Animals need information to make decisions, and a quick way to get this information is to watch what others are doing. Animals, like humans, have different social networks that they could acquire this kind of ‘social information’ from, yet we know little about which networks they actually use. In addition, once an animal has obtained social information, some aspect of their lives, such as their sex or social rank, could prevent them from using it. Once again, however, we know very little about the impact of these personal constraints.

Carter et al. found that information about the location of a highly preferred food flowed through a social network of wild baboons that was based on who was regularly in close proximity to whom. However, while individuals with more neighbours were better at obtaining social information about food location, they were not better at using it. Rather, individuals were more likely to successfully exploit such information if they were dominant, bold, male, and had good social bonds with others.

Carter et al.’s results show that the use of social information is a process with several stages – from information acquisition, to its application, and finally its exploitation. Furthermore, the characteristics of an individual can limit their success at each of these stages. The next step is to figure out whether different types of social information – whether short- or long-lived, easy to acquire or more complex – flow through the same networks and have the same personal constraints on who can use them.

Individuals require information to reduce uncertainty about their environment. Information can be acquired in two ways (Dall et al., 2005): by interacting with the environment directly (personal information) or by attending to the behaviour of others (social information). Individuals benefit from both personal and social information in myriad contexts, including foraging, predator avoidance, and mate choice (Giraldeau et al., 2002). Their use is moderated by their expense and reliability: personal information is usually reliable but costly and time consuming to collect, social information is less costly but more likely to become outdated and unreliable (Giraldeau et al., 2002; Laland, 2004). The low costs of social information also allow it to disseminate more rapidly across groups, such that it can play an important role in the formation of traditions and cultures (Whiten, 2000; Castro and Toro, 2004).

Despite the fitness benefits of information use, we have very little understanding of how individuals vary in their ability to capture these benefits. Indeed, theory developed to explain the costs and benefits of information use usually assumes homogeneity within a population (e.g. Pradhan et al., 2012). To understand individual variation in information use, either personal or social, we suggest it is helpful to decompose the process into a sequence of three steps: the acquisition of information, its application, and the exploitation of its benefits (Table 1). Up until now, many studies have implicitly assumed that these three steps are synonymous, but recent evidence indicates that information use is substantially more complex. In particular, Carter et al. (2014) found that the time spent acquiring social information about a task did not correlate with subsequent performance (information application) in wild baboons (Papio ursinus), while Atton et al. (2012) found differences in individual performance between task discovery (information acquisition) and task solving (information exploitation) in three-spine sticklebacks (Gasterosteus aculeatus). The recognition of three sequential steps allows us to begin unpacking the complexity of information use, and to explore variation in the performance of different individuals at different points along the sequence. Distinct sensory and motor capabilities are likely to be involved at each stage, leading to different phenotypic constraints. As a result, individuals who are effective at one step may be less so at another, with significant implications for who captures the most benefits.

The range of phenotypic constraints operating at each step might include cognitive, social, behavioural, ecological and demographic characteristics. The importance of these constraints is likely to differ not only between individuals but also between populations and species. Here, we focus on social, behavioural and demographic constraints on the social information use sequence. To begin with, we consider the social phenotype, i.e., phenotypic traits that emerge from social interactions with others and are likely to be under selection, in this case individual dominance rank (Moore, 1993) and position in the social network (Aplin et al., 2015). Dominant animals can aggressively monopolise resources such as mates (Cowlishaw and Dunbar, 1991) and food (Koenig, 2002), limiting the opportunities for others to apply and exploit information that they have acquired either personally or socially about these resources. This can further lead to voluntary inhibition in the use of information by subordinate animals, e.g., low-ranked rhesus monkeys (Macaca mulatta) only performed a socially-learnt task when high-ranked monkeys were not present (Drea and Wallen, 1999). The social network will likely manifest constraints on different stages of the information use sequence depending on the type of association indexed by the network, i.e., associations according to spatiotemporal proximity or direct interactions. For instance, positions in proximity networks may affect an individual’s opportunities for information acquisition, assuming individuals are more likely to acquire information from others with whom they are more frequently in visual contact (Coussi-Korbel and Fragaszy, 1995; Voelkl and Noë, 2008, 2010), e.g., stickleback proximity networks predict the flow of information about the location of a novel task (Atton et al., 2012). Similarly, positions in interaction networks may limit the application and exploitation of information about resources if social bonds are required to gain access to those resources (Henzi and Barrett, 2002; Clarke et al., 2010), e.g., vervet monkeys (Chlorocebus aethiops) allocate their social effort to access food provided by others (Fruteau et al., 2009).

The behavioural phenotype, specifically personality, may also be important in mediating individuals’ acquisition, application and exploitation of social information. We have previously shown that personality can affect both the first and second steps of the social information use sequence: calmer baboons were more likely to acquire social information but bolder individuals were more likely to apply it (Carter et al., 2014). In geese (Branta leucopsis), personality affected the final step in the sequence: shyer geese were more likely to exploit social information to forage where other geese were successfully foraging (Kurvers et al., 2010). Similarly, fast exploring great tits (Parus major) were more likely to apply social information and change their foraging behaviour to mirror a demonstrator’s (Marchetti and Drent, 2000).

Finally, individual demographic characteristics, particularly age and sex, may affect each step of the social information use sequence. Juveniles may be more reliant on social information because adults have already acquired the necessary information to survive to adulthood (Galef and Laland, 2005). This prediction is supported in baboons, where juveniles spend more time than adults acquiring social information about a novel food (Carter et al., 2014). Similarly, in Japanese macaques (Macaca fuscata), novel socially-transmitted behaviours were more likely to be adopted by juveniles (Huffman et al., 1996). Sex differences in the social information use sequence are also likely due to, e.g., sex-specific costs of competition at resources (e.g. Aragón, 2009).

A further challenge involved in elucidating the social information use sequence is the identification of the relevant network through which information diffuses during the acquisition phase. Researchers have usually assumed information transfers primarily between individuals who are in close spatial proximity (for examples, see Kendal et al., 2010; Aplin et al., 2012; Claidiére et al., 2013). However, individuals may preferentially acquire information from others besides those to whom they are associated as neighbours. For instance, individuals may be more attentive to those with whom they have strong affiliative bonds (Coussi-Korbel and Fragaszy, 1995) or to lower ranking animals from whom they can scrounge resources (King et al., 2009). The need to consider alternative networks in the identification of information diffusion paths is well illustrated by Boogert et al. (2014), who showed that the spread of solutions to a novel foraging task in captive starlings (Sturnus vulgaris) was better predicted by a network based on perching associations than foraging associations.

In this study, we explore phenotypic limitations on social information use. We examined information transmission among wild chacma baboons (Papio ursinus) by experimentally introducing ephemeral patches of a highly preferred food while the troops foraged naturally. We first compared which of five networks best predicted the diffusion of information through the troops about the location of a highly preferred food. Next, we investigated how individuals’ social, behavioural and demographic phenotypes affected their abilities to successfully acquire, apply and exploit this social information.

All individuals in both troops acquired social information in at least one experiment (barring one individual who acquired personal information of one patch, but died in the last week of experiments). On average (median), 10 individuals obtained information about the location of the patches (range = 2–27 individuals) in each diffusion experiment (see Video 4 for an example of information diffusion through a network).

Video 4

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Identifying phenotypic constraints on social information use

We found that individuals’ phenotypes limited the acquisition, application and exploitation of social information about the location of food patches (Table 6, Figure 3). Proximity strength was the only predictor of information acquisition: more central baboons acquired social information more frequently. Proximity strength also showed a similar pattern with information application, but not exploitation. Information application and exploitation were further limited by sex and grooming strength, with males and more central individuals in the grooming network more likely both to apply and exploit acquired information. In combination with sex, dominance rank played a further limiting role on individuals’ exploitation of information, such that females of low rank were most limited in their exploitation of patches. Finally, individuals’ behavioural phenotypes, i.e., boldness, also influenced information exploitation. Overall, individuals that were better connected in the 10 m network were more likely to acquire social information, but it was higher ranking males who were more likely to exploit this information.

Table 6

Response	Predictor	Effect size	S.E.	t	P
Social information acquisition	Intercept	0.23	0.21	1.11	0.27
	Proximity strength	0.66	0.07	8.87	<0.001
Social information application	Intercept	-1.30	0.38	-3.40	<0.001
	Proximity strength	0.65	0.10	6.45	<0.001
	Grooming strength	0.01	<0.001	4.74	<0.001
	Sexa	0.84	0.15	5.48	<0.001
Social information exploitation	Intercept	-2.43	0.39	-6.17	<0.001
	Grooming strength	0.02	<0.001	4.67	<0.001
	Sexa	0.73	0.33	2.21	0.03
	Boldness	0.01	<0.001	3.74	<0.001
	Rank	1.39	0.51	2.71	0.01

1. Presented are the predictor variables, their effect sizes, standard errors (S.E.), t values and p-values.

2. ^aReference category: female

Figure 3

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As a result of these constraints on successive steps in the social information use sequence, individuals only acquired social information about the patches on average (median) 6 times, applied social information 2.5 times, and exploited social information once (across a total of 25 trials per group). However, because of phenotypic variation, there was a substantial range around these medians. Thus, while the average individual acquired and exploited social information on <25% and <5% of occasions, respectively, others were able to acquire and exploit information on >50% and >35% of occasions, or not at all, depending on their phenotype.

Our study suggests that the route of information flow about ephemeral food patches is most closely matched by the 10 m proximity network, although the 5 m chain and nearest neighbour networks (both directed and undirected) also provided a good approximation. These results are consistent with several previous studies indicating the importance of spatiotemporal associations for information flow (e.g., great tits: Aplin et al., 2012; three-spine sticklebacks: Atton et al., 2012). While the most appropriate proximity network to capture information flow will vary depending on the type of information, the social forager, and the environment, our study emphasises the need to recognise that not all networks will be equally applicable. These findings build on the suggestions of previous authors (Lehmann and Ross, 2011; Madden et al., 2011; Castles et al., 2014), and provide the first quantitative demonstration that multiple networks should be considered when studying information transmission. In the present analysis, the grooming networks also provided a good match to the pattern of information flow, suggesting that individuals may be more likely to monitor those with whom they share strong social bonds, irrespective of the symmetry of those bonds (the model results for the undirected and directed networks were very similar). However, the absence of an effect of grooming strength on information acquisition at the individual level (Table 6) suggests that such effects are relatively weak in comparison to those of spatial proximity. In contrast, the dominance networks were entirely unrelated to information flow. Since information flow required visual observation, this suggests that the monitoring of conspecifics is independent of dominance rank. A recent study of social attention in wild vervet monkeys reported a similar pattern (Renevey et al., 2013). This may reflect the fact that dominants and subordinates monitor each other equally, albeit for different reasons: dominant animals seek to scrounge the food discoveries of others, while subordinates seek to avoid aggression.

In our analysis of phenotypic constraints on social information use, we identified three steps in the information use sequence: acquisition, application, and exploitation. In the first step, we found that information acquisition was independent of almost all phenotypic traits tested, i.e., age, sex, rank, personality, and social bonds (grooming strength). The only important trait was individual centrality in the 10 m proximity network. This suggests that visual information about the patch was inexpensive to collect, and limited only by an individual’s spatial associations with other group members. Where the acquisition of social information is more costly, we might expect other phenotypic traits to become important. For instance, among juvenile chimpanzees (Pan troglodytes), sex differences in attentiveness are believed to explain why females spend more time observing, and are faster to learn, the challenging skill of ‘termite fishing’ (Lonsdorf, 2005).

In the second and third steps of the information use sequence, the application and exploitation of information were closely linked. Both steps involved patch entry, but the latter also involved the successful capture of foraging benefits from the patch. The similarities and dissimilarities in phenotypic predictors between the two models are highly informative, not only with respect to understanding the different constraints that can operate along the information use sequence, but also in elucidating how information use mediates the acquisition of monopolisable resources. The latter is possible because our experimental design makes information exploitation synonymous with resource acquisition. Clearly, in many other cases, information exploitation will be unrelated to monopolisable resources but rather involve other types of knowledge, such as foraging skills, predation risk, and mate compatibility. In these instances, the phenotypic constraints on information application and exploitation may be quite different to those observed here.

We begin our assessment of phenotypic constraints on information application and exploitation with dominance rank. Dominant animals were far more likely to successfully exploit social information, because they were able to monopolise food patches. Indeed, as information about the patch spread, increasingly dominant animals would become informed and enter the patch, supplanting lower ranked occupants and preventing others from entering subsequently until the patch was exhausted. This pattern is consistent with how dominant animals scrounge from others in this population (King et al., 2009; Marshall et al., 2012) and across social foragers generally (Barta and Giraldeau, 1998). Surprisingly, however, dominance did not predict information application. The reason for this is that many subordinates also entered the patch, but only after the dominant animal had left (see Video 2). Some of these animals were late arrivals, but a large number would be waiting (‘queuing’) nearby for the dominant animal to leave. Since the patch was largely depleted when the dominant animal left, the subsequent patch entries by subordinates imply the application of outdated information, at a surprisingly large scale given over half of those entering the patch failed to exploit it. One possible explanation for such apparently maladaptive behaviour is that, while baboons are able to collect social information about patch location, they are unable to collect ‘public’ information about patch quality. A similar pattern has been observed in three-spined sticklebacks (Coolen et al., 2003). However, other experimental work in this population indicates that baboons are able to collect such information (Lee, 2015). A more likely explanation is that lower ranking individuals are aware that the patch is largely empty, but there is minimal cost in entering it and sifting through the sand in case any food items remain. Indeed, in a small number of cases, late arrivals did find a small number of kernels that had been overlooked.

Proximity strength remained a strong predictor for information application, as might be expected: individuals had to find the patch before they could enter it. However, because only a very small fraction of those who acquired and applied the information were able to benefit from it, the effect of proximity strength was lost in information exploitation. Grooming strength, however, was important for both information application and exploitation, possibly reflecting the role that social bonds play in tolerance at feeding sites, both in this baboon population (Sick et al., 2014) and in primates more generally (Ventura et al., 2006; Tiddi et al., 2011). Nevertheless, tolerance of direct co-feeding at the patch (patch sharing) was rare in this experiment: of the 293 patch entries observed in the 44 experiments for which these data could be extracted, only 14 (4.8%) resulted in co-feeding (where two or more individuals fed simultaneously from the patch). Moreover, in 4 of these cases (including one group of 3 co-feeders), there were vocal protests of intolerance from one or both parties (see Video 3 for an example of a vocal protest during co-feeding). Thus toleration of co-feeding could be said to occur on only 9 occasions (3.1%). Instead, the tolerance observed in this experiment was primarily of close proximity of individuals to the patch, which allowed individuals to queue for and quickly enter the patch on a dominant’s exit (see Video 3). There are thus two strategies for information application to occur, both of which may rely on social bonds: tolerated co-feeding and tolerated (close-proximity) queuing. A change in the dimensions of the patch to allow more foragers concurrently to occupy it, and thus a greater possibility of tolerated co-feeding, may show a greater effect of grooming strength on both social information exploitation and application.

Sex also played a role: females were less likely to apply and exploit social information. As we control for rank in the analyses, this finding may reflect female reproductive constraints. Previous work on nine-spine sticklebacks (Pungitius pungitius) has indicated that female gravidity can influence the use of social information (Webster and Laland, 2010). In our case, many of the observed females were either pregnant or lactating, and females in these states experience higher foraging demands (Silk, 1987; Barrett et al., 2006), potentially making them less willing either to forego valuable foraging time to queue for patch entry (information application) or to spend excessive time searching for food once in the patch (information exploitation). Shy animals also showed lower rates of information exploitation, presumably because they were more nervous and therefore spent more time in the social monitoring of conspecifics (Edwards et al., 2013). The observation that bolder animals were more likely to successfully exploit information is consistent with the finding that bolder animals are also more likely to demonstrate social learning in this population (Carter et al., 2014). In comparison, Harcourt et al. (2010) found no effect of boldness on social information use in three-spined sticklebacks. However, that study only went as far as the information application step of the information use sequence. We only found an effect of personality in the final information exploitation step.

Phenotypic variation was also observed in asocial learning. Younger, more dominant males were more efficient at finding food patches. The most likely explanation for this pattern is that dominant juveniles were more likely to be at the leading edge of a foraging group, and therefore the first to encounter the patches. Similarly, juvenile ring-tailed coatis (Nasua nasua) occupy positions at the leading edge of their foraging groups (Hirsch, 2011). The multiplicative effect further suggests that the probability of younger dominant males occupying this spatial position increased the better connected they were in their social network. Notably, we found no effect of age on social information use. While this is not surprising at the information acquisition stage, where there were no phenotypic constraints other than network position, it is more surprising for information application and exploitation, especially since juveniles appear to show greater propensity for social learning than adults, both in baboons (Carter et al., 2014) and more generally (e.g., meerkats, Suricata suricatta: Thornton and Malapert, 2009). However, this propensity usually refers to social learning tasks involving novelty or complexity, reflecting the tendency for juveniles to be more curious and exploratory about their environment (Reader and Laland, 2001; Kendal et al., 2005; Benson-Amram and Holekamp, 2012). In our case, the task simply involved entering and exploiting a patch of familiar food, and for such a task it might be expected that individuals of all ages would show equal abilities.

Our study raises a further point about the type of social information that is transmitted. We provided individuals with the opportunity to acquire social information about the location of a highly preferred food source in a novel location. These novel patches were rapidly depleted and the social information quickly became outdated. Such short-lived, ephemeral information may be easy and cheap to acquire and, as we have found, more likely be transmitted through proximity rather than interaction networks. Whilst our results support previous findings that proximity social networks are important for the transmission of ephemeral and/or easy-to-acquire information among individuals in the wild (Aplin et al., 2012), evidence from starlings suggests that more complex information diffuses through alternative networks. Boogert et al. (2014) showed that information about novel foraging skills diffused through the perching rather than foraging social networks. Whilst it is challenging to determine the difficulty with which species acquire different types of information (Griffin et al., 2015), research is needed to elucidate how the type of social information influences how quickly and through which networks it is transmitted. In the baboon system, we might similarly expect that social information that takes longer to acquire and/or process will transmit through different networks to those that transmit easy-to-acquire information.

Our finding that phenotype limits information use builds on previous work indicating that individual state, such as uncertainty or the possession of outdated information, can influence social learning strategies (reviewed in Rendell et al., 2011). Our study extends this work, revealing fundamental individual differences in the ability to use social information. Decomposing social information use into three constituent steps has further illuminated how these individual differences limit information use. The implications of such sequential phenotypic constraints are manifold. We conclude by considering two points. First, only a small number of individuals who acquire or apply social information may successfully exploit it. Similarly, Racine et al. (2012) report that ring-billed gulls (Larus delawarensis) may acquire social information about the location of food resources but be unable to apply it because of parenting constraints. Second, where phenotypic traits are expressed in relation to conspecifics (e.g., dominance rank, network position), social information use will vary markedly between social environments. For instance, in a captive setting where competition is minimised (e.g. by testing individuals when isolated and not at risk of aggression: Call et al., 2005) (c.f. Drea and Wallen, 1999), subordinate animals may show a propensity for copying others (e.g. Kendal et al., 2015), but in the wild, where subordinates are more vulnerable to aggression and where food resources are relatively more valuable, subordinates may rarely copy others. Together, these two points highlight a critical disjunction between an ability to acquire information and to capture its benefits. This disconnection is likely to have a fundamental impact on selection for social information use, such that even in social information-rich environments, only a small number of individuals of a particular phenotype may be selected to use it.

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Thank you for submitting your work entitled "Sequential phenotypic constraints on social information use" for consideration by eLife. Your article has been favorably evaluated by three reviewers, including Brianne Beisner. Brenda McCowan and a guest Reviewing Editor, and the evaluation was overseen by Ian Baldwin as Senior Editor.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

This study takes a novel approach to the analysis of information transmission and decision-making by viewing it as a three-step process of information acquisition, application and exploitation. Using social network analysis and diffusion analysis, it identifies the type of social network that best describes the diffusion of information about the location of small, novel artificial food patches for two troops of wild chacma baboons. It subsequently examines the role of several characteristics that govern the decision-making process at each of the three steps. The application of this novel approach is an important contribution that could have a significant, innovative influence on future research into decision-making and social transmission of information. The analysis presented in this paper goes beyond many other papers that use social network approaches by investigating multiple different social networks, which is critical to gaining a full understanding of social information transmission, because social groups are comprised of many different social networks. The data analysis techniques appear to be appropriate and state of the art. The article is well-organized and well-written. Although some of the results presented are not surprising and seem very intuitive (e.g., dominant animals were better able to exploit the information acquired about the food patches), other findings are quite valuable (e.g., boldness was relevant only at the stage of successful exploitation; proximity networks best predict social information transmission whereas dominance networks did not at all predict transmission). Our major concerns are primarily about details about the methods used to carry out the field experiments.

Essential revisions:

1) More information would be useful about the habitat, terrain, diet and foraging habits of the baboons at the study site. Although the authors say that individual baboons had to be within 1 m of the patch to see the maize, it would be helpful to understand how the authors determined this distance and whether this distance was the case in all trials. The reader is unable to judge the degree to which baboons may be able to spot kernels of maize from a greater distance without this information. Indeed, in the videos, the maize seems to be placed in areas bare of vegetation where it is plausible to think that it could have been spotted from more than 1 m away. Also, the videos suggest that the maize may have been concentrated over a much smaller area than 1 square meter, making spotting easier, but co-feeding less likely to occur.

2) Please give a breakdown of the age/sex composition of each group, and indicate whether all individuals over 2 years of age were individually recognizable to all observers.

3) It would be useful to distinguish between exploitation of patches in two different ways-via co-feeding with another individual, or waiting until the patch is vacated. The authors mention the waiting technique and allude to issues of tolerance, but do not state explicitly how many entrances into the patch and how much exploitation of the patch involved the two different strategies. If the area over which the maize was spread varied or tended to be smaller than the 1 m cited (see above), this could have affected the likelihood of individuals pursuing each strategy, and hence the importance of such factors as grooming strength. We suggest that both possible types of exploitation be described early in the paper to prepare the reader for further distinction in the data later. Re-analysis taking the two strategies into consideration would be useful, if possible. If not, discussion of this issue is needed.

Clarifying this issue should also help in the interpretation of the role of boldness in exploitation. The prior test of boldness concerned handling of a novel food in isolation, i.e., boldness in a nonsocial context. The nonsocial test of taking a novel food item in isolation is probably assessing the animal's boldness with regard to exploration. Yet the application of boldness in the study likely had a social element to it, particularly when/if individuals attempted to co-feed with others in these small patches. Hence, the choice of the word 'shy' (Discussion, fifth paragraph) to mean the opposite of bold may not be accurate. What evidence is there that the two forms of boldness are equivalent? Correlated? Certainly humans differ in social vs. nonsocial manifestations of boldness. If they are not known to be equivalent, it would probably be more accurate to avoid the word 'boldness' and to say instead that baboons that show a high tendency to explore novel objects and surroundings also had a higher rate of successfully exploiting the experimental food patches.

4) How were dental patterns of tooth eruption and wear observed? Were the baboons trapped and sedated? A brief background section on the history, management and handling of the population would be useful. Were their diets supplemented by humans in the past? If so, how was it done?

5) There was some confusion among the reviewers about how the data on grooming and dominance interactions were collected. Certainly the authors took pains to collect proximity data in a systematic manner that allowed them to compare individuals. However, it is less clear that this was the case for grooming and dominance-related interaction. The authors state that "Interaction data were recorded ad libitum by all observers at the project (n=6-7 in total) between dawn and dusk across all individuals as they moved continuously through the troop". Given that troops could be dispersed over 1 square km, was what they did equivalent to all occurrences sampling? Could the entire troop be observed at once and all instances of grooming and agonism recorded? Do the authors mean that all 6 or 7 observers collected data at the same time, working different parts of the troop? If so, what steps were taken to make sure coverage was even and that individuals were not sampled more than once over a short interval of time? Was the amount of time each individual was observed recorded and used to calculate rates? Was any other sort of correction made for variation in the observability of individuals? If not, this could have seriously biased the social networks they derived. Given that the ranges of grooming interactions and dominance interactions per initiator were so large (1-111 and 1-116, respectively), we suggest that it may be better to cite the means and ranges of total grooming and dominance interactions per subject rather than initiations.

6) Please clarify how dominance networks are different from dominance ranks for readers that are less familiar with social network analysis. Please also discuss your use of undirected and directed networks. While OADA can be used with both directed and undirected networks, the directionality of the grooming and dominance networks (and lack of directionality of the proximity networks) needs to be discussed more fully. We suggest the authors explain (a) how directionality affects their interpretations of their results and (b) if undirected networks were attempted for grooming and aggression to see whether pairs that interact aggressively/ submissive frequently also appeared to have monitored each other frequently enough to pass on social information.

7) Six or seven observers were used. Were interobserver reliability tests done? If so, how and what was the criterion for passing?

8) Figure 1, please provide median and range for number of scans per individual.

9) The authors state that they hid the food when out of sight from the troops, but stood 15 m away from it with a video camera as the monkeys approached. What steps were taken to insure that the presence of observers at this point did not provide cues to the monkeys that a food patch was nearby? Cues of this nature could potentially pose a serious flaw in the design of the experiment, especially given that baboons catch on quickly to such things, and the experiments were replicated 25 times for each troop.

10) More than half the time the patch was found by the leading edge of the troop. Please discuss how this may have influenced the outcome of the study and the results indicating the importance of position in the proximity network. Are the most central animals disproportionately found in the leading edge? Would it be possible to control for the part of the group that happened to encounter the patch first-or run separate analysis for each condition? A brief description of the attributes of animals in different positions of an advancing group might help interpret the findings. How many times was the patch not found by the baboons? Did the 50 experiments include only those trials in which the patch was found?

11) The determination of social acquisition of information about the patch was via gazing of an individual toward another individual that was in a patch. Given that baboons constantly monitor each other's positions with gaze, were frequencies of gazing corrected for baseline rates of gazing at other individuals not in the patch? Was there a difference, e.g., in the duration of gazes, that would indicate the likelihood that information was actually acquired and that the gaze was not a routine monitoring of position only?

12) Results subsection “Identifying phenotypic constraints on social information use”, last paragraph and elsewhere. What does 'average (median)' mean? Average (meaning mean) and median are the same?

13) In the Discussion, the authors should explicitly consider the implications of using only small and ephemeral food patches. The brief nature of their food patch experiments means that animals that acquired information about the location of the food patch (and perhaps even applied it, though unsuccessfully) did not have the opportunity to apply and exploit such information in the future. From an evolutionary perspective, however, social information can spread about more permanent food patches as well as ephemeral food patches, and there may be future opportunities for animals to return to the location of more permanent food patches and they may be able to apply the information acquired (about this new food patch) as well as successfully exploit it. This may even be a reason for low-ranking individuals to enter a depleted food patch (especially if visibility of patch details is somewhat limited without entering it) – to determine for themselves whether the food patch may be a permanent patch that they can return to at a later date.

1) More information would be useful about the habitat, terrain, diet and foraging habits of the baboons at the study site. Although the authors say that individual baboons had to be within 1 m of the patch to see the maize, it would be helpful to understand how the authors determined this distance and whether this distance was the case in all trials. The reader is unable to judge the degree to which baboons may be able to spot kernels of maize from a greater distance without this information. Indeed, in the videos, the maize seems to be placed in areas bare of vegetation where it is plausible to think that it could have been spotted from more than 1 m away. Also, the videos suggest that the maize may have been concentrated over a much smaller area than 1 square meter, making spotting easier, but co-feeding less likely to occur.

We have added the following text to explain the field site in more detail (Materials and Methods, subsection “Study area and study species, first paragraph”): “Two habitat types make up the Tsaobis terrain: open desert and riparian woodland. […] The baboons’ main predator, the leopard (Panthera pardus), is rare at Tsaobis and the risk of predation is low.”

Regarding the distance from which the patch was noticeable, we returned to the videos to code estimated distances from which the patches were spotted. Depending on when we started recording (we only recorded on discovery of the patch to save video camera battery and memory card space), we were able to extract distances for 38 patch trials. The median distance was 2 m (range = 0-8). We note that the missing distances were not random – we were more likely to miss the beginning (seconds) of a trial if the patch was found when an individual was in close proximity to it and on several occasions patches were missed by baboons even when they were in close proximity to it – on two occasions individuals walked over the top of the patches and did not notice them! However, we have amended the manuscript to replace our previous estimate of 1 m with the calculated median and range values (Materials and Methods, subsection “Information diffusion experiments”, first paragraph).

The reviewers are also correct that the majority of the kernels were concentrated in a smaller area (0.5 m²), but in most cases several kernels were beyond this area and could spread up to 1 m across. This is because we did not want the baboons to associate the observer’s behaviour with creating a patch, and as such we created the patches as quickly as possible (see response to Query 9 below for more details on our strategy), which meant that not all of the kernels were within our small patch area. We have amended the text to reflect this more precisely (Materials and Methods, subsection “Information diffusion experiments”, first paragraph): “…one observer (AJC) created food patches by moving ahead of a foraging troop and scattering 52.9 ± 5.3 g of maize kernels over a 0.5 m² core area (with a little surrounding scatter enlarging this area to no more than 1 m²), in the direction of travel of the troop.”

2) Please give a breakdown of the age/sex composition of each group, and indicate whether all individuals over 2 years of age were individually recognizable to all observers.

We have now provided this information (Materials and Methods, subsection “Study area and study species”, second paragraph).

3) It would be useful to distinguish between exploitation of patches in two different ways-via co-feeding with another individual, or waiting until the patch is vacated. The authors mention the waiting technique and allude to issues of tolerance, but do not state explicitly how many entrances into the patch and how much exploitation of the patch involved the two different strategies. If the area over which the maize was spread varied or tended to be smaller than the 1 m cited (see above), this could have affected the likelihood of individuals pursuing each strategy, and hence the importance of such factors as grooming strength. We suggest that both possible types of exploitation be described early in the paper to prepare the reader for further distinction in the data later. Re-analysis taking the two strategies into consideration would be useful, if possible. If not, discussion of this issue is needed.

This is an interesting idea. Following the reviewers’ suggestion, we now state explicitly in the Discussion how many instances of co-feeding there were (fifth paragraph) and summarise them for the reviewers here. We extracted instances of co-feeding from 44 experiments’ videos (due to a technical problem with one of the video cameras, we could not download 6 of them from the camera we used and consequently could not back them up). In the 44 trials, there were 14 instances of co-feeding i.e. individuals eating >1 kernel from the patch simultaneously (10 pairs, and 3 triplets); of these 14 co-feeding patch entries, 4 were not ‘tolerance’ per sei.e. two individuals fed at the patch but at least one of them vocally protested against the other. In total, there were 293 patch entries in this subset of 44 experiments; thus the vast majority of patch entries were not tolerated co-feeding. The tolerance that we observed was primarily for individuals to be allowed in close proximity to an occupier of a patch without being threatened or chased away. Tolerated queuing could thus be defined as a patch occupier allowing the proximity of an individual within, for example, 10 m of the patch for >10s. Unfortunately, as we did not set out to quantify this behaviour in these experiments, we cannot retrospectively accurately estimate instances of tolerated queuing – as our goal was to quantify the identities of individuals acquiring, applying and exploiting information, we did not film or keep an accurate dictated record of all those individuals who might be waiting around the patch, their distances from the patch, and their turnover. In our future experiments, we could endeavour to collect these data with the use of a second observer. As suggested by the reviewers, we discuss these two strategies in the text, suggest a change in the experimental design that could test this idea, and provide another video of “tolerated queuing” to illustrate this strategy in individuals of different ranks (as opposed to the infants queuing for the patch of the dominant male in Video 2) (Discussion, fifth paragraph).

Clarifying this issue should also help in the interpretation of the role of boldness in exploitation. The prior test of boldness concerned handling of a novel food in isolation, i.e., boldness in a nonsocial context. The nonsocial test of taking a novel food item in isolation is probably assessing the animal's boldness with regard to exploration. Yet the application of boldness in the study likely had a social element to it, particularly when/if individuals attempted to co-feed with others in these small patches. Hence, the choice of the word 'shy' (Discussion, fifth paragraph) to mean the opposite of bold may not be accurate. What evidence is there that the two forms of boldness are equivalent? Correlated? Certainly humans differ in social vs. nonsocial manifestations of boldness. If they are not known to be equivalent, it would probably be more accurate to avoid the word 'boldness' and to say instead that baboons that show a high tendency to explore novel objects and surroundings also had a higher rate of successfully exploiting the experimental food patches.

The reviewers have raised two of the perennial issues with personality studies: (1) how to label traits and (2) how to interpret cross-context correlations in behaviour. Regarding the first issue, we have shown convergent validity for this trait using a multimethod approach (Carter et al. 2012), which suggests that (i) this trait is more general than a “tendency to explore novel objects” and (ii) this trait is not exploration, though there may be overlap with such a trait (Carter et al. 2013). As such, we feel it is better to retain the term ‘boldness’. In addition, this approach is consistent with the terminology we have established in our past publications (while using the term “exploration” now would introduce confusion). Regarding the second issue, we have three lines of evidence that novel food boldness also relates to the social environment: novel food boldness predicts social learning (Carter et al. 2014), bolder individuals tend to associate with other bolder individuals (Carter et al. 2015), and novel food boldness correlates with cross-context observer assessment scores of boldness (Carter et al. 2012). Since one of the goals of personality research is to understand such overlaps (e.g. behavioural syndromes, Sih et al. 2004), we feel the current presentation is in-line with these approaches.

Carter, AJ; Marshall, HH; Lee, AEG, Torrents Ticó, M; Cowlishaw, G. 2015. Phenotypic assortment in wild primate networks: implications for the dissemination of information. Royal Society Open Science dx.doi.org/10.1098/rsos.140444

Carter, AJ; Marshall, HH; Heinsohn, R & Cowlishaw, G. 2014. Personality predicts the propensity for social learning in a wild primate. PeerJ, 2, e283.

Carter, AJ; Feeney, WE; Marshall, HH; Cowlishaw, G & Heinsohn, R. 2013. Animal personality: what are behavioural ecologists measuring? Biological Reviews, 88, 465-475.

Carter, AJ; Marshall, H; Heinsohn, R & Cowlishaw, G. 2012. Evaluating animal personalities: do observer assessments and experimental tests measure the same thing? Behavioral Ecology and Sociobiology, 66, 153-160.

Sih, A., Bell, A. M., Johnson, J. C. & Ziemba, R. E. 2004. Behavioral syndromes: an integrative overview. The Quarterly Review of Biology,79, 241–277.

4) How were dental patterns of tooth eruption and wear observed? Were the baboons trapped and sedated? A brief background section on the history, management and handling of the population would be useful. Were their diets supplemented by humans in the past? If so, how was it done?

We have added a subsection to the Materials and Methods that details the history of the population (subsection “History of the study population”). As specified in the Ethics section, all our protocols are independently approved by the ZSL Ethics Committee, adhere to the Guidelines for the Use of Animals in Behavioural Research and Teaching (Animal Behaviour 2003, 65:249–255), and meet the legal requirements of Namibia where the work was carried out.

5) There was some confusion among the reviewers about how the data on grooming and dominance interactions were collected. Certainly the authors took pains to collect proximity data in a systematic manner that allowed them to compare individuals. However, it is less clear that this was the case for grooming and dominance-related interaction. The authors state that "Interaction data were recorded ad libitum by all observers at the project (n=6-7 in total) between dawn and dusk across all individuals as they moved continuously through the troop". Given that troops could be dispersed over 1 square km, was what they did equivalent to all occurrences sampling? Could the entire troop be observed at once and all instances of grooming and agonism recorded? Do the authors mean that all 6 or 7 observers collected data at the same time, working different parts of the troop? If so, what steps were taken to make sure coverage was even and that individuals were not sampled more than once over a short interval of time? Was the amount of time each individual was observed recorded and used to calculate rates? Was any other sort of correction made for variation in the observability of individuals? If not, this could have seriously biased the social networks they derived. Given that the ranges of grooming interactions and dominance interactions per initiator were so large (1-111 and 1-116, respectively), we suggest that it may be better to cite the means and ranges of total grooming and dominance interactions per subject rather than initiations.

That the interaction data we collected was representative of actual rates of interaction was a concern of ours when designing our data collection and we apologise for the confusion introduced by the brevity of this section. We have now elaborated to clarify (Materials and Methods, subsection “Interaction networks”, first paragraph). No, unfortunately it is impossible to perform all-occurrences sampling of interactions, nor is it possible to record how much time observers spend in proximity to particular baboons to estimate sampling rates. However, as we explain in the amended manuscript, we believe that our sampling method was not biased because all observers were required to move throughout the troops and to monitor all group members throughout the day as part of their other data collection duties, and they thus regularly sampled the entire troop. Like the referees, we were also surprised by the range in the observations of interactions; however, on inspection of these, they made biological sense and we were satisfied they were representative: frequent groomers were females in consortship with males (and often the same males over months); infrequent groomers were juvenile males; frequent antagonists were males in consortship with females; infrequent antagonists were low ranking individuals. The patterns in the ad lib interactions data are also verified by the behavioural states observed during the focal individual proximity scans, i.e., some individuals were frequent groomers, while others were never observed grooming (across 94 individuals, the percentage of observations taken during grooming ranged from 0 to 35%, with 14 individuals never recorded grooming); moreover, females in consortship groomed more than all other individuals (Welch two-sample t-test: t = -3.13, df = 42.05, p = 0.003) while juvenile males groomed less than others (Welch two-sample t-test: t = 6.35, df = 91.97, p < 0.001). Finally, we now also specify how we sampled to avoid pseudoreplication (in the second paragraph of the aforementioned subsection).

6) Please clarify how dominance networks are different from dominance ranks for readers that are less familiar with social network analysis. Please also discuss your use of undirected and directed networks. While OADA can be used with both directed and undirected networks, the directionality of the grooming and dominance networks (and lack of directionality of the proximity networks) needs to be discussed more fully. We suggest the authors explain (a) how directionality affects their interpretations of their results and (b) if undirected networks were attempted for grooming and aggression to see whether pairs that interact aggressively/ submissive frequently also appeared to have monitored each other frequently enough to pass on social information.

We have elaborated on the difference between dominance networks and ranks (subsection “Interaction networks”, second paragraph) and directed and undirected networks (fourth paragraph). We were interested by the idea that we use undirected versions of the directed networks, and have now included these new analyses. Overall, they do not change the essence of our main findings, but we did find that (1) the undirected nearest neighbour network was better than the directed network, and (2) there was no difference between the directed and undirected versions of the interaction networks. As such, we discuss how directionality of the network affects information transmission (in the fourth paragraph of the aforementioned paragraph and in the first paragraph of the Discussion).

7) Six or seven observers were used. Were interobserver reliability tests done? If so, how and what was the criterion for passing?

Again, we apologise for the ambiguity introduced by our brevity. For the collection of the interaction data, there was a total of 7 observers, with 6 remaining onsite for the whole season, but only 1-4 attended each troop on any day. We have added the following text to clarify (subsection “Interaction networks”, first paragraph): “On any given day, 1-4 observers were present with each troop, from a total pool of 7 observers for the field season.” We have also added subheadings for both proximity and interaction data collection to further emphasise that different methods were used in each case, i.e., while the interaction data were collected by all observers, only one observer (MTT) collected most (99.7%) of the proximity data (the other 0.3% were performed by AJC during training). While we perform concurrent observations for interobserver reliability tests for data collected using focal observations, we do not perform such tests for the ad libitum data. While grooming is never ambiguous, some dominance interactions can be more subtle and difficult to identify correctly (such as during recruitment for coalition formation where it may not be clear which individual is being threatened by whom). New observers to the site thus receive intensive training at the beginning of the field season, and are tested by experienced observers until they consistently identify dominance interactions correctly. This usually takes two weeks. Observers are advised to collect dominance data only when they are sure of the interaction. We have added text to this effect to the manuscript (subsection “Interaction networks”, first paragraph).

8) Figure 1, please provide median and range for number of scans per individual.

We have now provided this information in the third paragraph of the subsection “Interaction networks”.

9) The authors state that they hid the food when out of sight from the troops, but stood 15 m away from it with a video camera as the monkeys approached. What steps were taken to insure that the presence of observers at this point did not provide cues to the monkeys that a food patch was nearby? Cues of this nature could potentially pose a serious flaw in the design of the experiment, especially given that baboons catch on quickly to such things, and the experiments were replicated 25 times for each troop.

This was a concern of ours, not least because we do not want the baboons to associate observers with providing food. We have amended the text for clarity and added the following to qualify our methodology (Materials and methods, subsection “Information diffusion experiments:, first paragraph): “To avoid the baboons observing the patch being created, the observer either (i) quickly scattered the kernels as she was walking or (ii) pretended to get something from her field backpack while scattering the kernels behind her bag. In all cases, the baboons did not see the kernels being placed. Furthermore, because the observer was present in the troops for many hours preceding and following these trials, the baboons did not associate the camera nor the waiting behaviour of the observer with the presence of the patches.”

10) More than half the time the patch was found by the leading edge of the troop. Please discuss how this may have influenced the outcome of the study and the results indicating the importance of position in the proximity network. Are the most central animals disproportionately found in the leading edge? Would it be possible to control for the part of the group that happened to encounter the patch first-or run separate analysis for each condition? A brief description of the attributes of animals in different positions of an advancing group might help interpret the findings. How many times was the patch not found by the baboons?

The reviewers’ queries above can be synthesised as the following two questions: (1) is the transmission of information affected by who discovers the patch and (2) is patch discovery dependent on individuals’ phenotypes? This is our current research focus! That is, we are now investigating whether particular (social and behavioural) phenotypes are more or less likely to generate information and, if so, whether individuals can pay attention to such information generators strategically to maximise social information acquisition. Whilst we have included information about the numbers of individuals who found a patch to demonstrate the diversity of patch discoverers (Materials and methods, subsection “Information diffusion experiments”, first paragraph), we are aware that this is not information about their phenotypes. Because this is a research topic for which we have been collecting data we do have some preliminary analyses to answer the reviewers’ queries. These suggest that older individuals are more likely to be on the periphery of the troop and higher ranking individuals tend to be at the front, though this latter relationship is not statistically significant. Perhaps surprisingly, the proportion of time individuals are found on the periphery or front of the troop does not predict whether or not they will find a patch, though again we stress that these analyses are preliminary. We have not yet analysed whether network and spatial positions are correlated. However, we would prefer not to present these results in the current manuscript. Our reasons for this are two-fold: (1) the analyses answer a different research question tangential to the main research questions, and (2) we are currently collecting a more robust dataset (pooled over 3 years) to answer this question and do not wish to present these limited analyses here.

Did the 50 experiments include only those trials in which the patch was found?

We now describe the numbers of failed trials in the text, together with a brief explanation of why the baboons failed to detect the patches in those cases (Materials and methods subsection “Information diffusion experiments”, first paragraph).

11) The determination of social acquisition of information about the patch was via gazing of an individual toward another individual that was in a patch. Given that baboons constantly monitor each other's positions with gaze, were frequencies of gazing corrected for baseline rates of gazing at other individuals not in the patch? Was there a difference, e.g., in the duration of gazes, that would indicate the likelihood that information was actually acquired and that the gaze was not a routine monitoring of position only?

This is a good point. We did discuss this possibility inasmuch as we were concerned whether we could be certain that an individual had acquired social information about the location of the patch. However, the routine monitoring of conspecific position tends to occur through rapid glances, rather than the prolonged gazes that we recorded. In addition, the vast majority of individuals approached the patch and stopped foraging to watch individuals in the patch (as is evident in the videos provided), which further indicates more than simple routine monitoring.

12) Results subsection “Identifying phenotypic constraints on social information use”, last paragraph and elsewhere. What does 'average (median)' mean? Average (meaning mean) and median are the same?

“Average” indicates the central tendency of data (e.g. mean, median, mode) and is not synonymous with mean, which is why we specified which average we used in all cases.

13) In the Discussion, the authors should explicitly consider the implications of using only small and ephemeral food patches. The brief nature of their food patch experiments means that animals that acquired information about the location of the food patch (and perhaps even applied it, though unsuccessfully) did not have the opportunity to apply and exploit such information in the future. From an evolutionary perspective, however, social information can spread about more permanent food patches as well as ephemeral food patches, and there may be future opportunities for animals to return to the location of more permanent food patches and they may be able to apply the information acquired (about this new food patch) as well as successfully exploit it. This may even be a reason for low-ranking individuals to enter a depleted food patch (especially if visibility of patch details is somewhat limited without entering it) – to determine for themselves whether the food patch may be a permanent patch that they can return to at a later date.

Again, the reviewers have highlighted a new research question raised by the findings of this study and for which we have now collected data to test: Does ephemeral information transmit through different social networks to those that transmit longer-lasting information? We did originally discuss this in our earlier versions of the manuscript, but removed the paragraph because of the length of the manuscript. We have now added this back to our Discussion on the encouragement of the reviewers’ interest in the idea.

Author details

1. Alecia J Carter

   Department of Zoology, University of Cambridge, Cambridge, United Kingdom

   Contribution

   AJC, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   For correspondence

   ac854@cam.ac.uk

   Competing interests

   AJC: Early Career Advisor for eLife.

   "This ORCID iD identifies the author of this article:" 0000-0001-5550-9312

2. Miquel Torrents Ticó

   Zoological Society of London, Tsaobis Baboon Project, Institute of Zoology, London, United Kingdom

   Contribution

   MTT, Acquisition of data, Drafting or revising the article

   Competing interests

   No competing interests declared.

3. Guy Cowlishaw

   Zoological Society of London, Institute of Zoology, London, United Kingdom

   Contribution

   GC, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   No competing interests declared.

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