How do individual behaviors based on visual and auditory cues facilitate spatiotemporal coordination in collective movement of patas monkeys (Erythrocebus patas)?

doi:10.21203/rs.3.rs-7212680/v1

Download PDF

Research Article

How do individual behaviors based on visual and auditory cues facilitate spatiotemporal coordination in collective movement of patas monkeys (Erythrocebus patas)?

https://doi.org/10.21203/rs.3.rs-7212680/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Collective movement requires individuals to coordinate their behaviors across time and space. Recent advances in GPS tracking have enabled the recording of whole-group movements and estimation of group cohesion. However, integrating individual behavior with group-level dynamics remains a developing approach. In this study, we combined GPS tracking with behavioral observations to examine visual monitoring and calling related to collective movement in a group of wild patas monkeys (Erythrocebus patas), with a focus on sex-specific patterns. Females engaged in visual monitoring when fewer juveniles were nearby, followed by increased juvenile proximity, suggesting a role in maintaining spatial cohesion with juveniles. In contrast, the male monitored visually when out of temporal synchrony with females, and his monitoring increased velocity differences at the future time. This implies that the male may be engaging in monitoring primarily as a form of vigilance against predators or conspecific groups, possibly contributing to the protection of females as potential mating partners, rather than to maintain temporal synchrony with them. Interestingly, female contact calls were associated with increased others’ velocity, particularly under conditions where the caller and others were previously moving at similar velocity. This suggests that females may produce calls with the goal of accelerating the movement of other individuals, consistent with intentional communication. Over all, our findings suggest that visual monitoring and calling function in context-dependent ways and highlight the importance of integrating movement dynamics, intentional communication and behavioral context to better understand the mechanisms of collective coordination in group-living animals.

Collective movement

Spatial cohesion

Temporal synchrony

Intentional communication

Visual monitoring

Calling

To live successfully in groups, animals need to coordinate their movements while staying together. This study combines GPS tracking and behavioral observation to explore how wild patas monkeys use visual information and auditory signals for collective movements. Females engaged in visual monitoring when fewer juveniles were nearby, followed by increased juvenile proximity, suggesting a role in maintaining spatial cohesion. In contrast, the male monitored visually when temporally out of sync with females, and his monitoring was associated with increased future velocity differences, implying vigilance rather than coordination. Interestingly, female contact calls were followed by increased travel velocity of others, especially when they had been moving at similar velocity. This suggests that females may use calls intentionally to prompt others to move, highlighting a potentially goal-directed use of auditory signals. These findings show that visual monitoring and calling serve distinct, context-dependent functions in collective coordination among social animals.

Membership in a cohesive group provides fitness benefits, including enhanced foraging efficiency (Wrangham 1980; Clark and Mangel 1986), and reduced predation risk (van Schaik 1983; Turchin and Kareiva 1989). However, these benefits come with costs, such as increased feeding competition (Markham and Gesquiere 2017) and coordination costs arising from individual variation in energetic demands (Main et al. 1996). Therefore, group-living animals need to coordinate their activities to maintain cohesion and maximize the benefits/costs of groups (Liao et al. 2024).

Collective movement (CM) is a key group-level behavior observed across diverse taxa, including humans (Sumpter 2010). CM is typically defined as a group moving in a shared direction with similar timing and velocity, thereby maintaining cohesion until the group stops moving or starts a new activity (Petit and Bon 2010). There are two main measures for assessing CM: spatial cohesion and temporal synchrony. The former is often evaluated based on the number of members in close proximity (Irwin 2007; Suzuki and Sugiura 2011) and the distances between individuals (Byrne 2000; King and Sueur 2011), whereas the latter is often evaluated based on individual variations in travel velocity (Bousquet et al. 2011). The maintenance of such spatial and temporal cohesion within the group often depends on inter-individual communication that facilitates mutual adjustment. Generally, group coordination in vertebrates relies on the transfer of information through visual and auditory channels, and social responses, such as approaching or leaving between individuals (Petit and Bon 2010). Visual information is primarily obtained by monitoring the positions and movement trajectories of nearby conspecifics (Ramoset al. 2015; Strandburg-Peshkin et al. 2015), whereas auditory information, such as vocalizations, can convey spatial position, movement intent, or motivational state (Boinski 1993; Cheney et al. 1996; Radford 2004).

In wild group-living mammals and birds, previous studies have addressed the relation of these individual behaviors to group coordination by estimating spatial cohesion in small-scale distances such as the number of members in close proximity (e.g., within 10 m, Radford and Ridley 2008; in the same tree, Kazahari and Agetsuma 2010) or over a limited scale such as inter-individual distances (IIDs) of only a few individuals using hand-held GPS devices (e.g., Sugiura et al. 2014). However, evaluating group cohesion and synchrony on a larger scale is essential to determine whether individual-level behaviors affect overall group behavior, particularly in species with spatial dispersion during travel.

Recently, technological advances in biologging and animal tracking (Krause et al. 2013; Yan et al. 2024) have contributed to a greater understanding of the mechanism of complex CM. In particular, fitting global positioning system (GPS) collars to animals allows researchers to track the large-scale movements of multiple individuals simultaneously, enabling the monitoring of the fine-scale locations and movements of numerous individuals within a group (Godfrey et al. 2014; Strandburg-Peshkin et al. 2015). Furthermore, studies are being developed that integrate GPS and acoustic tags to investigate the relationship between movement coordination and vocal communication (Demartsev et al. 2023). Although GPS methods have advanced our knowledge of spatial dynamics, the functional role and potential intentionality of communicative signals, such as visual monitoring and vocalizations, in group movement remain understudied. Behavioral approaches that infer communicative intent based on indicators such as goal-directed persistence and audience effects (i.e., behavioral adjustments made in response to the presence of a recipient) have been proposed to address this gap (Townsend et al. 2017; Mocha and Burkart 2021). Integrating these approaches into field studies of wild animals promises to clarify the communicative and cognitive foundations of group coordination.

Additionally, a recent review highlighted sex differences in leadership during collective decision-making processes (Smith et al. 2022). The sex that assumes leadership often depends on the species’ social structure, such as whether it is female- or male-philopatric, and social organization, including whether the group is one-male or multi-male (e.g., mountain gorilla, Gorilla beringei beringei: Harcourt 1979; Watts 1992; hamadryas baboon, Papio hamadryas: Kummer 1968). Thus, these social factors may influence sex-specific roles in the mechanisms of group coordination.

In this study, we examined the function of visual monitoring and calling for spatiotemporal coordination with other individuals in CMs by combining GPS tracking and behavioral observation. We focused on (1) which indicators of group cohesion and synchrony—including large-scale group metrics—influence visual monitoring and calling in females and the male, and (2) whether visual monitoring and calling will be effective in maintaining spatial cohesion and temporal synchrony in the future. This approach highlights spatiotemporal changes in group cohesion and synchrony by analyzing individual behavior and movement across space and time. We conducted this study on patas monkeys (Erythrocebus patas) that form female-philopatric one-male groups and live in a savannah environment. We fitted GPS collars to almost all adults in a group and observed visual monitoring and calling of one of them. Previous studies have reported that visual monitoring is continuous in both sexes (Rowell and Olson 1983), while contact calls are emitted mainly by females infrequently (Nakagawa 1992), although the function of these behaviors for CMs remains unknown. Patas monkeys forage on dispersed high-quality food, such as gums and insects (Chism and Rowell 1988; Isbell 1998; Nakagawa 2003), and travel long distances (Isbell et al. 1998; Nakagawa 1999), spreading out for foraging (Hall 1966). The risk of separation from the group is generally high during mobile activities such as foraging and travelling (Nishikawa et al. 2014; Bracken et al. 2021), patas monkeys will frequently encounter circumstances that require coordination with other individuals to prevent group separation. Moreover, the sole adult male of this species was described as spatially peripheral during travel (Hall 1966), allowing for a comparison of monitoring behavior in the presence or absence of females. These characteristics suggest that patas monkeys may be a promising species for investigating sex-related behavioral patterns in group coordination during CMs.

(1) Field site and study subjects

We conducted this study from December 2022 to March 2023 during the dry season in Mole National Park, Ghana (09°12′–10°06′ N, 01°25′–02°17′ W). This park is located in the Guinea savannah zone (Lawson et al. 1968), which mainly comprises the open savannah woodland, dominated by a layer of grass and riverine forest (Schmitt and Adu-Nsiah 1993). We studied a one-male group of patas monkeys (named the Motel group) comprising 17 individuals, including one adult male, five adult females, eight juveniles and three infants. Individuals in the group were identified and almost completely habituated by 2021.

(2) Spatial data collection

We fitted GPS collars (GLT-02, Circuit Design, Inc.) to the sole adult male (MC) and four adult females (Sa, Sk, Kr and Sh), except for one adult female that was not fully habituated to observers (supplementary material, Fig. S1). Veterinarians (YM or RS) immobilized the animals with zoletil (5 mg/kg) and medetomidine (0.1 mg/kg) using a blowpipe and later reversed the drugs with atipamezole (0.5 mg/kg). The GPS collar (less than 250 g) was less than 5% of the body mass (6.2–10.8 kg (n = 5); YM unpublished data), as suggested by the American Society of Mammalogists (1998). The GPS collars recorded data on location (latitude and longitude), time and positional dilution of precision (PDOP, an index of position accuracy) every 10 min from 7 a.m. to 5 p.m. After data collection, we successfully removed the collars from all the monkeys using remote electronic drop-off systems. We calculated the three-dimensional positioning success rate (the number of successful positioning attempts divided by the total number of positioning attempts), which was 100% for all data. We also confirmed a PDOP of 6 or less (D’Eon and Delparte 2005) in all data to ensure that only high-precision GPS fixes were used for analyses. Consequently, 28,849 GPS fix points were collected and distributed almost evenly across all dates and individuals for the analysis (Table S1).

(3) Behavioral data collection

One of five GPS-collared individuals was observed for 1-h sessions at a time. If we lost the focal individual but found it within 20 min, we resumed recording until the total following time reached 1 h. Consequently, the individuals were observed for a total of 708 h (Table S1). During focal animal observation, we recorded the individual’s activities (foraging, feeding, travelling, resting, drinking and others) every 10 min, corresponding to the timing of the GPS fixes. Foraging was defined as searching for food such as moving rocks, digging up the ground or looking at the ground and surrounding trees, regardless of whether moving forward or not and without having food in the mouth or with hands; feeding was defined as having food in the mouth or manipulating food with the hands, which was recorded exclusively with foraging; travelling was defined as continuing to move without looking at the ground or surrounding trees; resting was defined as an inactive state occurring either on the ground or tree.

We recorded the visibility of the location (clear or unclear) where the focal animal was observed at 10-min intervals, in accordance with the recording interval of the GPS collars. This is because habitat visibility generally affects the efficacy of visual information (Byrne 2000; Davidson et al. 2021). Clear locations included open lands with almost no undergrowth and unclear locations included rocky areas, grasslands, and forests. Unclear locations were typically covered with grass taller than the eye height of the patas monkeys (ca. 30–50 cm). We also recorded the number of non-collard individuals (eight juveniles and one adult female) within 20 m of the focal animal using instantaneous scan sampling at 10-min intervals. A distance of 20 m around the focal individual was the reliable range for observing other individuals. We excluded infants because they are usually in contact with their mothers (Chism 1986).

The time of visual monitoring for the focal animal was recorded using one-zero sampling at one-minute intervals. Patas monkeys perform the behavior known as ‘arboreal scan’ or ‘bipedal scan’ (Enstam and Isbell 2002; Rowell and Olson 1983): the former is defined as gazing into the distance with the head moving from side to side for more than 3 s on a tree and the latter is defined as gazing while standing on hind legs on the ground. We also frequently observed the patas monkeys gazing into the distance on the rocks and fallen trees; thus, we regarded these situations and two of the scanning behaviors as visual monitoring. When tracking females, the time of emitting contact calls was recorded using one-zero sampling at one-minute intervals. We did not record the contact calls of the male because the sole male hardly emitted contact calls (Nakagawa 1992).

(4) Statistical analyses

(4-a) Handling of location data collected by GPS collars and behavioral records

We handled the behavioral records of focal animals that lasted for more than 30 consecutive minutes. These included feeding, foraging, travelling or pausing (i.e., less than 10 minutes resting). Regarding visual monitoring, patas monkeys exhibit this behavior to observe group members and vigilance against predators and other groups (Enstam and Isbell 2002). Therefore, we omitted the visual monitoring data when we visually or auditorily detected potential predators such as olive baboon (Papio anubis) and African rock python (Python sabae), other groups of conspecifics or people while tracking the group to eliminate vigilance outside of the group. Consequently, we used data from 543 visual monitoring for analyses (MC: n = 120, Sa: n = 87, Sk: n = 140, Kr: n = 128, Sh: n = 68). Data on contact calls were excluded during encounters with other groups of conspecifics or other animals (Nakagawa 1992) to eliminate unrelated contexts and focus on analyzing the role of contact calls in coordinating group cohesion and synchrony. Consequently, we used 142 contact calls for analyses (Sa, n = 37; Sk, n = 65; Kr, n = 16; Sh, n = 24).

Behavioral records and GPS fixes were combined as follows: GPS fixes were collected every 10 min and the location of visual monitoring or contact calls was assigned to the GPS fix recorded immediately before the occurrence of these behaviors. We used only the behavioral records that occurred until 5 min later from GPS fixes to avoid a larger gap between the exact location at the time of these behaviors and GPS fixes. We calculated several indicators from GPS fixes using ‘adehabitatLT’ package (Calenge 2006) and ‘sf’ package (Pebesma 2018) in R as follows: (1) IID between individuals and (2) individual travel velocity (m/min). Generally, the spatial cohesion of groups was estimated using (1) and the number of members in close proximity to the focal animals (Cowlishaw 1998; Byrne 2000; King and Sueur 2011), while temporal synchrony was measured using (2) (Bousquet et al. 2011). We created time blocks of 10 min in accordance with the record interval of GPS collars, for which we established the distance covered by individuals as travel velocity (i.e., distance covered per 10-min time block; Fig. 1). As for the number of adults within 20 m of the focal animal, we combined the number of collared individuals calculated from GPS fixes with the presence of the non-collared female (1 or 0) collected by direct observation.

(4-b) Which indicators are used for each sex to monitor group cohesion and synchrony? (Model 1)

Our modelling approach was twofold when running the generalised linear mixed models (GLMMs). First, we examined which indicators of group cohesion and synchrony were related to the occurrence of monitoring behavior of each sex in the same 10-min time blocks (Model 1, Fig. 1). Second, with predictor variables that were significantly related to the occurrence of the monitoring behavior, we assessed changes in these predictor variables in the next time block, that is, the effect of monitoring behavior on future group cohesion and synchrony (Model 2). We initially aimed to construct separate models for conditions in the environment in which the group was in either clear or unclear visibility. However, owing to the limited number of samples under unclear conditions for both visual monitoring and contact calls, we restricted our analyses to data collected under clear visibility conditions.

In Model 1, we first investigated the occurrence of visual monitoring in females (Model 1a). The occurrence of visual monitoring (1 or 0) was included as a response variable. The following indicators were added as predictor variables: (i) nearest IID between the focal female and other females; (ii) IID between the focal female and the male; (iii) mean IID between other collared individuals; (ⅳ) the number of adults and (v) juveniles within 20 m from the focal female; (vi) travel velocity of focal female; (vii) whether the focal female was faster than the nearest collared individual (1 or 0), (viii) absolute value of the difference between the travel velocity of focal female and mean travel velocity of others.

Second, we analyzed the male as well (Model 1b). We included the following variables as predictor variables, which were largely the same as in the female model, to examine their differences: (i) nearest IID between the male and the collared female; (ⅱ) mean IID between collared females; (ⅲ) the number of females and (iv) juveniles within 20 m from the male; (v) travel velocity of the male; (vi) whether the male was faster than the nearest collared female (1 or 0) and (vii) absolute value of the difference between the travel velocity of the male and mean travel velocity of collared females.

Third, we examined the occurrence of female contact calls (Model 1c). We included the occurrence of contact calls (1 or 0) as the response variable and added the same predictor variables as in Model 1a to investigate the differences in indicators affecting visual monitoring. Variables (i)–(v) in Model 1a and (i)–(iv) in Model 1b were treated as indicators of spatial cohesion, whereas variables (vi)–(viii) in Model 1a and (v)–(vii) in Model 1b were used as indicators of temporal synchrony within the group. For the analysis, we included session ID as a random intercept in all models to account for non-independence among observation sessions and Focal ID as a random intercept in models for females to control for repeated measures from the same individual.

(4-c) Do visual monitoring and calling affect group coordination? (Model 2)

The next step was to examine whether visual monitoring and calling would coordinate group cohesion and temporal synchrony in the future. Hence, three different 10-min time blocks were used: one containing visual monitoring and calling, another representing the 10 min before the behaviors and the third covering the 10 min after the behaviors (hereafter: current time periods, previous time periods and future time periods; Fig. 1). Using predictor variables significantly related to the occurrence of visual monitoring and calling in Model 1, changes in these predictors were examined by comparing the pre- and post-visual monitoring and calling times.

First, we assessed the function of female visual monitoring as a group coordination (Model 2a). Because the number of juveniles within 20 m was significantly related to the occurrence of visual monitoring in Model 1a, the effect of visual monitoring on coordinating spatial cohesion with juveniles was investigated. Therefore, we incorporated changes in the number of juveniles within 20 m at the future time as the response variable (i.e., the value obtained by subtracting the number of juveniles at the current time from that at the future time). We added (ⅰ) whether visual monitoring occurred at the current time (1 or 0), (ⅱ) whether the number of juveniles within 20 m at the current time decreased from the previous time (1 or 0) and (ⅲ) their interaction as predictor variables. This interaction was added based on the prediction that a decrease in the number of juveniles would lead to increased visual monitoring, which in turn would help increase the number in the future.

Second, we assessed the function of visual monitoring in the male. The travel velocity difference between himself and females were significantly related to the occurrence of visual monitoring in Model 1b. Thus, we investigated whether visual monitoring of the male is effective in maintaining a small velocity difference with females. We incorporated the change in velocity difference from females between the current time period and the future time period as the response variable (Model 2b). We added (i) whether visual monitoring occurred at the current time (1 or 0), (ⅱ) whether the velocity difference with females at the current time period was smaller than the previous time period (1 or 0) and (ⅲ) their interaction as predictor variables. We incorporated the interaction because we predicted that when the velocity difference with females was small, visual monitoring would help to keep the small difference in the future.

Third, we examined the function of female contact calls. The travel velocity difference between herself and others were significantly related to the occurrence of contact calls in Model 1c. Hence, we first examined whether contact calls were effective in maintaining a small difference in travel velocity with others. We included the change in velocity difference from others between the current time period and the future time period as the response variable (Model 2c-1), the same as Model 2b. We added (i) whether contact calls occurred at the current time (1 or 0), (ⅱ) whether the velocity difference with others at the current time period was smaller than the previous time period (1 or 0) and (ⅲ) their interaction as predictor variables.

To further investigate the potential influence of contact calls on group coordination, we tested an additional model to examine whether contact calls affected changes in the travel velocity of other individuals. Unlike visual monitoring, vocalizations are inherently directed toward recipients and may elicit behavioral responses in receivers. We incorporated the change in the mean velocity of others from the previous time period (i.e., before calling) to future time periods (i.e., after calling) as a response variable (Model 2c-2). We added (ⅰ) whether contact calls occurred at the current time (1 or 0), (ⅱ) whether the velocity difference with others at the current time period was smaller than the previous time period (1 or 0), (ⅲ) their interaction and (ⅳ) focal velocity at the current time period. We added (ⅳ) to test whether the increase in other’s velocity was due to the contact calls rather than simply a consequence of the focal individual moving faster.

We included random effects in Model 2, following the same structure as in Model 1.

Model implementation

All analyses were conducted in R version 4.2.1 (R Core Team 2022). GLMMs were fitted using the ‘glmmTMB’ package (Brooks et al. 2023). Model 1 was fitted with a binomial distribution and a logit link function. Model 2 used a Gaussian distribution with an identity link function following confirmation of residual normality. We detected no problems with the GLMMs when checking the model assumptions, including under/overdispersion and zero-inflation, using the ‘simulateResiduals’ function in the DHARMa package (Hartig and Lohse 2022). Variance inflation factors (VIFs) were calculated for all test predictors using the ‘check_collinearity’ function in the performance package (Lüdecke et al. 2021), indicating low collinearity (VIF < 10; Roberts and Roberts 2015). If the models included interaction terms (Model 2), we performed post hoc pairwise comparisons to compare the estimated marginal means among parameters. We used the ‘estimate_contrasts’ function in the model-based package (Makowski et al. 2020) to conduct this analysis and p-values were adjusted using Holm’s method. The alpha level was set at 0.05 for all analyses.

(1) Indicators used to monitor group cohesion and synchrony for each sex

We found that females were more likely to engage in visual monitoring when the number of juveniles within 20 m was small. Females tended to perform visual monitoring when fewer adults were present within 20 m, although the effect was not statistically significant (p = 0.058; Model 1a; Table 1).

The male was more likely to engage in visual monitoring when the velocity difference between him and the females was large (Model 1b; Table 1). He also tended to monitor visually when fewer females were present within 20 m, although this effect was not statistically significant (p = 0.086). Females were also more likely to emit contact calls when the travel velocity difference with other adults was small (Model 1c; Table 1).

(2) Function of visual monitoring and calling as coordination of CMs

Following the results of Model 1a, we compared the effects of female visual monitoring under conditions in which the current number of juveniles around females was smaller than the previous time and when it was not (Model 2a). Although the interaction between visual monitoring and prior juvenile decrease was not statistically significant in the GLMM (Table 2), post hoc pairwise comparisons indicated that visual monitoring was associated with a significantly higher number of juveniles when a prior decrease had occurred (Table 3, Fig. 2a). This suggests that visual monitoring may have a restorative or deterrent effect specifically when a prior decrease has occurred.

For the male, we compared the effects of the male visual monitoring depending on whether the velocity difference with females at the current time period was larger than the previous time period (Model 2b). The result revealed a significant main effect of monitoring, indicating that visual monitoring was associated with larger velocity differences from the females (Table 2). Pairwise comparisons showed that when the velocity difference from the previous time period had not decreased, the velocity difference between the male and females was significantly greater under monitoring compared to no monitoring (Table 3, Fig. 2b). In contrast, when the velocity difference had decreased, there was no significant difference between the monitoring and non-monitoring conditions.

Regarding female contact calls, we first compared the effects of contact calls when the velocity difference with others at the current time period was smaller than the previous time period and when it was not (Model 2c-1). However, neither the main effect of nor its interaction with convergence was significant (Table 2). Post-hoc contrasts also showed no significant difference in velocity coordination between contact calls and non-calling individuals in either condition (Table 3, Fig. 2c-1). On the other hand, we found that contact calls were associated with a significantly increased the mean travel velocity of other individuals when there had been a prior decrease in the travel velocity difference between the focal female and others (Model 2c-2, Table 3, Fig. 2c-2).

This study examined the function of visual monitoring and calling in the spatiotemporal coordination of group-living patas monkeys. Notably, females were more likely to engage in visual monitoring when fewer juveniles were nearby (Model 1a), whereas the male engaged monitoring when his velocity differed from that of the females (Model 1b). In females, the number of juveniles in their vicinity increased after visual monitoring. These results suggest that females prioritise visual attention to maintain proximity to juveniles rather than to the male. The mother-juvenile offspring relationship is known to be an influential factor structuring proximity in not only patas monkeys (Nakagawa 1992) but also primates in general (see the review of Gouzoules and Gouzoules 1987). Given that all focal adult females except Sh had juvenile offspring, it is likely that they engaged in visual monitoring to avoid excessive separation from their juvenile offspring. Although juvenile offspring typically remain close to their mothers, previous studies have shown that juveniles increasingly engage in social play with other juveniles away from their mothers (chimpanzee; Pan troglodytes verus: Heintz et al. 2017; Japanese macaques; Macaca fuscata: Shimada and Sueur 2018; moor macaques; M. maura: Beltrán Francés et al. 2020). These behavioral tendencies may partly explain why the number of juveniles around females eventually decreases when separation occurs. While our model could not explicitly incorporate mother–offspring separation (e.g., distances >20 m) due to the difficulty of identifying individual juveniles in the field, the observed patterns align with the expected spatial dynamics of juveniles during early development.

In contrast, the male visual monitoring was associated with velocity differences from the females. Contrary to our expectations, visual monitoring increased the velocity gap when the male was already moving at a different pace from the females. This finding may reflect his typical role as a "watchdog," (cf. Hall 1966) that frequently scan the surroundings from peripheral positions. Thus, rather than facilitating group cohesion, his monitoring may primarily serve as vigilance against predators or other groups of patas monkeys, which could incidentally lead to greater spatial separation from the group.

Given this apparent sex difference, it remains unclear why the male engages in visual monitoring even at the cost of increasing his velocity differences from females, whereas females use visual monitoring to maintain spatial cohesion with juveniles. This divergence is likely to reflect sex differences in key resources required for survival and reproduction. Female mammal fitness is primarily influenced by access to food and caring for the young because of the constraint of energetic demands of gestation and lactation (Wrangham 1980; Kappeler and van Schaik 2002). Therefore, monitoring juvenile offspring to keep them within sight could increase survival rates for juveniles by protecting them from danger, which consequently may support reproductive value for females. In contrast, fertile females are normally a uniquely valuable resource for males because they generally represent a more limited and less divisible than food (Wrangham 1980; Kappeler and van Schaik 2002). In addition, the evolutionary fitness of defending mates is expected to exceed their future reproductive value more often for males than for females (Smith et al. 2022). As such, the male may use visual monitoring as a form of vigilance, which in turn could help him protect females as mating partners their associated food resources.

Another notable finding of this study is that female contact calls were clearly associated with the travel velocity of other group members. Although these calls did not significantly contribute to maintaining small velocity differences with other individuals, they significantly increased the velocity of others at the future time period when previous velocity differences were small. Thus, contact calls are more likely to function as a behavior that accelerates group movement, rather than one that maintains small inter-individual velocity differences. Depending on the type and context, vocalizations can function either as long-range signals reaching all group members (e.g., alarm calls; global communication) or as short-range signals targeting nearby individuals (local communication; Conradt and Roper 2005; Liao et al. 2024). In addition to indicating the caller’s location, auditory signals can also influence audience behavior (Demartsev et al. 2023). In our study, contact calls may function as global communication signals that prompt other group members to increase their velocity, particularly in situations where individuals are already moving at similar velocity, such as during feeding or traveling. Similar functions of vocalizations in coordinating behavioral transitions, such as group departures or shifts toward foraging sites, have been reported in various social mammals and birds (e.g., mongooses, Helogale parvula: Meier et al. 1983; white-faced capuchins: Boinski 1993; green woodhoopoes, Phoeniculus purpureus: Radford 2004; red-fronted lemur, Eulemur rufifrons:Sperber et al. 2017; African wild dogs, Lycaon pictus: Walker et al. 2017).

Once movement is initiated, directional coordination appears to rely more on movement cues (Fischer and Zinner 2011; Papageorgiou and Farine 2020; Averly et al. 2022). However, recent studies suggest that vocalizations continue to contribute to movement coordination even after travel has begun. In sooty mangabeys (Cercocebus atys), which often travel in subgroups within mixed-species associations, it has been shown that the vocalization rate of subgroup members is associated with the focal individual's future velocity (Neumann and Zuberbühler et al. 2016). Our study extends this perspective by demonstrating a similar effect at the scale of the entire group. In patas monkeys, contact calls produced by females were more likely to affect the velocity of other group members when the caller was already moving at a similar velocity to them. This audience-dependent effect implies that females may produce calls with the goal of accelerating the movement of other individuals, which aligns with the criteria for intentional communication as proposed by Townsend et al. (2017) and Mocha and Burkart (2021). Indeed, we observed that the group members synchronized both their travel velocity and direction when traveling toward freshly burned areas for feeding (Hanzawa et al. 2024). Such coordinated movement can be interpreted as a manifestation of shared intention among group members, which enables CM toward a common foraging goal. This coordination system may be particularly adaptive for species that travel over large distances to exploit distributed food resources repeatedly (Nakagawa 1999; Isbell et al. 1998). However, contact calls had no significant effect on maintaining small differences in velocity with other individuals. This may reflect the activity rhythms of patas monkeys, which alternate between foraging and feeding with continuous movement at varying velocities (Isbell 1998; Isbell et al. 1998).

In summary, our study reveals that both visual monitoring and calling in patas monkeys serve context-dependent roles in group coordination, potentially influenced by sex-specific priorities and social structures. Females primarily use visual monitoring to maintain proximity to their dependent juvenile offspring, whereas the male may engage in visual monitoring as vigilance to protect females as mating partners and their associated food resources. Moreover, our findings suggest that female contact calls function as intentional communication that promotes an increase in the group’s overall travel velocity. By integrating GPS tracking and direct behavioral observations, we highlight the flexible and dynamic nature of multimodal coordination in group-living animals, and offer possible ways in which sex-specific needs and behavioral contexts influence communicative strategies in CM.

Ethics declarations

Ethical approval

All procedures in this study were approved by the Animal Experimentation Committee of Kyoto University in Japan (# 202021) and by the Wildlife Division of the Forestry Commission of Ghana (WD/A.185/VOL. 13/69).

Competing interests

We declare we have no competing interests.

Funding

This study was supported by JSPS KAKENHI grant (20J23285 to Maho Hanzawa) and JSPS KAKENHI grant (19H05591 to Prof. Kaori Kawai, Tokyo University of Foreign Studies).

American Society of Mammalogists (1998) Guidelines for the capture, handling, and care of mammals as approved by the American Society of Mammalogists. J Mammal 74:1416–1431
Averly B, Sridhar VH, Demartsev V, Gall G, Manser M, Strandburg-Peshkin A (2022) Disentangling influence over group speed and direction reveals multiple patterns of influence in moving meerkat groups. Sci Rep 12:13844
Beltran FV, Castellano-Navarro A, Illa MR, Ngakan PO, MacIntosh AJ, Llorente M, Amici F (2020) Play behavior in immature moor macaques (Macaca maura) and Japanese macaques (Macaca fuscata). Amer. J Primatol 82:e23192
Boinski S (1993) Vocal coordination of troop movement among white-faced capuchin monkeys, Cebus capucinus. Amer J Primatol 30:85–100
Bousquet CA, Sumpter DJ, Manser MB (2011) Moving calls: a vocal mechanism underlying quorum decisions in cohesive groups. Proc. R. Soc. B, Biol. Sci 278:1482–1488
Bracken AM, Christensen C, O’Riain MJ, Fehlmann G, Holton MD, Hopkins PW, Fürtbauer I, King AJ (2021) Socioecology explains individual variation in urban space use in response to management in Cape chacma baboons (Papio ursinus). Int J Primatol 43:1159–1176
Brooks M, Bolker B, Kristensen K, Maechler M, Magnusson A, McGillycuddy M (2023) Package ‘glmmtmb’. R Packag Vers 1:7
Byrne RW (2000) How monkeys find their way: Leadership, coordination, and cognitive maps of african baboons. In: Boinski S, Garber PA (eds) On the Move: How and Why Animals Travel in Groups, Univ. Chicago, Chicago, pp 491–518
Calenge C (2006) The package adehabitat for the R software: A tool for the analysis of space and habitat use by animals. Ecol Model 197:516–519
Cheney DL, Seyfarth RM, Palombit R (1996) The function and mechanisms underlying baboon ‘contact’ barks. Anim Behav 52:507–518
Chism J (1986) Development and mother-infant relations among captive patas monkeys. Int J Primatol 7:49–81
Chism C, Rowell TE (1988) The natural history of the patas monkeys. In: Gautier-Hion A, Bourliére F, Gautier JP, Kingdon J (eds) A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge Univ. Press, New York, pp 412–438
Clark CW, Mangel M (1986) The evolutionary advantages of group foraging. Theor Popul Biol 30:45–75
Conradt L, Roper TJ (2005) Consensus decision making in animals. Trends Ecol Evol 20:449–456
Cowlishaw G (1998) The role of vigilance in the survival and reproductive strategies of desert baboons. Behaviour 135:431–452
Davidson JD, Sosna MM, Twomey CR, Sridhar VH, Leblanc SP, Couzin ID (2021) Collective detection based on visual information in animal groups. J R Soc Interface 18:20210142
Demartsev V, Gersick AS, Jensen FH, Thomas M, Roch MA, Manser MB, Strandburg-Peshkin A (2023) Signalling in groups: New tools for the integration of animal communication and collective movement. Methods Ecol Evol 14:1852–1863
D'Eon RG, Delparte D (2005) Effects of radio-collar position and orientation on GPS radio-collar performance, and the implications of PDOP in data screening. J Appl Ecol 42:383–388
Enstam KL, Isbell LA (2002) Comparison of responses to alarm calls by patas (Erythrocebus patas) and vervet (Cercopithecus aethiops) monkeys in relation to habitat structure. Amer J Phys Anthropol 119:3–14
Fischer J, Zinner D (2011) Communication and cognition in primate group movement. Int J Primatol 32:1279–1295
Godfrey SS, Anasri TH, Gardner MG, Farine DR, Bull CM (2014) A contact based social network of lizards is defined by low genetic relatedness among strongly-connected individuals. Anim Behav 97:35–43
Gouzoules S, Gouzoules H (1987) Kinship. In: Smuts BB, Cheney DL, Seyfarth RM, Wrangham RW, Struhsaker TT (eds) Primate Societies, Univ. Chicago, Chicago, pp 299–305
Hall KR (1966) Behaviour and ecology of the wild patas monkey, Erythrocebus patas, in Uganda. J Zool 148:15–87
Hanzawa M, Morimitsu Y, Owusu EH, Suu-Ire RD, Nakagawa N (2004) Rushing for burned food: Why and how does a group of patas monkeys (Erythrocebus patas) reach freshly burned areas? Primates 65:103–113. 10.1007/s10329-023-01113-5
Harcourt AH (1979) Social relationships between adult male and female mountain gorillas in the wild. Anim Behav 27:325–342
Hartig F, Lohse L (2022) DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models (0.4.6). (https://CRAN.R-project.org/package= DHARMa)
Heintz MR, Murray CM, Markham AC, Pusey AE, Lonsdorf EV (2017) The relationship between social play and developmental milestones in wild chimpanzees (Pan troglodytes schweinfurthii). Amer J Primatol 479:e22716
Isbell LA (1998) Diet for a small primate: insectivory and gummivory in the (large) patas monkey (Erythrocebus patas pyrrhonotus). Amer J Primatol 45:381–398
Isbell LA, Pruetz JD, Lewis M, Young TP (1998) Locomotor activity differences between sympatric patas monkeys (Erythrocebus patas) and vervet monkeys (Cercopithecus aethiops): implications for the evolution of long hindlimb length in Homo. Amer J Phys Anthropol 105:199–207
Kappeler PM, van Schaik CP (2002) Evolution of primate social systems. Int J Primatol 23:707–740
Kazahari N, Agetsuma N (2010) Mechanisms determining relationships between feeding group size and foraging success in food patch use by Japanese macaques (Macaca fuscata). Behaviour 147:1481–1500
King AJ, Sueur C (2011) Where next? Group coordination and collective decision making by primates. Int J Primatol 32:1245–1267
Krause J, Krause S, Arlinghaus R, Psorakis I, Roberts S, Rutz C (2013) Reality mining of animal social systems. Trends Ecol Evol 28:541–551
Kummer H (1968) Social organization of hamadryas baboons. Univ. Chicago, Chicago
Laver PN, Kelly MJ (2008) A critical review of home range studies. J Wildl Manag 72:290–298
Lawson GW, Jenik J, Armstrong-Mensah KO (1968) A study of a vegetation catena in Guinea savanna at Mole Game Reserve (Ghana). J Ecol 56:505–522
Liao CC, Magrath RD, Manser MB, Farine DR (2024) The relative contribution of acoustic signals versus movement cues in group coordination and collective decision-making. Philos Trans R Soc B Biol Sci 379:20230184
Lüdecke D, Ben-Shachar MS, Patil I, Waggoner P, Makowski D (2021) Performance: An R package for assessment, comparison and testing of statistical models. J Open Source Softw 6:3139
Main MB, Floyd WW, Vernon CB (1996) Sexual Segregation in Ungulates: New Directions for Research. J Mammal 77:449–461
Makowski D, Ben-Shachar M, Patil I, Lüdecke D (2020) Estimation of Model-Based Predictions, Contrasts and Means. CRAN
Markham AC, Gesquiere LR (2017) Costs and benefits of group living in primates: an energetic perspective. Philos Trans R Soc B Biol Sci 372:20160239. http://dx.doi.org/10.1098/rstb.2016.0239)
Meier VO, Rasa AE, Scheich H (1983) Call system similarity in a ground-leaving social bird and a mammal in the bush habitat. Behav Ecol Sociobiol 12:5–9
Mocha YB, Burkart JM (2021) Intentional communication: solving methodological issues to assigning first-order intentional signalling. Biol Rev 96:903–921
Nakagawa N (1992) Distribution of affiliative behaviors among adult females within a group of wild patas monkeys in a nonmating, nonbirth season. Int J Primatol 13:73–96
Nakagawa N (1999) Differential habitat utilization by patas monkeys (Erythrocebus patas) and tantalus monkeys (Cercopithecus aethiops tantalus) living sympatrically in northern Cameroon. Amer J Primatol 49:243–264
Nakagawa N (2003) Difference in food selection between patas monkeys (Erythrocehus patas) and tantalus monkeys (Cercopithecus aethiops tantalus) in Kala Maloue National Park, Cameroon, in relation to nutrient content. Primates 44:3–11
Neumann C, Zuberbühler K (2016) Vocal correlates of individual sooty mangabey travel speed and direction. PeerJ 4:e2298
Nishikawa M, Suzuki M, Sprague DS (2014) Activity and social factors affect cohesion among individuals in female Japanese macaques: A simultaneous focal-follow study. Amer J Primatol 76:694–703
Papageorgiou D, Farine DR (2020) Shared decision-making allows subordinates to lead when dominants monopolize resources. Sci Adv 6:1–8
Pebesma EJ (2018) Simple features for R: standardized support for spatial vector data. R J 10:439–446
Petit O, Bon R (2010) Decision-making processes: the case of collective movements. Behav Processes 84:635–647
Radford AN (2004) Vocal coordination of group movement by green woodhoopoes (Phoeniculus purpureus). Ethology 110:11–20
Radford AN, Ridley AR (2008) Close calling regulates spacing between foraging competitors in the group-living pied babbler. Anim Behav 75:519–527
Ramos A, Petit O, Longour P, Pasquaretta C, Sueur C (2015) Collective decision making during group movements in European bison, Bison bonasus. Anim Behav 109:149–160
R Core Team (2022) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. (https://www.R-project.org)
Roberts AI, Roberts SGB (2015) Gestural communication and mating tactics in wild chimpanzees. PLoS ONE 10:e0139683
Rowell TE, Olson DK (1983) Alternative mechanisms of social organization in monkeys. Behaviour 86:31–54
Samuni L, Mielke A, Preis A, Crockford C, Wittig RM (2020) Intergroup competition enhances chimpanzee (Pan troglodytes verus) in-group cohesion. Int J Primatol 41:342–362
van Schaik CP (1983) Why are diurnal primates living in groups? Behaviour 87:120–144
Schmitt K, Adu-Nsiah M (1993) The vegetation of Mole national park. Forest Resource Management Project Report No.14. Accra. Forestry Commission of Ghana Wildlife Division, Ghana
Shimada M, Sueur C (2018) Social play among juvenile wild Japanese macaques (Macaca fuscata) strengthens their social bonds. Amer J Primatol 80:e22728
Smith JE, Fichtel C, Holmes RK, Kappeler PM, Van Vugt M, Jaeggi AV (2022) Sex bias in intergroup conflict and collective movements among social mammals: male warriors and female guides. Philos Trans R Soc Lond B Biol Sci 377:20210142
Sperber AL, Werner LM, Kappeler PM, Fichtel C (2017) Grunt to go–Vocal coordination of group movements in redfronted lemurs. Ethology 123:894–905
Strandburg-Peshkin A, Farine DR, Couzin ID, Crofoot MC (2015) Shared decision-making drives collective movement in wild baboons. Science 348:1358–1361
Sugiura H, Shimooka Y, Tsuji Y (2014) Japanese macaques depend not only on neighbors but also on more distant members for group cohesion. Ethology 120:21–31
Sumpter DJT (2010) Collective animal behaviour. Princeton Univ. Press, Princeton, NJ
Townsend SW, Koski SE, Byrne RW, Slocombe KE, Bickel B, Boeckle M, Goncalves IB, Burkart JM, Flower T, Gaunet F, Glock HJ, Gruber T, Jansen DAWAM, Jansen K, Linke A, Miklósi Á, Moore R, van Schaik CP, Stoll S, Vail A, Waller BM, Wild M, Zuberbühler K, Manser MB (2017) Exorcising G rice's ghost: An empirical approach to studying intentional communication in animals. Biol Rev 92:1427–1433
Turchin P, Kareiva P (1989) Aggregation in Aphis varians: an effective strategy for reducing predation risk. Ecology 70:1008–1016
Walker RH, King AJ, McNutt JW, Jordan NR (2017) Sneeze to leave: African wild dogs (Lycaon pictus) use variable quorum thresholds facilitated by sneezes in collective decisions. Proc. R. Soc. B., Biol. Sci 284:20170347
Yan X, Wang X, Zhao Y, Zhu Q, Yang L, Li Z (2024) Collective decision-making and spatial patterns in orientation of an endemic ungulate on the Tibetan Plateau. Curr Zool 70:45–58
Watts DP (1992) Social relationships of immigrant and resident female mountain gorillas. I. Male-female relationships. Amer J Primatol 28:159–181
Williams JM, Pusey AE, Carlis JV, Farm BP, Goodall J (2002) Female competition and male territorial behaviour influence female chimpanzees’ ranging patterns. Anim Behav 63:347–360
Worton BJ (1989) Kernel methods for estimating the utilization distribution in home-range studies. Ecology 70:164–168
Wrangham RW (1980) An ecological model of female-bonded primate groups. Behaviour 75:262–300

Tables 1 to 3 are available in the Supplementary Files section

No competing interests reported.

Download PDF

Editorial decision: Revision requested
06 Aug, 2025
Editor assigned by journal
06 Aug, 2025
Submission checks completed at journal
05 Aug, 2025
First submitted to journal
25 Jul, 2025

You are reading this latest preprint version

How do individual behaviors based on visual and auditory cues facilitate spatiotemporal coordination in collective movement of patas monkeys (Erythrocebus patas)?

Status:

Version 1

Abstract

Figures

Significance Statement

Introduction

Methods

Results

Discussion

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1