Relations between spatial distribution, social affiliations and dominance hierarchy in a semi-free Mandrill population

Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual’s spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates.

Our methodological approach solely involved observations. Animals were not handled, and no invasive experiments were carried out on the mandrills. Animals were already accustomed to human presence in their enclosure. Our protocol followed the ethical guidelines of the CNRS (Centre National de Recherche Scientifique) and the recommendations of the Gabonese government. This study was conducted with the approval of the International Medical Research Center (CIRMF) scientific committee in Gabon via a research agreement (nu045/2011/CNRS). All occurrences of injuries or illness in the observed animals were reported to veterinary staff at the CIRMF primatological center. The study was comprised of 39 mandrills from a group of 75 individuals born in captivity and living in a large, naturally rainforested enclosure (6.5 ha), at the CIRMF in Franceville, Gabon. Mandrills were free to forage in the enclosure and were supplemented by a provision of homemade soya-cake and local seasonal fruits twice a day. Water was available ad libitum. Juveniles (<5 years old) were excluded from the study population because they spent all their time with their mothers and because of the instability of their relationships with other group members (Sueur et al., 2011d). Remaining individuals were aged between 5 and 26 years (mean = 10.42; SD = 4.09) and comprised of 18 females and 21 males. Dates of birth and matrilineage were recorded for all individuals. Kinship was computed from matrilineage by recording motherhood. All subjects were identified using morphological differences and/or ear tags. Data was collected from April to June 2012. One of the researchers (E.C.) observed the group 6 h per day (09:00–12:00 and 15:00–18:00) from a tower located behind the feeding zone. Observations were recorded in front of the feeding zone in a 30 × 30 m area covered with grass and small trees allowing good visibility (see Figure ​Figure1).1). At the beginning of each observation period (i.e., a.m. and p.m.), a food supplement was placed in a closed section, visible but not accessible to the mandrills during the whole observation period. At the end of each observation period (i.e., after 12:00 and 18:00), the door giving access to the food supplement was opened. This situation resulted in an artificial food patch, an advantageous spatial position for which the Mandrills could compete for. We used instantaneous scan sampling (Altmann, 1974) with a 15 min sampling frequency (total of 26 scans per day) to record individual spatial positions within the observation area. Individuals observed during a scan were positioned on a map representing the 30 × 30 m area in front of the feeding zone door using 1 m spaced vertical and horizontal grid lines (Figure ​(Figure2).2). A total of 631 scans were completed, representing 157.75 h of observations. All individuals were not observed at each scan (mean frequency of scans = 145.2; SD = 73.35). Photograph of the observation area from the tower where observations were realized. Credit Chailleux E. Schema used to record individuals' spatial position. The scale of this schema is 1 m2. Circles, ellipses, and polygons represent trees and bushes where the mandrill could get covered. The line on the upper side represents the beginning of the forest area. The feeding zone is contained to X = 12–15 and Y = 0–4 and the door is represented by the polygon in X = 5–6 and Y = 3–4. The two circular buffers are characterized by the 10 m (blue) and the 20 m (red) areas used to calculate frequencies of observation. When calculating the mean number of observed individuals by observation period (e.g., 9:00, 9:15), we noticed that more individuals were observed during the afternoon (i.e., 15:00–18:00) compared to the morning (i.e., 09:00–12:00; see Figure ​Figure3).3). In practice, the food was not always made available by the CIRMF at 12:00 but systematically at 18:00. Therefore, mandrills had possibly learned this pattern and food competition was probably more important during the afternoon. Consequently, we used only observations from the afternoon period to calculate spatial positions of individuals within different distances of the feeding zone (see Section Hierarchal Dominance). Histogram of the average number of individuals observed during each period. 12:00 is considered in the morning period (am) in this figure. The bar plot was realized with the ggplot2 package (Wickham, 2009). First, we calculate the Euclidian distance (Legendre and Legendre, 2012) between the center of the feeding zone door and the Cartesian coordinates of all observations (Figure ​(Figure2).2). We used the door as the centroid of the food patch because this location was the most coveted since it is the only access to the feeding zone. Then, the frequency of observations within 10 m and over 20 m distances of the food patch were computed from the Euclidian distances. We did not use observations between 10 and 20 m because we wanted to contrast spatial observations in proximity and distant from the feeding zone door. We used a 10 m scale in order to get sufficient observations for statistical analysis. For observations within 10 m of the feeding door, we calculated the relative frequencies to adjust for the number of scans during which individuals were observed. For observations over 20 m of the feeding door, individuals that were out of sight (i.e., in the forest area) were included in the measure. Two variables were created: (1) the relative frequency of observation within 10 m of the feeding door (F10M) and (2) the frequency of observations over 20 m of the feeding door (F20M). Agonistic interactions were recorded ad libitum during both observation periods (i.e., a.m. and p.m.). According to previous studies (Setchell, 1999), a list of 13 behaviors was chosen and described in a catalog. Actor, receivers, behavior, date, and time were recorded for each aggressive event. When interactions included a series of behaviors, only the last behavior (causing the submission of the other mandrill) was recorded. Also, only unidirectional aggression with a clear issue was used to calculate the hierarchy. Since dominance hierarchy is only based on dyadic interactions, interactions between more than two individuals were discarded. Linearity of the hierarchy was measured with de Vries' h' index (de Vries, 1995). Individual dominance indices were calculated with de Vries' modification of David's score (MDS) (David, 1987; de Vries et al., 2006). These measures were calculated with SOCPROG 2.4 (Whitehead, 2009). To measure the social network of affiliative relationship (i.e., affiliative network), we used spatial proximity (i.e., association measures) between individuals as a proxy of social preferences in our group (Whitehead, 2008). Two individuals (i.e., a dyad) were considered to be in association when they were seen within a distance of 1 m from each other during a scan. We assumed that a distance close to the average body length of adult mandrills represented a situation where touch interactions (e.g., grooming) may take place. The average body length of adult mandrills is 80 cm for males and 60 cm for females (Wickings and Dixson, 1992). We were, however, limited to 1 m because it was the smallest distance measured from the previous spatial observations (the data were already collected when the analyses were planned). For each pair of individuals, we calculated a half-weight association index (HWI) with the number of associations. Since we did not observe the whole group at each scan, all individuals were not observed at the same total frequency. HWI allow to control for the non-observation of all group members at each scan (Whitehead, 2008). Then, we tested if individuals associated in a non-random way by permuting associations within each scan (H0 = no preferred or avoided relationship for any dyad; Whitehead et al., 2005). We used the coefficient of variation of association indices as the test statistic for significance level. To measure if our population could be usefully divided into subgroups, we used the modularity test of Newman (Newman, 2004, 2006) which measures the difference between the proportion of the total associations in the subgroups and the summed associations of the whole group. Eigenvalues were used to determine the level of certainty through which individuals were assigned to subgroups. These three measures were computed with SOCPROG 2.6 (Whitehead, 2009). Finally, we created a second association matrix where every individual observed within 5 m of the feeding zone door in a same scan were considered associated (i.e., co-occurrence network). We used HWI to control for non-observation of group members. We used a smaller radius than for spatial proximity to the feeding zone door (5 m instead of 10 m) because we assumed that competition would be stronger in a limited space and therefore co-occurrence would indicate tolerance among individuals. To evaluate homoscedasticity assumptions, we used Spread-Location plots of standardized residuals against fitted values, Bartlett test, and the Breusch-Pagan test (Greene, 2003; Scherrer, 2007). We used square root transformations on the relative frequency within 10 m (SRF10M) in order to obtain homoscedasticity and reduce the skewness of the distribution. We had two missing values for the variable age. We replaced those values by the means of their respective age group (e.g., sub adults' mean ages = 6.8). We had one missing data for MDS and removed the individual from further analysis. All significance levels were obtained through permutations because our observations did not represent a sample from a larger statistical population with a known distribution and permutations allow parametric statistical methods to be used when distributional assumptions are not satisfied (Legendre and Legendre, 2012). We used 10,000 permutations in each analysis. First, we aimed to test how hierarchy is structured by age and sex by testing bivariate relationships between hierarchy, sex, and age. Relationship between dominance rank (MDS) and sex was tested using a student test (one-tailed). Relationships between dominance rank and age were tested on the full sample and stratified by sex using Pearson correlation tests (one-tailed). We used one-tailed tests because our hypothesis was that males were more dominant than females and there is a positive correlation between age and dominance ranking. Second, we tested the relationship between the explanatory variables (1) age, (2) sex, (3) dominance rank, and (4) matrilineage (i.e., kinship) and affiliative associations. Age, dominance rank, and sex variables were first transformed into three distance matrices. Distances for age and dominance ranking were calculated with Euclidian distance and sex was calculated with a binary coefficient (same sex = 1; different sex = 0). We then used a multiple regression quadratic assignment procedure (MRQAP) test (Whitehead, 2008) with the “double-semi-partialing” technique of Dekker et al. (2007). This analysis aimed to better understand how social relationships are distributed according to animal characteristics. To test our first research question—does dominance hierarchy explain observed proximity or distance from a food patch?—we used Pearson correlations (one-tailed) between dominance rank and frequency of observations within distances of the feeding door (SRF10M and F20M). To test our second research question—do affiliative associations also explain observed proximity or distance from a food patch?—we used partial regression to test the relationships between SRF10M or F20M as outcomes, and dominance rank and subgroups (found with modularity method as described above) as explanatory variables. Finally, to test our third hypothesis—do rank differences in the group hierarchy explain being co-observed in proximity of a food patch?—we tested the correlation between the co-occurrence network and the dominance distance matrix while controlling for kinship, age, and sex with the MRQAP test using the “double-semi-partialing” technique. Correlation were run between the co-occurrence network and the affiliative network (recalculated without observation within 5 m of the feeding zone) with a Mantel test to see if the co-occurrence within 5 m of the feeding door was related to the observed associations in the whole area. All statistics were performed in R 3.1.2. (CRAN, 2014) and SOCPROG 2.6. (Whitehead, 2009). We used Bartlett-test (stats library) and ncvTest (car package) functions for Bartlett and Breusch-Pagan tests, corPerm3 and t.perm (available from Pierre Legendre website) functions for bivariate relationships, mantel.test (ape package) function for mantel test, varpart and rda (vegan package) functions for partial regressions (Paradis et al., 2004; Fox and Weisberg, 2010; Legendre, 2015; Oksanen et al., 2016). MRQAP tests were performed in SOCPROG 2.6.

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• naud, alexandre
• chailleux, eloise
• kestens, yan
• bret, céline
• desjardins, dominic
• petit, odile
• ngoubangoye, barthélémy
• sueur, cédric