo of
interaction’, assuming that the queens ’ resources for
worker production are limited, is to increase colony
size through reduced body size of workers. We
suggest that if the almost universal ‘ 0.75 scaling rule
for metabolic rate i.e. metabolic rate scales with
the $
%power of body mass (see Schmidt-Nielsen,
1984) – applies to workers, then metabolic rate per
unit mass increases as workers are reduced (on
average) in size and overall metabolic rate for the
colony as a whole increases. In effect, we suggest that
the increase in colony metabolic rate is achieved by
partitioning a colony into smaller and higher
metabolic-rate units. This is supported by the
findings of Calabi & Porter (1989) who showed that
in the fire ant Solenopsis invicta, large workers have
approximately a 30% lower respiration rate per
milligram of tissue than smaller ants.
A third possibility and fairly speculative hy-
pothesis is that higher running speed might be a
secondary effect of colony size. The suggestion is that
colony size correlates with a larger absolute number
of workers on a foraging trail, which in turn may
correlate with total pheromone concentration. If
running speed is positively correlated with phero-
mone concentration – as an experimental study of
Eciton burchelli trails suggests (Franks et al., 1991) –
then we might expect higher tempo in larger
colonies. However, further study is required to test
this hypothesis at the cross-species level because if
members of larger and more complex colonies lay
pheromone with higher volatility (and thus lower per
capita concentration) then this could ameliorate or
even reverse this effect. A relationship between
colony size and trail pheromone volatility has not yet
been investigated, but doing so should be straight-
Irrespective of the underlying reasons for the
correlation between tempo and social complexity the
same conclusions can be drawn. Individuals from
larger colonies are more active and tend to be less
reliable, yet the colonies can afford to waste energy
at the individual level. However, as noted earlier,
larger systems are inherently more homeostatic and
predictable than equivalent smaller systems (e.g.
more predictable food influx) and species with larger
colonies tend to rely on recruitment during foraging.
Karsai & Wenzel (1998) also argue that parallel-
processing systems in insect societies are more
efficient per se in that it allows behavioural special-
ization of individuals and greater buffering of
stochastic fluctuations. Schmid-Hempel (1990) notes
that this creates an interesting paradox. Larger
colonies may be able to afford a reserve forager force.
Some of the workers could remain in the colony
saving energy until demand for their labour is
required when effective recruitment can be used.
[See model and review in Anderson (2001).] How-
ever, on energetic grounds workers in larger colonies
are shown empirically to be and from theory may be
required to be, more active than in simple societies,
i.e. there is an ergonomic cost. This cost is contrary
to complex societies’ greater potential for efficient
cooperative work organization, i.e. an ergonomic
benefit. We suggest that far-from-equilibrium dy-
namics – that larger colonies waste energy as a cost
of order ’ – may be a causal factor of Michener’s
(1974) much cited but puzzling decrease in per capita
productivity with increasing colony size, but this will
be difficult to test.
226 Carl Anderson and Daniel W. McShea
(7) Intermediate-level parts
Groups, teams and possibly nests are examples of
intermediate-level ‘parts ’ (sensu McShea 2000 ;
McShea & Venit, 2001; C. Anderson & D. W.
McShea, in preparation), or adaptive structures or
behaviours in an aggregate which are larger than a
single lower-level individual but a subset of the
whole. Such structures occur at the level of the
organism as well as that of the colony and are
possible only where there is a high degree of
cooperation and coordination among lower-level
individuals. They are important for several reasons.
First, they confer a higher level of functionality,
meaning that they allow individuals or colonies to
achieve things collectively that a single individual
cannot. Second, they introduce new organizational
levels. This has important implications in the way
that communication and feedbacks are effected
among individuals (see Section V). Third, some of
the structures are clearly associated with a reduction
in autonomy: in many self-assemblages, each in-
dividual is effectively reduced to a construction
component equivalent to a building brick or scaf-
folding pole (C. Anderson, G. The
!raulaz & J. L.
Deneubourg, in preparation). For instance, the
primary role of an individual ant within a Solenopsis
invicta raft or Eciton burchelli bridge is to hold on to
other ants and so help to form and maintain the
Intermediate-level parts can arise in at least three
ways. One is as a connected group of lower-level
individuals, a subgroup of the entire aggregate in the
same manner as an army ant bivouac. Also, most
metazoan tissues and organs would qualify as
intermediate-level parts. Or at the colony level, a
non-social-insect example might be the clusters of
non-feeding zooids (or clusters in which density of
feeding zooids is lower), i.e. maculae, which in some
cyclostome bryozoan species may function as ex-
current chimneys for the colony as a whole (Banta,
McKinney & Zimmer, 1974).
Alternatively, an intermediate-level part may
consist of a single lower-level individual which is
hypertrophied or elaborated in various ways to
attain intermediate size. For example, in eukaryotic
cells, the portion of the cell that is homologous with
the original eubacterial host, plus subsequent ad-
ditions – e.g. microtubular structures, Golgi appar-
atus and so on – constitutes an elaborated lower-
level individual. Notice that this set does not include
the former endosymbionts, such as mitochondria
and chloroplasts, which (historically) are different
individuals. At the colony level, modern chondro-
phorines, such as Velella and Porpita, consist of a large
pneumatophore, or float, overlying a central gas-
trozooid, ringed by smaller medusa-shaped gono-
zooids (Hyman, 1940; Mackie, 1959); the gastro-
zooid by itself constitutes an intermediate-level part.
This type of intermediate-level part appear to be
absent in insect societies. This may be so because of
several reasons. First, developmental constraints may
limit the size and form that ants may take (Wheeler,
1991). Second, large elaborate individuals may be
too costly. Calabi & Porter (1989) analyzed the
energetic costs – longevity, respiration rates and
energy content ’ of worker tissue – in various sizes of
workers in the fire ant Solenopsis invicta. They
concluded that although larger workers have a lower
respiration rate per milligram of tissue their larger
biomass means that ‘one large worker must provide
services equivalent to at least four small workers, to
justify the colony’s energy investment’ (Calabi &
Porter, 1989 : p. 643). Third, elaborated individuals
may reduce the increased reliability effects of system
redundancy. That is, assuming that these individuals
are relatively rare, they become ‘ key individuals
(see Robson & Traniello, 1999). ‘ Failure ’ by a single
key individual may have a large effect upon the
overall efficiency of the group and makes the system
less robust and reliable.
Finally, many of the various inanimate structures
produced by higher-level entities would count as
intermediate-level parts. At very low hierarchical
levels, such structures might include the sheaths that
enclose filamentous cyanobacterial colonies, or at
the eukaryotic cell level, the nucleus (assuming it is
not a former endosymbiont). In multicellular organ-
isms, shells and exoskeletons and in colonies in
addition to nests in social insects the various non-
zooidal support structures (Boardman & Cheetham,
1973) count as intermediate level.
Bonner’s (1988) argument that size increases
favours internal division of labour and therefore
differentiation, can be extended to predict inter-
mediate-level parts. As lower-level individuals ag-
gregate to form a whole, selection favours the
emergence of functional capabilities in the whole.
But as the whole grows, lower-level individuals
become less competent to perform higher-level
functions on account of their small size (Bell &
Mooers, 1997). Thus, selection favours collaborations
among a number of lower-level individuals (perhaps
with subdivision of labour), the elaboration of single
ones, or the production of larger inanimate structures
in order to magnify their effects. Also, the argument
227Individual versus social complexity
for the production of heterogeneity among indi-
viduals, namely the various advantages that flow
from the cooperative division of labour, predicts that
labour will be divided among intermediate-level
parts and therefore they will become differentiated
from each other. Notice that the main difference
between this argument and Bonner’s original is that
intermediate-level parts – unlike lower-level indi-
viduals (cells in multicellular individuals, or colony
members in colonies) – have no autonomous exist-
ence. A team in an insect colony, or a macula in a
bryozoan colony, has no autonomous existence ; even
the elaborated archaebacterial host has lost much of
its historical autonomy. However, autonomy is not a
prerequisite for collaboration and differentiation.
In the previous section, we suggested three different
task types (group, team and partitioned tasks) in
which coordination of multiple individuals is re-
quired for successful task completion. More gen-
erally, most, if not all, aspects of colony life require
coordination of individuals for successful colony
operation. Mechanisms exist to coordinate effort,
e.g. recruit additional help when required, with the
result that complex colonies can often exhibit group-
level adaptive behaviour (see Seeley, 1997 ;
Bonabeau, 1998). It is these mechanisms – mech-
anisms that are used functionally to integrate
individuals and thus the colony which are con-
sidered in this section.
We consider these mechanisms of functional
integration under Seeley’s (1995 : p. 248) broad
definition of communication: ‘ information transfer
via cues as well as signals’. It is important to
distinguish cues from signals because, as we show
below, cues play a relatively more important part in
complex society communication and integration
than in simple societies. According to Lloyd (1983)
a signal is an act of communication that has been
shaped by natural selection. An example of a signal
is alarm pheromone. When signaling occurs, natural
selection acts upon both the signal sender, e.g. by
canalizing the behaviour so that it is more stereo-
typed and also upon the receiver, e.g. increasing
sensitivity to that behaviour pattern. A cue on the
other hand, is a structure or behaviour that conveys
information, but only incidentally and has not been
shaped by natural selection (at least not directly).
For example, intranidal temperature and the num-
ber of brood are both cues. Clearly, as information
from cues is incidental and may originate from
inanimate objects, such as the nest, natural selection
may only act upon the information receiver.
(1) Signal range and system connectedness
The first signaling characteristic we consider is signal
range: that is, local versus global. Some types of
signal are expected to be global regardless of social
complexity. In particular, we refer to defence
behaviour and alarm pheromones. If a colony is
under attack it is imperative that this information is
conveyed to all members of the colony as quickly as
possible so that individuals can become involved in
colony defence, or in some cases escape or hide inside
the nest. [In several ant species, young workers react
to an alarm signal by retreating into the nest while
older workers – a disposable caste (Porter &
Jorgensen, 1981) who are more likely to have
degenerate ovaries – move out and defend the nest
$lldobler, 1984a).] Consequently, these signals
are expected to be volatile chemical signals or
mechanical signals, such as rapping the nest sub-
stratum or jittering (Wilson, 1976), with ‘ one-to-
many’ effects, which will reach a large proportion of
the individuals quickly.
Signals for other colony functions, however, are
expected to differ among simple and complex
societies. In a small simple society, local signals could
potentially reach a relatively large proportion of the
colony. Also, direct one-to-one interactions with
individuals, such as antennation, as they move
around the nest may also mean that individuals in
simple societies interact with a relatively large
proportion of the colony. However, in a complex
society, individuals are spatially separated. For
instance, they may be segregated among different
nest chambers. We suggest that this does not imply
that signals should be necessarily be long range as
one might initially expect. We have argued (Sections
II and IV) that in complex societies, individuals
exhibit division of labour and specialization, work
more cooperatively and also that work tends to be
concentrated in different sections of the nest [which
would favour ‘ foraging for work ’ (Tofts 1993 ;
Franks & Tofts, 1994)]. This means that individuals
should primarily interact with others in the local
vicinity, i.e. other individuals who may have the
skills and opportunity to help with a task. In short,
we should expect the existence of ‘ cliques : a group
of individuals who preferentially interact with each
other rather than with others outside the group.
Thus, the term clique is used here sensu Moritz &
228 Carl Anderson and Daniel W. McShea
Southwick (1992 : p. 145) rather than Ho
$lldobler &
Wilson’s (1990 : p. 343) more stringent – and from
our current knowledge of social insect cognitive
abilities, unrealistic – definition : a ‘ group of workers
whose members recognize one another as individuals
to accomplish some task’.
It is not clear whether the average signal range,
the physical distance, in a simple society is greater
than in complex societies. Indeed, simple societies
may rely more on direct one-to-one interaction.
However, we do expect signaling behaviour and
interaction in complex societies to be relatively more
locally concentrated and organized. One way of
quantifying this is to consider the average system
connectedness (or ASC; Moritz & Southwick, 1992).
The basis of this analysis is to consider all the possible
interactions between pairs of individuals, or ‘ dyads ’.
Given nindividuals, there are n(nk1)\2 possible
pairings. If one can observe interaction behaviour
and quantify the number of unique pairs of
individuals that actually interact within a colony,
then the ASC is the observed number of dyads
divided by the possible number of dyads. ASC values
range from 0 to 1; a value of 1 means that all
individuals are fully connected to each other. We
would expect a high ASC value when considering
alarm pheromones. A low ASC would be expected
when interaction patterns are very localized, i.e.
cliques occur and members within a clique interact
with each other but cliques have little interaction
with other cliques. On this basis, we make the
following prediction: with the exception of im-
portant necessarily global signals such as alarm
pheromones, ASC for other tasks is expected to
decrease with increasing social complexity. This is
not to say that individuals are not highly connected
in a complex society, but simply that for a given task,
a relatively small and exclusive group of individuals
will be involved in tackling that task. More
specifically we predict that patterns of interaction, as
reflected by ASC, are more heterogeneous in
complex societies than in simple ones. This pattern of
interaction does not necessarily reflect the total
number of interactions among individuals which is a
function of signaling rate, or the strength of
interaction, simply who is communicating with
whom. Moritz & Southwick (1992 : pp. 149–150)
provide some estimates of ASC for various tasks in
the honey bee. Thus, as expected, an ASC of 1
(100%) was observed for defensive behaviour but
the ASC was very low, only 3.1%, for water-
handling behaviour. These methods could be used to
compare the ASC in simple versus complex societies.
(2) Signals versus cues
We predict that communication in simple societies
makes relatively little use of cues whereas they are of
much greater importance in more complex societies.
Unfortunately, it is not possible to make a more
explicit prediction, e.g. concerning the ratio of
communication that flows through cues rather than
signals since the effects of confounding variables,
such as the rate of signaling and existence of
modulatory signals (see below), are not clear. We
make the above prediction on the basis that we
expect a vastly different pattern of social regulation
in simple versus complex societies. Social regulation
in complex societies is based upon feedback from
groups to individuals and also from groups to groups
[see Wilson & Ho
$lldobler (1988) and Seeley (1995)],
while regulation in simple societies occurs mostly
through direct worker-worker interaction and feed-
back is primarily from individual to individual.
Wilson & Ho
$lldobler (1988) talk of ‘dense
heterarchies’ and mass communication as the basis
of organization in ant colonies. (We suggest that this
applies only to relatively complex ant societies.)
Their findings are mirrored by Seeley’s (1995)
analysis of honey bee social integration. A heterarchy
is a communication network in which interaction
occurs between different levels of the system or
subsystems. Thus, feedback occurs from higher-level
parts ’ (sensu McShea, 2000 ; McShea & Venit,
2001), such as intermediate-level parts, including
groups and teams, to lower-level parts, such as
individual workers. In turn, lower-level parts have
effects upon the higher-level parts. For instance, low
food reserves in the nest could influence a worker to
forage and collect more food. The lack of stored food
may influence many individuals to forage and as the
forage reserve within the nest increases this may
inhibit further foraging. Thus, there is interaction
from the group-level summed foraging effort, i.e. the
food pile (an intermediate-level part) and the lower-
level individual foragers. Notice that this example
used a cue – the amount of stored food – to influence
individual activity. Seeley (1995) argues that cues
are relatively important in complex social systems,
for at least three reasons. First, the group-level cues
are effectively a summation of many individuals’
inputs and thus are expected to be accurate
indicators. Second, cue-based communication means
that information may be conveyed to many in-
dividuals at once. Third, cues are probably more
easily sensed than the underlying variables of supply
and demand. For instance, it should be easier to
229Individual versus social complexity
assess the size of a seed pile than to directly assess the
flow of returning foragers adding to the pile and
other individuals depleting the resource (see
Anderson & Bartholdi, 2000).
The honey bee society is probably our most well-
understood complex insect society. Seeley (1998)
reviewed the state of our current knowledge of cues
and signals in honey bee colonies and found that
there are twice as many known cues as signals (34 vs.
17). Unfortunately, the ant literature lacks this
degree of detail for any ant species and is certainly an
area where more research is needed.
(3) Modulatory signals
$lldobler (1999) reviewed the complexity of signals
(in general) in ant communication. One important
aspect of that review which relates to social com-
plexity is the existence of modulatory signals.
$lldobler (1995 : p. 20) explicitly states that com-
munication in complex social systems is not always
characterized by a deterministic releasing process
but sometimes plays a more subtle role’. He proceeds
to explain the concept of a modulatory signal – a
signal that does not necessarily evoke a behavioural
response in itself from the recipient, but does alter
the way that the recipient responds to another signal
(Markl, 1985). For instance, in Camponotus spp. ants,
workers may strike the nest substratum during alarm
behaviour. This signal does not necessarily induce
aggressive defensive behaviour per se but appears to
act as a modulatory signal. Ants that have first
received this drumming signal react more aggres-
sively to their alarm pheromone than ants that have
not (See Ho
$lldobler, 1999 and references therein).
Many other examples of modulatory signals are
known (see Ho
$lldobler, 1999) and we suggest that
they are more likely to be found in complex societies
than in simple societies. Their primary function
appears to be in fine-tuning. Through the use of
these signals, the colony is able to alter its level of
response to the same stimulus depending upon other
colony needs and circumstances. Thus, a Camponotus
spp. colony may increase its defensive response by
using the drumming signal in conjunction with the
alarm pheromone to elicit a large response or can use
the alarm pheromone by itself for a smaller reaction.
We predict that these modulatory and other fine
tuning signals will tend to be lacking in simple
societies because they are generally less integrated,
more conflict ridden, more susceptible to stochastic
fluctuations and tend to be composed of relatively
autonomous generalists rather than cooperative
specialists. In order to test this, we need to detect
these signals; one approach to doing so is that of
Anderson & Ratnieks (1999c) in their analysis of the
coordination of nectar foragers and nectar receivers
in the honey bee. In their study, they estimated the
minimum set of signals and feedbacks that are
needed to regulate a society or an aspect of a society
and then compared it with the actual set of signals
exhibited. They found that only three different
signals and feedback mechanisms should be needed
to regulate the number of honey bee nectar foragers
and the number of receiver bees [to whom the
foragers regurgitate their nectar for storage (e.g.
Seeley, 1995)]. However, in reality, honey bee
colonies use five different signals and feedbacks, two
more than the minimum. One of these two additional
signals was a modulatory signal, the shaking signal,
which was used to ‘fire up’ the forager-receiver
system after nectar dearth by altering the probability
that individuals will respond to the forager re-
cruitment signal (waggle dance). The other signal,
the stop signal, was used to counteract effects of
heterogeneity on the dance floor in an attempt to
prevent both forager and receiver recruitment
dances occurring simultaneously. Thus, both these
additional signals were fine-tuning signals.
(4) Integration and connectedness
The above predictions are tentative at best. There
are many aspects of signaling behaviour and colony
functional integration that are not at all clear. For
instance, we do not understand how the overall rate
of signaling should vary with social complexity.
Complex societies may rely more on cues rather than
signals for direct feedback but they may also employ
modulatory signals. Increased cooperation and co-
ordination when tackling tasks in complex societies
may require more communication than in simple
societies. On the other hand, larger systems are more
homeostatic and are less prone to stochastic fluctu-
ations (thus requiring recruitment), than smaller
systems. The net effect of these various factors is
unknown. Sensing a cue is an act of communication
and possibly individuals of more complex societies
may test their environment very frequently, perhaps
more frequently than sensing signals: for example,
perhaps one waits to be antennated in a simple
society. Specificity of signals may vary with social
complexity. It is possible that simple societies use
generic ‘help me with my task ’ signals whereas more
complex societies with their reduced individual
230 Carl Anderson and Daniel W. McShea
behavioural flexibility, meaning individuals cannot
switch to all tasks, may need more specific signals
such as ‘help me with a task of class x’ (see
$lldobler & Carlin, 1987). This too is currently
Two aspects of signaling, however, are well
understood. The first aspect concerns the changes in
foraging strategy with increasing colony size (Section
IV). It is clear that ‘low complexity’ strategies such
as tandem running employ mechanical one-to-one
signals, and as the ‘complexity’ of the strategies
increases and more and more individuals are
involved in a foraging group, such as in mass
recruitment, these individuals are coordinated by
chemical signals with one-to-many effects, such as
trail pheromones. The second aspect concerns the
regulation of interaction rates with increasing colony
size. This solely concerns direct interaction among
individuals through antennation. Gordon (1999 b
and references therein; see also Mangel, 1995) have
shown that as group size increases ants reduce their
density in the nest which in turn reduces their per
capita interaction rate. Under the assumption that
environmental stimuli, such as the demand for a
task, increase roughly linearly with colony size,
theory predicts (see also Bonabeau, The
!raulaz &
Deneubourg, 1998a) and experiments show, that
ants should reduce their density to reduce per capita
interaction. The reason is that interaction rates are
expected to scale at a greater rate than environ-
mental stimuli (under random Brownian motion
they would scale as the square of the number of
individuals) and thus could swamp out the en-
vironmental stimuli effects.
More generally, connectedness is expected to be a
function of differentiation and of individual auton-
omy. Harvell (1994) pointed out that in polymorphic
marine invertebrate colonies, individuals specializing
for functions other than food gathering (in bryo-
zoans, polymorphs), tend to lose food-gathering
capability and therefore their activities must be
subsidised by the colony as a whole. In other words,
connections among individuals must be available for
sharing resources. On the other hand, Harvell (1994)
also raised the possibility that over-connectedness
may present a barrier to differentiation. She rejected
the notion ultimately, because it appears to be
falsified by the Siphonophora and the Hydroida, in
which polymorphism is high and individuals are
highly connected, sharing a common gut. However,
there are theoretical reasons to think that the notion
may be worth exploring further. Kauffman (1993)
has shown that in N-K Boolean networks, stable
cycles of activation emerge only at intermediate
levels of connectivity. More particularly, in organ-
isms, proper function in a specialist individual would
seem to require at least a modicum of isolation and
therefore a constraint on connectedness, in order to
limit outside interference with internal flows of
signals and materials. Thus, cell boundaries would
seem to be necessary to maintain cellular different-
iation; or, to put it another way, a prediction is that
syncytial forms should be less differentiated.
In this study, we have attempted to broaden our
understanding of social complexity in insect societies
and where possible to draw parallels with coloniality
at other hierarchical levels. Our study is organized in
a particular manner to tell a ‘story’ such that each
section is a consequence of changes in social
organization in the previous section(s). Thus, dif-
ferentiation (Section II) has implications for special-
ization (Section II) – the greater the differentiation,
the greater the specialization. In turn, both different-
iation and specialization have consequences for
intracolony conflict, totipotency and individual
constraint (Section III) – the larger and more
differentiated the society, the more specialized
individuals become such that a reduction in an
individual’s capacities may follow. The ability to
shift to a higher degree of cooperative activity when
tackling tasks (Section IV) is a direct consequence of
reduced intracolony conflict (Section III), colony
size and differentiation (Section II). Finally, in-
creased cooperation, specialization and spatial seg-
regation of activity in the nest require enhanced
coordination and functional integration (Section V).
We present the whole suite of social correlates in
Table 1 to summarise our findings and in the hope
that the high degree of interdependence and con-
nectedness among these correlates will be apparent.
One of our major themes has been the reduction of
complexity of lower-level individuals with increases
in social complexity. Our findings support Jaffe &
Hebling-Beraldo’s (1990, 1993) claims about insect
societies in this respect and we extend their argu-
ments with additional correlates, causal relationships
and parallels with other social entities. One reason
we consider it an especially significant trend is that
it runs contrary to the conventional wisdom (e.g.
Seeley, 1995: pp. 254–255) and perhaps contrary to
intuition as well. Another reason is that in most
231Individual versus social complexity
Table 3. Various ant species mentioned in the text assigned to five levels of complexity (first column). Some of the major
reasons for placing the particular individuals within a complexity class are given in the second column.This is a
subjective procedure in which consideration of different aspects may place species in different classes.The third column
shows mature colony size for the species and shows that colony size generally increases with complexity but there is large
variation due to other correlates such as work organization or totipotency.Colony sizes are taken from Beckers et al.
(1989), Table 3.2 of HoWlldobler & Wilson (1990), or Kaspari &Vargo (1995), except where indicated otherwise.
Degree of complexity
and species
Reasons for placing in particular
complexity level
Atta colombica Agriculture, polymorphism 1750000
Eciton burchelli Teams, polymorphism 825000
Oecophylla Teams, polymorphism 480000
Pheidole pallidula Teams, polymorphism 5000
Acromyrmex landolti Agriculture and polymorphism (but small colony size) 1000
Daceton armigerum Task partitioning, majors that cannot feed themselves 10000
Pogonomyrmex badius Polymorphism and trunk trails 4300
Camponotus truncatus Working as group (as living door) 50
Megaponera foetans Polymorphism and task partitioning 518
Aphaenogaster rudis Small colony size 303
Cataglyphis Autonomous individuals, no recruitment 5000
Colobopsis fraxinicola Small colony size, but guards at nest entrance 165a
Myrmica punctiventris Small colony size 86
Amblyopone pallipes Very small colony size and lack of division of labour 18b
Dinoponera quadriceps Small colony size, loss of queen caste, high intracolony conflict 89c
aWilson (1974); bTraniello (1978); cMonnin & Peeters (1999)
treatments of the advent of new hierarchical levels,
including the origin of multicellularity as well as of
complex societies, the focus has been on the
accompanying increase in complexity (e.g. Stebbins,
1969; Bonner, 1988; Maynard Smith & Szathma
1995). Indeed, it seems clear that complexity does
increase in these transitions in two senses. There is
the obvious increase in a hierarchical sense, simply
on account of the advent of a new level, but also an
increase in a non-hierarchical sense, on account of
the increase in number of different types of parts, i.e.
differentiation among individuals at the same level.
Here, we have drawn attention to the fact that
certain decreases are also expected to accompany
these increases, in particular, the number of different
functional capabilities of lower-level individuals – as
reflected in numbers of parts, physiological capacities
and distinct behaviours – is expected to decline. In
sum, the suggestion is that as the complexity of the
whole rises, the complexity of its components
decreases (presumably with some limits) (McShea,
in press a).
Exceptions to this general rule may occur and
may be worth further study for the insight they offer
into it. Possibilities include species in which in
individuals spend significant amounts of time away
from the nest working alone. This may be true of
species that fly to forage sites, such as bees and wasps
and thus cannot rely on interaction with other
colony members on some trail. For instance, the
evolution of the waggle dance in the honey bee
means that individuals can forage significantly
further from the nest and therefore are required to be
more individually capable (Beekman & Ratnieks,
Our treatment of social complexity is intentionally
agnostic on the subject of causes of complexity
change. That is, it seems clear that the correlations
we discuss and their tendencies to change in
particular ways with increasing social complexity,
could be understood as the product of selection and
thus throughout the discussion we have offered a
number of possible selective mechanisms (primarily
for heuristic purposes). However, non-selective
232 Carl Anderson and Daniel W. McShea
routes are also possible. In principle, for example,
behavioural differentiation could be the result of
self-organizing properties that emerge when colony
size passes some crucial threshold (Bonabeau et al.,
1997; Bonabeau, 1998 ; Camazine et al., in press).
Still, causes aside, it also seems clear that increases in
social complexity provide an opportunity for selec-
tion. That is, the increases in differentiation and
integration, as well as the losses of individual
functional capability, that accompany the formation
of a complex society, whatever their sources, produce
among individuals a condition of extreme depen-
dency, of shared fate, which in turn makes selection
at the level of the whole possible.
Also, our discussion has been agnostic on the
subject of evolutionary trends, on whether or not any
tendency exists for social complexity to increase. The
focus of many treatments of trends has been on
increases (Bonner, 1988; Maynard Smith &
!ry, 1995), but it is well known that decreases
also occur (e.g. Wcislo & Danforth, 1997). However,
no systematic study has been carried out to de-
termine whether increases occur more frequently
than decreases, either among the social insects or
among social metazoans generally (although see D.
W. McShea, in preparation). Moreover, we are
currently unable to demonstrate that ‘primitive ’ (in
the sense of lacking derived characters) equals
simple’, and ‘ advanced ’ (having many derived
characters) equals ‘complex ’. For instance, are
agrarian attine species, such as Atta and Acromyrmex,
both socially complex and more advanced? We
suspect that this is the case, but without a sufficiently
detailed phylogeny this is currently untestable. We
make a number of other predictions throughout the
study which are potentially testable – e.g. that
complex societies tend to construct their own nests,
and that ASC should decrease with colony size – but
for which there is currently insufficient data. (To
help readers less familiar with particular ant species,
in Table 3 we have placed a number of ant species
discussed above in five categories of social complexity
and given some reasons for their placement –
alternative reasons or a different focus could reorder
the list. Colony sizes are also reported to make the
point that this in general does correlate well with
social complexity but there is much variation.) Some
genera and species, such as Atta and Oecophylla have
been studied intensively, while others, such as
Amblyopone and Aphaenogatser have received far less
attention. It is not always the case that the research
has not been conducted, but that it has not been
published. Thus, we reiterate Tschinkel’s (1991)
plea for publication of sociometric data and, ideally,
the establishment of a social insect sociometric data
bank so that broad comparative studies, such as
ours, can be carried out and thus provide further
insights into sociality in insect societies.
(1) We review the relationships among various
correlates of social complexity and in particular
focus on ant colonies as an explicit ‘ test case ’.
(2) Social complexity is positively correlated with
differentiation among individuals. That is, individ-
uals in larger more complex societies may differ from
each other in three main ways: polymorphism
(caste), physiological specialization and behavioural
(3) Individuals in complex societies tend to be less
totipotent ’. That is, they are somehow restricted
from being generalist fully-functional individuals,
e.g. by not possessing functional ovaries, or by
possessing certain physiologically or morphologically
adaptations which favour them adopting certain
specialised roles in the colony.
(4) Complex societies, which tend to have rela-
tively little intracolony conflict, often tackle colony
tasks in a highly cooperative manner, e.g. by working
as groups or teams or using group foraging strategies
and constructing tailor-made nests.
(5) Complex societies tend to be ‘high tempo
comprising very active and fast-running individuals.
(6) Complex societies are highly ‘ integrated
involving a sophisticated and heterogeneous com-
munication network of signals and importantly,
modulatory signals and cues.
(7) Our conclusions support Jaffe & Hebling-
Beraldo’s (1990: p. 538) hypothesis that ‘ individuals
of highly social ant species are less complex than
individuals from simple ant species’.
We would like to thank the following for their helpful
comments and criticism during the preparation of this
manuscript: Ehab Abouheif, Andrew Bourke, Gabe
Byars, ‘Chuck’ Ciampaglio, Nigel Franks, Istva
Karsai, Kara O’Keefe, Philip Novack-Gottshall, Francis
Ratnieks, Airlie Sattler and Valerie Simon. C. A. was
supported by funds from the Department of Biology at
Duke University.
233Individual versus social complexity
Tempo,as measured by running speed (cm s") versus colony size in 26 species of ants.The species are grouped by
subfamilies from HoWlldobler & Wilson (1990: pp.919). Colony size data are taken from the running speed reference,
Beckers et al. (1989), Boomsma (1982), Table 3.2 of HoWlldobler & Wilson (1990), or Kaspari & Vargo (1995).
Where an expression relating running speed and worker size was given,e.g.Lighton et al., (1987), the mean or median
worker size was used.The data are plotted in Fig.1D and discussed in Section IV.6.
Species Colony size Running speed (cm s") and Reference
Eciton burchelli 425 000 5.2 Franks et al. (1991)
E.burchelli 425000 8.4 Franks (1986)
E.hamatum 300000 8.92 Bartholemew et al. (1988)
Acromyrmex lundi 1500 2.6 Roces (1993)
Aphenogaster rudis 145 1.02 Leonard & Herbers (1986)
Atta cephalotes 500000 3.78 Rudolph & Loudon, 1986
A.colombica 1750000 5.2 Lighton et al. (1987); Burd (1996)
Monomorium pharaonis 800 3.29 Ross, Shimabukuro & Dixon (1992)
Myrmica punctivientris 145 1.16 Leonard & Herbers (1986)
M.rubra 1000 1.1 Cammaerts et al. (1981)
M.ruginodis 2000 1.06 Cammaerts et al. (1981)
M.sabuleti 3000 0.72 Cammaerts et al. (1981)
M.scabrinodis 2000 0.96 Cammaerts et al. (1981)
Ocymyrmex barbiger 200 30.6 Marsh (1985)
Pogonomyrmex barbatus 12358 2.3 Morehead & Feener (1998)
P.desertorum 500 2.3 Morehead & Feener (1998)
P.maricopa 400 2.9 Weier et al. (1995)
P.occidentalis 3024 2.3 Morehead & Feener (1998)
P.rugosus 7740 3.95 Lighton & Feener (1989)
Veromessor pergandei 27500 3.64 Rissing (1982)
Camponotus hurculeanus 13376 2.0 Jensen & Holm-Jensen (1980)
Cataglyphis bicolor 2000 14.4 Wehner & Srinivasan (1981)
Formica aquilona 400000 1.4 Holt (1955)
F.fusca 500 2.7 Jensen & Holm-Jensen (1980)
F.lugubris 40000 3.2 Breen (1976)
F.polyctena 450000 2.3 De Bruyn & Kruk-De Bruin (1972)
F.rufa 150000 0.98 Holt (1955)
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... Task allocation can also result in individuals changing their main task over time. Task allocation in ants has been the subject of much previous work (Anderson & McShea, 2001;Gordon, 2016). Across ant species, studies have shown that, depending on the tasks and on the colony, ants may display varying degrees of task flexibility, from small colonies of totipotent ants to larger ones with a structured division of labour (Anderson & McShea, 2001). ...
... Task allocation in ants has been the subject of much previous work (Anderson & McShea, 2001;Gordon, 2016). Across ant species, studies have shown that, depending on the tasks and on the colony, ants may display varying degrees of task flexibility, from small colonies of totipotent ants to larger ones with a structured division of labour (Anderson & McShea, 2001). Factors affecting task changes can occur at the individual level or at the group level. ...
... Factors affecting task changes can occur at the individual level or at the group level. Individual level factors include physiology (Anderson & McShea, 2001), age (Tripet & Nonacs, 2004), corpulence (Robinson et al., 2009) and past experience (Ravary et al., 2007), whereas group level factors involve colony size (Ravary et al., 2007) and interaction rates at the colony level (Gordon & Mehdiabadi, 1999). Studying individual level factors associated with task change is often simpler than studying group level ones. ...
In animal societies, individuals may take on different roles to fulfil their own needs and the needs of their group. Ant colonies display high levels of organizational complexity, with ants fulfilling different roles at different timescales (what is known as task allocation). Factors affecting task allocation can be at the individual level (e.g. physiology), or at the group level (e.g. the network of interactions). We focus on group level processes by exploring the relationship between interaction networks, task allocation and task switching using a previously published data set (Mersch et al., 2013, Science, 340(6136), 1090–1093) tracking the behaviour of six Camponotus fellah colonies over 41 days. In our new analyses, our goal was to better explain the noisy process of task switching beyond simple age polyethism. First, we investigated the architecture of interaction networks using node (individual) level network measures and their relation to the individual's task – foraging, cleaning or nursing – and whether or not the ant switched tasks. We then explored how noisy information propagation was among ants, as a function of the colony composition (how many ants carried out which tasks), through the information-theoretic metric of ‘effective information’. Our results show that interaction history is tied to task allocation: ants that switched to a task were more likely to have interacted with other ants carrying out that task. The degree to which interactions related to task allocation, as well as the noise in those interactions, depended on which groups of ants were interacting. Overall, we found that colony cohesion was stable even as ant level network measures varied more for ants when they switched functional groups; thus, ant colonies maintained a high level of information flow as determined by network analysis, and ant functional groups played different roles in maintaining colony cohesion through varied information flows.
... Within a multicellular organism, phenotypic complexity is most often quantified as the number of cell types [3]. A eusocial insect colony, such as that of ants, bees, wasps and termites, is thought to be analogous to a superorganism with a reproductive queen caste functioning as its germline and non-reproductive worker caste functioning as its soma [4][5][6][7]. In solitary multicellular organisms, a single genome can produce differentiated cell types in response to cues from its internal environment, like morphogen gradients. ...
... Such species are considered more morphologically complex than species with limited worker body size variation (i.e. monomorphic worker castes) but less complex than species with discrete morphological castes, which vary tremendously in both size and head-to-body scaling (reviewed in [5]). Therefore, superorganisms fall along a continuum of phenotypic complexity that is governed by multiple-levels of selection, from individual to colony-level selection [7,9,14]. ...
... Solenopsis) and big-headed ants (e.g. Pheidole), comprise species with larger colony sizes (thousands to millions of ants within a colony), dramatic morphological differences between workers in the colony and enhanced division of labour [5]. Many of these same species have strong effects on the structure of food webs and ecosystems as dominant predators, herbivores and ecosystem engineers [21]. ...
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Biologists have long been fascinated by the processes that give rise to phenotypic complexity of organisms, yet whether there exist geographical hotspots of phenotypic complexity remains poorly explored. Phenotypic complexity can be readily observed in ant colonies, which are superorganisms with morphologically differentiated queen and worker castes analogous to the germline and soma of multicellular organisms. Several ant species have evolved 'worker polymorphism', where workers in a single colony show quantifiable differences in size and head-to-body scaling. Here, we use 256 754 occurrence points from 8990 ant species to investigate the geography of worker polymorphism. We show that arid regions of the world are the hotspots of superorganism complexity. Tropical savannahs and deserts, which are typically species-poor relative to tropical or even temperate forests, harbour the highest densities of polymorphic ants. We discuss the possible adaptive advantages that worker polymorphism provides in arid environments. Our work may provide a window into the environmental conditions that promote the emergence of highly complex phenotypes.
... Within a multicellular organism, phenotypic complexity is most often quantified as the number of cell types [3]. A eusocial insect colony, such as that of ants, bees, wasps and termites, is thought to be analogous to a superorganism with a reproductive queen caste functioning as its germline and non-reproductive worker caste functioning as its soma [4][5][6][7]. In solitary multicellular organisms, a single genome can produce differentiated cell types in response to cues from its internal environment, like morphogen gradients. ...
... Such species are considered more morphologically complex than species with limited worker body size variation (i.e. monomorphic worker castes) but less complex than species with discrete morphological castes, which vary tremendously in both size and head-to-body scaling (reviewed in [5]). Therefore, superorganisms fall along a continuum of phenotypic complexity that is governed by multiple-levels of selection, from individual to colony-level selection [7,9,14]. ...
... Solenopsis) and big-headed ants (e.g. Pheidole), comprise species with larger colony sizes (thousands to millions of ants within a colony), dramatic morphological differences between workers in the colony and enhanced division of labour [5]. Many of these same species have strong effects on the structure of food webs and ecosystems as dominant predators, herbivores and ecosystem engineers [21]. ...
Full-text available
Biologists have long been fascinated by the processes that give rise to pheno-typic complexity of organisms, yet whether there exist geographical hotspots of phenotypic complexity remains poorly explored. Phenotypic complexity can be readily observed in ant colonies, which are superorganisms with morphologically differentiated queen and worker castes analogous to the germline and soma of multicellular organisms. Several ant species have evolved 'worker polymorphism', where workers in a single colony show quantifiable differences in size and head-to-body scaling. Here, we use 256 754 occurrence points from 8990 ant species to investigate the geography of worker polymorphism. We show that arid regions of the world are the hotspots of superorganism complexity. Tropical savannahs and deserts, which are typically species-poor relative to tropical or even temperate forests , harbour the highest densities of polymorphic ants. We discuss the possible adaptive advantages that worker polymorphism provides in arid environments. Our work may provide a window into the environmental conditions that promote the emergence of highly complex phenotypes.
... Superorganisms represent an increase in biological complexity from solitary organisms, making them a common focus of complexity studies (Cole, 1985;Bonner, 1993;Szathmáry and Maynard Smith, 1995;Bourke, 1999;Anderson and McShea, 2001;Jeanson et al., 2012;Kennedy et al., 2017). In social insects the colony is the reproductive unit of the superorganism and complexity may scale with colony size in a manner similar to complexity scaling with body size or group size across other taxa (Bonner, 1993). ...
... Studies addressing the role of social structure in nervous system trait evolution often propose that social complexity, generally measured by colony size, will be negatively correlated with individual worker behavioral complexity (Anderson and McShea, 2001;Gronenberg and Riveros, 2009;O'Donnell et al., 2015) and hypothesize that relative brain investment, particularly in brain regions associated with more complex behaviors such as multi-modal learning and memory, will decrease with increasing colony size (Riveros et al., 2012;O'Donnell et al., 2015;Kamhi et al., 2016). However, individual workers of social species often show behavioral and cognitive skills comparable to solitary relatives (Gruter et al., 2011;Pasquier and Grüter, 2016;Hollis et al., 2017;Yilmaz et al., 2017), and comparisons seeking to link colony size with changes in brain structure may be complicated by confounding variables such as habitat differences or phylogenetic distance (Kamhi et al., 2016;Godfrey and Gronenberg, 2019b). ...
... Since the evolution of sociality involves an expansion of the type and number of relationships among conspecifics, it represents an increase in biological complexity from solitary life histories (McShea, 1996). Similarly, the number and type of interactions may also scale with group size across social species and have consequences for individual traits (Anderson and McShea, 2001), particularly those related to intraspecific recognition and communication (Dunbar, 1992). ...
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In social insects colony fitness is determined in part by individual worker phenotypes. Across ant species, colony size varies greatly and is thought to affect worker trait variation in both proximate and ultimate ways. Little is known about the relationship between colony size and worker trait evolution, but hypotheses addressing the role of social structure in brain evolution suggest workers of small-colony species may have larger brains or larger brain regions necessary for complex behaviors. In previous work on odorous ants (Formicidae: Dolichoderinae) we found no correlation between colony size and these brain properties, but found that relative antennal lobe size scaled negatively with colony size. Therefore, we now test whether sensory systems scale with colony size, with particular attention to olfactory components thought to be involved in nestmate recognition. Across three species of odorous ants, Forelius mccooki , Dorymyrmex insanus , and D. bicolor , which overlap in habitat and foraging ecology but vary in colony size, we compare olfactory sensory structures, comparing those thought to be involved in nestmate recognition. We use the visual system, a sensory modality not as important in social communication in ants, as a control comparison. We find that body size scaling largely explains differences in eye size, antennal length, antennal sensilla density, and total number of olfactory glomeruli across these species. However, sensilla basiconica and olfactory glomeruli in the T6 cluster of the antennal lobe, structures known to be involved in nestmate recognition, do not follow body size scaling observed for other structures. Instead, we find evidence from the closely related Dorymyrmex species that the larger colony species, D. bicolor , invests more in structures implicated in nestmate recognition. To test for functional consequences, we compare nestmate and non-nestmate interactions between these two species and find D. bicolor pairs of either type engage in more interactions than D. insaus pairs. Thus, we do not find evidence supporting a universal pattern of sensory system scaling associated with changes in colony size, but hypothesize that observed differences in the olfactory components in two closely related Dorymyrmex species are evidence of a link between colony size and sensory trait evolution.
... As with non-biological individuals, some have tried to define biological individuals in terms of spatial and temporal contiguity (Huxley, 1912;Hull, 1980;Anderson and McShea, 2001). ...
... There is a related cluster of individuality criteria relating to functional integration (Huxley, 1912;J.A. Wilson, 1999), physiological union (Anderson and McShea, 2001), metabolism and selfmaintenance (Maturana and Varela, 1981). In a distinct approach, some have preferred to rely on genetic concepts, especially genetic homogeneity and uniqueness as definitive of biological individuals (Simpson, 1957;Janzen, 1977;Santelices, 1999). ...
The biological world as we see it today has a part-whole hierarchical structure. For example, eusocial societies are made up of many organisms, multicellular organisms are made up of many cells, those cells contain numerous organelles and so on. This hierarchical organisation is thought to have evolved over a long period of time in a series of events known as ‘evolutionary transitions in individuality’. Evolutionary transitions present an interesting challenge for evolutionary theory because they involve changes in the hierarchical level at which the evolutionary process itself acts. This thesis is intended as a contribution to theoretical work aiming to explain such transitions in the hierarchical structure of life. Evolutionary transitions are extreme cases of the evolution of cooperation. Social evolution theory is the part of evolutionary theory that tries to explain the evolution of cooperation. It typically takes an externalist explanatory stance, explaining cooperative behaviour in terms of external factors (e.g. genetic relatedness) that make cooperation sustainable. In this thesis, I move from an externalist to an interactionist explanatory stance, in the spirit of Lewontin and the niche construction theorists. I develop the theory of social niche construction, which has it that biological entities are both the subject and object of their own social evolution. That is, the niche in which social behaviour occurs is not entirely externally defined but is partly modified by the organisms in it. Then, cooperation and the social niche modifier traits supporting it can each evolve as evolutionary responses to the other. This claim is supported by detailed argument and by simulation modelling. Some important social niche modifiers enabling cooperation (e.g. life-history bottlenecks) have the side-effect of raising the hierarchical level at which the evolutionary process acts. This is because modifier traits acting to align the fitness interests of lower-level units (e.g. cells) in a collective also diminish the extent to which those units are bearers of heritable fitness variance, while augmenting the extent to which collectives of such units (e.g. multicellular organisms) are bearers of heritable fitness variance. So while there is no selection-for evolutionary transitions in individuality, there is selection-of the sufficient conditions for transitions to occur. My explanation for evolutionary transitions is couched only in terms of evolutionary self-interest of the lower-level units, so avoiding many of the problems that befall alternative accounts.
... For ants, colony defence depends on the number of workers and features such as worker aggression, morphology and stings or other chemical weapons, as well as structural defence of the nest Species with large, polydomous colonies are also more likely to by polygynous (i.e., have multiple queens). Polygyny is in turn correlated with dependent colony founding and ecological dominance (Boulay et al. 2014) and hypothesised to be associated with morphological differentiation in the worker caste (worker polymorphism) (Bourke 1999;Anderson & McShea 2001), with fast-growing colonies investing more in soldier castes (Kaspari & Byrne 1995). Further, polygyny may facilitate social parasitism because colonies accept returning young queens (Buschinger 1990). ...
Current global challenges call for a rigorously predictive ecology. Our understanding of ecological strategies, imputed through suites of measurable functional traits, comes from decades of work that largely focussed on plants. However, a key question is whether plant ecological strategies resemble those of other organisms. Among animals, ants have long been recognised to possess similarities with plants: as (largely) central place foragers. For example, individual ant workers play similar foraging roles to plant leaves and roots and are similarly expendable. Frameworks that aim to understand plant ecological strategies through key functional traits, such as the “leaf economics spectrum”, offer the potential for significant parallels with ant ecological strategies. Here, we explore these parallels across several proposed ecological strategy dimensions, including an “economic spectrum”, propagule size‐number trade‐offs, apparency‐defence trade‐offs, resource acquisition trade‐offs and stress‐tolerance trade‐offs. We also highlight where ecological strategies may differ between plants and ants. Further, we consider how these strategies play out among the different modules of eusocial organisms, where selective forces act on the worker and reproductive castes, as well as the colony. Finally, we suggest future directions for ecological strategy research, including highlighting the availability of data and traits that may be more difficult to measure, but should receive more attention in future to better understand the ecological strategies of ants. The unique biology of eusocial organisms provides an unrivalled opportunity to bridge the gap in our understanding of ecological strategies in plants and animals and we hope that this perspective will ignite further interest.
... The applicability of social brain theory as developed for vertebrates to eusocial insects has thus been questioned (Lihoreau et al., 2012;Farris, 2016). Here we use the term social complexity as a working concept consistent with Anderson and McShea (2001): socially complex ants have large colony size, worker polymorphism and division of labor, and collective foraging strategies. Dornhaus et al. (2012) further discuss how collective organization may scale with colony size. ...
... Such significant differences between queenright and queenless nests of E. ruidum sp. 2 could be related to the extreme shallowness of the Colombian nest in comparison to other known populations from Mexico, Costa Rica, and Panama and could account for the polydomic nesting strategy observed in the population studied [6,[47][48][49]. Nest size and, consequently, the number of chambers in which the nest population is segregated, may have important implications for the potential reproductive control by the queen because the fewer the chambers, the greater the diffusion of any regulatory pheromones released by the queen [82]. Some degree of functional inhibition, presumably of pheromonal origin, has been shown to occur in polygynous Mexican populations of E. ruidum sp. 2 [75,77]. ...
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Nest architecture plays a fundamental role in the adaptation of ants to their habitat, favoring the action of economically important species. Ectatomma ruidum sp. 2 (ruidum species complex) is a biological control agent in Neotropical agroecosystems, exhibiting high bioturbation impact due to high nest densities. The architecture and composition of 152 nests were studied in two Andean populations of southwestern Colombia, 24 of them being cast using the paraffin wax technique. Nest entrance was a single, circular, 4 mm hole at ground level, without any special external structure, connected to a single vertical tunnel communicating with successive half ellipsoidal chambers. Nests were extremely shallow (depth range: 28.7-35.4 cm), with an average of six chambers and an overall volume of 92.2 cm3 per nest. The deeper the chamber, the smaller its volume. Nest building was independent of plants or roots, and no surface or underground physical connections were found between neighboring nests. Few nests possessed a queen, and neither ergatoids nor microgynes were recorded. Despite significant interactions between localities and the number of both males and workers, queen presence had an overall highly positive effect on the number of workers and larvae and a negative one on the number of gynes. Overall, the studied Colombian populations of E. ruidum sp. 2 retained the simple nest structure described for other species of this species complex and for colonies of the same species from other geographical areas, though they constrasted in their extreme shallowness. Our data suggest that E. ruidum sp. 2, at the local level, does not follow the usual monodomic pattern of this species with facultative polygyny but, rather, has a polydomic pattern with monogyny, perhaps related to the extreme shallowness of the nests due to soil structure, which could significantly enhance the queen's reproductive inhibition previously reported for this species.
Significance A central problem in evolutionary biology is explaining variation in the organization of task allocation across collective systems. Why do human cells irreversibly adopt a task during development (e.g., kidney vs. liver cell), while sponge cells switch between different cell types? And why have only some ant species evolved specialized castes of workers for particular tasks? Although it seems reasonable to suppose that such differences reflect, at least partially, the different ecological pressures that systems face, there is no general understanding of how a system’s dynamic environment shapes its task allocation. To this end, we develop a general mathematical framework that reveals how simple ecological considerations could potentially explain cross-system variation in task allocation—including in flexibility, specialization, and (in)activity.
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The evolution of eusociality in social insects, such as termites, ants, and some bees and wasps, has been regarded as a major evolutionary transition (MET). Yet, there is some debate whether all species qualify. Here, we argue that worker sterility is a decisive criterion to determine whether species have passed a MET (= superorganisms), or not. When workers are sterile, reproductive interests align among group members as individual fitness is transferred to the colony level. Division of labour among cooperating units is a major driver that favours the evolution of METs across all biological scales. Many METs are characterised by a differentiation into reproductive versus maintenance functions. In social insects, the queen specialises on reproduction while workers take over maintenance functions such as food provisioning. Such division of labour allows specialisation and it reshapes life history trade-offs among cooperating units. For instance, individuals within colonies of social insects can overcome the omnipresent fecundity/longevity trade-off, which limits reproductive success in organisms, when increased fecundity shortens lifespan. Social insect queens (particularly in superorganismal species) can reach adult lifespans of several decades and are among the most fecund terrestrial animals. The resulting enormous reproductive output may contribute to explain why some genera of social insects became so successful. Indeed, superorganismal ant lineages have more species than those that have not passed a MET. We conclude that the release from life history constraints at the individual level is a important, yet understudied, factor across METs to explain their evolutionary success.
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Self-organization was introduced originally in the context of physics and chemistry to describe how microscopic processes give rise to macroscopic stuctures in out-of-equilibrium systems, Recent research that extends this concept to ethology suggests that it provides a concise description of a wide range of collective phenomena in animals, especially in social insects. This description does not rely on individual complexity to account for complex spatiotemporal features that emerge at the colony level, but rather assumes that intractions among simple individuals can produce highly structured collective behaviours.
The honeybee (Apis melli/era L. ) is one of the better studied organisms on this planet. There are plenty of books on the biology of the honeybee for all, the scientist, the beekeeper, and the layman. In view of this flood of publications one is tempted to ask: why does it require another one? The answer is simple: a new one is not required and we do not intend to present a new book on "the honeybee". This would really just add some more inches to the already overloaded bookshelf without sub­ stantial new information. Instead, we intend to present a book on the honeybee colony. This of course immediately releases the next question: so what is the difference? Although the difference may look insignificant at first glance, we try to guide the reader with a fundamentally different approach through the biology of honeybees and eusocial insect societies in general. The biology of individual colony members is only addressed when it is necessary to explain colonial mechanisms, and the colony as a whole, as a biological unit, which is the main focus of this treatise. Both of us felt that all current textbooks on bee biology put too much emphasis on the individual worker, queen or drone in the colony. Often it is com­ pletely neglected that the colony is a very significant (if not the most significant) biological structure in bee biology.