Role of immigrant males and muzzle contacts in the uptake of a novel food by wild vervet monkeys

  1. Pooja Dongre
  2. Gaëlle Lanté
  3. Mathieu Cantat
  4. Charlotte Canteloup
  5. Erica van de Waal  Is a corresponding author
  1. Department of Ecology and Evolution, University of Lausanne, Switzerland
  2. Inkawu Vervet Project, Mawana Game Reserve, South Africa
  3. University of Poitiers, France
  4. Laboratory of Cognitive & Adaptive Neurosciences, CNRS - UMR 7364, University of Strasbourg, France

Abstract

The entry into and uptake of information in social groups is critical for behavioral adaptation by long-lived species in rapidly changing environments. We exposed five groups of wild vervet monkeys to a novel food to investigate the innovation of processing and consuming it. We report that immigrant males innovated in two groups, and an infant innovated in one group. In two other groups, immigrant males imported the innovation from their previous groups. We compared uptake between groups with respect to the initial innovator to examine the extent to which dispersing males could introduce an innovation into groups. Uptake of the novel food was faster in groups where immigrant males ate first rather than the infants. Younger individuals were more likely overall, and faster, to subsequently acquire the novel food. We also investigated the role of muzzle contact behavior in information seeking around the novel food. Muzzle contacts decreased in frequency over repeated exposures to the novel food. Muzzle contacts were initiated the most by naïve individuals, high rankers, and juveniles; and were targeted most towards knowledgeable individuals and high rankers, and the least towards infants. We highlight the potential importance of dispersers in rapidly exploiting novel resources among populations.

Editor's evaluation

This important study provides new insights into behavioural mechanisms involved in the transmission of information surrounding innovation in a social species. Combining experimental and observational evidence, the results are solid and convincing regarding the effects of age, rank and muzzle contacts in transmitting knowledge among vervet monkeys. The work will be of interest to ethologists, behavioural ecologists and comparative psychologists.

https://doi.org/10.7554/eLife.76486.sa0

Introduction

To thrive in rapidly changing environments, including those induced by humans, animals must respond quickly to relevant information about their surroundings (Barrett et al., 2019). Climate change or human-induced invasions of species novel to the area, as well as the introduction of human artifacts into the environment can affect different species in myriad ways, for example, bringing new threats, disruptions, competition, or novel resource opportunities. Adaptive behavioral responses to such changes can include effectively avoiding new predators, maintaining the high competitive ability, and exploiting novel resources (Barrett et al., 2019; Jesmer et al., 2018; Gruber et al., 2019; Sih et al., 2011). For long-lived species, fast, learned behavioral adaptations are crucial for survival when circumstances change too rapidly for genetic adaptation to suffice. Whilst transmission mechanisms of genetic adaptation are well understood, our understanding of how behavioural adaptations arise and spread is murky, and the role of individual heterogeneity in a group remains underexplored (Jolles et al., 2020).

Research has identified two main classes of behavioral responses to novel stimuli in animals. These are neophobia and exploration (Forss et al., 2017; Carter et al., 2012). Neophobia refers to the avoidance of novelty, which could expose individuals to risky situations such as entering unknown home ranges of predators or ingesting toxins. Neophobia is common in response to potential novel foods (Modlinska and Pisula, 2018). Exploration, on the other hand, involves behaviors that seek information about novel stimuli. Obtaining novel information directly from the environment requires overcoming neophobia and engaging in exploration, tendencies for which may vary between individuals (Jolles et al., 2020). If this information is used, it can facilitate innovation. (Kummer and Goodall, 1985) defined innovation as, ‘a solution to a novel problem, or a novel solution to an old one,’ and ‘a new ecological discovery such as a food item not previously part of the group.’ Behavioral innovations can, therefore, allow species with slow generational turnover to adapt their behavior quickly to changing circumstances, for example, to exploit a novel resource introduced into the current habitat (e.g. McLennan and Hockings, 2014). To innovate, however, it is necessary to go beyond obtaining information through exploration. Individuals must interact with the environment in novel ways, either using novel behaviors with known environmental features, or performing familiar behaviours on novel aspects of the environment, which additionally requires behavioural plasticity (Brosnan and Hopper, 2014). This plasticity can also be highly variable, both between individuals of a species, and within individuals across time (Modlinska and Pisula, 2018). Given the risks associated with novelty and innovation, it is likely only beneficial to innovate when necessary; and motivation based on the physiological states of individuals is likely important in variation in innovation within species (Brosnan and Hopper, 2014; Sol, 2015). Moreover, neophobia and motivation to innovate may vary over time according to an individual’s current needs, developmental status, and transient environmental conditions (Modlinska and Pisula, 2018; Sol, 2015). For example, innovation might be more likely in juveniles who may be less neophobic due to their need to learn about their environment before adulthood, or in dispersing individuals who need to find a new home territory. Accordingly, dispersing individuals may go through a transitory exploratory behavioral syndrome (Sih et al., 2012) at the time of dispersal making them more likely to innovate during that period. Greater behavioral flexibility (‘…adaptive change in the behavior of an animal, in response to changes in the external or internal environment…,’ including stopping or starting a behavior Brown and Tait, 2014) is an important requisite for innovation and is apparent in both juvenile (Kumpan et al., 2020) and dispersing male (Bono et al., 2018) vervet monkeys.

On the other hand, if innovative conspecifics or individuals that uniquely possess particular knowledge are present, individuals can save energy and avoid risks by learning socially from them. Indeed, many studies of diverse species in captivity have found that observing a conspecific eating a novel food reduces neophobic responses (Forss et al., 2017; Modlinska and Pisula, 2018). A study on wild jackdaws found the same (Greggor et al., 2016), and similarly, wild baboons with a ‘bold’ personality handled a novel food for longer after seeing a demonstrator do so (though ‘shy’ baboons did not) (Carter et al., 2014). Further investigation is required in the wild, since the risk for foraging animals to ingest toxins via unknown foods can be high, whilst this risk is diminished in captivity due to human feeding with edible food only. Indeed, captivity and increased exposure to human artifacts appear to increase exploration of novel objects in vervet monkeys (Forss et al., 2022), suggesting differences in risk-taking due to familiarity with human provisions. In addition, individual differences, such as age or sex, of the demonstrating conspecifics may be important (Kendal et al., 2018) and more work is needed on the topic. Moreover, in several species, dispersing individuals have been hypothesized to import information or behavioral innovations, upon immigration, into new groups (O’Malley et al., 2012; Biro et al., 2003; Barrett et al., 2017; Perry, 2003; Péter et al., 2022; McDougall et al., 2010; Gunst et al., 2007). For example, one study reports an immigrant vervet monkey providing spatial knowledge to his new group of a remaining water hole, during a drought, in a neighboring territory (McDougall et al., 2010). Detailed work in capuchins suggests the involvement of immigrants in both creating and spreading innovations in social and foraging domains (Barrett et al., 2017; Perry, 2003). Male Japanese macaques have been suspected to transfer stone handling patterns between troops (Gunst et al., 2007). While these studies show that dispersing individuals might facilitate the spread of information at the population level, experimental evidence focusing on multiple groups is sparse, resulting in a small pool of evidence.

Within wild groups, animals can use social information to guide foraging decisions. Many social learning studies in primates have focused on visual access to information (e.g. Bono et al., 2018; Carter et al., 2014; Barrett et al., 2017; Canteloup et al., 2021; van de Waal et al., 2010; Grampp et al., 2019, and see review in Whiten, 2019). However, for Cercopithecoid monkeys, detailed olfactory information, in a foraging context, may also be acquired through muzzle contact behavior – the act of one individual bringing their muzzle into very close proximity with another’s (Laidre, 2009; Drapier et al., 2002; Chauvin and Thierry, 2005; Nord et al., 2021). Indeed, previous studies found that, whilst foraging, muzzle contacts were most commonly initiated by infants and juveniles towards adults (Nord et al., 2021; Lycett and Henzi, 1992), which supports their function in information acquisition as young animals are still learning about their dietary repertoire, and adults are likely the most reliable sources of information. (Nord et al., 2021) also suggest that, due to the necessary close proximity, social tolerance may constrain information transmission in this modality, which can be affected by age, sex, and rank. In the presence of novel resources, muzzle contacts may be useful to adults as well as youngsters. Experimental research into this mode of information transmission in the presence of a novel resource is now required.

Vervet monkeys (Chlorocebus pygerythrus) are a species that thrive in natural, urban, and agricultural habitats, and are widely distributed throughout eastern sub-Saharan Africa (Turner et al., 2019). Their diverse habitats, including those highly modified by humans, make them an ideal species in which to investigate adaptation to novel environmental conditions. They live in multi-male multi-female troops, with philopatric females, and males dispersing multiple times during their lives. Frequently dispersing males may serve as vectors of information between groups. In addition, if dispersal triggers an increase in exploratory behavior, necessary to seek novelty in order to leave one group to join a new one, around the dispersal period they may also become more likely innovators in novel environments (Sol, 2015), potentially facilitating behavioral adaptation to diverse habitats across their geographical range (Turner et al., 2019). In a previous study by our team (Canteloup et al., 2021), in 2018, two groups (NH, KB) of wild vervet monkeys were provided with a novel food that required extraction (peanuts in shells, Figure 1A) before consumption. The aim of this initial study was to test whether vervet monkeys socially learned how to extract peanuts from their shells, and from whom they did learn. The results supported social transmission of the opening techniques used to extract peanuts, based on visual attention to demonstrators, and that vervet monkeys socially learned the technique that yielded the highest observed payoff and that was demonstrated by higher-ranked individuals (Canteloup et al., 2021). Here, we replicated the same experimental paradigm in 2019 and 2020 in three more groups (AK, BD, LT) after some males from the initially studied groups dispersed to other studied groups. The aim was to investigate whether dispersing males could trigger the uptake of an innovation in their new groups. Specifically, we took advantage of the natural dispersals of males from groups already accustomed to extracting and eating peanuts (Canteloup et al., 2021) into groups that never had. This endeavor afforded us the opportunity to also observe innovation, which subsequently inspired hypotheses about the potential role of dispersal in innovation, building upon the work of others (Brosnan and Hopper, 2014; Sol, 2015). Our observations of innovation are limited in number, but further testing of the hypotheses we propose as a result of our exploratory analysis that we present may aid our understanding of animal innovation.

Dispersal events between study groups where monkeys were exposed to peanuts.

(A) A vervet monkey holding an unshelled peanut, about to open it. (B) Aerial view of the study area with colored shapes showing a rough estimate of group home ranges for study groups AK, BD, KB, LT, and NH. White arrows with annotations represent relevant dispersals. Names of males and year of dispersal are shown. Black outlined text indicates the immigrant innovators who were naïve to peanuts, solid white text shows the immigrants that imported innovations, and white outlined text shows: parallel dispersal with innovator (Yan 2018); that the innovator was habituated in a study group prior to participation in this experiment (Bab 2016); or that the innovator left the study group (Avo 2018). Question mark shows that males dispersed to an unstudied group.

The present study addressed the following questions: First, (1a) Who innovated and how did it affect the extent to which the innovation was adopted by the group? We expected, when the innovators or initiators (in case of immigrant males importing the innovation) were adults rather than juveniles or infants, greater neophobia reduction and, therefore, faster and more widespread uptake of the novel food, in agreement with the three phases in the ontogeny of social learning in primates (Whiten and van de Waal, 2018). Next, to further our understanding of the uptake of innovations, we assessed (1b) whether socio-demographic characteristics (age, sex, rank) of group members predicted their adoption of the innovation at the first exposure, and across all four exposures after the first eating event. We expected adoption of the innovation to be more likely in younger monkeys due to previous findings that juveniles take more risks (Fairbanks, 1993), are less neophobic (Benson-Amram et al., 2013; Bergman and Kitchen, 2009; Miller et al., 2015; Sherratt and Morand-Ferron, 2018), and generally tend to learn faster (Kumpan et al., 2020) than adults.

Second, we experimentally investigated the function of muzzle contact behavior in novel food information acquisition. Specifically, we tested (2a) the effects of the amount of exposure to the food (and, therefore, familiarity with it) and the number of monkeys eating it on the rate of muzzle contacts. We expected that the rate of muzzle contacts would decrease as monkeys had more exposure to peanuts, if there were many monkeys eating. This would provide evidence for the function of muzzle contact in obtaining novel food information, by showing the dependence of muzzle contact rate on individuals developing their own knowledge of it through more group exposures and through eating the food. We also analyzed (2b) whether individuals’ knowledge of the food, and their age, sex, and rank predicted initiating and being targets of muzzle contacts. We expected an effect of knowledge, specifically for naïve monkeys to initiate more, and knowledgeable monkeys to be targeted more, with muzzle contact being a medium to obtain information about what conspecifics are eating. When referring to knowledge we are referring to the individuals’ own knowledge acquired in this specific case that peanuts are a food source. We do not invoke any more complex cognitive skills such as inference of the knowledge of others beyond what is observable of a conspecific eating the novel food. As in Nord et al., 2021, we also expected effects of age, with juveniles more likely initiators and adults more likely targets, as these are the theoretically predicted directions of social information transfer (Whiten and van de Waal, 2018), under the rationale that adults should have the most reliable information. Given the close proximity required to initiate muzzle contacts, we also expected low-ranked individuals to be less likely to initiate muzzle contacts, as they are tolerated by fewer group members (Nord et al., 2021).

Results

We refer to the group AK differentially as AK19 and AK20, representing their status in 2019 and 2020, respectively, as 40% of the group composition changed between years due to dispersals, deaths, and changes in age categories (see Supplementary file 1a and detailed description in Materials and methods).

Across the experiment, a total of 81/164 vervet monkeys in all five groups, learned to successfully extract and eat peanuts during four exposures from each group’s first eating event (Table 1).

Table 1
Cumulative numbers of monkeys eating at each exposure in each group, with a total of 81 (of a possible 164) monkeys eating across the whole experiment.
Exposure number
GroupGroup size123456Total
AK~200*5**13**17**19**-19
BD6519252932--32
KB190013333
LT255131621--21
NH353336--6
Grand total =81
  1. NB. *AK in 2019; **AK in 2020.

When presented with the novel food, multiple individuals (2–16 individuals) in all groups (except BD where the knowledgeable immigrant approached the box first and immediately started eating) approached the box, looked at the peanuts, and retreated without touching any (visual inspection; Table 2); and at least one group member (1–7 individuals) approached and handled, sniffed or nibbled the peanuts before rejecting them and retreating from the box (contact inspection; Table 2).

Table 2
Number of individuals in each group that showed each type of response to the peanuts before the innovator or knowledgeable immigrant started eating.
GroupApproach box and leaveContact exploration and rejection
AK19125
AK2031
BD00
KB154
LT167
NH21

Who innovated and how did it affect the extent to which the innovation was adopted by the group?

When tested in 2018, in NH, a naïve immigrant male, Avo, was the third monkey to approach the box, and innovated extracting and eating peanuts during the group’s first exposure to the novel food. In KB a naïve infant male, Aar, was the 16th monkey to approach the box (across all the exposures) and innovated at the group’s third exposure.

In 2019, in BD, a knowledgeable immigrant male, Pro (who emigrated from NH, Figure 1B), was the first to approach the box and started extracting and eating immediately at the first exposure. In LT, an immigrant male, Bab, was the 17th monkey to approach the box and innovate during the group’s first exposure. In AK, no monkeys innovated in 2019 (AK19), but in 2020 (AK20), at the group’s second exposure (but the first with a knowledgeable immigrant), Yan (also emigrating from NH; Figure 1B), was the fourth to approach the box and the first to extract and eat peanuts (Supplementary file 1a).

During the first exposures to peanuts in BD, LT and NH, when new immigrant males initiated eating peanuts, we observed that the following percentages of these groups started to extract and eat peanuts during that exposure: BD: 31% (group n=65); LT: 20% (group n=25); NH: 9% (group n=35; Figure 2A). In the first exposures in AK19 and KB, no monkeys started to extract and eat peanuts. After an immigrant male ate in AK20, at the second exposure in that group, 30% (group n=20) of the group followed during that exposure (Figure 2A). When an infant innovated at the third exposure in KB, no other group members followed during that exposure (Figure 2A). The immigrant who innovated in NH left the group after the group’s first exposure, leaving just two juveniles who had also started eating at the first exposure. After four exposures from the first eating event in all groups, the percentages of each group extracting and eating peanuts were: 95% in AK20; 66% in BD; 21% in KB; 84% in LT; and 20% in NH (Figure 2B).

Uptake of extracting and eating peanuts in each group.

(A) Shows the proportion of each group that started eating when the first eating event took place. Total numbers of individuals, split by age, are shown below the x-axis. In NH the asterisk highlights the one adult which was the innovator male that left after their first exposure, and was only followed by juveniles learning to extract and eat. (B) Shows the progression in each group over four exposures from the first eating event. Solid squares represent when immigrant males were the first to eat, and the open square shows when the infant was first to eat. Solid lines show when there were adults present who had started to eat, whereas dashed lines show when there were only juveniles and infants present that had already started to eat. Males who were knowledgeable and imported innovations from other groups (Pro in BD and Yan in AK) are excluded from totals in both panels (visualized in Microsoft Excel).

Socio-demographic variation in uptake of the innovation

Here, we examined whether age, sex, and rank predicted successfully extracting and eating peanuts in the first exposure with an eating event and over the four subsequent exposures. During the first exposure an eating event, we found a significant main effect of age, with juveniles 4.17 times (417%) more likely to extract and eat peanuts than adults, and 5.43 times (543%) more likely than infants, but there was no significant difference between infants and adults (Model 1, Table 3). We did not find any significant effect of rank and sex on extracting and eating peanuts at the first exposure with an eating event. Conditional R2=0.25, meaning that model 1 explains a small amount of variance (Table 4). Maximum variance inflation factor (Max. VIF)=1.23, for the variable Age, suggesting no collinearity and that overfitting is not an issue and the dispersion test was not significant (p=0.60), meaning that data were not over or underdispersed.

Table 3
Models outputs for binomial and Poisson generalized linear mixed models.
Model no.OutcomePredictors*CoefficientOdds ratioSEz- valuep-value
1Eat at first exposure with eating event: yes/no (binomial)
N=161
Age: Infant – Adult
Juvenile – Adult
Juvenile – Infant
Sex (M)
Standardized rank
–0.27
1.43
1.69
0.57
–1.52
-
4.17
5.43
-
-
0.65
0.52
0.67
0.42
0.81
–0.41
2.74
2.51
1.36
–1.89
0.912
0.017
0.032
0.175
0.058
2Eat over four exposures from first eating event: yes/no (binomial)
N=161
Age: Infant – Adult
Juvenile – Adult
Juvenile – Infant
Sex (M)
Standardized rank
–0.23
1.68
1.91
0.18
–2.69
-
5.39
6.77
-
0.07
0.55
0.55
0.63
0.41
0.81
–0.42
3.09
3.01
0.45
–3.34
0.908
0.006
0.007
0.656
<0.001
3Freq. muzzle contact per individual per exposure
(Zero-Inflated Poisson)
N=256
Exposure no.
No. eating (std.)
Exposure no.
X no. eating
–0.75
–0.56
0.40
-
-
-
0.10
0.21
0.10
–7.20
–2.70
3.92
<0.001
0.007
<0.001
4Frequency of muzzle contacts initiated (Poisson)
N=253
Prior knowledge (K)–0.460.630.09–5.035<0.001
Sex (M)–0.03-0.29–0.110.911
Standardized rank–2.540.080.57–4.42<0.001
Age: Infant – Adult
Juvenile – Adult
Juvenile – Infant
0.39
1.79
1.40
-
6.00
4.07
0.43
0.36
0.45
0.90
5.02
3.09
0.635
<0.001
0.006
5Frequency targeted by muzzle contacts (Poisson)
N=253
Prior knowledge (K)1.143.130.1011.67<0.001
Sex (M)0.88-0.451.960.050
Standardized rank–1.56-0.85–1.840.065
Age: Infant – Adult
Juvenile – Adult
Juvenile – Infant
–3.44
–0.52
2.92
0.03
-
18.6
1.03
0.51
0.93
–3.98
–0.94
3.13
<0.001
0.603
0.005
  1. *

    Reference categories are Adult, Female, and Naïve for categorical predictors: age, sex, and knowledge, respectively; abbr.: N=naïve; K=knowledgeable; M=male.

  2. Bold italics show significant p-values at 0.05 level.

  3. Indicates post-hoc multiple comparisons (with Tukey correction).

Table 4
Variance and standard deviation of random effects and marginal and conditional R squared of the five generalized linear mixed models presented in the paper.
Random effectsVarianceStandard deviationR2 marginalR2 conditionalSample sizes
Model 1
Eat at 1st expo w/eating event
Group0.420.650.140.24161
Model 2
Eat all expos
Group3.211.790.120.55161
Model 3
MC rate per ind, per expo
Individual<0.0010.910.550.91256
Group<0.001<0.001
Model 4
Freq. MC initiated per ind
Individual1.711.310.120.95253
Group3.421.85
Model 5
Freq. MC received per ind
Individual3.731.930.280.98253
Group1.581.26

Over four exposures from the first eating event, we found a significant main effect of age, with juveniles 5.39 times (539%) more likely to extract and eat peanuts than adults, and 6.77 times (677%) more likely than infants, but no significant difference between infants and adults (Model 2, Table 3). We also found a significant main effect of rank, whereby higher-ranked individuals were more likely to extract and eat peanuts. Specifically, low-ranked individuals were 93% less likely, per unit of standardized rank, than higher-rank individuals to eat. Again, we found no significant effect of sex (Model 2, Table 3). Conditional R2=0.55, meaning that model 2 explains a good amount of variance (Table 4). Max. VIF = 1.30, for the variable Age, suggesting no collinearity and that overfitting is not an and the dispersion test was not significant (p=0.60), meaning that data were not over or underdispersed.

Muzzle contact rate across repeated exposure to novel food

We recorded a total of 498 muzzle contacts initiated by 64 different individuals in all four study groups during the first four exposures from the first eating event.

Regarding the rate of muzzle contacts across exposures, we found a significant interaction between the number of monkeys eating and exposure number (Model 3, Table 3). The main effects of exposure number and the number of monkeys eating were also significant but are not interpretable in this model due to the presence of the interaction. The significant interaction shows that the effect of exposure number depends on the number of monkeys eating (Figure 3). In Figure 3A and B, we can see that whilst muzzle contact rate decreased across the exposures, this decrease was less extreme when more monkeys were eating. This suggests that whilst muzzle contacts decreased as the food become, overall, more familiar in the group, it was still dependent on how many opportunities for muzzle contacts there were, i.e., the number of individuals eating, suggesting a potential social function of muzzle contacts. Conditional R2=0.91, meaning that model 3 explains a significant amount of variance (Table 4). Max. VIF = 4.36, for the variable no. monkeys eating (z-score), suggesting low collinearity and the dispersion test was not significant (p=0.57), meaning that data were not over or underdispersed.

Muzzle contact rate across exposures.

(A) Variation in muzzle contact rate according to the number of monkeys eating and exposure number. Shading shows 95% CI. (B) Model predictions based on the significant interaction between exposure number and number of monkeys eating. When greater numbers of monkeys are eating (blue) the effect of exposure number is less extreme than when fewer monkeys are eating (red).

Influence of knowledge of novel food and socio-demographic variation on muzzle contact behavior

For all individuals present in groups during the experiment, across the four exposures from the first eating event, the mean (s.d.; range) number of muzzle contacts each naïve individual initiated was 2.30 (4.79; 0–26) and they were targeted 0.91 (3.21; 0–22) times; and each knowledgeable individual initiated 2.20 (4.01; 0–26) muzzle contacts and they were targeted 4.81 (11.18; 0–79) times.

We found significant main effects of prior knowledge, age, and rank on the frequency of initiating muzzle contacts (Model 4, Table 3). The number of muzzle contacts initiated by knowledgeable individuals, who had already extracted and eaten peanuts, was reduced by 37% compared to the number initiated by naïve individuals. The odds of lower-ranked individuals initiating muzzle contacts were 92% lower than higher-ranked individuals, per unit of standardized rank. Post-hoc multiple comparisons between age categories showed that juveniles initiated six times (600%) more than adults did and 4.07 times (407%) more than infants did. Conditional R2=0.95, meaning that model 4 explains a significant amount of variance (Table 4). Max. VIF = 1.26, for the variable age, suggesting no collinearity and no overfitting and the dispersion test was not significant (p=0.63), meaning that data were not over or underdispersed.

Regarding being targets of muzzle contacts, we found significant main effects of knowledge and age, and trends for effects of sex and rank (Model 5, Table 3). Here, knowledgeable individuals who had succeeded to extract and eat peanuts were targeted 3.13 times (313%) more than naïve individuals were; juveniles were targeted 37.9 times (3790%) more than infants were, the odds of infants being targeted were 98% less than adults, and there was no significant difference between juveniles and adults (Model 5, Table 3). Conditional R2=0.98, meaning that model 5 explains a significant amount of variance (Table 4). Max. VIF = 1.18, for the variable age, suggesting no collinearity and no overfitting, and the dispersion test was not significant (p=0.98), meaning that data were not over or underdispersed.

Discussion

By exposing five groups of wild vervet monkeys to a novel extractive foraging problem, we created conditions under which to (1) observe innovation by individuals, and the uptake of transmission of knowledge within and between groups, and (2) assess the function and patterns of muzzle contact behavior in the context of encountering a novel food. We found evidence of immigrant males as fast innovators, and as potential vectors of information between groups. We observed faster uptake of the innovation in groups when new immigrant males, rather than infants or juveniles, ate first. We found effects of age and rank on uptake of the food, both during the first exposure, and over four exposures, with juveniles and high-rankers eating the novel food more readily than adults and low-rankers. Furthermore, as groups had more exposure to the food, if many monkeys had started to eat peanuts and olfactory contact with novel food increased, the rate of muzzle contacts decreased. Initiating muzzle contacts was influenced by prior knowledge of the food, age, and rank, and being targeted by muzzle contacts was influenced by knowledge and age. Below we discuss the contributions of these results to perspectives on the potential value of dispersing individuals in the innovation and transmission of behavioural adaptations to novel circumstances within populations.

Who innovated and how did it affect the extent to which the innovation was adopted by the group?

In the two groups where innovation occurred at the first exposure to peanuts (LT and NH), immigrant males, each with less than three months tenure in the group, were the innovators. In KB, an infant innovated, but only at their group’s third exposure to the novel food. Fast innovation (i.e. at the first exposure) to exploit a novel resource by new immigrants could be linked to a physiological state related to dispersal but we remain cautious here as our N=2. In the first exposure in AK19 there was a relatively new male, Boc (Supplementary file 1), who had immigrated within four months, but he was very old (>12 years old) and had recently become very inactive. Boc disappeared, presumably due to natural death, two months after AK19’s exposure to peanuts. Such characteristics may counteract any effects of recent dispersal on exploratory tendencies. Indeed, very old age has been found to be related to declining boldness – a personality trait related to exploration – in big horn ewes (Réale et al., 2000). In addition, the group did not show sustained interest in the peanuts, and after brief inspections of the contents of the box, started traveling away from the experiment area within 5 min from the start of the experiment.

Dispersal has previously been associated with exploration and boldness (i.e. low neophobia) in several taxa, with associated neurochemical variation, both within (ontogenetically) and between individuals (Cote et al., 2010). Moreover, evidence links lower serotonergic activity with earlier dispersal in rhesus macaques (Kaplan et al., 1995), greater social impulsivity in vervet monkeys (Fairbanks, 2001), and reduced harm avoidance in humans (Hansenne and Ansseau, 1999); all of which together relate to low neophobia, or novelty-seeking, with dispersal. Evidence does not, however, suggest that the dispersing sex in wild vervet monkeys are more bold or explorative overall (Blaszczyk, 2017), and in the present study long-term resident males did not show increased interest in the novel food. In another population, long-term resident males also showed reduced responses to novel foods compared to other age-sex classes (Nord, 2021). We suggest rather that the unique individual, social, and environmental factors that prompt a male to disperse (L’Allier, 2020) may trigger a transitory exploratory behavioral syndrome (Sih et al., 2012) that may subside again once males acquire more secure residency in a group. Since dispersal inherently involves heightened risk, periods of long-term residency would be well-served by a state characterized by reduced exploration and increased neophobia to balance the costs of risk-taking over the lifetime. The large variation in risky predator inspection by adult male vervet monkeys, compared to adult females found in Blaszczyk, 2017 also supports this. In the case of Boc, being likely near the end of his lifetime, this could also explain why he did not innovate, however further data are needed to understand whether this is a valid explanation or not. Future work focusing on the behavior of dispersing individuals at multiple time points, both proximal and distal to dispersal events, in this species, and others, will help to more conclusively address this hypothesis. We highlight the need for researchers to consider the nuances of life-history characteristics beyond simply splitting by broad age-sex categories.

We found that when immigrant males were first to extract and eat a novel food in their new groups, during the first exposure to it in BD, LT, and NH, and during the second exposure in AK20, other monkeys quickly followed them in doing so. As discussed above, two of these cases (LT, NH) involved innovation by the immigrant males, and in BD and AK20, the males had learned to extract and eat the food in their previous groups. In contrast, following innovation by the infant in KB at their third exposure, no other individuals followed in extracting and eating peanuts during that exposure. Over the three subsequent exposures that followed these initial eating events, very few monkeys started to extract and eat peanuts in KB, whereas in BD, LT, and AK, where new immigrants ate first, large proportions of these groups learned to extract and eat peanuts. In NH however, this was not the case and is of great interest because though a new immigrant male innovated at the first exposure, he left the group before the second exposure. Closer inspection of our data revealed that only juveniles had started extracting and eating peanuts after the male in the first exposure and were thus the only knowledgeable individuals at the second exposure. Similarly, in KB, only juveniles ate after the infant innovated. Our interpretation of these results is that immigrant males were more effective in facilitating group members to overcome neophobia towards a novel food than infants or juveniles, which is in line with studies reporting age-biased social learning (Barrett et al., 2017; Canteloup et al., 2021). Nonetheless, in NH, more individuals did eventually start to eat during their fourth exposure, including a high-ranked adult female (after which the innovation spread rapidly, resulting in the data presented in Canteloup et al., 2021). In NH, the juveniles eating at the beginning were older than the infants and 1-year-old who started eating in KB. It is possible that age bias is less strong for older juveniles since they should have more reliable knowledge than their very young counterparts. Alternatively, this difference between NH and KB could be because the juveniles eating earlier in NH were of high rank, whereas the infants and juveniles who began to eat in KB were of low rank. Indeed, rank-biased social learning has also been found in previous work in two groups (KB and NH) of this study population (Canteloup et al., 2021; Canteloup et al., 2020). It is nonetheless likely that various interactions of socioecological factors affect the influence of juveniles in overcoming food neophobia in the wild, and it still took repeated exposures before groupmates of the NH juveniles began eating.

Alternative explanations for these patterns of uptake, such as group habituation level to humans or the different experimental histories of each group (see STRANGE framework: Webster and Rutz, 2020), are unlikely. Indeed, in two groups with extensive experimental history (NH, AK), few individuals ate the novel food at their first exposure, whilst in the least habituated group (LT), with the most minimal experimental history (Forss et al., 2022), a great proportion of individuals adopted the novel food at the first exposure (Figure 2A). We hypothesize that observing new immigrants eat the novel food triggered groupmates to try it, rather than factors related to group idiosyncrasies that would be expected according to the STRANGE framework (Webster and Rutz, 2020).

Moreover, whilst previous experiments suggested that high-ranked adult philopatric females are preferred over high-ranked adult males as models to learn from van de Waal et al., 2010, in the context of exploiting a novel resource, risk dynamics come into play. Adult females are likely to be the most risk-averse age-sex category, due to the great potential negative impact of risks on their inclusive fitness, especially when young dependent offspring are present or whilst pregnant. This might limit their potential to discover new information that others can exploit. Under these conditions, adult males that are either in an exploratory dispersal state, or that enter a group with knowledge of resources previously unknown to the group (as in McDougall et al., 2010) may play important roles in generating and/or facilitating the spread of behavioral adaptations to exploit novel resources and face rapid environmental changes.

Socio-demographic variation in the uptake of the novel food

Both, in the first exposure, and over four exposures, juveniles were more likely to eat than adults and infants. These results suggest that juveniles overcome neophobia faster, corresponding closely with results regarding risk-taking in another population of vervet monkeys (Fairbanks, 1993). Furthermore, juvenile vervets have been found to learn faster (Kumpan et al., 2020), and work on other species suggests that juveniles are overall more exploratory and less neophobic than adults (Benson-Amram et al., 2013; Bergman and Kitchen, 2009; Miller et al., 2015; Sherratt and Morand-Ferron, 2018). Taken together we propose that juveniles are, in general, more prone to taking risks around novelty, particularly when conspecifics provide social information. Moreover, alongside the results of section 1 a, we propose that it could be adaptive that groups do not follow novel foraging information from juveniles as readily as adults (i.e. in NH), as this may limit the spread of potentially dangerous information acquired by exploratory but inexperienced juveniles. We also expect that infants were not more likely than adults to eat due to still being at least partly reliant on their mothers to learn their foraging repertoire (Whiten and van de Waal, 2018) in contrast to juveniles who explore more independently.

Over four exposures, higher-ranked individuals were significantly more likely to eat than lower-ranked individuals, probably due to preferential access to the resource as it became more familiar and sought-after.

Muzzle contact frequency in groups

Muzzle contact rates decreased over repeated exposure to the novel food, providing some support for our hypothesis that the less muzzle contacts would occur when the food had become more familiar in each group. However, we expected this effect to be greatest when many monkeys were eating. Contrary to this, muzzle contact rates decreased more slowly when more monkeys were eating. This also makes sense, because more monkeys eating means more monkeys were in the area of the novel food, and therefore, there were more opportunities to engage in muzzle contact. The steeper decrease in muzzle contact rate when fewer monkeys were eating also likely reflects that there were more muzzle contacts at the very beginning, when very few monkeys were eating, and the later exposures where very few monkeys were eating also gave rise to fewer opportunities for muzzle contacts. Cases where very few monkeys were eating in later exposures were due to KB and NH, where very few individuals started to eat over the four exposures time frame examined here, and the two exposures in BD (Expo. 4) and LT (Expo. 3) with only small portions of the group present. Nonetheless, the overall decrease in muzzle contact rate demonstrates the relevance of the behavior in the context of an unknown foraging item, because as the monkeys became more familiar with it by eating it, they sought olfactory information from their conspecifics less frequently. This result concurs with findings from a similar study in wild olive baboons (Laidre, 2009). It could be argued that our conclusion regarding muzzle contact serving to acquire information is premature in the absence of evidence that muzzle contact directly led to individuals eating. However, unlike in the context of observing and learning to use novel tools (e.g. Hobaiter et al., 2014), we do not expect muzzle contact to be a prerequisite to learning to extract and eat peanuts. We argue that muzzle contacts need not be correlated with extracting peanuts in such a manner in order to support that they serve to acquire information. We provide further evidence to support this function below (section 2b).

That there were more muzzle contacts when more monkeys were eating could be interpreted that muzzle contacts are provoked by seeing conspecifics consume any food, regardless of its novelty. We have, however, used provisions of corn kernels in experiments for 10 years with this study population, and when presenting monkeys with this now familiar resource, we do not see rates of muzzle contact anywhere close to those observed during the early exposures in this experiment (Rochat, 2022). This is supported by the significant main effect of exposure number (Figure 3).

Influence of knowledge of novel food and socio-demographic variation on muzzle contact behavior

Muzzle contacts were initiated the most by individuals that had not yet extracted and eaten peanuts (hereafter, naïve individuals; opposite: knowledgeable), higher-ranked individuals, and juveniles. Contrastingly, muzzle contacts were targeted the most towards knowledgeable individuals, and the least towards infants. We find the most compelling evidence for our hypothesis of the function of muzzle contact in information acquisition in that naïve individuals initiated the most and knowledgeable individuals were targeted the most. We do not make claims related to knowing what others know, but rather we assume that seeing a group member eating an unknown resource prompts the initiation of muzzle contact toward that individual. Moreover, this result corroborates the finding in (2a) of decreasing muzzle contact frequency with increased exposure to and familiarity with the resource, and the overall function of muzzle contact in soliciting foraging information.

The effect of age on initiating muzzle contacts falls in line with the expected direction of information transfer from older to younger individuals (Whiten and van de Waal, 2018), with juveniles initiating the most (as also found in Drapier et al., 2002; Chauvin and Thierry, 2005; Nord et al., 2021). It also corroborates general findings regarding juveniles’ novelty seeking and faster learning (e.g. Kumpan et al., 2020; Benson-Amram et al., 2013; Bergman and Kitchen, 2009; Miller et al., 2015; Sherratt and Morand-Ferron, 2018) as discussed above. However, that adults were not targeted significantly more than juveniles in this study (as in Drapier et al., 2002; Chauvin and Thierry, 2005; Nord et al., 2021) is probably because juveniles were more likely to become knowledgeable of the novel food in this experiment (section 1b), and were, therefore, targeted more. This may seem contradictory to our assertion above, that individuals would adaptively not follow information from juveniles, however it is also possible that there is a critical mass effect, whereby when many individuals are already consuming a novel resource, juveniles may become valid sources of information. This is, however, beyond the scope of the present study, but requires further investigation. Furthermore, that infants were targeted the least does follow the direction of information transfer from older to younger individuals, and complements our finding that when an infant innovated, the innovation was not taken up widely in the group.

That high-ranked individuals were more likely to be both initiators and targets is likely because, first, like juveniles, they were far more likely to become knowledgeable, and second, because a high degree of tolerance is required by the target towards the initiator due to the close proximity in which this behavior occurs (as described in Nord et al., 2021). Lower-ranked individuals are not tolerated at the close proximity required to initiate muzzle contacts, especially around food resources; and they were much less likely to become knowledgeable, likely reducing their salience as targets.

Conclusion

We add to the literature an experimental example of exploitation of a novel resource by multiple groups, facilitated here by dispersers. Our results provide evidence that dispersing individuals may promote the generation of new, environmentally relevant information and its spread around populations – a factor that has been largely overlooked, despite the known role of dispersal in gene flow (Greenwood, 1980). We urge future research to investigate what physiological mechanisms might exist underpinning a transitory dispersal syndrome characterized by heightened exploration and reduced neophobia that is triggered during, or triggers, dispersal. We studied a species with sex-biased dispersal and we open up the question of whether similar dynamics as suggested here might be at play in species where both sexes disperse, and whether dispersing females and males show similar levels of boldness during dispersal or not, due to different life-time risk mitigation strategies. Finally, we suggest further research, in diverse species, into whether dispersers transmit valuable information between groups, which can have major implications for population fitness, especially in the context of the rapid anthropogenic change that most animal populations now face. This study contributes novel insights into the roles of dispersers in wider behavioral ecology, which we hope will inspire and inform future work, spanning the disciplines of animal behavior and cultural evolution.

Materials and methods

Experimental model and subject details

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The study was conducted at the ‘Inkawu Vervet Project’ (IVP) in a 12000-hectares private game reserve: Mawana (28°00.327 S, 031°12.348E) in KwaZulu Natal province, South Africa. The biome of the study site is described in Bono et al., 2018.

Five groups of habituated wild vervet monkeys (Chlorocebus pygerythrus) took part in the study: ‘Ankhase (AK)’, ‘Baie Dankie (BD)’, ‘Kubu (KB)’, ‘Lemon Tree (LT)’, and ‘Noha (NH)’. Habituation began in 2010 in AK, BD, LT and NH, and in 2013 in KB. All observers in the field were trained to identify individuals by individual bodily and facial features (eye rings, scars, color, shape etc.). During the study period, these stable groups comprised between 19 and 65 individuals including infants (Table 1). We refer to the group AK differentially as AK19 and AK20, representing their status in 2019 and 2020, respectively, as 40% of the group composition changed between years due to dispersals, deaths, and changes in age categories (infants that became juveniles; see Supplementary file 1a).

Dominance rank calculations

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Agonistic interactions (aggressor behavior: stare, chase, attack, hit, bite, take place; victim behavior: retreat, flee, leave, avoid, jump aside) were collected ad libitum (Altmann, 1974) on all adults and juveniles of each group. These data were collected for a duration of one year, up until the date of each group’s first exposure, during all behavioral observation hours and during experiments involving food provisions. Data were collected by CC, PD, and different trained observers from the IVP team. Before beginning data collection, observers had to pass an inter-observer reliability test with Cohen’s kappa >0.80 McHugh, 2012 for each data category between two observers. Data were collected on handheld computers (Palm Zire 22) using Pendragon software version 5.1 and, from the end of August 2017, on tablets (Vodacom Smart Table 2) and smartphones (Runbo F1) equipped with the Pendragon version 8.

Individual ranks were calculated using the I&SI method (de VRIES, 1998), based on win/lose outcomes of dyadic agonistic interactions, using Socprog software version 2.7. Linearity of hierarchies are reported in Supplementary file 1b. Ranks were standardized to represent the proportion of the group that outranks each individual, falling between 0 (highest) and 1 (lowest) in each group (rank – 1/group size). Agonistic data on adults and juveniles were included, and we assigned infants with the rank just below their mother, based on the youngest offspring ascendency in this species (Cheney and Seyfarth, 1990).

Peanut exposures

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We provided each group with a highly nutritious novel food that required extraction before consumption – unshelled peanuts (Figure 1A) – in large quantities to avoid monopolization by single individuals. Experiments took place after sunrise when the monkeys were located at their sleeping site during the dry, food-scarce South African winter, to maximize both the motivation to engage in food-rewarded experiments and the number of group members in the vicinity.

CC ran field experiments from May-June 2018 in KB and NH, and PD led the experiments during August-September 2019 in AK (AK19), BD and LT, and May-June 2020 in AK (AK20; Supplementary file 1). AK19 and AK20 are used to denote AK in 2019 and 2020, respectively, because approximately 40% of the group composition changed in the year in between exposures, and no individuals ate in 2019, meaning the food was still novel to the group in 2020. Figure 1B illustrates the relevant male immigrations into and emigrations out of these groups. Avo left his natal group KB to immigrate to NH two weeks before their first experiment in 2018. Avo never ate peanuts before the first exposure in NH. KB had no new males since 2017. Pro originated from NH and learned to eat peanuts during their experiment in 2018. He immigrated to BD three weeks before their first experiment in 2019. Bab immigrated into LT six weeks before their first experiment in 2019, from an unhabituated group, though he was habituated to humans and food experiments due to previous residence in two habituated study groups. Bab never ate peanuts before LT’s first exposure. In 2020, two males, Twe and Yan, who were present in NH during peanut exposures in 2018, immigrated to AK, six and ten weeks, respectively, before their experiment in 2020. Twe ate peanuts in NH during peanut exposures that continued beyond the four presented here in a previous study (Canteloup et al., 2021), and Yan had observed many others eating peanuts. Yan was the first to eat in AK in 2020 (Figure 1B).

Peanuts were presented to all groups in clear rectangular plastic boxes (34 × 14 × 12 cm), containing 1–2.5 kg of unshelled peanuts. We considered the beginning of an exposure when the experimenters placed the box on the ground, removed the lid, and stepped away, giving access to the monkeys. Exposures ended when the monkeys were clearly traveling away from the experiment site. Experimental sites were chosen at whichever sleeping site the monkeys were found, except in BD, in which it was wherever the group was after 1 hr of a focal follow of Pro, due to previous aims of the study, and thus was not always at the sleeping site. The boxes were placed visible to as many group members as possible, with the exception of the first exposure in BD where we placed the box close to the knowledgeable male, Pro, due to our initial aim to investigate intergroup transmission. One box of peanuts was offered per exposure in AK, BD, and LT. In KB and NH, two boxes were offered during each exposure, and were topped up when they were empty. Exposure durations ranged from 5 min (AK19) to 74 min (LT). KB and NH had 10 exposures on 10 different days; AK20, BD, and LT had four exposures on four different days; and AK19 had a single exposure (Supplementary file 1). The groups tested by PD (AK, BD, LT) had fewer exposures overall due to time constraints. Here, we present results for each group from the first four exposures from the first eating event in each group. Whilst AK, NH, and KB had more than four exposures in total, BD and LT had only four, meaning that taking four exposures from the first eating event is the most reasonable way to compare these groups. In addition, after four exposures from the first eating event, over 90% of AK and LT had learned to eat peanuts, limiting the reasons to run further exposures with them.

Reactions to and interactions with peanuts were recorded by three to five observers using handheld JVC video cameras (EverioR Quad Proof GZ-R430BE) and cameras mounted on a tripod. Observers narrated the identities of monkeys interacting with peanuts for later video coding.

Quantification and statistical analysis

Video coding

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To extract the identities of individuals who successfully extracted and ate peanuts from their shells during each exposure, PD-coded videos of AK19-20, BD, and LT with the Windows 10 default video software, and CC-coded videos of KB and NH with Media Player Classic Home Cinema software version 1.7.11. Having extensive experience working in the field with these groups, PD and CC were proficient in recognizing individuals from the videos, and often the identities were narrated live in the audio of the video recordings which provided additional assurance of accuracy.

For analyses of muzzle contacts, GL and PD counted the frequency of muzzle contacts in videos of AK20, BD, KB, LT, and NH. MC assigned identities of individuals involved in these muzzle contacts using data provided by PD in the form of scan samples of the identities of all monkeys on the screen from left to right at every minute of each video.

To test interobserver reliability, PD recorded 15% of all videos in the study that were originally coded by CC, to verify agreement on what each coded as ‘successful extracting and eating,’ and achieved a Cohen’s kappa of 0.96. PD also recorded 10% of the videos of the study that were originally coded by GL to verify agreement on what constituted muzzle contact interactions, and achieved a Cohen’s kappa of 0.98.

Data analysis

Who innovated and how did it affect the extent to which the innovation was adopted by the group?

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We did not formally analyze these data, we only described who innovated and which individuals began to consume the novel food in each group.

Demographic variation in the uptake of the novel food

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We used two generalized linear mixed models (GLMMs) for data following a binomial distribution to investigate demographic variation in whether or not individuals extracted and ate peanuts (question 2b). The first model investigated (i) the first exposure with an eating event (AK20, BD, KB, LT & NH; Model 1; Table 5), and the second model investigated (ii) four exposures from the first eating event (AK-20, BD, KB, LT & NH; Model 2; Table 5). In each model, the outcome was a binomial yes/no variable (did the individual eat), we considered age, sex, and rank (standardized rank) as fixed effects and the group was included as a random effect. Males that dispersed between groups were only considered in their first group in this analysis, so all individuals were only considered once in these models. Effect sizes are reported as odds ratios. Here and in all subsequent models, we inspected Q-Q plots and residual deviation plots, and tested for over-/underdispersion using the DHARMa R package (Hartig, 2022) to assess model suitability.

Table 5
Model structures.
DistributionOutcomeFixed effectsRandom effects
Model 1
Eat at 1st expo w/eating event
BinomialEat: Yes / NoAge (adult/juv./infant)
Sex (F/M)
Rank*
Group
Model 2
Eat all expos
BinomialEat: Yes / NoAge (adult/juv./infant)
Sex (F/M)
Rank*
Group
Model 3
MC rate per ind, per expo
Zero-inflated PoissonFreq. initiatedExposure number (1-4)
No. monkeys eating (z-score)
Duration of exposure (mins.; offset)
Group
Individual
Model 4
Freq. MC initiated per ind
PoissonFreq. initiatedPrior success (1/0)
Age (adult/juv./infant)
Sex (F/M)
Rank*
Total exposure duration per ind. (mins.; offset)
Group
Individual
Model 5
Freq. MC received per ind
PoissonFreq. receivedPrior success (1/0)
Age (adult/juv./infant)
Sex (F/M)
Rank*
Total exposure duration per ind. (mins.; offset)
Group
Individual
  1. *

    Dominance rank calculated with I&SI method, and standardized between 0 (high rank) –1 (low rank) – see Methods for more details.

Rate of muzzle contact over repeated exposure to the novel food

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To investigate the effect of exposure to the novel food on muzzle contact rate, we looked at four exposures from the first eating event for each group, as this event marks when at least one member of the group had recognized the novel food as a viable food. We also wanted to account for the number of individuals eating during each exposure, as it was inherent in our hypothesis that muzzle contacts around the novel food would be related to individuals eating it. Specifically, we expected the muzzle contact rate to decrease across exposures when there were many monkeys eating it and, therefore, developing their own knowledge of it, but not if only very few were eating. To test this, we fitted a Zero-Inflated Poisson GLMM (using the glmmTMB function from R package ‘glmmTMB’ Brooks et al., 2017) with a frequency of muzzle contacts initiated by each individual as the outcome variable, exposure number, and the number of monkeys eating during the exposure (z-transformed) as fixed effects, with an interaction between the two, and group and individual as random effects. We included the log of the duration of the experiment as an offset in order to model the rate of muzzle contacts per minute per individual (Model 3; Table 5). Effect sizes are reported as odds ratios. We used the DHARMa R package (Hartig, 2022) to assess model suitability (as above), and to test zero inflation in an initial Poisson GLMM.

Influence of knowledge of novel food and socio-demographic variation in muzzle contact behavior

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We wanted to assess which factors influenced individuals’ involvement in muzzle contact interactions. Specifically, we wanted to test hypotheses regarding the function of this behavior in information acquisition, so whether individuals’ prior knowledge of the food was an important factor or not. We expected individuals who had not yet successfully extracted and eaten peanuts to initiate more muzzle contacts, and those who had already successfully extracted and eaten peanuts to be targeted more. In addition, if muzzle contact is involved in information acquisition, as we predicted, we would also expect variation between different age, sex, and rank classes in whether they initiated more or were targeted more in line with our current state of understanding of social learning in this species. To investigate this, we counted how many muzzle contacts each individual of each group was involved in, first separated by whether they were the initiator or target, and further, by whether they were naïve or knowledgeable about the novel food. We then used two GLMMs to analyze (i) what factors influenced initiating muzzle contacts (Model 4), and (ii) what factors influenced being targeted by muzzle contacts (Model 5). Model 4 had the frequency of initiating as the outcome variable, with prior knowledge, age, sex, and standardized rank as predictors, and individual and group as random effects (Table 5). Model 5 had the frequency of being targeted as the outcome variable, with prior knowledge, age, sex, and standardized rank as predictors, and individual and group as random effects (Table 5). In both of these models, the log of each group’s total duration (minutes) of exposure to peanuts was used as the offset, and effect sizes for both of these models were assessed as odds ratios.

We ran post-hoc multiple comparisons (with Tukey correction) between the age categories (adult/juvenile/infant) using estimated marginal means comparisons from the ‘emmeans’ R package (Lenth, 2021).

In all analyses described above, we probed interactions using post-hoc multiple comparisons (with Tukey correction) of estimated marginal means using the R package ‘emmeans’ (Lenth, 2021) and plotted the interactions using the R package ‘interactions’ (Long, 2019). All model diagnostics were analyzed using the ‘DHARMa’ R package (Hartig, 2022), and multicollinearity was assessed using variance inflation factors (VIFs) calculated with package ‘car.’ We calculated marginal and conditional r-squared for each model using the MuMIn package in R and compared their value to assess the amount of variance explained by the fixed effects only (R2 marginal) and by the fixed effects and the random effects (R2 conditional). We also compared the AICs of the models with and without random effects and the lowest AICs were always those of the models with random effects, meaning that the models that fitted better to our data were those with random effects. Model assumptions were satisfied unless otherwise reported and adjustments made. Statistics were computed in R Studio (R version 4.0.3), and linear regression was done with the base R stats package (R Development Core Team, 2020). GLMMs were done using the ‘lmerTest’ package (Kuznetsova et al., 2017).

All data and R scripts are made available at: https://doi.org/10.5281/zenodo.7376673.

Data availability

All data and code used for analyses are freely available at: https://doi.org/10.5281/zenodo.7376673.

The following data sets were generated
    1. Dongre P
    2. Lanté G
    3. Cantat M
    4. Canteloup C
    5. van de Waal E
    (2022) Zenodo
    Role of immigrant males and muzzle contacts in the uptake of a novel food by wild vervet monkeys.
    https://doi.org/10.5281/zenodo.6827878

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Decision letter

  1. Ammie K Kalan
    Reviewing Editor; University of Victoria, Canada
  2. George H Perry
    Senior Editor; Pennsylvania State University, United States
  3. Julie Teichroeb
    Reviewer; University of Toronto, Canada

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "Role of immigrants and muzzle contacts in the uptake of a novel food by wild vervet monkeys" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and George Perry as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Julie Teichroeb (Reviewer #3).

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

Essential revisions:

All three reviewers found this study to hold great potential in providing significant new insights into the field of social learning and transmission in wild animals. However, due to a number of important concerns with the analysis it is difficult to ascertain whether the authors' claims are valid given the evidence. We invite the authors to address these major concerns in a substantially revised version of the manuscript.

1) Statistical analysis needs revising:

A number of concerns regarding multiple testing and the structure of your mixed models require attention. In particular, please consider using a multimodel approach due to the exploratory nature of your analyses (see suggestions from Reviewer 1 and 2) and revise the structure of your mixed models to include essential random effects where necessary, and address potential confounding variables such as group size, combining age and sex into one variable, and the directionality of muzzle-muzzle contact initiations (see all 3 Reviewer comments for details). Please also ensure the code for all your models/analyses have been provided.

2) Methods need to be more transparent:

All reviewers found that parts of your study lacked sufficient detail to be repeated by others. Could you please provide clear criteria for the various decisions made throughout the study as well as justifications for cut offs used (e.g., why 3 months for immigrant males?). The rank calculation also needs more clarity and various decisions made by the authors are not justified/clear. Please also provide interobserver reliability tests regarding coding (see Reviewer 1 and 2 for details).

3) Study needs reframing:

All three reviewers found the introduction lacked direction and conceptual clarity. Please provide a more thorough rationale for your study and integrate this into a list of explicit research questions and predictions. The discussion would also benefit from consideration of alternative explanations (see details in comments from all 3 Reviewers).

Reviewer #1 (Recommendations for the authors):

I have some suggestions regarding the methods:

– It needs to be reported what decided when a trial was begun, and ended, as this would help explain the differences in the trial lengths.

– It would be very helpful to report how STRANGE these animals are, especially given this manuscript is about innovation; see:

Webster, M. M., and Rutz, C. (2020). How strange are your study animals. Nature. Nature, 582, 337-340. https://www.nature.com/articles/d41586-020-01751-5?sf235295265=1

Farrar, B. G., and Ostojić, L. (2020). It's not just the animals that are strange. Learn Behav. Learn Behav. https://doi.org/10.3758/s13420-020-00442-5

I have some suggestions regarding the analyses:

– The R package DHARMa is a great resource for model residual diagnostics.

– There are no effect sizes reported for any of the models.

– The code for the first muzzle contact model, looking at rate, wasn't included, and so I was unable to review it. Further, it was unclear as to if only a subset of the available data was used for this model (groups with lots of eaters), and if so, why. Including group as a random effect could help account for any group differences that the authors may have felt relevant to subsetting the data, thus allowing all of the data to be examined.

– Collecting data in the field is quite different from coding from videos, and reporting a reliability measure on the video data would help readers to assess the manuscript's findings.

– It seems to me that all models need both ID and group as grouping variables (random effects). This is because all of the models, as far as I can tell, include some of the same adult males (though on different troops), and all of the analyses are all conducted across all of the groups, requiring group to be a random effect.

– Exposure to the experiments varied widely across groups, and it is unclear if all animals on the same groups were around for the trials (I'm assuming they weren't as some trials were dropped due to low numbers of participants). These discrepancies need to be accounted for in the manuscript and analyses.

– There is no explanation as to why there are three different versions for the provided models looking at muzzle contact (1 model with (non-normalized) rank, 1 with two interactions but without rank, and 1 with three interactions, but also without rank). Why was rank dropped? Why were interactions included? If multiple models are going to be considered, a model comparison value, like AIC, should be included to compare the models (after first explaining the theoretical reasons as to why different versions were considered).

– How was rank normalized, and why was normalized rank considered in some models but not others?

– Figure 2A y-axis is unclear- shouldn't it be closer to 50% for BD given 35 innovated? Or is this just after the first exposure? Or first eating event?

Other questions/ suggestions:

– Line101: why the possessive on "groups"?

– Line 286: this is in line with the hypothesis of Nord et al. 2020, which concluded that, "both kin and low-rank- ing animals serve as discriminative stimuli for social tolerance and that foraging animals serve as discriminative stimuli for food availability" Though, this manuscripts first muzzle contact model (for which the code was not provided) found no evidence of a rank effect (though rank wasn't included in the interaction models), which is in contrast to Nord et al., thus providing an interesting extension to findings about muzzle contacts, in that social tolerance may play less of a role in cases of novel foods.

– Line 289: This also agrees with Nord et al.

– Line 300-302: Do the juveniles referred to here out rank adults? Are ranks calculated across all age types in these data?

– Line 303-305: The manuscript reports that juveniles have information, but aren't passing it…how is this an adaptation to risky behavior, if juveniles are more likely to eat something novel anyway? Isn't this doubly bad for juveniles, in that they are more likely to eat something they don't know, which can be dangerous, and also aren't functioning as a source of information when they have it?

– 309-311: This could possible be tested putting age and sex, as a combined variable, in the model, creating no need to have an interaction between age and sex and knowledge, and instead would only need one between Age-Sex and knowledge

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Role of immigrant males and muzzle contacts in the uptake of a novel food by wild vervet monkeys" for further consideration by eLife. Your revised article has been evaluated by George Perry (Senior Editor) and a Reviewing Editor.

The manuscript has been greatly improved but there are some remaining issues that need to be addressed. In particular, the responses to reviewer concerns regarding the conceptual framing of the study and the analysis are not sufficiently addressed and we find the justification for not making the suggested changes unsatisfactory.

In your revised submission please ensure you adequately address the major comments provided by Reviewers 1 (points 1-6) and 2 (points 1 and 2).

To summarize, the introduction still requires substantial revisions to provide a more clear conceptual framework and predictions, along with how this aligns with your analyses. The analysis also requires attention as key components of models are still missing, (i.e., random effects) and the transparency of your results will be much improved if sample sizes and R-squared values are reported for each model. See Reviewer comments below for details.

Reviewer #1 (Recommendations for the authors):

The authors have done a great job making the introduction more applicable to the research conducted. It is still a bit disorganized, which I comment on explicitly below. Furthermore, the exploration of role of knowledge in information-seeking is an important contribution, as this kind of social/contextual account is not often a topic of study in the social learning and innovation literature.

1. The introduction seems to present the idea that learning what to eat is innovation, and that dispersing is reflective of innovative abilities, though I'm not certain that this is what the authors intend. In the discussion, the explanation as to why dispersing animals may be more likely to innovate when they are dispersing (a "transitory exploratory behavioural syndrome") is much more clear. Indeed, it might work better to introduce this idea in the introduction, and continue along the same lines with regard to juveniles-that given that they need to learn about their environments, they might be better primed to innovate akin to the transitory behavioural syndrome of dispersing animals, rather than viewing ontogeny as a constant state of innovation. However, it is still unclear as to when males are considered immigrants vs. residents. Surely after group integration, they are no longer experiencing a "transitory exploratory behavioural syndrome.". Explicitly outlining this distinction (dispersing vs. resident) would greatly help the manuscript.

2. Additionally, it is very odd that all of the predictions presented in the introduction are exactly what is found, even when they are in contrast to the literature. This is especially difficult given the predictions about rank, and that, as long as I'm reading the methods correctly, the rank results are actually presented backwards, meaning that the authors found the opposite of what they report (i.e., because increasing rank values equals decreasing rank--higher ranking animals are represented by lower values--and the models found a positive effect of rank, then it is that lower ranking animals were more likely to eat the novel foods, not higher ranking animals; this is in line with the neophobia literature that predicts that higher ranking animals should be more neophobic, in contrast with the prediction provided in the introduction).

I have a number of questions with regard to the analysis:

3. I must disagree with part of the explanation given as to why group wasn't included as a random effect in one of the models. As I mention below, multilevel modeling (the use of grouping variables/random effects) isn't done in order to test predictions (though it can be used as such), it's about controlling for structure inherent in the data. Given that these animals exist in groups, then this fact needs to be accounted for in the statistical models. This seems especially important to me given that many of the models find variation with regard to group, which can be seen when investigating the summary output of these models using the code provided, and comparing the marginal vs. conditional r-squares. Furthermore, I don't understand this assertion of no expectation between groups, as there are at least two papers by the last author of this study arguing for the consideration of group-level variation in primate groups, especially when it comes to foraging:

Tournier, E., Tournier, V., van de Waal, E., Barrett, A. S., Brown, L., and Bshary, R. (2014). Differences in diet between six neighbouring groups of vervet monkeys. Ethology, 120(5), 471-482. https://doi.org/10.1111/eth.12218

van de Waal, E. (2018). On the neglected behavioural variation among neighbouring primate groups. Ethology, 340(10), 485-410. https://doi.org/10.1111/eth.12815

I think it is fine to say that the model wouldn't converge with group as a random effect and leave it there, as long as this is a limitation acknowledged in the results and their interpretation. Using a Bayesian approach would likely solve this issue because it performs better with smaller datasets and more complicated modeling than lmer, though I don't see it necessary that the authors change their statistical approach, though this is clearly the method preferred in the materials included supporting why group was dropped as a random effect in the R script.

4. When looking to the data and analysis code, there are 21 individuals that are measured twice in model 1 and 3 that are measured twice in model 2. It appears that some are males that moved groups, so I'm confused by the authors' reply that each dispersing male was only measured in the group that they first ate. Others appear to be animals that aged up during the study. I do see that if Individual is included as a random effect in models 1 and 2, the fit is singular. Perhaps a solution is to filter the observations to those in which the individual first ate, and mention this in the methods, as the authors replied they did (but my review of the analysis doesn't confirm). Another solution would be to run the models using a Bayesian approach, which would also fix the fitting problem with model 6 when including group as a random effect. Also, for model 2, there are 27 individuals marked as NAs for group AK19 for the measure of whether they ate in the first 4 exposures, when they have 0 for eating in the first exposure. Did I miss information as to why these animals were dropped from model 2 given they were measured in model 1? That is, while there are 191 observations (of 170 unique animals) in model 1, there are only 164 observations (of 161 unique animals) in model 2.

5. Model 3 doesn't seem to meet model assumptions for the residuals, and the R code state that this is fine for the sample size used. This needs to be reported in the main text-that model diagnostics reported an issue, and why the authors believe that this issue is not relevant.

6. The table for model 3 is not reported in the text.

Please see my detailed comments below:

20-21: Consider changing "according to the innovator" to "with respect to the initial innovator"

28-30: This sentence is a bit hard to follow. It might be better to talk about what was found, rather than what wasn't found, i.e.,

"Knowledgeable males and adults were more likely the targets of muzzle contacts compared to knowledgable females and juveniles, while also being less likely to be initiators."

48: What is meant by "potential" novel foods?

50-51: the line between "obtaining novel information" and "produces information or knowledge, potentially facilitating information" is murky. New information gained by an individual isn't always reduced by them…perhaps something like "and has the potential to produce information on which other group members can act." instead.

58: Behavioural patterns don't have be novel to be adaptive in new environments, as in the definition of innovation provides above-innovation could be a solution to a novel problem, including generalizing one behaviour, e.g., extractive foraging like getting acacia seeds from seed pods, to a novel situation, like extracting peanuts.

60: What's "this"? Behavioural plasticity? Behavioural patterns?

61: The risks association with novelty and innovation are unclear here. Up until this point, innovation and novelty have been largely been framed as positive, whereas only neophobia was mentioned with avoiding ris

66: Are juveniles required to innovate to learn about their environments? Learning about what is available as food in your group is not the same as finding a new food. Similarly, do dispersing animals need to innovate, or do they need to use previously-learned social skills to ingratiate themselves to a new group? Neither of these examples are a "a solution to a novel problem" or a "novel solution to an old one". Learning what to eat is not a novel problem…much like learning who your allies are isn't a novel one either. What really is the problem here is whether innovation happens at the level of the individual or group… certainly learning what to eat as a juvenile, or integrating into a new group, isn't a novel problem for this species, but one every animal must meet (save females re: dispersal). What I mean to say here, just because juveniles might be more prone to innovate, it's not necessarily from necessity, but could be a result of a developmental period that functions primarily to allow them to learn about their environments-while behavioural flexibility is necessary for innovation, it is not the same as innovation.

70: Why "nonetheless" here? The points following "nonetheless" seem to follow the points before it, and are not in contrast.

77: How is the risk diminished? Are captive animals are less neophobic because they are fed-is risk assessment, for which neophobia is a conserved trait across many species, is ontogenetically determined? Or is the point here that is more difficult to study such phenomenon in captivity, because there is no risk? I assume it's this latter point, but such risk assessment is never addressed in the current study, other than to mention that wild animals often experience changing environments, especially resulting from anthropogenic origins.

77-79: Individual differences with regard to innovation and behavioural plasticity has been shown to be true across many studies, including vervets, though there has been some conflicting evidence (cited below)…would it be better to say more work is needed, given the conflicting evidence?

Bono, A. E. J., Whiten, A., Schaik, C. V., Krützen, M., EichenBerger, F., Schnider, A., and van de Waal, E. (2018). Payoff-and sex-biased social learning interact in a wild primate population. Current Biology. Current Biology, 28(17), 2800-2805. https://doi.org/10.1016/j.cub.2018.06.015Bono, A. E. J., Whiten, A., Schaik, C. V., Krützen, M., EichenBerger, F., Schnider, A., and van de Waal, E. (2018). Payoff-and sex-biased social learning interact in a wild primate population. Current Biology. Current Biology, 28(17), 2800-2805. https://doi.org/10.1016/j.cub.2018.06.015

Renevey, N., Bshary, R., and van de Waal, E. (2013). Philopatric vervet monkey females are the focus of social attention rather independently of rank. Behaviour. Behaviour, 150(6), 599-615. https://doi.org/10.1163/1568539X-00003072

Canteloup, C., Hoppitt, W., and van de Waal, E. (2020). Wild primates copy higher-ranked individuals in a social transmission experiment. Nat Commun. Nat Commun, 11(1), 459-469. https://doi.org/10.1038/s41467-019-14209-8

79: "For example" might work better here rather than "moreover", since it's continuing the previous point. The reference to chimpanzees explicitly here is unnecessary, as the citations used include species beyond chimpanzees. "For example, across many species where males disperse, dispersing individuals…" would work better.

80: Citations [19] and [20] here use capuchins, not chimpanzees

85: Add "While these studies show that dispersing individuals…experimental (no "but")". However, at this point it is not clear to me why we need to compare multiple groups experimentally-this needs support.

70-100: This paragraph is very confusing to follow, as there are multiple independent points being made, including how social learning is beneficial, how the dispersing sex can import innovations or create them, a brief mention of the interface between social learning and innovation (i.e., it is implied that they are separate processes, but all of the benefits of this introduction point to species-level benefits of innovation, which require innovations to spread, so the brief mention of social learning here seems too minimal), and a discussion of social learning modalities.

97: Why the mention of social tolerance here? It is not clear how social tolerance speaks to the questions asked by this study.

103: What's "this"?

107: I'm still not sure why males need to innovate? Don't they, at most, need to generalize the behaviours of their previous groups to a new one? Why must they innovate?

123-124: Consider changing to "Our observations of innovation are limited in number, but further testing of the hypotheses we propose, as a result of our exploratory analysis that we present here, may aid our understanding of animal innovation.

125: Consider changing to "Given that animals learned to eat a novel food source, a behaviour that spread socially [24], (1a)…"

126-129: Why did you expect this?

130: "which" implies the results were known beforehand; "whether" might work better here.

131: Change "over all" to "overall"

131-133: Why differentiate across exposures here, especially since the predictions are the same? I know there are 2 different models, but I need to know why here so that I can understand the differing predictions. Moving the explanation as to why the first 4 exposures were considered to here would be helpful.

132: What's "this"?

134-136: There seems to be a bit of double-dipping here, as the findings from one dataset (at least for 2 groups) are used as evidence for a prediction for data in the same dataset (the current study). Additionally [24] and [39] found that higher-rankers are more likely to be observed, not that they were more likely to uptake a novel food. In fact, the common prediction here is that higher-ranking animals should be more neophobic, because they have better access to food and thus eating unknown food is riskier for them given their prime access to food overall:

Wolf, M., van Doorn, G. S., Leimar, O., and Weissing, F. J. (2007). Life-history trade-offs favour the evolution of animal personalities. Nature. Nature, 447(7144), 581-584. https://doi.org/10.1038/nature05835

Greenberg, R. (2003). The Role of Neophobia and Neophilia in the Development of Innovative Behaviour of Birds Animal Innovation. In S. M. Reader and K. N. Laland (Eds.), Animal Innovation (pp. 175-196). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780198526223.003.0008

Laland, K. N., and Reader, S. M. (1999). Foraging innovation in the guppy. Animal Behaviour. Animal Behaviour, 57(2), 331-340. https://doi.org/10.1006/anbe.1998.0967

But see:

Amici, F., Widdig, A., MacIntosh, A. J. J., Francés, V. B., Castellano-Navarro, A., Caicoya, A. L., Karimullah, K., Maulany, R. I., Ngakan, P. O., and Hamzah, A. S. (2020). Dominance style only partially predicts differences in neophobia and social tolerance over food in four macaque species. Scientific reports. Scientific reports, 10(1), 1-10. https://doi.org/10.1038/s41598-020-79246-6

Drea, C. M. (1998). Social context affects how rhesus monkeys explore their environment. American journal of primatology. American journal of primatology, 44(3), 205-214. https://doi.org/10.1002/(SICI)1098-2345(1998)44:3%3C205::AID-AJP3%3E3.0.CO;2-%23

140-142: This makes sense to me, but I have no idea why this prediction is made. Perhaps moving the explanation given to the me

146-147: "the media" implies that this is how animals are learning to eat the peanuts…but the author replies to reviewers mention multiple times that this is not what is meant.

147-150: This has been previously found in [31]; thus there is both theoretical and empirical support for this prediction.

152: [31] found this, and hypothesized that social tolerance is necessary for muzzle contact to afford foraging information, but perhaps and additional citation here about how lower ranking animals are tolerated by fewer group members would help make the point.

153-154: Initiated vs targeted…via muzzle contact?

158-161: I don't follow…this seems to assume that initiators are seeking information and this seeking will outweigh any social tolerance constraint, but only previous study of muzzle in vervets found that tolerance was the best predictor of the behaviour. Thus, this prediction needs more support as to why it is in the opposite direction of what the literature shows, i.e., that social tolerance constrains information-seeking and information spread, akin to Carter's (2016) sequential social learning hypothesis.

161-173: What kind of different experiences of novelty arise from the life history trajectories of the philopatric vs. dispersing sex? Again, why do dispersing animals experience more novelty? Why should we expect the groups to which they are dispersing to have significantly different diets that we can call "novel"? Do dispersing animals need to gain totally new information? Surely not, as the kinds of foods available are likely very similar and behavioural generalization can do a lot of work. When it comes to conspecifics, isn't a plausible alternative hypothesis that dispersing animals need to enter groups using the same skills needed to integrate in to the adult social networks as they age in their natal groups before dispersal…so what counts as novel here? Again, I see these problems as being neither novel or the success of dispersing animals after integration into new groups as being dependent on a novel solution. It seems to be the novelty of interest here is much larger, as mentioned at the beginning with reference to anthropogenic-induced changing environments, rather than the kinds of problems these animals have encountered throughout their evolution.

164-165: Why this prediction? I can think of some reasons why this is, but there is no support for this prediction that naive adults should initiate and receive at the same rates…prior evidence [31] suggests that adults should more often be targeted than initiate, so it seems here that this prediction relies on explicit knowledge seeking, which requires the prediction the muzzle contact is primarily used to gain novel information.

166-167: Why should females initiate if they don't "need" info, which is what this prediction is implying…presented like this, this prediction reads as if the results were already known when it was made.

169-171: Why would malesy stop initiating? Why does initiating influence receiving? One does not preclude the other…

170-173: I don't follow this prediction at all… that knowledgeable males are somehow more tolerated…doesn't the work reviewed in the introduction at least imply that new immigrants have novel information, and by definition, new immigrants are less known to the group, so should be interacted with less. How does a muzzle contact initiator know that a new male is knowledgeable? And why wouldn't a new male be less tolerated by others compared to an established male, who has relationships with the group? Again, I'm not sure of the dismissal of tolerance here, when the only previous work on muzzle contact in vervets found that social tolerance, above all else, influences muzzle contact behaviour? Especially given that prediction 2b makes a social tolerance prediction, that lower ranking animals will initiate less than higher ranking animals.

179-182: Why mention this here? Perhaps this would be better at the very beginning of the results, or near where the differentiation is first referred to in the results.

209: Should this be "his" instead of "their"?

213-221: This use of uptake is confusing… in the reply, the authors state " the reason we talk about 'uptake' rather than social learning is that we really see this as a case of social disinhibition of neophobia, rather than more detailed social learning such as copying or imitation" but this disinhibition hypothesis is never mentioned in the introduction. The introduction needs to make clear this distinction, and why, despite that this behaviour was previously shown to be socially transmitted, social learning language here. I see no reason not to report that this behaviour is socially transmitted and that this study takes the opportunity to explore who innovated and whether socio-demographic variation corresponded with innovation, as well as the opportunity to further explore muzzle contact as a means of learning about novel foods given previous evidence showing that muzzle has the potential for being a learning modality, rather than proposing an entirely different mechanism.

Also, how does one prove the difference between the uptake of the innovation being the result of social disinhibition and the topography of opening the peanut being socially transmitted? I understand the use of EWA to show the latter, but am not sure how that is separate in fact from the former…how does one show the approach and willingness to interact is only socially facilitated, but the opening itself is socially learned? Especially given that all of the results in this study are presented in regard to who extracted and ate the peanuts, and not some other measure of neophobia.

218-220: Wasn't rank standardized, with 0 being the highest ranking? Because this model found a positive "non-significant trend" of rank, doesn't this mean that lower ranking animals (e.g., those with higher values in the model) were more likely to eat at first exposure? And this is the same for the findings over 4 exposures (225-228), as well as frequency of initiating muzzle contacts (lines 253-260), and of being targets (lines 267-269).

219-221, 267, 268: the use of "trend" when results are not significant has been recently been convincingly objected to by Wood, Freemantle, and Nazareth:

https://www.bmj.com/content/348/bmj.g2215

I'm not sure interpreting the direction of rank effects is useful here given that the rank variable did not meet the significance threshold used. Here is the place where the use of a Bayesian approach would allow such interpretations, as Bayesian credible intervals can be interpreted in this way, whereas p-values cannot (more on a Bayesian approach below).

219-onward: Was R-squared calculated for any of the models? This would help in understanding how much variance in the data each model explained. Additionally, the n of each model should be reported.

295-296: Shouldn't this be low ranking ate the novel food more readily?

297: This seems to me to be a question of what counts as exposure…if, as olfactory contact with novel food increased is considered the actual measure of exposure relevant to muzzle contact, than the number of animals eating the food is just a proxy for this, i.e., it isn't about the number of animals eating the food, but the proportion who have had olfactory experience. Thus, as this proportion of olfactory exposure increase, muzzle contact decreased.

316-317: Why would you expect this?

329-332: What about Boc doesn't meet these criteria?

307-340: This is very good, and would help them in the introduction!

364: Does this need to be re-interpreted given that the rank effects in the results are presented in the opposite direction (i.e., a positive effect in the model represents lower ranking animals engaging more in the target response than higher ranking animals)

370: These results are impossible to interpret given that the random effects are not reported.

404-407: This needs to be reevaluated given that it was actually lower ranking that ate more; however, if this was the finding, a discussion as the fact that this is in contrast to the literature that predicts that higher ranking animals should be more neophobic is warranted.

431: Same point of the rank interpretation

444: This is also in line with [31], which is on vervet monkeys

446: as in 29, 30, and 31

448: Could it be that adults were acquiring information from juveniles, but not applying it, for some reason, akin to Carter et al. (2016)?

456: Again, this needs to be reevaluated-lower ranking animals were more knowledgeable, and were more often the targets of muzzle contact; [31] found that lower ranking animals were more likely the targets of muzzle contact, and used social tolerance to understand this; it's not that low ranking receivers are less tolerated by higher ranking initiators, it is that lower ranking animals cannot refuse initiators as much as higher ranking animals might. (See figure 2b and table 4 of 31; in this paper, higher values indicate higher rank, so the negative effect of rank in table 4 indicates that lower ranking animals were more often the targets of muzzle contact).

466-487: This is great, and an important contribution. Context matters for behaviour, but it is rarely explored-this neglect may be an important reason why social learning isn't as widespread as we'd expect (in my opinion).

510-516: The interpretation of males needs more work…why would males remain bold, outside of dispersal, when it is so risky, and arguably when they have established relationships with group members? And this interpretation is in contrast to the discussion in 307-340 that recent immigrant males are in a specific state that makes them more likely to innovate.

615-618: Why wasn't exposure time included as a control in the model, given that it varies?

618-622: This is in contrast to 595-598: was it always after sunrise in the sleep site, or opportunistically?

660 onward: It would be helpful to mention model names with each description, i.e., that 1b first exposure was model 1, 1b 4 exposures was model 2, etc.

Table 3: Where are the group effects reported, i.e., the random effects?

673-675: This needs to be mentioned much earlier (see my comments questioning why 4 exposures above)

677-679: Why is this prediction here, and not in the introduction? And what is the support for this prediction?

691-696: Again, why are the predictions being restated and/or elaborated in the methods? Perhaps it would be easier to number the predictions in the introduction and refer to them here.

699-701: What were the offsets for these models, given they were poissons?

727: But this manuscript presents many predictions for rank, finding a rank effect in many of the models. I don't see a reason for dropping rank here.

733-736: Please see my main comment above regarding the use of group as a random effect.

"Final model" is used throughout the manuscript (e.g., lines 273-274, 738), implying the authors used a model comparison approach, but any information about how models were selected is not provided.

Reviewer #2 (Recommendations for the authors):

I commend the authors for their hard work in improving their manuscript to accommodate the comments raised by myself and the other reviewers. However, I still feel there is considerable conceptual fuzziness that constrains a clear interpretation of the data presented here, as well as some remaining issues with the analysis. Much of this is made apparent in the authors' Reply to Review, so I will primarily address this. Below that, I have some more minor comments on the revised manuscript.

1) Conceptual and inferential ambiguity

"My comment: Line 281: More detail needed. Did these knowledgeable individuals typically have their mouths full of the target food during these events? If so then it seems parsimonious to assume the muzzlers were simply following this rather than tracking knowledge-states.

Authors reply: We do not claim that they track knowledge states – we are claiming that they can tell who is currently eating or has eaten a food that they do not know about, and try to obtain information about that food. We use the word "knowledgeable" for our human readers to easily identify and refer to "individuals that have already learned to extract and eat peanuts". We never report in the manuscript that we are inferring that the monkeys track the knowledge state. We do assume that if they are close enough to muzzle contact, they are close enough to have probably seen them eat the food."

"…we never report in the manuscript that we are inferring that the monkeys track the knowledge state." Throughout the manuscript the authors make statements to this effect…"

I'm particularly surprised by this final comment since one need not even read past the abstract to see that it is clearly untrue: "Finally, knowledge influenced females and juveniles less than males and adults in becoming more likely targets than initiators.". The manuscript is riddled throughout with examples of such causal language that heavily implies a direct effect of knowledge on the outcome measures. This is extremely misleading and serves no purpose. The word 'knowledge' should be removed from the manuscript entirely and the authors find another way to describe their variable. For example, why not just call the 'knowledgeable' individuals "demonstrators"?

Below I answer several comments at once:

"We did not intend to claim that muzzle contact was the specific mechanism by which individuals learned to extract and eat peanuts – we rather use this experiment to evaluate the function of muzzle contact in the presence of a novel food."

"For this, and the above points: We did not record an observation network for the groups added in this study and are not able to answer this – it is not the focus of this study. For this reason, we do not make claims in this line in the present study, and are cautious with our social learning related language. Whilst we examine the role of muzzle contact in acquiring information about a novel food, we do not expect this behaviour to be a necessary prerequisite in being able to extract and eat this food – indeed many individuals who learned to eat did not perform muzzle contacts. This aspect of the study is about using this novel food situation to explore whether muzzle contact serves information acquisition – which our evidence suggests it does. Moreover, the processing of this food is not complex and is similar to natural foods in their environment, and we do expect individuals to be capable of reinventing it easily (and this point with Tennie's hypothesis is actually discussed in Canteloup et al. 2021 paper) – but the point here is that their natural tendency is to be neophobic to unknown food, and therefore they do not readily eat it until they see a conspecific doing so, after which they do. And we also used this opportunity, though in a very small sample size, to investigate which individuals would overcome that neophobia and be the first to eat successfully."

"See above – the reason we talk about 'uptake' rather than social learning is that we really see this as a case of social disinhibition of neophobia, rather than more detailed social learning such as copying or imitation, as it would be in a tool-use setting, for example (though in Canteloup et al. 2021 paper, evidence is found that the specific methods to open peanuts are socially transmitted)."

"…there is a distinction between information acquisition and information use – obtaining olfactory information about a novel resource that conspecifics are eating is not the same as learning a complex tool use behaviour for which detailed observation of a model is required. We are not claiming that muzzle contact is THE mechanism by which the monkeys learn how to eat the food"

To summarise: When I suggested the authors have implied a role in social learning, they deny this (okay! But I'm unsure about the need for evasiveness on this one – there are more kinds of social learning than just action-copying). Nevertheless, they argue that the monkey are 'gaining information' about the food and that the decline in MC as they become more knowledgeable implies a role in learning (social or asocial) or 'overcoming neophobia'. This seems plausible and a worthy hypothesis to test!

However, when I asked for evidence that individuals who MC more often are more likely to learn how to eat the food, the authors refused to examine this on the basis that "MC is not THE mechanism by which learning occurs". Regardless of whether it is THE mechanism, or simply a means of overcoming neophobia, if MC serves the function the authors have argued then it should lead to an increase in the likelihood or rate of uptake – otherwise what is the point? The authors refusal to support their argument with easily accessible data (they have apparently already recorded the identity of all individuals and their feeding/Mc behaviour) that would robustly confirm the behavioural function one way or the other is quite frustrating.

In fact, the authors do present some data that contradicts their hypothesis:

Line 681: "Inspection of Figures 4A and 4D suggests that juveniles, relative to adults, still initiate more than they are targeted even when knowledgeable."

Why should knowledgeable individuals muzzle-contact at all? These individuals already have the information they need. This is a major hole in the authors' argument.

"We recorded muzzle contacts visible within 2m of the box, so individuals were not necessarily eating at the box at the time of engaging in muzzle contacts. However, the majority of muzzle contacts that we could record took place directly at the edge of the box – at the location where the food is accessed – so an individual would not likely be if they were not able to have access to the food. It is possible they could be there and not eating, but they would not have been chased off, otherwise they would not be able to engage in muzzle contacts there. But it is not entirely clear what the reviewer's point is here."

If muzzle contact was only recorded within 2m of the food source, is it any wonder that knowledgeable individuals were chosen more often? Surely the majority of individuals at the food are those who have figured out how to eat it. See the comment below this one.

"My comment: What proportion of PRESENT (not total) individuals were naïve and knowledgeable in each group for each trial (if 90% present were knowledgeable, then it is not surprising that they would be targeted more often)?

Authors reply: We agree somewhat with this statement, but given the multiple ways we show the effect of knowledge – both at the individual level and the group level (effect of exposure number i.e. overall group familiarity) – we feel we present enough evidence to establish the link between knowledge of the food and muzzle contacts. We find that the model showing the interaction between exposure number and number of monkeys eating on the overall rate of muzzle contacts actually addresses this issue, because we see that when many monkeys are eating during later exposures when many were indeed knowledgeable, the rate of muzzle contacts is massively decreased. Moreover, if 90% of the individuals present are knowledgeable, then only 10% of the individuals present are naïve, and we show both that knowledgeable individuals are targeted, but also that naïve individuals are initiators."

The authors have not really addressed my original point here, so I apologise if it was unclear. First, I accept the authors' conclusion that knowledgeable individuals are less likely to carry out a MC (but see below for problems regarding their interpretation of this). Instead, I was raising a point of basic sampling bias and statistical inference: If the majority of individuals at a feeding site are knowledgeable, then even a blindfolded individual who is choosing recipients are absolute random will select knowledgeable individuals more frequently. If all of the knowledgeable individuals are male, a blindfolded individual will similarly demonstrate a "bias" towards male, knowledgeable individuals. If this is not factored into the analysis then it is not inferentially sound.

"…but we do believe that the clear separation between naïve individuals initiating and knowledgeable individuals being target, and the decrease of the rate of this behaviour as groups' familiarity with the food increases – is good evidence that this behaviour functions to acquire information about a novel food."

That is one interpretation (but see comment above re: sampling bias for initiators) – Another explanation is that these behaviours are simply mutually exclusive at a given moment in time: once they know how to eat the food, they prefer to spend their time doing this than engaging in MC behaviour. Rates of resting, grooming, etc within 2m of the food presumably also decrease once the monkeys have figured out how to eat it, not because there is any causal relationship between these behaviours but because they can only do one thing at a time and feeding is a priority.

2) Analysis

The authors have heavily revised their original analysis and it is largely improved. I have a few remaining issues which I describe below.

"My comment: The text for this muzzle-contact analysis would indicate that this model was not fit with any random effects, which would be extremely concerning. However, having checked the R code which the authors provided, I see that Individual has been fit as a random effect. This should be mentioned in the manuscript. I would also strongly recommend fitting Group (it was an RE in the previous models, oddly) and potentially exposure number as well.

Author reply: The model about muzzle contact rate never contained individual as a random effect because individuals are not relevant in this model – it is the number of muzzle contacts occurring during each exposure. However, the reviewer might refer here to the model that we forgot to provide the script for. Nonetheless, we have substantially revised this model, it now (Model 3) includes all groups, and has group as a random effect."

I do not accept that individual is not a relevant random effect. I understand that the model is intended to examine group-level rates of M-C, but groups are made of individuals. Let us imagine a scenario where a single individual is a highly prolific muzzle-contacter in group BD, accounting for 95% of M-C events, and NH contains no such individuals. An analysis that takes a straightforward group rate without accounting for individual contributions will likely find a significant difference between the two, driven by a single individual. If the authors have structured their data and analysis in such a way that they cannot control for this factor then that is an issue. One "quick and dirty" solution, that would require a minimal amount of restructuring of the data, would be to take an individual rate for each monkey in a group, or at the feeding site, or whatever, and then derive the group average from this. Otherwise, it is not clear what we can infer from this analysis.

"Authors: We have now checked for overfitting in our models."

Where is the evidence of this, please? There are metrics and methods that can be used to achieve this (such as AIC/LOO-based model comparison approaches I suggested in my last review) but the authors do not report them.

"We included individual as a random effect, but we did not include group as a random effect here for two reasons. First, we did not have any theoretical basis to expect residing in different groups to have an effect here, since we were concerned with the effects of life history strategies of individuals on their information acquisition behaviour, which should not differ for individuals from different groups."

This is not theoretically sound. Individuals from groups are more likely to be similar than individuals from different groups – this is the purpose of grouping variables. They live in similar ecologies, share life history events, and are more closely related.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Role of immigrant males and muzzle contacts in the uptake of a novel food by wild vervet monkeys" for further consideration by eLife. Your revised article has been evaluated by George Perry (Senior Editor) and a Reviewing Editor.

The edits to the manuscript were much appreciated but unfortunately have also brought to our attention some additional issues with your statistical analysis that must be addressed, as outlined below.

1. The issue is that once you reported your dispersion parameter results, it is now clear that Models 4 and 5 are highly underdispersed, and model 3 moderately so. Underdispersion can be considered as much an issue as overdispersion for poisson models so we urge you to rethink the error structure used for these models so that you do not violate the assumptions of a poisson distribution.

https://doi.org/10.7554/eLife.76486.sa1

Author response

Essential revisions:

All three reviewers found this study to hold great potential in providing significant new insights into the field of social learning and transmission in wild animals. However, due to a number of important concerns with the analysis it is difficult to ascertain whether the authors' claims are valid given the evidence. We invite the authors to address these major concerns in a substantially revised version of the manuscript.

1) Statistical analysis needs revising:

A number of concerns regarding multiple testing and the structure of your mixed models require attention. In particular, please consider using a multimodel approach due to the exploratory nature of your analyses (see suggestions from Reviewer 1 and 2) and revise the structure of your mixed models to include essential random effects where necessary, and address potential confounding variables such as group size, combining age and sex into one variable, and the directionality of muzzle-muzzle contact initiations (see all 3 Reviewer comments for details). Please also ensure the code for all your models/analyses have been provided.

We have updated our models according to the reviewers’ comments. Importantly, we added two new models in the muzzle contact section, due to reviewer #3’s correction about the model we originally used to answer question 3b (Individual variation in muzzle contact behaviour). They correctly noticed that the model we used was not suitable for some of the comparisons we were drawing from it. We retained this model (now Model 6) as the things it does show are very interesting regarding the life history strategies of the two sexes in this species, and still strengthen the overall message of the paper. The two new models that we have added are suitable to examine what we originally intended, which was the likelihood of (a) initiating muzzle contacts (Model 4), and (b) being targets of muzzle contacts (Model 5), between different ages, sexes, ranks and knowledge-bases. We are very grateful for that correction.

Second, following reviewer #1’s advice, we checked all models for whether individual needed to be a random effect, but our original models for which they made this comment only include each dispersing male once – in the group where they ate first – so there was no repetition of individuals and we did not need to add this there. Regarding group as a random effect, we now include this everywhere that we believe it is necessary – which is all but one model (Model 6) where we did not, because we do not theoretically expect residing in different groups to have an effect there, and the model was too complex to include it – we mention this again below, and we also show our process in the R code.

Lastly, whilst model selection approaches were recommended, we chose not to implement this, because wherever we used models, we did have specific predictions based on previous work and theory. The only time we actually referred to exploratory work is for what were originally questions 1 and 2a, and now we have now merged into the present question 1. We do not formally analyse these data using models. We hope this is clearer now from the way we have now written the hypotheses and predictions (also following advice from reviewer #2).

2) Methods need to be more transparent:

All reviewers found that parts of your study lacked sufficient detail to be repeated by others. Could you please provide clear criteria for the various decisions made throughout the study as well as justifications for cut offs used (e.g., why 3 months for immigrant males?). The rank calculation also needs more clarity and various decisions made by the authors are not justified/clear. Please also provide interobserver reliability tests regarding coding (see Reviewer 1 and 2 for details).

We have now addressed these issues: more detailed information regarding our observations of the tenure of the innovators and other relatively short-tenured males (lines 312 – 317); reported interobserver reliability for the video coding (lines 647 – 651); explained the criteria for ending an exposure (lines 614 – 615); and other methodological clarifications are indicated below next to the relevant comments from the reviewers.

3) Study needs reframing:

All three reviewers found the introduction lacked direction and conceptual clarity. Please provide a more thorough rationale for your study and integrate this into a list of explicit research questions and predictions. The discussion would also benefit from consideration of alternative explanations (see details in comments from all 3 Reviewers).

We have added more background supporting our interest in dispersers in the introduction, and completely re-wrote the research aims with much more detail and supporting evidence to back up our hypotheses (lines 125-173). We also add more discussion of alternative hypotheses to the discussion (lines 370 – 380 regarding uptake of novel food; and lines 412 to 417, regarding muzzle contact results). We hope this is clearer now.

Reviewer #1 (Recommendations for the authors):

I have some suggestions regarding the methods:

– It needs to be reported what decided when a trial was begun, and ended, as this would help explain the differences in the trial lengths.

This is now specified in the method (lines 614-625).

– It would be very helpful to report how STRANGE these animals are, especially given this manuscript is about innovation; see:

Webster, M. M., and Rutz, C. (2020). How strange are your study animals. Nature. Nature, 582, 337-340. https://www.nature.com/articles/d41586-020-01751-5?sf235295265=1

Farrar, B. G., and Ostojić, L. (2020). It's not just the animals that are strange. Learn Behav. Learn Behav. https://doi.org/10.3758/s13420-020-00442-5

We now refer to the STRANGE framework when discussing about potential group size and experimental history effects (lines 371-380).

I have some suggestions regarding the analyses:

– The R package DHARMa is a great resource for model residual diagnostics.

We thank the reviewer and we used this.

– There are no effect sizes reported for any of the models.

We now report effect sizes of our models.

– The code for the first muzzle contact model, looking at rate, wasn't included, and so I was unable to review it. Further, it was unclear as to if only a subset of the available data was used for this model (groups with lots of eaters), and if so, why. Including group as a random effect could help account for any group differences that the authors may have felt relevant to subsetting the data, thus allowing all of the data to be examined.

Apologies for that omission – it is added now, and all groups are in.

– Collecting data in the field is quite different from coding from videos, and reporting a reliability measure on the video data would help readers to assess the manuscript's findings.

We have added this.

– It seems to me that all models need both ID and group as grouping variables (random effects). This is because all of the models, as far as I can tell, include some of the same adult males (though on different troops), and all of the analyses are all conducted across all of the groups, requiring group to be a random effect.

ID was already a random effect in all the models with repeated rows of data per individuals, but we actually only included the dispersing males in groups where they ate first, so this was not an issue. Group is now a random effect everywhere where we can see a theoretical reason to include it – we did not include it in the final muzzle contact model because the model was too complex to converge with it in, and we also see in this case, no reason for the groups to have different outcomes. This question is more related to individuals’ life history differences, specifically between age and sex classes, and we do not expect that be variable among groups.

– Exposure to the experiments varied widely across groups, and it is unclear if all animals on the same groups were around for the trials (I'm assuming they weren't as some trials were dropped due to low numbers of participants). These discrepancies need to be accounted for in the manuscript and analyses.

We no longer drop these exposures. We are unable to obtain accurate records of how much of the group was present from our videos, but in all except the originally dropped exposures, the whole groups were in the area and within visual access of the experiment at least at some point, and therefore had to opportunity to approach the box if they liked (besides intragroup dynamics e.g. monopoly by high rankers)

– There is no explanation as to why there are three different versions for the provided models looking at muzzle contact (1 model with (non-normalized) rank, 1 with two interactions but without rank, and 1 with three interactions, but also without rank). Why was rank dropped? Why were interactions included? If multiple models are going to be considered, a model comparison value, like AIC, should be included to compare the models (after first explaining the theoretical reasons as to why different versions were considered).

We have updated this model and how we set it up, also in accordance with the comments from Reviewer #3 who correctly found discrepancy between what we intended this model to do, and what it actually did. Nonetheless we found what it did measure to be highly interesting and have reframed it, whilst adding appropriate models for our original intention. This issue with rank is no longer relevant as we did not expect rank to have an effect in what was actually being measured here.

– How was rank normalized, and why was normalized rank considered in some models but not others?

This was a mistake and we apologize for that. Has been checked and all models now presented which test rank use the normalised rank. It was normalised (or maybe “standardised” is better terminology) so that despite group size, all ranks fall between 0 (highest rank) and 1 (lowest rank). [(rank -1) / group size] – this shows us the proportion of the group that each individual outranks.

– Figure 2A y-axis is unclear- shouldn't it be closer to 50% for BD given 35 innovated? Or is this just after the first exposure? Or first eating event?

The y-axis label and the figure caption do both specify the first eating event.

Other questions/ suggestions:

– Line101: why the possessive on "groups"?

– Line 286: this is in line with the hypothesis of Nord et al. 2020, which concluded that, "both kin and low-rank- ing animals serve as discriminative stimuli for social tolerance and that foraging animals serve as discriminative stimuli for food availability" Though, this manuscripts first muzzle contact model (for which the code was not provided) found no evidence of a rank effect (though rank wasn't included in the interaction models), which is in contrast to Nord et al., thus providing an interesting extension to findings about muzzle contacts, in that social tolerance may play less of a role in cases of novel foods.

Our results support Nord et al. results now, and we refer to this study (ref N°31) in the discussion. The previous difference was due to our mistake of using non-standardised rank in that model (line 459).

– Line 289: This also agrees with Nord et al.

– Line 300-302: Do the juveniles referred to here out rank adults? Are ranks calculated across all age types in these data?

Ranks are calculated across all adults and juveniles, and infants are given the rank just below their mother (due to lack of data on infants) – this is described in the methods now.

– Line 303-305: The manuscript reports that juveniles have information, but aren't passing it…how is this an adaptation to risky behavior, if juveniles are more likely to eat something novel anyway? Isn't this doubly bad for juveniles, in that they are more likely to eat something they don't know, which can be dangerous, and also aren't functioning as a source of information when they have it?

We think it could be adaptive that individuals do not learn from juveniles, because if they are more prone to risky behaviours, it is better that these risky behaviours do not spread in the group (lines 398-401) – the adaptive aspect is that by preferring to learn from adults, hopefully the information that is learned is more reliable as they are more risk-averse. However, with our new modelling approach, we did not find a difference in how adults and juveniles were targeted with muzzle contacts, though it is what we expected, and we discuss this in lines 448-452.

– 309-311: This could possible be tested putting age and sex, as a combined variable, in the model, creating no need to have an interaction between age and sex and knowledge, and instead would only need one between Age-Sex and knowledge

We tried this but it did not change the results, and made the results more complicated to discuss. We maintain the separate interactions.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

The manuscript has been greatly improved but there are some remaining issues that need to be addressed. In particular, the responses to reviewer concerns regarding the conceptual framing of the study and the analysis are not sufficiently addressed and we find the justification for not making the suggested changes unsatisfactory.

In your revised submission please ensure you adequately address the major comments provided by Reviewers 1 (points 1-6) and 2 (points 1 and 2).

To summarize, the introduction still requires substantial revisions to provide a more clear conceptual framework and predictions, along with how this aligns with your analyses. The analysis also requires attention as key components of models are still missing, (i.e., random effects) and the transparency of your results will be much improved if sample sizes and R-squared values are reported for each model. See Reviewer comments below for details.

Reviewer #1 (Recommendations for the authors):

The authors have done a great job making the introduction more applicable to the research conducted. It is still a bit disorganized, which I comment on explicitly below. Furthermore, the exploration of role of knowledge in information-seeking is an important contribution, as this kind of social/contextual account is not often a topic of study in the social learning and innovation literature.

1. The introduction seems to present the idea that learning what to eat is innovation, and that dispersing is reflective of innovative abilities, though I'm not certain that this is what the authors intend. In the discussion, the explanation as to why dispersing animals may be more likely to innovate when they are dispersing (a "transitory exploratory behavioural syndrome") is much more clear. Indeed, it might work better to introduce this idea in the introduction, and continue along the same lines with regard to juveniles-that given that they need to learn about their environments, they might be better primed to innovate akin to the transitory behavioural syndrome of dispersing animals, rather than viewing ontogeny as a constant state of innovation. However, it is still unclear as to when males are considered immigrants vs. residents. Surely after group integration, they are no longer experiencing a "transitory exploratory behavioural syndrome.". Explicitly outlining this distinction (dispersing vs. resident) would greatly help the manuscript.

This is what we intended. We added explanation of our ‘transitory exploratory behavioural syndrome’ hypothesis to the introduction (L 71-72).

2. Additionally, it is very odd that all of the predictions presented in the introduction are exactly what is found, even when they are in contrast to the literature. This is especially difficult given the predictions about rank, and that, as long as I'm reading the methods correctly, the rank results are actually presented backwards, meaning that the authors found the opposite of what they report (i.e., because increasing rank values equals decreasing rank--higher ranking animals are represented by lower values--and the models found a positive effect of rank, then it is that lower ranking animals were more likely to eat the novel foods, not higher ranking animals; this is in line with the neophobia literature that predicts that higher ranking animals should be more neophobic, in contrast with the prediction provided in the introduction).

Whilst the reviewer has previously spotted other errors in our scripts and data files, for which we are very grateful, in this case they are mistaken. We have checked and we report the rank results correctly, and describe them in the text accurately. The effects of rank are not positive – they are negative – odd ratios <1 are negative. To make this clearer, we have added a column to the results table (L850) that also shows the model coefficient, as we believe the reviewer has mistakenly read our odds ratios as coefficients, thus believing them to portray positive effects, when they are in fact odd ratios portraying negative effects.

I have a number of questions with regard to the analysis:

3. I must disagree with part of the explanation given as to why group wasn't included as a random effect in one of the models. As I mention below, multilevel modeling (the use of grouping variables/random effects) isn't done in order to test predictions (though it can be used as such), it's about controlling for structure inherent in the data. Given that these animals exist in groups, then this fact needs to be accounted for in the statistical models. This seems especially important to me given that many of the models find variation with regard to group, which can be seen when investigating the summary output of these models using the code provided, and comparing the marginal vs. conditional r-squares. Furthermore, I don't understand this assertion of no expectation between groups, as there are at least two papers by the last author of this study arguing for the consideration of group-level variation in primate groups, especially when it comes to foraging:

Group is now included as random effect in all the models. We provide the variance and standard deviation of the random effects and the marginal and conditional r-squares in table 4.

Tournier, E., Tournier, V., van de Waal, E., Barrett, A. S., Brown, L., and Bshary, R. (2014). Differences in diet between six neighbouring groups of vervet monkeys. Ethology, 120(5), 471-482. https://doi.org/10.1111/eth.12218

van de Waal, E. (2018). On the neglected behavioural variation among neighbouring primate groups. Ethology, 340(10), 485-410. https://doi.org/10.1111/eth.12815

I think it is fine to say that the model wouldn't converge with group as a random effect and leave it there, as long as this is a limitation acknowledged in the results and their interpretation. Using a Bayesian approach would likely solve this issue because it performs better with smaller datasets and more complicated modeling than lmer, though I don't see it necessary that the authors change their statistical approach, though this is clearly the method preferred in the materials included supporting why group was dropped as a random effect in the R script.

We have decided to remove model 6 from our analyses. Given that it was originally intended to investigate what models 4 and 5 now correctly investigate, it is not worth the small amount of additional information that it might glean, especially given that there are too many problems with the model diagnostics and model convergence.

4. When looking to the data and analysis code, there are 21 individuals that are measured twice in model 1 and 3 that are measured twice in model 2. It appears that some are males that moved groups, so I'm confused by the authors' reply that each dispersing male was only measured in the group that they first ate. Others appear to be animals that aged up during the study. I do see that if Individual is included as a random effect in models 1 and 2, the fit is singular. Perhaps a solution is to filter the observations to those in which the individual first ate, and mention this in the methods, as the authors replied they did (but my review of the analysis doesn't confirm). Another solution would be to run the models using a Bayesian approach, which would also fix the fitting problem with model 6 when including group as a random effect. Also, for model 2, there are 27 individuals marked as NAs for group AK19 for the measure of whether they ate in the first 4 exposures, when they have 0 for eating in the first exposure. Did I miss information as to why these animals were dropped from model 2 given they were measured in model 1? That is, while there are 191 observations (of 170 unique animals) in model 1, there are only 164 observations (of 161 unique animals) in model 2.

It seems that the reviewer may not have overlooked our explanation that AK19 only had one exposure in 2019 (in the methods: line 523), which is why they were not given scores for eating across all four exposures (and thus absent from model 2). This is why they have NAs for eating across all four exposures. As we described in the text (L174; and now also in the methods in L 523), we considered AK in 2019 and 2020 separately because 40% of the group changed and there was a year worth of gap between the single exposure in 2019 and the four subsequent ones in 2020. As no individuals had eaten in 2019, the peanuts were still novel to them in 2020 as a food source. Nonetheless, this does not actually affect any of the analyses (see next paragraph) and is just a descriptive difference. The issues you noted with the numbers of individuals should now be rectified, with dispersing males only considered in the group they were first present in, and no repeated individuals in the actual analyses.

Part of this issue arose as we intended to look at the exposure with the first eating event but had accidentally used the first exposure. We have now corrected this data file in accordance with looking at the exposure with the first eating event (see L215 in the results and L 555 in the methods). Therefore, the AK19 individuals are not in either analysis, only AK20 are because they had both a first eating event and four exposures. We could remove AK19 all together from the data file but have not done so for completeness of the data set, and to allow analysis of the very first exposure to be carried out if wanted.

5. Model 3 doesn't seem to meet model assumptions for the residuals, and the R code state that this is fine for the sample size used. This needs to be reported in the main text-that model diagnostics reported an issue, and why the authors believe that this issue is not relevant.

We have completely re-done this model in accordance with reviewers 1 and 2 comments about it – please see L233-244 in the results and L 608-612 in the methods as well as Table 3. Model diagnostics are good as one can see in the model script.

6. The table for model 3 is not reported in the text.

We had previously reported this model in the text, and thus not repeated its results in the table because it was a linear model not a glmm like the others presented in the table. Since we changed this analysis to a glmm we now report model 3 in the table.

Please see my detailed comments below:

20-21: Consider changing "according to the innovator" to "with respect to the initial innovator"

We have changed this.

28-30: This sentence is a bit hard to follow. It might be better to talk about what was found, rather than what wasn't found, i.e.,

"Knowledgeable males and adults were more likely the targets of muzzle contacts compared to knowledgable females and juveniles, while also being less likely to be initiators."

48: What is meant by "potential" novel foods?

Anything an animal might try to eat to see if it is edible. To consider something to be a novel food, to me, it should first of all actually be edible, and in this context, it should be investigated for it’s potential as a food by the animal. Not everything novel in an animal’s environment is a novel food. This is why I used the word “potential”. I would prefer to leave it like this as I think it makes sense, and it did not raise concern in previous versions. If the editor has the same issue and wants us to remove the term ‘potential’ we will do so.

50-51: the line between "obtaining novel information" and "produces information or knowledge, potentially facilitating information" is murky. New information gained by an individual isn't always reduced by them…perhaps something like "and has the potential to produce information on which other group members can act." instead.

We believe the reviewer refers to this line “…directly from the environment requires overcoming neophobia and engaging in exploration, tendencies for which may vary between individuals”? We are not sure why this is unclear. We are simply saying that exploration tendencies are variable between individuals.

We do not understand the reviewers comment: “New information gained by an individual isn't always reduced by them” – our best guess is that you mean the information is not always “used?

Here we are not yet talking about information being used by other individuals, nor even being used by the individual finding the information – this is why we said it “potentially” facilitates innovation, not that it always leads directly to it. We have broken this sentence into two and hope it is clearer now: “Obtaining novel information directly from the environment requires overcoming neophobia and engaging in exploration, tendencies for which may vary between individuals [5]. If this information is used, it can facilitate innovation.” (L51-53)

58: Behavioural patterns don't have be novel to be adaptive in new environments, as in the definition of innovation provides above-innovation could be a solution to a novel problem, including generalizing one behaviour, e.g., extractive foraging like getting acacia seeds from seed pods, to a novel situation, like extracting peanuts.

Yes true, this sentence did not come across as intended – we meant that the behaviour in interaction with the environment would be novel, whether it was a novel behaviour or not, as per the definition in the previous sentence, but indeed this is not how it sounds. We have updated it now to “Individuals must interact with the environment in novel ways, either using novel behaviours with known environmental features, or performing familiar behaviours on novel aspects of the environment, which additionally requires behavioural plasticity [11]” (L 59-62).

60: What's "this"? Behavioural plasticity? Behavioural patterns?

Yes – we have now clarified this in the text (L 62-63).

61: The risks association with novelty and innovation are unclear here. Up until this point, innovation and novelty have been largely been framed as positive, whereas only neophobia was mentioned with avoiding ris

We gave examples of risks associated with novelty at the start of this paragraph and have added to this sentence now so hope this is clearer (L 46-50)

66: Are juveniles required to innovate to learn about their environments? Learning about what is available as food in your group is not the same as finding a new food. Similarly, do dispersing animals need to innovate, or do they need to use previously-learned social skills to ingratiate themselves to a new group? Neither of these examples are a "a solution to a novel problem" or a "novel solution to an old one". Learning what to eat is not a novel problem…much like learning who your allies are isn't a novel one either. What really is the problem here is whether innovation happens at the level of the individual or group… certainly learning what to eat as a juvenile, or integrating into a new group, isn't a novel problem for this species, but one every animal must meet (save females re: dispersal). What I mean to say here, just because juveniles might be more prone to innovate, it's not necessarily from necessity, but could be a result of a developmental period that functions primarily to allow them to learn about their environments-while behavioural flexibility is necessary for innovation, it is not the same as innovation.

“Are juveniles required to innovate to learn about their environments? “

No, we have updated the sentence to read now: “For example, innovation might be more likely in juveniles who may be less neophobic due to their need to learn about their environment before adulthood…” L 68-70

“do dispersing animals need to innovate,” – they have to explore and approach and interact with novelty, which may well increase the likelihood of innovation, which can also be due a transitory exploratory behavioural syndrome as specified in the introduction (L 71-72) and in the discussion (L 315-316).

Learning what to eat is not a novel problem” – not if they learn from someone else, but if they individually learn to eat a novel food we would count this as an innovation. This is explicitly stated in the definition of innovation that we provide (“a new ecological discovery such as a food item not previously part of the group“, L 54-55). It also relates to the earlier part of that definition, i.e. applying an old solution (eating) to a novel problem (a novel object that was not previously known to be edible).

70: Why "nonetheless" here? The points following "nonetheless" seem to follow the points before it, and are not in contrast.

We have changed it to “on the other hand” (L77)

77: How is the risk diminished? Are captive animals are less neophobic because they are fed-is risk assessment, for which neophobia is a conserved trait across many species, is ontogenetically determined? Or is the point here that is more difficult to study such phenomenon in captivity, because there is no risk? I assume it's this latter point, but such risk assessment is never addressed in the current study, other than to mention that wild animals often experience changing environments, especially resulting from anthropogenic origins.

We are simply trying to point out that the risk of ingesting toxins is diminished in captivity due to being fed with edible food only. We have added a reference to support this wild-captive difference [L83-87].

77-79: Individual differences with regard to innovation and behavioural plasticity has been shown to be true across many studies, including vervets, though there has been some conflicting evidence (cited below)…would it be better to say more work is needed, given the conflicting evidence?

Bono, A. E. J., Whiten, A., Schaik, C. V., Krützen, M., EichenBerger, F., Schnider, A., and van de Waal, E. (2018). Payoff-and sex-biased social learning interact in a wild primate population. Current Biology. Current Biology, 28(17), 2800-2805. https://doi.org/10.1016/j.cub.2018.06.015Bono, A. E. J., Whiten, A., Schaik, C. V., Krützen, M., EichenBerger, F., Schnider, A., and van de Waal, E. (2018). Payoff-and sex-biased social learning interact in a wild primate population. Current Biology. Current Biology, 28(17), 2800-2805. https://doi.org/10.1016/j.cub.2018.06.015

Renevey, N., Bshary, R., and van de Waal, E. (2013). Philopatric vervet monkey females are the focus of social attention rather independently of rank. Behaviour. Behaviour, 150(6), 599-615. https://doi.org/10.1163/1568539X-00003072

Canteloup, C., Hoppitt, W., and van de Waal, E. (2020). Wild primates copy higher-ranked individuals in a social transmission experiment. Nat Commun. Nat Commun, 11(1), 459-469. https://doi.org/10.1038/s41467-019-14209-8

These cited studies do not represent conflicting evidence neither of innovation nor on social learning biases as we already offered some explanation regarding results’ inconsistencies. Bono et al. (2018) study trained models to use one technique over the other, while Canteloup et al. (2020) did not train any models, then the ‘innovators’ are not comparable in those studies. As one can read in Canteloup et al. (2020) p 6:” While previous studies of vervet monkeys reported both a female bias (van de Waal et al. 2010; Bono et al. 2018) and a mother bias (van de Waal et al. 2012; 2014; 2013) our findings did not identify any such biases. On the one hand, such inconsistencies could be due to our relatively small sample size compared to previous studies that tested more than two groups. On the other hand, discrepancies might be explained by the fact that in both cited studies (van de Waal et al. 2010; Bono et al. 2018), female and male models were of high social rank while in our study, they were of varying social ranks. The possibility that different results could have arisen by running the same kind of experiment with only low rankers or low-ranking females and high-ranking males as models is an open question. Finally, in the above cited studies (van de Waal et al. 2014; 2013), only infants of less than one year of age were tested whereas in our study, individuals of all ages took part in the experiment. It is then possible that young infants focus on maternal figures during a first phase of learning and later widen their attention during a second phase of learning, focusing on specific individuals such as high-rankers (Whiten and van de Waal 2018) who could be considered as experts (Whiten and van de Waal 2018; Kendal et al. 2015)”. That being said, we have added that “…more worked is needed on the topic.” (L 89).

79: "For example" might work better here rather than "moreover", since it's continuing the previous point. The reference to chimpanzees explicitly here is unnecessary, as the citations used include species beyond chimpanzees. "For example, across many species where males disperse, dispersing individuals…" would work better.

We prefer to keep “moreover” to emphasise the shift of focus towards dispersers whilst continuing the overall point. (“Moreover” can be used to continue a point – similar to “furthermore”; L 89).

80: Citations [19] and [20] here use capuchins, not chimpanzees

We have updated this citation to include all the subsequent references related to this point. (L93-95)

85: Add "While these studies show that dispersing individuals…experimental (no "but")". However, at this point it is not clear to me why we need to compare multiple groups experimentally-this needs support.

Good suggestion, thanks. (L96)

However, at this point it is not clear to me why we need to compare multiple groups experimentally-this needs support.

To look at between-group transmission experimentally, multiple groups are required by definition, and the more groups the better as results will be more representative of the population. In addition, as dispersers represent few individuals, decent sample sizes can be built up if multiple groups are studied. We have added “resulting in a small pool of evidence” to reflect this. (L98)

70-100: This paragraph is very confusing to follow, as there are multiple independent points being made, including how social learning is beneficial, how the dispersing sex can import innovations or create them, a brief mention of the interface between social learning and innovation (i.e., it is implied that they are separate processes, but all of the benefits of this introduction point to species-level benefits of innovation, which require innovations to spread, so the brief mention of social learning here seems too minimal), and a discussion of social learning modalities.

We have split it into two paragraphs, to separate the social learning modalities from the rest. (second paragraph starting L99)

97: Why the mention of social tolerance here? It is not clear how social tolerance speaks to the questions asked by this study.

We are referring here to Nord et al. (31) study who suggest that social tolerance may constrain information transmission with tolerant individuals accepting more individuals in close proximity than more intolerant ones would; and some individuals are tolerated more than others are. To make this more obvious, we have added: “which can be affected by age, sex and rank” (L107-109) which are all parameters that we measure and analyse in this study.

103: What's "this"?

“This” referred to the sentence directly before the word “this”. It is now updated to be more specific (“Their diverse habitats, including those highly modified by humans,…” (L 115)).

107: I'm still not sure why males need to innovate? Don't they, at most, need to generalize the behaviours of their previous groups to a new one? Why must they innovate?

The point is that they might be more predisposed to innovate because they have to seek novelty (new group, new habitat, interact with new group mates using familiar behaviours with new individuals, explore an unfamiliar area…). Thus, relative to females, the likelihood of them ending up innovating is increased, even if they don’t have to be overall extremely innovative – just more likely to than the philopatric females.

We have expanded L 118 to hopefully make this clearer: “Frequently dispersing males may serve as vectors of information between groups. In addition, if dispersal triggers an increase in exploratory behaviour, necessary to seek novelty in order to leave one group to join a new one, around the dispersal period they may also become more likely innovators in novel environments [12], potentially facilitating behavioural adaptation to diverse habitats across their geographical range [33].” (L 118-122).

123-124: Consider changing to "Our observations of innovation are limited in number, but further testing of the hypotheses we propose, as a result of our exploratory analysis that we present here, may aid our understanding of animal innovation.

Thanks, we have updated this sentence as such (now L 137-139)

125: Consider changing to "Given that animals learned to eat a novel food source, a behaviour that spread socially [24], (1a)…"

We disagree here with this change as when we asked (1a) who innovated, this was the first exposure of animals to the novel source so they did not already learn to eat it.

126-129: Why did you expect this?

We expected it because adults are more likely to be preferred learning models than juveniles in agreement with the three phases in the ontogeny of social learning in primates (L 141-145).

130: "which" implies the results were known beforehand; "whether" might work better here.

This has been updated (L 146).

131: Change "over all" to "overall"

In this instance “over all” was actually correct – we were using the two separate words as separate words, but have changed it to “across all” to be clearer (L 147-148).

131-133: Why differentiate across exposures here, especially since the predictions are the same? I know there are 2 different models, but I need to know why here so that I can understand the differing predictions. Moving the explanation as to why the first 4 exposures were considered to here would be helpful.

We have removed the differentiation between the first and across all four exposures from here, since the predictions are anyway the same (L148-150). We chose to do this instead of moving the explanation here as the latter seems more complicated and will disrupt the flow of the predictions if we were to start explaining the methodical decisions here.

132: What's "this"?

We changed “this” to “adoption of the innovation” (L 148).

134-136: There seems to be a bit of double-dipping here, as the findings from one dataset (at least for 2 groups) are used as evidence for a prediction for data in the same dataset (the current study). Additionally [24] and [39] found that higher-rankers are more likely to be observed, not that they were more likely to uptake a novel food. In fact, the common prediction here is that higher-ranking animals should be more neophobic, because they have better access to food and thus eating unknown food is riskier for them given their prime access to food overall:

Wolf, M., van Doorn, G. S., Leimar, O., and Weissing, F. J. (2007). Life-history trade-offs favour the evolution of animal personalities. Nature. Nature, 447(7144), 581-584. https://doi.org/10.1038/nature05835

Greenberg, R. (2003). The Role of Neophobia and Neophilia in the Development of Innovative Behaviour of Birds Animal Innovation. In S. M. Reader and K. N. Laland (Eds.), Animal Innovation (pp. 175-196). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780198526223.003.0008

Laland, K. N., and Reader, S. M. (1999). Foraging innovation in the guppy. Animal Behaviour. Animal Behaviour, 57(2), 331-340. https://doi.org/10.1006/anbe.1998.0967

But see:

Amici, F., Widdig, A., MacIntosh, A. J. J., Francés, V. B., Castellano-Navarro, A., Caicoya, A. L., Karimullah, K., Maulany, R. I., Ngakan, P. O., and Hamzah, A. S. (2020). Dominance style only partially predicts differences in neophobia and social tolerance over food in four macaque species. Scientific reports. Scientific reports, 10(1), 1-10. https://doi.org/10.1038/s41598-020-79246-6

Drea, C. M. (1998). Social context affects how rhesus monkeys explore their environment. American journal of primatology. American journal of primatology, 44(3), 205-214. https://doi.org/10.1002/(SICI)1098-2345(1998)44:3%3C205::AID-AJP3%3E3.0.CO;2-%23

As the reviewer highlighted, predictions about the effect of rank on uptake of a novel food in the literature are various. We analysed here rank in the models because it was likely to have an effect as it was found to have an effect in the Canteloup et al. 2020 paper with the same peanut experiments on two groups, and we wanted to control for this, and also to explore what might be the influence of rank in this context.

140-142: This makes sense to me, but I have no idea why this prediction is made. Perhaps moving the explanation given to the me

The reviewer’s comment is incomplete, and it is not clear what changes they are requesting about.

146-147: "the media" implies that this is how animals are learning to eat the peanuts…but the author replies to reviewers mention multiple times that this is not what is meant.

According to the Merriam-Webster online dictionary, a medium is “a means of effecting or conveying something such as a channel or system of communication, information, or entertainment”. Following this definition that does not imply any mechanism of learning (how animals are learning), we changed the sentence for: “muzzle contact being a medium to obtain information about what conspecifics are eating” (L 160-163).

We are suggesting that the monkeys are using the muzzle contacts around the novel food to obtain information about it, thus indeed potentially informing whether they eat the peanuts or not – as the reviewer mentions here. But we are focussing on whether we have evidence that muzzle contacts convey information about the novel food, not whether and how this information is used. We are not looking at whether the monkeys eat peanuts because they’ve done muzzle contacts, but rather at whether their MC behaviour is influenced by whether they have eaten or not (the opposite direction of causality, not that we can measure the causality directly, but rather we believe we build evidence in this paper for the latter). As we have said before, there may be a lot of other information that is important too in the novel food-learning process, such as visual cues (e.g. see Canteloup et al. 2021 on the opening techniques which follow an observation network) and individual learning that might be occurring in the process of learning to eat peanuts that we are not interested in in this paper. We hope this is clearer now.

147-150: This has been previously found in [31]; thus there is both theoretical and empirical support for this prediction.

Reference [35] was indeed cited at this place but we added another reference to that study (L 166).

152: [31] found this, and hypothesized that social tolerance is necessary for muzzle contact to afford foraging information, but perhaps and additional citation here about how lower ranking animals are tolerated by fewer group members would help make the point.

This is already clearly stated L169-171.

153-154: Initiated vs targeted…via muzzle contact?

We remove this whole paragraph as we removed model 6 from the paper.

158-161: I don't follow…this seems to assume that initiators are seeking information and this seeking will outweigh any social tolerance constraint, but only previous study of muzzle in vervets found that tolerance was the best predictor of the behaviour. Thus, this prediction needs more support as to why it is in the opposite direction of what the literature shows, i.e., that social tolerance constrains information-seeking and information spread, akin to Carter's (2016) sequential social learning hypothesis.

This whole paragraph has been removed now.

161-173: What kind of different experiences of novelty arise from the life history trajectories of the philopatric vs. dispersing sex? Again, why do dispersing animals experience more novelty? Why should we expect the groups to which they are dispersing to have significantly different diets that we can call "novel"? Do dispersing animals need to gain totally new information? Surely not, as the kinds of foods available are likely very similar and behavioural generalization can do a lot of work. When it comes to conspecifics, isn't a plausible alternative hypothesis that dispersing animals need to enter groups using the same skills needed to integrate in to the adult social networks as they age in their natal groups before dispersal…so what counts as novel here? Again, I see these problems as being neither novel or the success of dispersing animals after integration into new groups as being dependent on a novel solution. It seems to be the novelty of interest here is much larger, as mentioned at the beginning with reference to anthropogenic-induced changing environments, rather than the kinds of problems these animals have encountered throughout their evolution.

This whole paragraph has been removed now.

164-165: Why this prediction? I can think of some reasons why this is, but there is no support for this prediction that naive adults should initiate and receive at the same rates…prior evidence [31] suggests that adults should more often be targeted than initiate, so it seems here that this prediction relies on explicit knowledge seeking, which requires the prediction the muzzle contact is primarily used to gain novel information.

This whole paragraph has been removed now.

166-167: Why should females initiate if they don't "need" info, which is what this prediction is implying…presented like this, this prediction reads as if the results were already known when it was made.

This whole paragraph has been removed now.

169-171: Why would malesy stop initiating? Why does initiating influence receiving? One does not preclude the other…

This whole paragraph has been removed now.

170-173: I don't follow this prediction at all… that knowledgeable males are somehow more tolerated…doesn't the work reviewed in the introduction at least imply that new immigrants have novel information, and by definition, new immigrants are less known to the group, so should be interacted with less. How does a muzzle contact initiator know that a new male is knowledgeable? And why wouldn't a new male be less tolerated by others compared to an established male, who has relationships with the group? Again, I'm not sure of the dismissal of tolerance here, when the only previous work on muzzle contact in vervets found that social tolerance, above all else, influences muzzle contact behaviour? Especially given that prediction 2b makes a social tolerance prediction, that lower ranking animals will initiate less than higher ranking animals.

This whole paragraph has been removed now.

179-182: Why mention this here? Perhaps this would be better at the very beginning of the results, or near where the differentiation is first referred to in the results.

It was placed there at the suggestion of a reviewer. We moved this paragraph back to the beginning of the Results section now (L 174-177).

209: Should this be "his" instead of "their"?

We changed it for “the group’s” as it refers to the “group” (L 190).

213-221: This use of uptake is confusing… in the reply, the authors state " the reason we talk about 'uptake' rather than social learning is that we really see this as a case of social disinhibition of neophobia, rather than more detailed social learning such as copying or imitation" but this disinhibition hypothesis is never mentioned in the introduction.

In the introduction, we talk about neophobia being reduced after seeing conspecifics eat a novel food in various species L 79-80. We modified the wording of our prediction for this result to be more explicit about this: “We expected, when the innovators or initiators (in case of immigrant males importing the innovation) were adults rather than juveniles or infants, greater neophobia reduction and therefore faster and more widespread uptake of the novel food…” – L 141-144

The introduction needs to make clear this distinction, and why, despite that this behaviour was previously shown to be socially transmitted, social learning language here. I see no reason not to report that this behaviour is socially transmitted and that this study takes the opportunity to explore who innovated and whether socio-demographic variation corresponded with innovation, as well as the opportunity to further explore muzzle contact as a means of learning about novel foods given previous evidence showing that muzzle has the potential for being a learning modality, rather than proposing an entirely different mechanism.

Also, how does one prove the difference between the uptake of the innovation being the result of social disinhibition and the topography of opening the peanut being socially transmitted? I understand the use of EWA to show the latter, but am not sure how that is separate in fact from the former…how does one show the approach and willingness to interact is only socially facilitated, but the opening itself is socially learned? Especially given that all of the results in this study are presented in regard to who extracted and ate the peanuts, and not some other measure of neophobia.

To clarify: The first paragraph of results of the section ‘(1a) Who innovated and how did it affect the extent to which the innovation was adopted by the group?’ (L189) refers to the individuals who innovated – ate the novel food first. Innovation relies on individual learning as one individual has to start eating the food the first time. The paragraphs of this section ‘(1b) Socio-demographic variation in learning the innovation’ (L213-228) refers to who ate the food over four exposures, and here social learning might happen as shown in Canteloup et al. (2021) but, as one can read in that paper, a combination of individual and social learning is at stake when learning which peanuts opening technique to use. In that sense, we changed “uptake” for “learning” (L 212). We hope that this explicit statement clarifies things. If not, we are of course willing to modify the term if requested by the editors.

Reviewer #2 (Recommendations for the authors):

I commend the authors for their hard work in improving their manuscript to accommodate the comments raised by myself and the other reviewers. However, I still feel there is considerable conceptual fuzziness that constrains a clear interpretation of the data presented here, as well as some remaining issues with the analysis. Much of this is made apparent in the authors' Reply to Review, so I will primarily address this. Below that, I have some more minor comments on the revised manuscript.

1) Conceptual and inferential ambiguity

"My comment: Line 281: More detail needed. Did these knowledgeable individuals typically have their mouths full of the target food during these events? If so then it seems parsimonious to assume the muzzlers were simply following this rather than tracking knowledge-states.

Authors reply: We do not claim that they track knowledge states – we are claiming that they can tell who is currently eating or has eaten a food that they do not know about, and try to obtain information about that food. We use the word "knowledgeable" for our human readers to easily identify and refer to "individuals that have already learned to extract and eat peanuts". We never report in the manuscript that we are inferring that the monkeys track the knowledge state. We do assume that if they are close enough to muzzle contact, they are close enough to have probably seen them eat the food."

"…we never report in the manuscript that we are inferring that the monkeys track the knowledge state." Throughout the manuscript the authors make statements to this effect…"

I'm particularly surprised by this final comment since one need not even read past the abstract to see that it is clearly untrue: "Finally, knowledge influenced females and juveniles less than males and adults in becoming more likely targets than initiators.". The manuscript is riddled throughout with examples of such causal language that heavily implies a direct effect of knowledge on the outcome measures. This is extremely misleading and serves no purpose. The word 'knowledge' should be removed from the manuscript entirely and the authors find another way to describe their variable. For example, why not just call the 'knowledgeable' individuals "demonstrators"?

Below I answer several comments at once:

"We did not intend to claim that muzzle contact was the specific mechanism by which individuals learned to extract and eat peanuts – we rather use this experiment to evaluate the function of muzzle contact in the presence of a novel food."

"For this, and the above points: We did not record an observation network for the groups added in this study and are not able to answer this – it is not the focus of this study. For this reason, we do not make claims in this line in the present study, and are cautious with our social learning related language. Whilst we examine the role of muzzle contact in acquiring information about a novel food, we do not expect this behaviour to be a necessary prerequisite in being able to extract and eat this food – indeed many individuals who learned to eat did not perform muzzle contacts. This aspect of the study is about using this novel food situation to explore whether muzzle contact serves information acquisition – which our evidence suggests it does. Moreover, the processing of this food is not complex and is similar to natural foods in their environment, and we do expect individuals to be capable of reinventing it easily (and this point with Tennie's hypothesis is actually discussed in Canteloup et al. 2021 paper) – but the point here is that their natural tendency is to be neophobic to unknown food, and therefore they do not readily eat it until they see a conspecific doing so, after which they do. And we also used this opportunity, though in a very small sample size, to investigate which individuals would overcome that neophobia and be the first to eat successfully."

"See above – the reason we talk about 'uptake' rather than social learning is that we really see this as a case of social disinhibition of neophobia, rather than more detailed social learning such as copying or imitation, as it would be in a tool-use setting, for example (though in Canteloup et al. 2021 paper, evidence is found that the specific methods to open peanuts are socially transmitted)."

"…there is a distinction between information acquisition and information use – obtaining olfactory information about a novel resource that conspecifics are eating is not the same as learning a complex tool use behaviour for which detailed observation of a model is required. We are not claiming that muzzle contact is THE mechanism by which the monkeys learn how to eat the food"

To summarise: When I suggested the authors have implied a role in social learning, they deny this (okay! But I'm unsure about the need for evasiveness on this one – there are more kinds of social learning than just action-copying). Nevertheless, they argue that the monkey are 'gaining information' about the food and that the decline in MC as they become more knowledgeable implies a role in learning (social or asocial) or 'overcoming neophobia'. This seems plausible and a worthy hypothesis to test!

However, when I asked for evidence that individuals who MC more often are more likely to learn how to eat the food, the authors refused to examine this on the basis that "MC is not THE mechanism by which learning occurs". Regardless of whether it is THE mechanism, or simply a means of overcoming neophobia, if MC serves the function the authors have argued then it should lead to an increase in the likelihood or rate of uptake – otherwise what is the point? The authors refusal to support their argument with easily accessible data (they have apparently already recorded the identity of all individuals and their feeding/Mc behaviour) that would robustly confirm the behavioural function one way or the other is quite frustrating.

Whilst we have all of the muzzle contact interactions coded with the identities of individuals, and we know which exposure individuals successfully shelled and ate their first peanut, we do not have the exact timing of the latter for all individuals. We therefore cannot do the analysis that the reviewer proposes without extensive recoding of videos and the authors responsible for coding the videos with individuals’ identities are no longer employed in this field of work to do so.

In addition, we stand by our points, that information acquisition and information use are not the same, and that MC is not the only way to gain information. Specifically, not all monkeys that started to eat peanuts engaged in muzzle contact beforehand – this is our point about it not being the only way to obtain information – less tolerated individuals are unlikely to be able to engage in MC as easily (see Nord et al.), and therefore must rely on other kinds of information. Thus, we focussed at the group level on whether muzzle contacts decreased as the group increasingly ate peanuts.

Nonetheless, we do now report a different analysis that illustrates that as more individuals gain knowledge of the food, muzzle contact rate decreases.

In fact, the authors do present some data that contradicts their hypothesis:

Line 681: "Inspection of Figures 4A and 4D suggests that juveniles, relative to adults, still initiate more than they are targeted even when knowledgeable."

Why should knowledgeable individuals muzzle-contact at all? These individuals already have the information they need. This is a major hole in the authors' argument.

Even if muzzle contact is used, particularly, to gain information about unknown food, an uncertainty might remain. Moreover, primates are social animals, and we cannot exclude a social function to this behaviour.

"We recorded muzzle contacts visible within 2m of the box, so individuals were not necessarily eating at the box at the time of engaging in muzzle contacts. However, the majority of muzzle contacts that we could record took place directly at the edge of the box – at the location where the food is accessed – so an individual would not likely be if they were not able to have access to the food. It is possible they could be there and not eating, but they would not have been chased off, otherwise they would not be able to engage in muzzle contacts there. But it is not entirely clear what the reviewer's point is here."

If muzzle contact was only recorded within 2m of the food source, is it any wonder that knowledgeable individuals were chosen more often? Surely the majority of individuals at the food are those who have figured out how to eat it. See the comment below this one.

Not necessarily as all the individuals that came within 2m of the box did not eat the peanuts, especially at the beginning when most muzzle contacts happened. In addition, individuals that had not yet eaten would have to approach the box to begin eating too. We understand your logic here, but we disagree with it because there being more knowledgeable individuals at the box already does not preclude those knowledgeable individuals to do MCs towards naïve individuals that approach the box. So even around the experimental setup muzzle contact could theoretically be initiated by both naïve and knowledgeable monkeys.

"My comment: What proportion of PRESENT (not total) individuals were naïve and knowledgeable in each group for each trial (if 90% present were knowledgeable, then it is not surprising that they would be targeted more often)?

Authors reply: We agree somewhat with this statement, but given the multiple ways we show the effect of knowledge – both at the individual level and the group level (effect of exposure number i.e. overall group familiarity) – we feel we present enough evidence to establish the link between knowledge of the food and muzzle contacts. We find that the model showing the interaction between exposure number and number of monkeys eating on the overall rate of muzzle contacts actually addresses this issue, because we see that when many monkeys are eating during later exposures when many were indeed knowledgeable, the rate of muzzle contacts is massively decreased. Moreover, if 90% of the individuals present are knowledgeable, then only 10% of the individuals present are naïve, and we show both that knowledgeable individuals are targeted, but also that naïve individuals are initiators."

The authors have not really addressed my original point here, so I apologise if it was unclear. First, I accept the authors' conclusion that knowledgeable individuals are less likely to carry out a MC (but see below for problems regarding their interpretation of this). Instead, I was raising a point of basic sampling bias and statistical inference: If the majority of individuals at a feeding site are knowledgeable, then even a blindfolded individual who is choosing recipients are absolute random will select knowledgeable individuals more frequently. If all of the knowledgeable individuals are male, a blindfolded individual will similarly demonstrate a "bias" towards male, knowledgeable individuals. If this is not factored into the analysis then it is not inferentially sound.

Thank you for clarifying this – we do see and agree with your point here. However, our data do not fit the pattern of bias that you describe. We have a situation where when very few individuals were knowledgeable, and many were naïve, the knowledgeable minority were targeted by the naïve majority, and this decreased as more individuals became knowledgeable. Given that we have an increase of knowledgeable individuals over time AND a decrease in muzzle contacts over time, we think this counteracts the random bias that was pointed out here. In addition, we can see in Figure 3A, that at the beginning of the experiment when very few individuals were eating, there were the highest rates of MC, which decreased across the experiment.

"…but we do believe that the clear separation between naïve individuals initiating and knowledgeable individuals being target, and the decrease of the rate of this behaviour as groups' familiarity with the food increases – is good evidence that this behaviour functions to acquire information about a novel food."

That is one interpretation (but see comment above re: sampling bias for initiators) – Another explanation is that these behaviours are simply mutually exclusive at a given moment in time: once they know how to eat the food, they prefer to spend their time doing this than engaging in MC behaviour. Rates of resting, grooming, etc within 2m of the food presumably also decrease once the monkeys have figured out how to eat it, not because there is any causal relationship between these behaviours but because they can only do one thing at a time and feeding is a priority.

We understand the point here (essentially an activity budget point) and the comparison of MC rates to rates of other behaviours such as resting and grooming in the context of consuming food. However, we did not observe particularly high rates of individuals coming to the vicinity of the food and engaging in resting or grooming at that location, whether the food was novel or not. This contrasts with what we observed of MC – which became unusually high, in the vicinity of the box, when the food was novel, decreasing as the food became familiar. We believe this difference does suggest a causal relationship of the novelty of the food and conspecifics eating it as triggering the MCs.

During experiments with food rewards, individuals tend to not rest or groom at the vicinity of the food box. Muzzle contacts are being carried out specifically at this location where their group mates are consuming a novel food. We do also see individuals follow other who carry food away from the box, and MC them at the location where they stop to eat. Unfortunately, we did not collect data in this experiment on occurrence of grooming and resting at the food box that we can analyse to show statistically that grooming and resting rates are not increased relative to baseline levels in the vicinity of the box. We believe that the high rates of muzzle contact that we see directly at the vicinity of the box do imply a causal relationship that the monkeys have come to this place to do muzzle contacts prior to engage with the novel food.

2) Analysis

The authors have heavily revised their original analysis and it is largely improved. I have a few remaining issues which I describe below.

"My comment: The text for this muzzle-contact analysis would indicate that this model was not fit with any random effects, which would be extremely concerning. However, having checked the R code which the authors provided, I see that Individual has been fit as a random effect. This should be mentioned in the manuscript. I would also strongly recommend fitting Group (it was an RE in the previous models, oddly) and potentially exposure number as well.

Author reply: The model about muzzle contact rate never contained individual as a random effect because individuals are not relevant in this model – it is the number of muzzle contacts occurring during each exposure. However, the reviewer might refer here to the model that we forgot to provide the script for. Nonetheless, we have substantially revised this model, it now (Model 3) includes all groups, and has group as a random effect."

I do not accept that individual is not a relevant random effect. I understand that the model is intended to examine group-level rates of M-C, but groups are made of individuals. Let us imagine a scenario where a single individual is a highly prolific muzzle-contacter in group BD, accounting for 95% of M-C events, and NH contains no such individuals. An analysis that takes a straightforward group rate without accounting for individual contributions will likely find a significant difference between the two, driven by a single individual. If the authors have structured their data and analysis in such a way that they cannot control for this factor then that is an issue. One "quick and dirty" solution, that would require a minimal amount of restructuring of the data, would be to take an individual rate for each monkey in a group, or at the feeding site, or whatever, and then derive the group average from this. Otherwise, it is not clear what we can infer from this analysis.

We have re-structured the data and redone this analysis with both individual and group as random effects and hope the reviewer find these changes satisfactory. Please see L 612 in the methods, as well as Table 3 for updated results.

"Authors: We have now checked for overfitting in our models."

Where is the evidence of this, please? There are metrics and methods that can be used to achieve this (such as AIC/LOO-based model comparison approaches I suggested in my last review) but the authors do not report them.

We calculated the variance inflation factor (VIF) for each variable in all models and, except for the variable “number of monkeys eating” in model 3 where VIF = 4.36, suggesting a moderate correlation, all VIF are <3, meaning that there is no overfitting. Moreover, we compared the AIC of our models including random effects with AIC of models without random effects, and the lowest AIC were always those of the models including random effects. This is now specified in the method (L 650-654) and in the annotated R script.

"We included individual as a random effect, but we did not include group as a random effect here for two reasons. First, we did not have any theoretical basis to expect residing in different groups to have an effect here, since we were concerned with the effects of life history strategies of individuals on their information acquisition behaviour, which should not differ for individuals from different groups."

This is not theoretically sound. Individuals from groups are more likely to be similar than individuals from different groups – this is the purpose of grouping variables. They live in similar ecologies, share life history events, and are more closely related.

We now removed this model so this is no longer an issue.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Role of immigrant males and muzzle contacts in the uptake of a novel food by wild vervet monkeys" for further consideration by eLife. Your revised article has been evaluated by George Perry (Senior Editor) and a Reviewing Editor.

The edits to the manuscript were much appreciated but unfortunately have also brought to our attention some additional issues with your statistical analysis that must be addressed, as outlined below.

1. The issue is that once you reported your dispersion parameter results, it is now clear that Models 4 and 5 are highly underdispersed, and model 3 moderately so. Underdispersion can be considered as much an issue as overdispersion for poisson models so we urge you to rethink the error structure used for these models so that you do not violate the assumptions of a poisson distribution.

We consulted a statistician from the University of Lausanne for the issue 1 listed here below. He confirmed to us that our dispersion test were correct and that our models are not over or underdispersed, but that what we reported as dipsersion parameter is not that. Here his feedback:

'The testDispersion() function in R is actually not very useful, because it pretends to display the dispersion (by writing "dispersion = 0.0017655, p-value = 0.592"), but actually, it is not.

The value (0.0017655) is actually saved in the object under the name "statistic"; so it is not the dispersion, but a ratio that is calculated by the model by comparing the observed model to simulated data. This ratio is then compared to 1, but there is no intrinsic notion of scale (e.g. the fact that the observed value is 0.0017 does not mean much, and certainly not that the dispersion is so low; the simulation are then run to estimate the significance of this difference).

In this case, p=0.59, so that the value is not significantly different from 1, and so there is no evidence that the data is significantly underdispersed.'

https://doi.org/10.7554/eLife.76486.sa2

Article and author information

Author details

  1. Pooja Dongre

    1. Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
    2. Inkawu Vervet Project, Mawana Game Reserve, KwaZulu Natal, South Africa
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6957-3972
  2. Gaëlle Lanté

    1. Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
    2. University of Poitiers, Poitiers, France
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared
  3. Mathieu Cantat

    Inkawu Vervet Project, Mawana Game Reserve, KwaZulu Natal, South Africa
    Contribution
    Data curation
    Competing interests
    No competing interests declared
  4. Charlotte Canteloup

    1. Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
    2. Inkawu Vervet Project, Mawana Game Reserve, KwaZulu Natal, South Africa
    3. Laboratory of Cognitive & Adaptive Neurosciences, CNRS - UMR 7364, University of Strasbourg, Strasbourg, France
    Contribution
    Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Writing – review and editing, Supervision, Writing – original draft
    Competing interests
    No competing interests declared
    Additional information
    Joint last authorships
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5462-081X
  5. Erica van de Waal

    1. Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
    2. Inkawu Vervet Project, Mawana Game Reserve, KwaZulu Natal, South Africa
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing – review and editing
    For correspondence
    erica.vandewaal@unil.ch
    Competing interests
    No competing interests declared
    Additional information
    Joint last authorships
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7778-418X

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (PP03P3_170624)

  • Erica van de Waal

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (PP00P3_198913)

  • Erica van de Waal

Branco Weiss Fellowship – Society in Science

  • Erica van de Waal

Fondation Fyssen

  • Charlotte Canteloup

Fondation des Treilles

  • Charlotte Canteloup

Horizon 2020 (949379)

  • Erica van de Waal

Centre National de la Recherche Scientifique

  • Charlotte Canteloup

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

This study was supported by the Swiss National Science Foundation (PP03P3_170624 and PP00P3 198913), the Branco Weiss Fellowship – Society in Science, granted to Erica van de Waal, and by the Fyssen Foundation and the Fondation des Treilles granted to Charlotte Canteloup. At the time of revisions, Erica van de Waal was supported by the European Research Council under the European Union’s Horizon 2020 research and innovation program for the ERC ‘KNOWLEDGE MOVES’ starting grant (grant agreement No. 949379) and Charlotte Canteloup was supported by the CNRS. We are grateful to the van der Walt family for their permission to conduct the study on their land and to Arend van Blerk and Michael Henshall for their support in the field. We are particularly thankful to Mabia Biff Cera, Adam Cogan, Adwait Deshpande, Sashimi Wieprecht, Manon Kerréveur-Lavaud, Varun Manavazhi, Maria Teresa Martinez Navarrete, Tecla Mohr, Aurora Rozmaryn, Claudia Seminara, and Luca Silvestri for their help in data collection. We are grateful to Frédéric Schütz, Rachel Harrison, and Cédric Girard-Buttoz for their advice on statistical analyses. We thank Redouan Bshary, Sofia Forss, Rachel Harrison, Carel van Schaik, and Andrew Whiten for comments on an earlier version of the manuscript.

Ethics

Our study was approved by the relevant local wildlife authority, Ezemvelo KZN Wildlife, South Africa (though no reference number was provided by them). The University of Lausanne, Switzerland, did not have an ethics committee for the study of animals in other countries, however, we ensured our research adhered to the "Guidelines for the use of animals in research" of the Association for the Study of Animal Behaviour (available here: doi:10.1016/j.anbehav.2019.11.002).

Senior Editor

  1. George H Perry, Pennsylvania State University, United States

Reviewing Editor

  1. Ammie K Kalan, University of Victoria, Canada

Reviewer

  1. Julie Teichroeb, University of Toronto, Canada

Version history

  1. Preprint posted: December 17, 2021 (view preprint)
  2. Received: December 20, 2021
  3. Accepted: December 13, 2023
  4. Version of Record published: January 9, 2024 (version 1)

Copyright

© 2024, Dongre et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Pooja Dongre
  2. Gaëlle Lanté
  3. Mathieu Cantat
  4. Charlotte Canteloup
  5. Erica van de Waal
(2024)
Role of immigrant males and muzzle contacts in the uptake of a novel food by wild vervet monkeys
eLife 13:e76486.
https://doi.org/10.7554/eLife.76486

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https://doi.org/10.7554/eLife.76486

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