1 Title page
2 New research frameworks in the study of chimpanzee and gorilla
3 sociality and communication
4 Running Title: Chimpanzee and gorilla sociality
5 Sam George Bradley Roberts1*†, Anna Ilona Roberts2*†
6 Affiliations:
7 1School of Natural Sciences and Psychology, Liverpool John Moores
8 University, Byrom Street, Liverpool, L3 3AF
9 2Department of Psychology, University of Chester, Chester; Parkgate
10 Road, Chester CH1 4BJ, UK
11 *Correspondence to: [email protected],
12 [email protected] ,
13 †Equally contributing authors
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2 23Abstract
24Group size in primates is strongly correlated with brain size, but exactly
25what makes larger groups more ‘socially complex’ than smaller groups is
26still poorly understood. Chimpanzees (Pan troglodytes) and gorillas
27(Gorilla gorilla) are among our closest living relatives and are excellent
28model species to investigate patterns of sociality and social complexity in
29primates, and to inform models of human social evolution. The aim of this
30paper is to propose new research frameworks, particularly the use of
31social network analysis, to examine how social structure differs in small,
32medium and large groups of chimpanzees and gorillas, to explore what
33makes larger groups more socially complex than smaller groups. Given a
34fission-fusion system is likely to have characterised hominins, a
35comparison of the social complexity involved in fission-fusion and more
36stable social systems is likely to provide important new insights into
37human social evolution.
38Keywords: sociality, communication, social network analysis,
39chimpanzees, gorillas
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50Introduction
51 One of the distinctive features of primates is that they have
52unusually large brains for their body size (Jerison, 1973). The social brain
53hypothesis proposes that the social world of primates is especially
54complex, and that this has imposed selection pressure for increasingly
55large brains. Group size in primates is strongly correlated with brain
56size, and specifically with neocortex size in relation to the rest of the
57brain (R. I. M. Dunbar, 1998). Thus, primates living in larger groups have
58larger neocortex ratios. However, exactly what makes larger groups
59more ‘socially complex’ than smaller groups is poorly understood. The
60social brain hypothesis itself is based on the relationship between social
61complexity (i.e. managing a more complex network of social
62relationships) and neocortex size, not simply on the quantitative
63relationship between group size and brain size (Manninen et al., 2017).
64 To date most of the studies which examined primate social
65complexity and cognitive ability have used the approach of comparing the
66neocortex ratio to group size, or the neocortex ratio to behaviours
67thought to be indicative of social complexity such as tactical deception,
68complex male mating strategies or social play (R. I. Dunbar & Shultz,
4 692007; Graham, 2011; Manninen et al., 2017). However, group size is a
70relatively crude measure of social complexity, and does not provide a
71detailed explanation of why larger groups are more complex than smaller
72ones, or of how the way in which the group is structured affects the
73number and types of relationships an individual primate has to keep
74track of (Aureli & Schino, 2019). Further, examining how individual
75behaviours are related to the neocortex ratio is a piecemeal approach,
76and only focuses on a limited number of the many behavioural
77interactions that go into forming complex social relationships.
78 The purpose of this paper is to review research in a newly
79emerging field of social and communicative complexity of primates and
80identify key areas for future research. First, we examine how social
81structure differs in small, medium and large groups of chimpanzees and
82gorillas to explore what makes larger groups more socially complex than
83smaller groups. Second, we explore how these variations in social
84structure in different size groups are affected by the social organisation
85of the species. Chimpanzees are characterised by a fluid fission-fusion
86social system (Goodall, 1986), whereas gorillas have more stable,
87cohesive groups (D. M. Doran & McNeilage, 1998). Social network
88analysis provides a novel way to describe and compare social
89relationships and social structure (Koyama, Ronkainen, & Aureli, 2017;
90Krause, Lusseau, & James, 2009; Sueur, Jacobs, Amblard, Petit, & King,
912011). Examining these links will therefore lead to a novel, systematic
92way of comparing social structure and social complexity in humans,
93primates and other animals, something that is sorely lacking in current
5 94comparative studies of social structure. Given a fission-fusion system is
95likely to have characterised hominins, a comparison of the social
96complexity involved in fission-fusion and more stable social systems will
97provide new insights into human social evolution (Filippo Aureli et al.,
982008; Foley & Gamble, 2009).
99 Specific objectives
100 Social systems vary in the degree of temporal and spatial stability
101shown in group size and composition. Fission-fusion social systems have
102subunits (known as parties or subgroups) that change in size by means of
103the fission and fusion according to both the activity (e.g. resting, feeding)
104and distribution of resources (F. Aureli et al., 2008). Thus fission-fusion
105dynamic refers to the extent of variation in spatial cohesion and
106individual membership in a group over time. Gorilla groups have a low
107degree of fission-fusion dynamics in that the membership of the group is
108stable temporally and spatially, and thus all individuals will typically
109encounter every member of the group every day (D. M. Doran &
110McNeilage, 1998; Robbins & Robbins, 2018). The majority of gorilla
111groups consist of one adult male (although up to four males may be
112present in a group) and a number of unrelated females, plus juveniles
113and infants. The mean group size is 9, with a range of 2 to 34. The groups
114are cohesive, with the strongest bonds between the adult females and the
115silverback. Gorillas are folivores, and because they rely on an abundant,
116easily available food resource, there is little competition between groups
117and home ranges are typically small, between 3 and 15 km2(D.M. Doran &
118McNeilage, 2001; Robbins & Robbins, 2018).
6 119 In contrast chimpanzee groups have a high degree of fission-fusion
120dynamics (Goodall, 1986; Lehmann & Boesch, 2004). Individuals form
121socially and geographically circumscribed communities, within which
122they associate in temporary subgroups (‘parties’) that vary in size,
123composition and duration. The community size can range from 20-150,
124and the community as a whole is rarely seen together in one place
125(Goodall, 1986; Lehmann & Boesch, 2004; Reynolds, 2005a).
126Chimpanzees are frugivores and communities defend a communal home
127range, which is typically much larger than that of gorillas, ranging from
1285-35 km2. Individuals in the wider community may thus only see each
129other at infrequent intervals, often weeks apart, but each individual can
130recognise members of their own community and is capable of
131maintaining long-term relationships with these individuals (Goodall,
1321986; Reynolds, 2005b).
133 Thus chimpanzees (frugivores with a fluid fission-fusion system)
134and gorillas (folivores with stable, cohesive groups) are at opposite ends
135of a continuum of ape dietary and social patterns. A review of gorilla and
136chimpanzee sociality therefore offers an ideal opportunity to examine
137both how the patterns of association between individuals changes with
138increasing group size, and how the underlying social structure affects
139these changes in patterns of association. Increasing group size in a
140gorilla group will result in individuals simply encountering more
141individuals each day, whereas increasing community size in the
142chimpanzee will result in the chimpanzee having to keep track of more
143indirect relationships with whom interaction may be infrequent. How
7 144gorillas and chimpanzees adjust their social strategies and patterns of
145association in groups of differing sizes is thus informative of the key
146cognitive and time-budget pressures involved in sociality (Aureli &
147Schino, 2019; Freeberg, Dunbar, & Ord, 2012).
148 As well as furthering our understanding of primate sociality,
149understanding the social structure of systems with varying degrees of
150fission-fusion dynamics is of crucial importance for understanding the
151course of human social evolution (Foley & Gamble, 2009). Fission-fusion
152dynamics characterise chimpanzee and bonobos, and also are typical of
153modern-day hunter-gatherers. This suggests that fission-fusion dynamics
154were characteristic of the social system of the last common ancestor of
155chimpanzees, bonobos and modern humans (F. Aureli et al., 2008; Foley
156& Gamble, 2009). Further, a general trend in the course of human
157evolution is an increase in brain size, and this is likely to have been
158accompanied by a corresponding increase in social group size (L. C.
159Aiello & R. I. M. Dunbar, 1993). Thus understanding the complexity
160involved in fission-fusion systems, as compared to more stable social
161groups, and how this complexity changes in groups of different sizes, will
162help us understand the processes involved in social evolution in our
163hominin ancestors (R. Dunbar, Gamble, & Gowlett, 2014; Foley &
164Gamble, 2009).
165Social networks and group size in gorillas
166Within primates, large groups are assumed to be more socially complex
167than small groups, as there are more relationships to track, and
8 168individuals must spend an increasing amount of their time servicing their
169social relationships in order to enable large groups to function as stable,
170functional cohesive units (R. I. Dunbar & Shultz, 2007; Manninen et al.,
1712017). However, there is currently no standard way to compare social
172complexity across groups of different sizes, and we have little
173understanding of how the patterning of social relationships changes with
174increasing group size (R. I. Dunbar & Shultz, 2010). Gorilla groups vary
175greatly in size, with a range of 2-43 (D.M. Doran & McNeilage, 2001;
176Robbins & Robbins, 2018). Future research could collect data on a
177number of behavioural interactions (e.g. grooming, vocalisations,
178gestures, proximity, visual attention) in small, medium and large groups
179of gorillas and carry out three main sets of network analyses. First,
180features of the overall network structure (e.g. connectedness, density)
181and the extent to which there are sub-structures within the overall
182network should be examined in the three groups. Thus larger groups of
183gorillas, especially those with more than one adult male, may be more
184likely to contain sub-groups. Network analysis is an ideal way of
185statistically identifying and characterizing such sub-groups, which are
186defined as nodes that are more densely connected to themselves than
187they are to other nodes in the network (Croft, James, & Krause, 2008).
188Second, the extent to which the networks based on the different types of
189behavioural interactions overlap may be explored. There is a limit on the
190time available for grooming, so as group size increases, we predict that
191there will be an increasing dissociation between networks based on
192grooming and networks based on vocal and gestural communication, as
9 193gorillas use communication rather than grooming to maintain their
194relationships. Third, use of network analysis would identify how age, sex
195and dominance rank affect the patterning of social relationships, and the
196roles that different individuals play in the group as a whole. Adult social
197bonds in gorilla groups are strongest between females and silverbacks,
198with the females in the group associating less regularly with each other
199(D.M. Doran & McNeilage, 2001; Robbins & Robbins, 2018). Network
200analysis allows precise quantification and statistical analysis of sex
201differences in the network characteristics and position of adult females
202and males. This type of data will lead to a comprehensive, quantitative
203understanding of the network structure of gorillas groups, how gorillas
204use different modes of interaction to manage their social relationships,
205the different roles the sexes play in gorilla groups and how this changes
206with increasing group size.
207Social networks and group size in chimpanzees
208Chimpanzees live in a fission-fusion society, where individuals form
209socially and geographically circumscribed communities, within which
210they associate in temporary subgroups (parties) that vary in size,
211composition and duration (Lehmann & Boesch, 2004; Mitani, Watts, &
212Muller, 2002). Because of this dynamic and fluid social structure,
213discerning regularities in grouping, dispersal, range use and associations
214is more challenging for chimpanzees than for primates that live in
215temporally and spatially stable groups such as gorillas (Aureli & Schino,
2162019). Thus the internal structuring of chimpanzee communities, how
10 217this varies with group size and variations in sex differences in association
218patterns are all still poorly understood. Network analysis offers a
219powerful set of tools for characterising and analyzing individual
220associations within a population-level social context, and is particularly
221valuable in characterising complex fission-fusion social systems (Sueur et
222al., 2011). Chimpanzee community size can range from 20-150 (Lehmann
223& Boesch, 2004), and it would be valuable to explore how social networks
224vary in small, medium and large communities of chimpanzees. Particular
225attention may be given to identifying sub-structures within the wider
226community of chimpanzees, as it is possible that the very large
227communities of chimpanzees in fact consist of a number of sub-
228communities only loosely linked together. This has important implications
229for determining how many relationships an individual chimpanzee has to
230keep track of, and thus how cognitive complexity increases as group size
231increases (Aureli & Schino, 2019). As with gorillas, how the position and
232network characteristics of individual vary by age, sex and dominance
233rank may be explored. Traditionally, male chimpanzees have been seen
234as more gregarious than females, forming strong bonds with other males
235and distribute their activities more widely over their territories than
236females (Mitani et al., 2002). Females, in contrast are often portrayed as
237less sociable, and spending most of their time with their own offspring,
238except when they are in oestrus. However, there is considerable variation
239in the extent of the sex differences in sociality in different populations of
240chimpanzees (Lehmann & Boesch, 2008). By exploring the extent to
241which position and network characteristics vary by sex, this can precisely
11 242identify the different roles male and female chimpanzees play in the
243wider community, the extent of variation between individuals in these
244characteristics, and how this varies with group size. This would provide
245new network methods to analyse chimpanzees’ complex sociality, and
246provide new insights into the cognitive challenges imposed by living in a
247fission-fusion system.
248Comparison of social networks in gorillas and chimpanzees
249Chimpanzees and gorillas are among our closest living relatives, and they
250exhibit remarkable diversity in various aspects of their social
251organisation both within and between species. Gorillas are folivores and
252their groups exhibit a low degree of fission-fusion dynamics in the
253membership of the group is stable temporally and spatially. In contrast
254chimpanzees are frugivores with a high degree of fission-fusion
255dynamics. Thus a comparison of social structure in chimpanzees and
256gorillas provides an ideal opportunity to explore the implications of
257increasing group size for increased levels of social complexity, and how
258this is affected by the social organisation of the species. This would
259provide important insights into the nature and evolution of primate
260sociality. Comparisons between the two species can be made of the
261nature of the networks themselves, the extent to which the networks
262based on the different types of behavioural interactions overlap, the
263extent to which the groups or communities are based on a number of
264distinct sub-groups, and how the position and network characteristics of
265individuals vary by age, sex and dominance rank. Due to the differences
12 266in social organisation, an increase in group size in gorillas results in them
267interacting with more individuals on a daily basis, whereas an increase in
268group size in chimpanzees results in them having to manage more
269indirect relationships with individuals they may only see occasionally.
270Tracking these indirect relationships is hypothesised to be cognitively
271demanding, as in fission-fusion systems individuals must be able to retain
272and manipulate information about others whom they see only
273infrequently, as compared to systems with groups that are stable
274spatially and temporally where members see each other every day (Aureli
275& Schino, 2019; Barrett, Henzi, & Dunbar, 2003). By comparing two
276social networks in species with different forms of social organisation, and
277how these networks vary with group size, the cognitive demands of living
278in different social systems, and in groups of different sizes, can be
279determined. For example, how frequently do chimpanzees actually
280encounter other members of the community, what sort of interactions do
281they have with these other individuals (grooming, proximity, vocal and
282gestural communication), how does this vary with group size and
283network structure, and how does this compare with gorillas?
284Stress hormones, social networks and group size in chimpanzees
285and gorillas
286A key part of examining social complexity is determining the extent to
287which increases in group size produces social stress for individual
288primates. Sociality can impose stress due to competition for resources
289such as food and mates, and thus living in large groups is predicted to be
13 290more demanding than living in smaller groups. Glucocorticoid (GC) is a
291hormone excreted in response to stress, and although in the short term,
292an increase in GC levels increases energy levels and can trigger
293behaviour which helps primates cope with environmental and social
294challenges, chronic stress can lead to reduced survival, fecundity and
295immunity (David H Abbott et al., 2003). Glucocorticoid levels provide an
296objective way to estimate primates overall physiological well-being in
297different social circumstances, which can be used to complement
298measures based on behavioural data such as social affiliation patterns (D.
299H. Abbott et al., 2003). One of the primary mechanisms to offset stress,
300both in humans and primates, is social affiliation (Robin I.M. Dunbar,
3012010). GC levels in wild primates are sensitive to stressful events, such
302as the entry of a new male into the group, bringing a risk of infanticide
303(Crockford, Wittig, Whitten, Seyfarth, & Cheney, 2008). Further, female
304baboons with a less diverse grooming network - meaning that they
305focused a greater proportion of their grooming effort on a smaller
306number of social partners - showed a faster decrease in levels of GC after
307the stressful event than females with a more diverse grooming network
308(Wittig et al., 2008).
309This suggests how primates manage their social relationships can have a
310significant effect on their levels of stress, as measured by GC levels.
311However, it is currently not known how GC levels vary with group size in
312chimpanzees or the gorillas, with large groups predicted to be more
313stressful and thus resulting in higher GC levels. Further, individual
314variation in how primates adjust their social strategies in larger groups
14 315may affect their GC levels. For example, some individuals may adjust to
316an increase in group size by increasing their number of grooming
317partners, whereas others may actually reduce their number of grooming
318partners, and focus on their few key allies. Based on previous research
319(Crockford et al., 2008), it may be predicted that the latter strategy
320would be more effective in reducing stress, leading to lower GC levels.
321An important area of future research would be to examine how group
322size (small, medium and large groups of gorillas and chimpanzees), and
323individual variations in the pattern of social relationships, affects GC
324levels. This would give an objective, biological indicator of the social
325stress imposed by living in groups of different sizes, and thus provide
326important insights into the fitness consequences of sociality in primates
327(David H Abbott et al., 2003).
328Repertoire size and group size in chimpanzees and gorillas
329Through hominin evolution there has been an increase in both brain size
330and this is likely to have been accompanied by an increase in group size
331(L.C. Aiello & R.I.M. Dunbar, 1993). Dunbar (1993; R. Dunbar, 2012) has
332argued that the pressure to maintain larger social groups through
333hominin evolution may have driven the evolution of language as a novel
334social bonding mechanism that is more time efficient than grooming.
335Between primate species, it has been shown that evolutionary increases
336in the size of the vocal repertoire in non-human primates were associated
337with increases in both group size and also time spent grooming (McComb
338& Semple, 2005). This suggests that vocal communication may indeed
15 339play a key role in the evolution of social behaviour - larger groups are
340more complex to manage, and thus require a larger repertoire to
341maintain an increasing number of differentiated relationships. However,
342it is increasingly being recognised that gestural communication also
343plays a key role in regulating social behaviour, and the role of gestural
344communication in wild primates in relation to sociality is still unclear
345(Byrne et al., 2017; S. G. B. Roberts & Roberts, 2016). Future research
346could examine how both gestures and vocalisations in chimpanzees and
347gorillas are related to group size. There is currently an active debate as
348to whether human language evolved from vocal or gestural
349communication(M. Corballis, 2009; M. C. Corballis, 2017; McComb &
350Semple, 2005), and how the usage and repertoire size of gestural and
351vocal communication varies with group size will provide important
352insights into this debate.
353Intentionality and socio-ecology in chimpanzees and gorillas
354In intentional communication behaviour of the sender must involve a goal
355and some flexibility in the means for attaining it (Tomasello & Call,
3561997). This may be operationalised in the form of goal persistence,
357means-ends dissociation or sensitivity of the signaller to the recipient’s
358attentional state when emitting acts of communication. While
359intentionality of communication and especially gestures using criteria
360such as signaller’s responses to attentional state of recipients has been
361relatively well established (D. A. Leavens & Hopkins, 1998; D. A.
362Leavens, Hopkins, & Bard, 1996; Liebal, Call, & Tomasello, 2004; Liebal,
16 363Pika, & Tomasello, 2004, 2006; Pika, Liebal, & Tomasello, 2003, 2005),
364communication flexibility in response to social and ecological factors has
365received limited research attention and degree to which individuals can
366take into account socio-ecological conditions when communicating is
367poorly understood. Chimpanzees and gorillas are among our closest
368living relatives (Reynolds, 2005a; Taylor & Goldsmith, 2003) and they
369show important behavioural responses to the effects of social and
370ecological factors in various aspects of their social behaviour (Boesch,
371Hohmann, & Marchant, 2002). To what extent the social and
372environmental constraints will be reflected in flexibility of communication
373in chimpanzees and gorillas is thus of particular interest.
374According to the current studies of communication in primates, flexibility
375in communication may be expressed in a number of behavioural
376characteristics such as influence of the attentional status of an observer
377on the propensity to communicate and goal persistence of a signaler in
378face of apparent communicative failure (Byrne et al., 2017). Research to
379date has thus shown flexibility in use of gestures in relation to various
380behavioural characteristics (Hobaiter & Byrne, 2011; A. I. Roberts &
381Roberts, 2018). However, it seems reasonable to assume that such
382flexibility will also emerge in response to social and ecological factors
383such as food type and availability, habitat characteristics and degree of
384risks that may act directly upon communication. In habitats with low
385transmission properties (e.g. low light intensity, high habitat density,
386high background noise), primates may gesture less frequently or adapt
387communication modality to the transmission properties of habitat (see
17 388e.g. Hoedl & Amezquit, 2001). For instance, with declining light intensity
389and increasing habitat density, the communication may be less effective
390at influencing the recipient and thus primates may gesture less
391frequently or increase effectiveness of signalling by increasing the rate of
392vocalisations, or more intense auditory gestures at expense of less
393intense visual signalling. With increasing intensity of background noise,
394there may be increase in the frequency of visual gestures and/or a
395decrease in the frequency of auditory gesturing.
396Furthermore, where risks of detection and injury are high primates may
397aim to avoid detection by predators or other individuals which would
398pose risk of injury or death by adopting more criptic behaviour (e.g.
399decrease frequency of vocalisations and auditory gestures and/or
400increase rate of tactile and visual gestures) (see e.g. Croes et al., 2006).
401Again, this use would depend on efficiency of communication in eliciting
402behavioural response. Thus, if communication is likely to be
403unsuccessful, primates may defer from trying to avoid detection and
404avoid social interaction altogether. For instance, low ranking
405chimpanzees use auditory gestures when in full view of the dominant
406male to elicit mating from the female. These attempts are often
407unsuccessful and therefore chimpanzees gesture least frequently in these
408contexts. However, when the visual attention of the dominant male is
409directed elsewhere chimpanzees use visual gestures to elicit mating and
410in these contexts they are most likely to elicit mating. Thus, the
411propensity to modify communication to avoid detection in mating
18 412contexts would be contingent upon the assessment of the potential
413success of these types of signalling (A. I. Roberts & Roberts, 2015).
414In addition, degree of risk may also affect communication indirectly by
415influencing sociospatial organisation depending on the contexts (e.g.
416party size and composition, spread, spatial geometry and proximity). For
417instance, research has shown that in areas where risk of mortality or
418injury is high vulnerable individuals may stay in closer proximity to a
419dominant ‘protector’ males, party spread may be reduced and proximity
420between individuals increased (Altmann, 1979; DeVore & Washburn,
4211963; Hockings, Anderson, & Matsuzawa, 2006; Otali & Gilchrist, 2006;
422Reynolds, 1963). Food type, availability and temperature are another
423factor that may influence communication because it can influence the
424surplus of energetic resources that are available to the signaller and that
425may be diverted into socialisation and communication with the partners.
426The combined direct and indirect influences of socio-environmental
427conditions influence the number and type of viable signal recipients,
428which may be reflected in the type and frequency of communication used
429by a signaller. For instance, with increasing number of potential
430recipients in close proximity and in mutual visual contact with the
431signaller there would be increase in total frequency of communication
432used by signallers such as intention movements. Alternatively, when
433proximity or mutual visual contact between signaller and recipient is low,
434absence of reliable signal recipients may be associated with a reduction
435in communication and especially visual gestures and a corresponding
436increase in attention getters such as auditory or tactile gestures and
19 437vocalizations. Thus, when spatial cohesion is high or low one may see
438effects on choice of communication.
439Furthermore, relatively little is known about flexibility in contextual
440usage of communicative behaviours and the existing studies examined
441usage of communication in subadult individuals (see e.g. Liebal, Call, et
442al., 2004; Plooij, 1978, 1979). However, it is important to examine
443communication use by adult primates because observed flexibility in use
444of communication in subadult subjects may be a product of ontogenetic
445processes. For instance, in the vocal domain young individuals
446overgeneralise eliciting stimuli and only later they learn to produce
447vocalisations in appropriate contexts (Fischer, Cheney, & Seyfarth, 2000;
448Fischer, Hammerschmidt, Cheney, & Seyfarth, 2002). Contextual usage
449may be influenced by social factors by influencing specificity of
450communication required to effectively manage social relationships. For
451instance, in smaller groups or parties primates may use low intensity
452communication of which meaning may be determined from context. On
453the other hand, in larger groups or parties, use of more intense and
454specific signalling may be more effective without the need to use context
455to infer meaning of signalling. Examining flexibility in communication use
456in relation to social factors can thus provide important insights into the
457function of signals and its communicative properties. However, to date,
458this possible relationship between social and ecological factors and
459flexibility of communication has not been examined.
460Group size and culture in chimpanzees and gorillas
20 461It is assumed that larger groups are related to greater rates of cultural
462diversity than smaller groups (Powell, Shennan, & Thomas, 2009). With
463more individuals, there is more opportunity for innovation and through
464social learning this can spread through the group, giving rise to
465population level differences in behavior occurrence or morphology (A.
466Whiten et al., 1999; Andrew Whiten, 2017). Moreover, in larger groups
467there is greater competition for food and resources and this may lead to
468greater pressure for innovation, as compared to smaller groups in which
469there is less competition. Within primates, cultural differences are well
470established and include the grooming hand-clasp, which is variable both
471in occurrence and morphology across sites (McGrew, Marchant,
472Nakamura, & Nishida, 2001; McGrew & Tutin, 1978; Van Leeuwen, Cronin,
473Haun, Mundry, & Bodamer, 2012). However, previous research mostly
474considered single behavior patterns and so far none of the research has
475systematically examined cultural differences in both the occurrence and
476morphology of communicative behavior in the wild (A. Whiten et al.,
4771999; Andrew Whiten, 2017). Hence, how group size affects rates of
478innovation and communication diversity has not been explored. It is
479therefore important to describe and compare the communication
480diversity across the groups of gorillas and the chimpanzees which are
481genetically and ecologically homogenous but live in groups of different
482size.
483Social network analysis
21 484 Social network analyses is now established as key tool in
485behavioural analysis (Farine & Whitehead, 2015; Krause et al., 2009;
486Sueur et al., 2011). Social network analysis is important because it can
487take a number of different types of behavioural interactions e.g.
488grooming, vocalisations, gestures, proximity, body contact, visual
489attention, participation in coalitions, food sharing, social play and
490boundary patrols and directly compare them across dyads (Sueur et al.,
4912011). The network analyses may be based on weighted, directed ties.
492The network is weighted in that the tie between two individuals, A and B,
493will be given a numerical value based on the rate or frequency of the
494behaviour. The network is directed in that the value of the tie from A to B
495may be different from that from B to A if there is inequality in the
496relationships (e.g. A grooms B more than B grooms A). If no interaction is
497observed in a particular category of interaction between a particular pair
498of individuals, the tie between those individuals will be scored as zero
499and undirected.
500 Once the value of the ties for all individuals in the network is
501known, different networks may be constructed for the different
502behavioural interactions listed above. The data analysis may then
503proceed through six steps for each of these networks (Krause, Croft, &
504James, 2007). First, the information on social interactions may be
505organised into a matrix for data analysis, where the rows and columns
506represent individuals, and the values within the matrix represent the
507frequency of behavioural interaction. Second, the networks may be
508constructed and visualised. Algorithms such as ‘spring embedding’ may
22 509be used to arrange the network based on the closeness of interactions
510between individuals, and thus reveal interesting network structural
511features. Arrows may be used to represent the directionality of social
512interactions, and thickness used to represent the weight of the tie.
513Attribute data (e.g. sex of individual) may also be incorporated into the
514network diagram. These diagrams can be a valuable way of seeing
515patterns in the networks, before proceeding onto the third step which is
516performing detailed network analysis (Sueur et al., 2011).
517 Network analysis provides a wealth of quantitative metrics that
518may be calculated to describe the social structure across different scales
519of organisation, from the individual to the population (Sueur et al., 2011).
520‘Node-based’ measures may be used to examine the properties of how
521individual nodes are connected to each other in a network. Although
522many of these measures are based on binary networks, there are
523measures available for weighted and directed networks, (reviewed by
524Boccaletti, Latora, Moreno, Chavez, & Hwang, 2006). To give just two
525examples, node strength measures the total weight of all the ties
526connected to a node, and is thus the weighted equivalent of the binary
527measure node degree (the number of ties joined to a particular node). A
528weighted clustering coefficient may also be calculated, which measures
529the cliquishness of a network - the extent to which a nodes immediate
530neighbours that are themselves neighbours. These measures may be
531averaged over the network as a whole and be used to describe social
532organisation at the level of the group. The fourth step is to interpret
533these network measures, and the networks generated may be compared
23 534to randomized networks that provide a null model with which to test
535whether the observed network patterns are different from those expected
536by chance. For example, is the level of clustering observed in the
537network different from that which would be expected by chance?
538Weighted networks require different randomisation techniques than
539binary networks (Lusseau, Whitehead, & Gero, 2008), and these type of
540methods may be used to examine if the observed networks are
541significantly different from chance.
542 Fifth, the network data may be used to look for non-random
543patterns of association between individuals. A ‘community’ in a network
544is defined as a set of nodes that are more densely connected amongst
545themselves than they are to the rest of the network (Croft et al., 2008).
546Relating the communities found in networks to known individual
547characteristics, group characteristics or ecological variables can lead to
548a better understanding of the interplay between biological, ecological
549and other factors and the observed patterns of social interaction. These
550sub-structures would be difficult to detect using traditional dyad-based or
551population methods, especially in fluid fission-fusion systems such as
552those found in chimpanzees. Further, if a key property (e.g. node
553strength) varies significantly between communities, it is misleading to
554present a mean or medium value of that property over the whole
555population, as this ignores the internal structure of that population. Thus
556a key advance would be to identify these sub-structures within the
557groups of chimpanzees and gorillas, and examine how the number and
558properties of these sub-structures change with increasing group size.
24 559Again, although many of the statistical techniques used to detect
560communities in networks are based on binary networks, there are a small
561number of recently developed methods to detect communities in
562weighted networks and these types of methods may be used for
563community detection.
564 Finally, after quantifying the network and searching for sub-
565structures, the crucial step it to compare the observed network to other
566network. This may be done at three levels. First, networks based on the
567different behavioural interactions may be compared, to test the extent to
568which there is dissociation between, for example, the network based on
569the grooming data and the network based on the gesture data. Second,
570networks between the three different size groups within species may be
571compared, to explore how group size effects network structure within
572gorillas and chimpanzees. Finally, the networks may be compared
573between species, to explore the extent to which the differences in social
574organisation (fission-fusion vs. stable groups) and other differences
575between the species (e.g. in diet, in absolute group size) affect network
576structure. Comparing networks based on the same individuals is the most
577straightforward type of comparison, as the network has the same number
578of nodes and there are well-established statistical techniques for
579comparing these types of networks (Hemelrijk, 1990). Comparing
580networks of different individuals is more problematic, as most network
581measures vary with the number of nodes and ties in the network. The
582majority of the methods developed to compare these types of networks
583are for binary, undirected networks. Methods for comparing weighted,
25 584directed networks are starting to be developed (Li, Zhang, Wang, Zhang,
585& Chen, 2007), and a key part of future research will to be use these
586methods to compare weighted, directed networks. As many networks in
587both biological and social sciences are weighted and directed (even if
588they are often analysed as if they were binary) the set of results in
589respect to characterising, analyzing and comparing weighted, directed
590networks would have wide applicability across a range of disciplines.
591Conclusions
592 A particularly challenging and unconventional aspect of the study
593of primate sociality lies in its use of social network analysis and in
594particular, use of weighted and directed ties to characterise the
595relationships between individuals. In weighted, directed networks a
596numerical value which reflects the strength of the tie, and there is the
597possibility of asymmetry in the ties. In contrast, the great majority of
598network analysis, in social sciences, biological sciences and mathematics,
599considers only binary networks, where the tie between two nodes is
600classified as present (1) or absent (0). This is appropriate for certain
601types of physical or mathematical networks and is often used as a
602simplifying assumption in the study of social networks. However,
603characterising a tie between two individuals in a binary fashion does not
604provide a rich insight into complex social relationships. Although it is
605clear when two animals are linked, in a binary network the difference
606between ties categorised by 1 is lost, and due to sampling issues it is
607rarely certain that two animals in a population are not linked, and thus
608the reliability of ties classed as 0 is often questionable. This severely
26 609limits the usefulness of network analysis in understanding social
610networks, where the weight and direction of the tie is a major component
611of the characterising the interaction between two individuals. Because
612analysing binary networks is more straightforward than analysing
613weighted networks, current approaches in social networks often use a
614cut-off value to transform weighted ties into binary ties. This is an
615unsatisfactory solution, as the cut-off is an arbitrary value, and where it
616is set can affect the resulting network structure (Lusseau et al., 2008).
617Whilst there has been some initial work on weighted, directed networks,
618the work is still in its infancy. If network analysis is to fulfil its potential
619in the study of social systems, it is necessary describe and compare
620weighted networks, so the nature of the tie between two individuals can
621be characterised more precisely.
622 This use of weighted ties is challenging, as techniques of analysing
623- and in particular comparing - weighted networks are less well
624established than those using binary networks, and work on weighted
625social networks in animals is in its infancy. However, the use of weighted
626networks, and the comparison between weighted networks of different
627sizes and in different species, has the potential to open up a major new
628field of research in network analysis, representing a major advance on
629the current reliance on binary network analysis. Given the inter-
630disciplinary nature of network analysis, this is likely to have wide
631applicability in many different fields of research, reaching across the
632mathematical, biological and social sciences.
27 633 Improving our understanding of primate social complexity is likely
634to lead to new insights into human evolution. Although much progress
635has been made in assessing the archaeological record, our understanding
636of hominin social life is in its infancy (R. Dunbar et al., 2014; Foley &
637Gamble, 2009). Gorillas and chimpanzees are two of our closest living
638ancestors, and as such an improved understanding of the forces
639governing their sociality will provide valuable insights into human social
640evolution. In particular, fission-fusion dynamics characterise chimpanzee
641and bonobos (Furuichi, 2009), and also are typical of modern-day hunter-
642gatherer (Filippo Aureli et al., 2008; Marlowe, 2005). This suggests that
643fission-fusion dynamics were characteristic of the social system of the
644last common ancestor of chimpanzees, bonobos and modern humans (F.
645Aureli et al., 2008; Foley & Gamble, 2009). Further, a general trend in
646the course of human evolution is an increase in brain size, and this is
647likely to have been accompanied by a corresponding increase in social
648group size (L.C. Aiello & R.I.M. Dunbar, 1993). A comparison of gorillas
649and chimpanzees offers the opportunity to explore the complexity
650involved in fission-fusion systems, as compared to more stable social
651groups, and how this complexity changes in groups of different sizes.
652This will help us understand how the social structure is likely to have
653changed with increasing group size in the fission-fusion system of early
654hominins, and the cognitive complexity involved in managing groups of
655increasing size (Aureli & Schino, 2019; Freeberg et al., 2012).
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