Shared space use and avoidance among groups of wild non-territorial Assamese macaques

Shared space use and avoidance among groups of wild non-territorial Assamese macaques | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Shared space use and avoidance among groups of wild non-territorial Assamese macaques Sofya Dolotovskaya, Suthirote Meesawat, Suchinda Malaivijitnond, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8432416/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Between-group competition in territorial taxa is evident in patrolling and avoidance behaviors. In non-territorial animals, signs of competition are more subtle, and little is known about how neighbors use their shared space. We investigated space use in four groups of wild, non-territorial Assamese macaques ( Macaca assamensis ). Using locational data collected over six years, we quantified group ranging patterns to identify factors influencing home range size and daily travel distances, and investigated spatial relationships among neighboring groups by examining the patterns of shared use of space and sleeping trees. We found that daily travel distances were positively affected by group size and day length, but not fruit availability, while home range size was not influenced by any of the examined variables. Despite considerable home range overlap between groups, we found evidence for spatial and temporal landscape partitioning. Groups used their core areas more exclusively than entire home ranges and preferred to sleep within the core areas. Additionally, home ranges overlapped less when assessed over shorter time scale (annual vs. 3-month intervals). The analysis of spatial dynamics between simultaneously tracked groups demonstrated that patterns of avoidance or attraction were influenced by demographic history and possibly by the distribution of food resources. These findings show that space use in Assamese macaques is influenced by between-group competition and feeding needs. Our study suggests that even in the absence of territoriality, non-territorial species can maintain some exclusivity in their space use via avoidance behaviors to reduce competition with neighbors. Between-group competition group size home range overlap territoriality space partitioning macaques Figures Figure 1 Figure 2 Figure 2 Figure 3 Figure 3 Figure 4 Figure 5 Figure 5 Figure 6 Figure 6 Figure 7 Figure 8 Significance Statement In non-territorial animals, home ranges are shared with neighbors, leading to increased between-group competition. To investigate how this competition affects space use, we examined ranging patterns and spatial relationships between neighbors in four groups of wild Assamese macaques. Despite considerable home range overlap, groups used spatial and temporal partitioning to maintain some exclusivity in their space use. This suggests that even in the absence of territorial behaviors, between-group competition can be reduced by avoiding neighbors. Introduction Space use in group-living animals is influenced by both resource availability and patterns of within-group and between-group competition (Brown and Orians 1970 ; Macdonald 1983 ; Morrell and Kokko 2005; Maher and Lott 2000). In many territorial species, where residents aggressively defend parts of their home range and the limited resources therein (Brown 1964 ; Börger et al. 2008), space use is mainly determined by between-group contest competition, with bigger groups gaining access over larger areas (e.g., African lions, Panthera leo : Mosser and Packer 2009; blue monkeys, Cercopithecus mitis : Roth and Cords 2016; dwarf mongooses, Helogale parvula: Arbon et al. 2024 ). However, neither group size nor home range size can grow indefinitely, as both are constrained by various factors. Benefits of larger group size can be counter-balanced or even outweighed by increasing within-group feeding competition and resulting increases in foraging effort and daily travel length (McNab 1963 ; Carbone et al. 2005 ), as shown in a variety of vertebrates (e.g., carnivores: Gittleman and Harvey 1982 ; Wrangham et al. 1993 ; Arbon et al. 2024 ; primates: Wrangham et al. 1993 ; Majolo et al. 2008; fish: Grand and Dill 1999 ), or in longer feeding times and reduced food quality (Schülke and Ostner 2012 ). At some point, energy spent exceeds energy obtained, thus constraining both maximum group size and home range size – a relationship formalized in the ecological constraints model (Chapman et al. 1995 ; Chapman and Chapman, 2000a ; 2000b ). Acting together, within- and between-group feeding competition can promote intermediate groups with small home ranges that can be exploited with short day journeys if food resources are limited (Markham et al. 2015 ; Teichroeb et al. 2022 ; Stevenson and Castellanos 2001). Beyond feeding competition, social factors may affect the costs and benefits of living in larger groups. Group coordination becomes increasingly difficult the more members are involved in decision making, which decreases movement speed and may result in shorter daily travel distances and smaller home ranges in larger groups relative to intermediate-sized groups (e.g., guinea fowls, Acryllium vulturinum : Papageorgiou and Farine 2020). Furthermore, cooperative home range defense may become less efficient with the higher number of individuals of the larger/dominant sex, resulting from the 'collective action problem' (Willems et al. 2013 ). With weaker defenses, the proportion of home range overlapping with neighboring groups increases (Pearce et al. 2013 ; Willems et al. 2013 ), leading to increased between-group competition and diminishing foraging returns in overlap areas (Grant et al. 1992 ; Jetz et al. 2004 ). To manage competition with neighbors, animals may use different strategies. First, individuals might actively defend their home range or parts of it from conspecifics, preventing their intrusion, which leads to territoriality (Börger et al. 2008; Burt 1943 ; Brown and Orians 1970 ; see also Maher and Lott (1995) for a review of definitions of territoriality). Territory defense, however, carries costs that increase with territory size, because more time and energy are required to patrol it and expel intruders (Schoener 1987 ; Grant et al. 1992 ). The basic economic approach suggests that the emergence of territoriality is ultimately dependent on the 'economic defendability' of resources, i.e., it will only evolve when limited resources within a sufficiently small area can be economically defended from conspecifics (Carpenter and MacMillen 1976 ; Jensen et al. 2005 ; Maher and Lott 2000; Schoener 1987 ). When this is not feasible, home ranges are left undefended, and varying proportions of home ranges, including resources they contain, are shared with neighbors. This, in turn, can lead to loss of resources to neighbors (Grant et al. 1992 ; Jetz et al. 2004 ) and to increased risks of injuries from fighting with competitors over resources (Wrangham et al. 2007 ; Sillero-Zubiri and Macdonald 1998 ). To mitigate these risks, animals with undefended home ranges might actively avoid their neighbors by partitioning a shared landscape. Partitioning may be spatial, with certain parts of the home range used more exclusively, and temporal, with animals avoiding other groups while moving within their home ranges. One mechanism of spatial partitioning is to maintain core areas (i.e., most intensively visited areas within the home range) with largely exclusive use by one group, as shown, e.g., in primates, rodents, and lizards (Seiler et al. 2017 ; Wartmann et al. 2014 ; Pierro et al. 2008 ; Kerr and Bull 2006). Another mechanism is to avoid the areas of overlap, as shown, e.g., in wolves, primates, and birds (Wrangham et al. 2007 ; Sillero-Zubiri and Macdonald 1998 ; Mech 1977 ; Gibson and Koenig 2012; Wakefield et al. 2013 ). Even when all parts of a home range overlap extensively with the home ranges of neighboring groups, animals may still use temporal landscape partitioning, where different groups actively avoid each other and use the same area sequentially, so that the ranges overlap less when assessed over shorter time scales (e.g., yellow baboons, Papio cynocephalus (Markham et al. 2013 ); gray-cheeked mangabey, Cercocebus albiqena (Waser 1976 )). Finally, in some cases,, if crucial resources are over-abundant, home ranges of neighboring groups may overlap extensively not because of high defense costs, but because of low defense benefits (Carpenter and MacMillen 1976 ; Mcloughlin et al. 2000 ; Ohrndorf et al. 2025 ; Maher and Lott 2000). One of the critical resources for which neighboring groups might compete are safe sleeping sites. As animals usually do not choose sleeping trees randomly and show sleeping-site preferences, the availability of suitable sleeping sites can influence space use and social interactions, as shown in various species of mammals and birds (Day and Elwood 1999; Lutermann et al. 2010 ; Kalko et al. 2006 ; Du Plessis 1992; Doncaster and Woodroffe 1993). In non-territorial animals, sleeping sites in overlapping areas may be shared by neighboring groups, simultaneously or successively. While in some taxa, several groups may share sleeping sites on the same night (vulturine guineafowl: Papageorgiou et al. 2019 ; olive baboons, Papio anubis : Loftus et al. 2024 ), in other taxa, groups may maintain some exclusivity in the use of sleeping sites by preference for sleeping sites located in non-overlapping parts of home ranges or by avoiding sleeping near other groups (e.g., in colobus monkeys: Teichroeb et al. 2012 ; Von Hippel 1998). As sharing of sleeping trees may affect competition over nearby food resources and exposure to predators or parasites (Loftus et al. 2024 ; Barclay 1988 ; Chapman et al. 1989 ), patterns of the shared use constitute an important part of inter-group dynamics. In this study, we investigated space use in a non-territorial species with large home range overlap between neighboring groups, Assamese macaques, Macaca assamensis , living in their natural environment in Phu Khieo Wildlife Sanctuary in Thailand. Assamese macaques live in multimale-multifemale groups characterized by female philopatry and male dispersal (Heesen et al. 2013 ; Schülke et al. 2011 ). Home range overlap between neighboring groups is large, and sleeping trees are shared by neighboring groups (Schülke and Ostner, unpublished data), but patterns of shared space use have not yet been quantified. In an earlier study on changes in space use in one group over multiple years, home range size increased with decreasing rainfall and with an interaction of food abundance and distribution (Richter et al. 2016 ). Controlling for these ecological factors, the number of males, but not the total group size, positively affected home range size (Richter et al. 2016 ). Here, we extended this earlier analysis to four groups, studied over six years, to additionally examine shared use of space and of sleeping sites by neighboring groups. We aimed to: (1) quantify group ranging patterns, focusing on identifying demographic and ecological factors influencing home range size and daily travel distances; and (2) investigate spatial relationships among neighboring groups by examining the extent and patterns of shared space use. To address objective 1, we analyzed the effects of demographic (total group size, male group size) and ecological (fruit availability, rainfall, day length) factors on home range size and daily travel distances. In addition, we calculated an index of economic defendability, introduced and tested on primates by Mitani and Rodman (1979), that uses the ratio of daily travel distances to the size of the home range to assess the ability of a group to monitor the boundaries of its home range in order to defend it. To address objective 2, we first compared annual home range and core area overlap between neighboring groups to assess spatial partitioning and test whether core areas were more exclusive. We then calculated home range overlap at two temporal scales: annual and 3-month periods, to assess temporal partitioning and to test whether overlap decreased when assessed over shorter intervals. While these “static” measures (sensu Doncaster 1990 ) reflect the extent of shared space, they do not capture simultaneous movements and the nature of spacing behavior (i.e. avoidance, attraction, or neutrality) between groups. To examine these "dynamic" interactions, we compared the observed encounter rates between groups with the expected rates if groups moved independently from each other. Observed encounter rates higher than expected would indicate attraction, whereas lower rates suggest avoidance. Finally, to gain further insight into shared resource use, we investigated the degree of exclusivity and re-use of sleeping trees. Methods Study site and study groups This study is part of a long-term research project on a population of fully habituated Assamese macaques living in their natural environment at Phu Khieo Wildlife Sanctuary in northeastern Thailand (PKWS, 16°050 −350 N, 101°200 −550 E). The sanctuary is part of the > 6500 km² protected forest of the Western Isaan Forest Complex (Borries et al. 2002). The climate is characterized by a cold dry season from November through mid‐March and a warm rainy season with peak precipitation in May and September (Richter et al. 2016). The study population inhabits hill evergreen forest with bamboo stands and breeds seasonally, with a mating season spanning from October to February and births spread from March to August (Fürtbauer et al. 2010; Shivani et al. 2025). This study is based on data collected on four groups from October 2013 until September 2019, i.e., the years following the previous study (Richter et al. 2016). Each study group was composed of adult females, adult males, and immatures, with a total group size between 20 and 86 animals, with fluctuations resulting from male immi- and emigration, births, deaths, and group splits. Groups Mst, Sst, and Mot existed since the beginning of the study period. Group Sot was established in May 2014 after splitting off from group Mot. Spatial data The study groups were followed on average 9 days per month (range: 1-23 days) from sleeping tree to sleeping tree by various observers. The monkeys emerged from sleeping trees on average at 05:59 (range: 04:50 - 07:37) and retired to sleeping trees on average at 17:08 (range: 15:00 - 18:40). GPS coordinates were recorded for the sleeping trees and, as part of behavioral data collection, at the beginning and at the end of each 30-min (until October 2014) or 40-min (from October 2014) focal sampling session (GPS device: Garmin GPSMAP 64s). When multiple observers followed different animals in the same group, we averaged coordinates with timestamp differences of less than 10 min. This resulted in an average of 28 (range 2-57) GPS points per day/group. The number of GPS points varied because the number of animals followed on a given day differed, not all protocols lasted 30 or 40 min (e.g., focal animal was out of sight), and sleeping tree coordinates were sometimes missing (i.e., if the group was lost during the day). It was not possible to record data blind because our study involved focal animals in the field. Ecological factors Climate data were recorded throughout the study period. Precipitation data were taken daily using a HOBO Event data logger. At the middle of each month, we assessed fruit availability based on phenological scores from a sample of more than 650 macaque food trees and tree species abundance scores from 21 ha (0.21 km²) of botanical plots and calculated a monthly fruit availability index (see details in Anzà et al. 2025). Daily day length data was downloaded from www.timeanddate.com for Bangkok, as it was the closest location for which data were available (situated about 320 km SSW of the study area). Mean monthly day length varied between 11 h 20 min (December) and 12 h 55 min (June). Demographic factors The presence or absence of every individual was recorded every day. Group size was calculated from the total group size excluding unweaned infants up to the age of 1 year as they are not independent foragers yet. This measure of group size varied between 17 and 78 individuals; the number of resident males varied between 1 and 14. Average group size and number of adult males per month and per 3-month intervals, used for statistical analysis (below), were calculated from these daily counts. Home range sizes and site fidelity We estimated the home range and core areas of each group using the fixed kernel density method (Erran Seaman and Powell 1996) in the R package adehabitatHR (Calenge 2006). We chose this technique because it is less sensitive to outliers and to differences in sampling effort than minimum convex polygons and is more suitable for comparisons between groups (Börger et al. 2006). We defined home ranges as the area within the 95% fixed kernel contour and the core areas as the are within the 50% fixed kernel contour (Asensio et al. 2012; Holzmann et al. 2012). To avoid oversmoothing the data, we first selected the lowest smoothing factor h that did not create discontinuity in the 95% isopleth, except for gaps already present in the corresponding isopleth when using the reference smoothing factor. As the lowest h was equal to reference h , we continued the analysis with the reference h . Annual home ranges were calculated from October (beginning of mating season) until September the following year (mean number of GPS fixes per year/group = 2575, range = 770 - 4530). These home ranges were then used to draw maps and calculate overlaps in QGIS 3.28 (QGIS Development Team, 2022). To assess site fidelity (home range stability over the years), we calculated home range overlap between years for each group in QGIS 3.28, defined as the percentage of an annual home range area (95% kernel estimates) which was used in the previous year. Daily travel distance We calculated daily travel distances as the sum of distances between consecutive GPS locations. We used only days with complete observations (from sleeping tree to sleeping tree) and omitted days with time gaps >3 h, resulting in 1134 days in total (mean = 283.5 days per group). Predictors of home range size and daily travel length To investigate which factors influenced the home range size, we calculated 95% kernel home ranges over 3-month intervals. This interval was chosen because it was the shortest interval providing at least 100 GPS fixes for most group-intervals. We used 100 GPS fixes as a minimum sample size because the 95% kernel home range size reached asymptote around 100 fixes; moreover, 100 relocations were recommended as a minimum sample size adequately representing home range size for spread data (spanning over at least 5 weeks) (Jacobson et al. 2024). After excluding 3-month blocks which had < 100 GPS points, the sample size was 72 3-month blocks, with a mean of 703 GPS points per 3-month block/group (range = 116-1400). We then used a Generalized Linear Mixed Model (GLMM; Baayen 2008) with the size of 3-month home ranges as response variable and mean group size, mean fruit availability index, and the mean amount of rainfall calculated for a given 3-month period as predictor variables. To investigate potential non-linear relationship between home range size and number of males, we additionally included squared group size as a predictor variable. To account for repeated observations, we used group identity as a random effect. Prior to fitting the model, all predictors were z-transformed to a mean of zero and a standard deviation of one to make model convergence more likely. To rule out collinearity, we checked Variance Inflation Factors (VIFs (Quinn and Keough 2002)) using R package car (version 3.1-3). The original model also included the mean number of resident males as a response variable. However, as this variable was strongly correlated with the group size, and VIFs indicated problematic levels of collinearity (VIF = 6 for both variables), the number of males was excluded from the analysis. The assumptions of normality and homogeneity of residuals were checked and met, and the model was stable for all estimates. To test the effect of the individual predictors, we applied likelihood ratio tests using R function drop1. We ran the model using R package lme4 version 1.1-36 (Bates et al. 2015). To identify ecological and demographic factors affecting daily travel distances, we used a Generalized Linear Mixed Model (GLMM; Baayen 2008) with mean monthly daily travel distance as response variable. We only included months with at least 7 data points, resulting in a sample size of 82 months. As predictor variables, we included the mean monthly group size, monthly fruit availability index, mean monthly day length, and the amount of rainfall per month (mean: 100.1 mm, range: 0 - 282.4 mm). Group identity was used as a random effect. The model was fit and tested in the same way as the model described above. Home range and core area overlap between neighboring groups To compare overlap between annual home ranges (95% kernel) and core areas (50%) of neighboring groups, we calculated for each group the percentage of the respective group’s annual home range (or core area) overlapped by the home ranges (or core areas) of neighboring habituated groups in QGIS 3.28 (QGIS Development Team, 2022). We included only years for which data for all four groups were available, which included October to September in 2014-2015, 2015-2016, and 2016-2017. To assess the overlap of home ranges and core areas on a shorter time scale, we followed the same procedure using 3 months instead of full years and including only 3-months intervals with ≥100 GPS points (Mot, Mst: 23 3-month intervals, Sot: 10, Sst: 18). Defendability index To assess the economic defendability of the home ranges, we calculated the D-index (Mitani and Rodman 1979), which is specified as the ratio of the average daily travel length to the diameter of the (idealized) home range. We calculated D-index for each study group on both time scales: annually and 3-monthly. D-index was calculated as follows: DI = d/ , where d = mean daily travel distance (km) in a given time unit and A = the area of the annual home range (km 2 ) for that time unit. Between-group dynamics To investigate how neighboring groups move throughout their home ranges relative to each other, we examined whether groups were in proximity to one another more or less often than expected by chance. As there were no occasions when all four groups were followed on the same day, we examined pairwise spatial relationships between two groups. We first selected the days when any two groups were followed and when both groups had at least 10 GPS points, resulting in the following sample sizes for groups dyads: Mst/Mot: 89 days; Mst/Sst: 37 days; Mot/Sot: 12 days; Sst/Sot: 16 days; Mst/Sot: 9 days; Mot/Sst: 3 days. We then tested for attraction and avoidance within each dyad using MoveMine, a program for mining movement databases (Li et al. 2013, https://faculty.ist.psu.edu/jessieli/MoveMine/). In this analysis, the observed rates at which two groups encountered each other were compared to rates that would be expected to occur if groups moved independently through their home ranges, generated for each dyad by repeatedly permuting the locations in the movement sequence of one group (1000 permutations). The statistical significance of the observed number of encounters was obtained by comparing the observed number to the tails of the null distribution. As a threshold for what constitutes an encounter we first used 50 m, as this was a minimum group spread shown in an earlier study (Heesen et al. 2015). To confirm robustness of our findings, we additionally considered proximity thresholds of 100 m, 150 m, and 200 m, which are distances over which groups can still hear each other. Sleeping tree usage To quantify the usage of sleeping trees and the extent to which they are shared between groups, we mapped the locations of 85 sleeping trees used in the study period onto the 95% kernel home ranges and the 50% kernel core areas calculated for all study years combined and examined the frequency of use of the trees by all study groups. To test whether sleeping trees are concentrated in core areas of the home ranges, we compared the observed and expected numbers of sleeping trees in the core area vs. in the rest of the 95% kernel home range using Fisher’s exact tests (two-tailed), for each group separately. We calculated expected values under the null hypothesis of sleeping trees being evenly distributed across the home ranges, taking into account the size of each area. To test whether monkeys preferred to sleep in trees located inside their core areas, we conducted a similar analysis, comparing the observed number of nights spent in the core area vs. in the rest of the home range with the numbers expected if nights were distributed evenly throughout the home range, for each group separately. In total, we analyzed 2011 group-nights. Results Home range sizes and site fidelity The size of an annual home range (95% kernel) varied between 266 and 848 ha (mean = 463 ha), the size of an annual core areas varied between 73 and 205 ha (mean = 128 ha) (Table 1). The annual home ranges were stable in location, with mean overlap between the ranges for consecutive years of 87% for Mot, 81% for Mst, 80% for Sot, and 77% for Sst (Table 1, Fig. 1). The most prominent shift of the home range location occurred for Sot between 2014/2015 and 2015/2016, after Sot split from Mot in May 2014; the largest annual home ranges of all (848 ha) was observed for Sot in the same year. Table 1 Yearly home range (95% kernel) and core area (50% kernel) sizes for each group in ha, and the annual overlap of home ranges (percentage of yearly 95% kernel home range area used in the previous year) Mot Mst Sot Sst Year Home range size (ha) Core area size (ha) Overlap with previous year (%) Home range size (ha) Core area size (ha) Overlap with previous year (%) Home range size (ha) Core area size (ha) Overlap with previous year (%) Home range size (ha) Core area size (ha) Overlap with previous year (%) 2013/2014 540.4 173.6 434.9 108.1 - - - - 2014/2015 632.6 156.1 78.0 412.8 93.0 75.9 848.1 204.5 358.2 109.5 2015/2016 607.1 185.0 87.5 523.0 131.4 70.3 512.0 153.1 83.0 380.7 96.9 77.6 2016/2017 567.0 180.7 92.5 408.7 113.0 85.4 444.7 110.6 76.5 266.1 72.7 95.1 2017/2018 557.4 163.9 86.5 435.4 115.6 85.6 - - 355.7 107.4 62.6 2018/2019 371.8 83.7 89.8 327.9 79.9 89.8 - - 357.0 76.0 72.0 Predictors of home range size and daily travel length The size of a 3-month home range (95% kernel) varied between 116 and 741 ha (mean = 368 ha). None of the predictors included in the GLMM model (group size, squared group size, fruit availability index, amount of rainfall) influenced the size of 3-month home ranges (Table 2). As the number of males was strongly correlated with the groups size, we could not include both these variables in the model. Multiple regression models ran for each group separately (using the same set of predictors as in the GLMM) did not reveal consistent associations either; there was a trend for non-linear associations between home range size and group size, U-shaped for Mot and Sst and bell-shaped for Sot (Fig. 2a), as well a trend for a U-shaped non-linear association between home range size and number of males for Mot and Sst (Fig. 2b), although none of these associations reached statistical significance. Table 2 Estimates of factors influencing home range sizes based on a GLMM and standardized (z-transformed) predictor variables. Group size excludes dependent infants Term Estimate SE z-value p-value Intercept 374.4 34.3 10.9 Group size 5.9 26.7 0.2 0.83 Group size 2 -5.2 12.0 -0.4 0.67 Rainfall 8.8 17.4 0.5 0.61 Fruit availability -1.4 17.3 -0.1 0.94 Mean distance traveled per day was 1778 m (range = 474-6949 m). The mean monthly daily travel distance was significantly influenced by group size and daylength, increasing in months with higher average group size (an increase of 4.7 m per group member) and longer average daylength (an increase of 3.9 m per minute) (Table 3, Fig. 3). Table 3 Estimates of factors influencing mean monthly daily travel distance based on a GLMM and standardized (z-transformed) predictor variables. Group size excludes dependent infants Term Estimate SE z-value p-value Intercept 1738.6 27.3 63.6 Group size 58.5 28.2 2.1 0.045 Daylength 129.1 37.6 3.4 0.0009 Fruit availability -41.0 29.7 -1.4 0.17 Rainfall 12.7 38.3 0.3 0.74 Defendability index The annual D-index, i.e., the ratio of average daily travel distances to the diameter of the home range, was less than 1 for all groups in all years (mean = 0.75, range 0.58-0.93; Table S1, Electronic Supplementary Material). The mean D-index for 3-month intervals was slightly higher (mean = 0.84, range 0.47-1.2), in some cases exceeding 1 (Table S1). Spatial partitioning The annual core areas of neighboring groups overlapped less than the annual home ranges in all groups in all years (Fig. 4, Fig. 5; Table S2, Electronic Supplementary Material). While the mean per cent of home range shared with other groups was 69% (range 30 - 100%), the mean per cent of core area shared with other groups was only 30% (range 11-76%), driven to some degree by very low values for Sst. Group Mst shared the highest percentage of both home ranges and core areas with neighboring groups, because of its central position among the four study groups. Due to the substantial range shift of group Sot after its split from Mot in 2014, the percentage of space shared with the neighbors decreased each year for all groups except Sst, as Sot shifted its range mostly towards the range of Sst. Temporal partitioning To compare home range overlap on two temporal scales, annual and 3-month, we first calculated the percentages of 3-month home ranges shared with neighboring groups and then averaged these values for corresponding group/years. When these averaged overlaps at the 3 months scale were compared with overlaps of annuals home ranges for corresponding years, the overlap of annual home ranges was higher in all cases but three cases (Fig. 6; Table S3, Electronic Supplementary Material). Distance between neighboring groups, when two were simultaneously followed throughout the day, varied from 32 m to 4526 m (mean = 1319 m, sd = 409 m; Table 4). Using 50 m as the criterion for an encounter, we assessed whether groups met more or less often than expected from independent movements. Sot had avoidant relationships with Mot and Mst, i.e., they encountered each other less often than by chance. Sst had neutral relationships with Mot and Sot. Group Mst had attraction relationships with groups Sst and Mot, i.e., the encounters with these groups were more frequent than expected. Except for one case, these patterns were consistent when we increased the encounter thresholds up to 200 m. Table 4 Mean between-group distances and significance value for attraction-avoidance relationship analysis for each group dyad for four proximity threshold distances, 50 m, 100 m, 150 m, and 200 m. Values close to 0 (in bold) indicate a significant avoidance relationship between the groups, values close to 0.5 (normal font) indicate neutral relationship between groups, values close to 1 (in italics) indicate a significant attraction relationship between the groups. The number of follow days represent the number of days both groups were followed simultaneously Group 1 Group 2 N follow days Mean distance (m) 50 m 100 m 150 m 200 m sot mot 12 1233 0.32 0.26 0.11 0.05 sot mst 9 651 0.20 0.02 0.08 0.30 sst sot 3 1583 0.50 0.48 0.44 0.88 sst mot 16 1625 0.5 0.5 0.5 0.5 mst mot 89 1729 1 1 1 0.99 mst sst 37 1093 1 1 1 1 To examine whether attraction relationship between Mst and Mot, as well as between Mst and Sst, could be explained by unavoidable encounters at certain times of day, e.g., around sleeping trees, we then explored the distribution of between-groups distances throughout the day in these two dyads. The distances, however, were evenly distributed throughout the day and were not lower around the time when monkeys emerged from sleeping trees in the morning (05:59 on average) or when they retired to sleeping trees in the evening (17:08 on average) (Fig. 7). Usage and sharing of sleeping trees Across 2011 group-nights, macaques used a total of 85 individual sleeping trees. These trees were not concentrated in core areas, but were evenly distributed between core and other parts of the home range based on the size of the areas (Fisher's tests: Mot: p = 1.00, N = 65 trees; Mst: p = 0.47, N = 44 trees; Sot: p = 0.41, N= 60 trees, Sst: p = 0.44, N = 36 trees). Of the 85 sleeping trees, 37 were shared by two or more groups (yet never on the same night), while 48 trees were used exclusively by only one of the study groups. Exclusively used trees were not concentrated in the core area of the respective group but rather located in the areas least overlapping with neighboring groups' ranges (Fig. 8a). All groups spent more nights in shared trees than in 'exclusive' trees (Mst: 99% of nights spent in shared trees, 20 of 22 trees are shared; Mot: 80% of nights spent in shared trees, 24 of 54 trees are shared; Sst: 76% of nights spent in shared trees, 22 of 29 trees are shared; Sot: 68% of nights spent in shared trees, 24 of 40 trees are shared). When we identified five most popular trees for each group separately (i.e., trees a group used most frequently), all these trees except one (tree 'Nga', used by Sot) were shared with one or more neighboring groups. Moreover, two trees appeared in the list of five most popular trees for all four groups, and one tree appeared in the list of five most popular trees for three groups (Fig. 8b). Despite the high degree of shared use of sleeping trees, all groups preferred to sleep inside their core areas. Comparison of number of nights spent in the core area vs. in the rest of the home range showed that all groups spent more nights in the core areas than would be expected if nights were distributed evenly throughout the home range (Fisher's exact test p-value < 0.001 for all groups, N = 679 nights for Mot, 825 for Mst, 171 for Sot, 336 for Sst). Moreover, all most popular five trees for each group, with the exception of only one tree, were located within these groups' core areas (Fig. 8b). Discussion In territorial species, between-group competition is often evident in inter-group fights over contested territories, and in patrolling and avoidance behaviors once territories are established (Wrangham et al. 2007 ; Mech 1977 ; Roth and Cords 2016; Müller and Manser 2007). In non-territorial animals, where parts of home ranges are shared by neighboring groups, signs of between-group competition may be more subtle. Our study brings new insights into how intraspecific competition affects space use in a non-territorial species, Assamese macaques. We showed that, despite considerable home range overlap between neighboring groups, groups maintained some degree of exclusivity in their space use employing both spatial and temporal landscape partitioning. Patterns of avoidance and attraction in the daily movements of neighboring groups indicated that between-group spatial dynamics are further influenced by demographic history of the groups and possibly by the distribution of food resources. Finally, we found that daily travel distances of our study groups increased with group size, suggesting that Assamese macaques may also experience within-group competition for food. Below, we discuss mechanisms by which macaques may avoid neighbors in the absence of territorial defense to decrease within- and between-group competition, and possible evolutionary reasons for the absence of territoriality in Assamese macaques. Space partitioning The observed annual home range overlap represents the whole range reported for other macaque species (37–85%: Willems et al. 2013 ). The actual overlap between neighboring groups is likely even higher, as our analysis included only habituated groups, which were surrounded by unhabituated groups on all sides. Not only space, but also sleeping trees were shared to a high degree. Although more than half of the sleeping trees were used only by one group, all groups preferred to sleep in trees shared with other groups. For all groups, five most popular trees were shared with neighbors, with the exception of only one tree, and groups spent 68–99% of nights in the shared trees. Moreover, some of the trees were among the most preferred for more than one group. Although both space and sleeping trees were shared to a high degree, we found evidence that neighboring groups used spatial and temporal space partitioning to avoid each other. Spatial partitioning was indicated by comparing the core area and the home range overlap. The annual core areas of neighboring groups overlapped on average only at 30%, which is less than half of the mean overall annual home range overlap of 69%. Temporal space partitioning was indicated by comparing home range overlap at different temporal scales. Home ranges overlapped less when assessed over shorter temporal scale, suggesting that neighboring groups limited simultaneous use of shared areas by sequential occupation of shared space. The same spatial and temporal effects were evident from sleeping tree usage data. Many sleeping trees were used by more than one group, but never simultaneously. Although sleeping trees were evenly distributed throughout the home range, all groups preferred to sleep in their core areas. This pattern of sleeping trees use is in line with the risk avoidance hypothesis, that suggests animals select sleeping trees located in the parts of their home range least shared with the neighbouring groups to decrease the risk of intergroup encounters (Wrangham et al. 2007 ). The preference for sleeping in central, more exclusive areas of the home range was shown for several other non-territorial macaque species (Albert et al. 2011 ; Rismayanti et al. 2023 ; Del Castillo et al. 2025 ), as well as for some territorial primates (e.g., Heymann 1995 ; Teichroeb et al. 2012 ; Phoonjampa et al. 2010 ). Taken together, our findings indicate that Assamese macaques actively avoid each other, suggesting they may experience between-group competition for resources. How this avoidance is achieved remains unclear. One possibility is that macaques are able to locate neighboring groups through auditory or visual cues to avoid them during their daily ranging. This mechanism was suggested for other two non-territorial species where active avoidance of neighbors has been demonstrated, mountain gorillas (avoidance using chest beats; Seiler et al. 2017 ) and baboons (avoidance using visual cues in the relatively open and flat savannah habitats; Markham et al. 2013 ). However, Assamese macaques do not advertise their location by loud calls, and visibility in the habitat is low. It is also possible that macaques avoid the areas where encounters happened earlier or, alternatively, avoid the areas previously used by neighbors by visually inspecting signs of foraging, as suggested for mountain gorillas (Seiler et al. 2017 ). To test this, future studies should investigate movement decisions of the macaques after the intergroup encounters and in relation to foraging patterns. Daily between-group spatial dynamics The analysis of simultaneous movements of neighboring groups showed that, within most group dyads, groups either avoided each other, being in proximity less often than expected by chance, or had neutral relationships, neither avoiding nor being attracted to each other. The avoidant relationships are to be expected if groups try to minimize between-group competition. Competition may also explain that dyads composed of one small (SSt or Sot) and one large group (Mst or Mot) had avoidant or neutral relationships, with only one exception (SSt/Mst). Avoidance also may have underlain the home range shift of Sot. After group Sot split off from Mot in 2014, their home ranges overlapped almost entirely. Then Sot gradually shifted towards the Northeast of the study area, reducing overlap with Mot and Mst. This avoidance movement may have been facilitated by human observes pushing unhabituated groups in the east aside when following Sot. Contrasting this pattern of avoidance, two pairs of groups (Mst/Sst and Mst/Mot) moved into close distances more often than expected. This attraction might reflect unavoidable (non-intentional) encounters around limited resources, such as sleeping or feeding trees. Such pattern was observed, e.g., in yellow baboons, where groups avoided each other during the day but had a higher encounter rate in the evening around sleeping sites (Markham et al. 2013 ). In Assamese macaques, most sleeping trees in the areas of home-range overlap are shared by several groups, so one may expect frequent intergroup encounters around them. However, the distribution of between-group distances throughout the day did not reveal any temporal patterns, and the distances were not lower in the evening or in the morning, when the animals are around their sleeping sites. It is possible that the observed attraction relationships are caused by groups' driven to shared feeding trees. Because of the creek located in the area of overlap between these three groups, this area has an unusually high density of feeding trees (Schülke and Ostner, unpublished data) and represents a center of attraction for all the groups. Another possibility is that some groups might intentionally seek out intergroup encounters. Young males in Assamese macaques can use the encounters as an opportunity to assess dispersal opportunities (Schülke and Ostner, unpublished data). Dispersal decisions of males can be influenced by home range overlap and availability of females (Janmaat et al. 2009 ; Olupot and Waser 2001). It is conceivable that macaque groups with many young males intentionally seek proximity with the neighbors. Resident males, on the other hand, might use avoidance tactics to reduce competition from immigrants (Markham et al. 2013 ). The patterns of attraction-avoidance relationships between groups, therefore, might be shaped by their demographic characteristics, in addition to the distribution of food resources and group fission history. To investigate this further, systematic quantitative data on behavior during and after intergroup encounters and in relation to feeding data and demographic history are needed. Factors affecting ranging behavior Further evidence for intraspecific feeding competition in Assamese macaques comes from our finding that daily travel distances were positively associated with total group size. Among other factors that we tested, only the day length had a significant positive effect on daily travel distances. The positive relationship between daily travel distances and group size is in line with the general principle of bigger groups increasing their foraging effort and hence their travel distances in search for food because they deplete food patches faster (McNab 1963 ; Chapman et al. 1995 ; Chapman and Chapman, 2000a ; 2000b ). Within-group feeding competition was also demonstrated in earlier studies on the same study population, where the animals were shown to adjust their foraging behavior to reduce contest competition (Heesen et al. 2014 ; 2015 ). These adjustments included lower ranking individuals occupying peripheral positions within the group, apparently to avoid direct competition for food by spacing out, entering food patches after higher ranking individuals, and using their cheek pouches more to reduce risks of co-feeding with dominant individuals (Heesen et al. 2014 ; 2015 ). In another, mainly folivorous, population of Assamese macaques inhabiting limestone forests, larger groups did not increase day journey length, an effect presumably related to a high abundance and perhaps more even distribution of leaves as food in their habitat (Chen et al. 2025 ). In our study population, variation of food availability was indeed shown to influence individual energy intake, physical condition, and female fecundity (Heesen et al., 2013 ). While the effect of within-group feeding competition is evident in the increased travel distances in bigger Assamese macaque groups, larger groups may be favored in between-group contest competition so that the resulting relationship between home range size and group size is U-shaped. The smallest groups may need larger areas because they are often displaced by larger groups, which have to travel over larger areas to meet their energetic needs ( Angolan colobus , Colobus angolensis : Teichroeb et al. 2022 ; baboons: Markham et al. 2015 ; wooly monkeys, Lagothrix lagothricha : Stevenson and Castellanos 2001). In cases when the smallest groups are those that recently split off from a larger one, the large home ranges of these small groups may also be explained by reduced foraging efficiency in unknown areas. This was shown, e.g., in blue monkeys, Cercopithecus mitis , where small post-fission groups, which tended to move to new areas after fission, spent less time feeding on preferred food (fruit) compared to pre-fission (Wakeford and Cords 2025). Post-fission groups were also shown to increase time spent moving and, in some cases, to expand their newly established home ranges (blue monkeys: Cords 2012 ; red-tailed monkeys, Cercopithecus ascanius : Windfelder and Lwanga 2002). Our smallest group Sot indeed had the largest home range right after splitting off from Mot, and in the following years it shifted the home range away from Mot and shrunk it. However, despite the evidence suggestive of between-group contest competition presented above, we did not find medium-sized groups to have the smallest home ranges in our overall analysis, and within-group analysis revealed inconsistent patterns. In an earlier study in our study population, home range size, examined for one group (a group that split into Mst and Sst later) over six years, was positively affected by the number of males, but not the total group size, after controlling for ecological factors (home range size also increased with decreasing rainfall and with an interaction of food abundance and distribution: Richter et al. 2016 ). This result was not replicated in the current study, with data collected in later years on more groups. In contrast to the earlier study, strong collinearity between the number of adult males and group size did not allow us to disentangle the variance between the two. It is possible that the absence of demographic effects in our study is related the fact that the data were collected around several group splits: Mst and Sst had split in 2012, Mot and Sot in 2014, and Mst split again in 2020. These changes could have disrupted the associations between demographic factors and ranging patterns. Data density also differed between studies, with 75 data points per group in the previous study and 19 data points per group on average in the current study. Finally, a potentially relevant difference between the two studies is that the group examined by Richter et al. ( 2016 ) was the only habituated group at that time. This could have allowed less constrained home range expansion, compared with four groups examiend in the current study, which were all habituated to the presence of human observers. Possible reasons for non-territoriality in Assamese macaques Taken together, our findings provide evidence for the existence of both within- and between-group competition in Assamese macaques. This, in turn, raises the question of why the macaques do not defend their home ranges from neighboring groups to decrease the competition. It has been suggested that a pre-requisite for the evolution of territoriality is the economic defendability of resources. In a comparative study across primates, territorial species were all found to present a D-index larger than 1, whereas most non-territorial species presented a D-index less than 1, indicating that their daily travel distances were not long enough to cross the home range, which suggests that the D-index reflects aspects of economic defendability (Mitani and Rodman 1979). Our finding of D-index sometimes exceeding 1 in Assamese macaques when calculated for 3-month home ranges may help explain the pattern of temporal partitioning we observed, where home ranges overlapped less when assessed over the shorter temporal scale (annual vs. 3-months). While mobility around the range is required for territorial defense, high mobility itself is not a sufficient condition for the evolution of territoriality (Mitani and Rodman 1979). Indeed, the fit between economic defendability and range defense is far from perfect, and there are taxa where territoriality is absent, although it would be expected from the perspective of defendability (Willems et al. 2013 ; Mitani and Rodman 1979; Grant et al. 1992 ). One explanation suggested for the absence of territoriality in such taxa invokes a collective action problem (Willems et al. 2013 ; Willems and Van Schaik 2015; Nunn 2000 ; Willems et al. 2015 ). Because benefits gained from collective range defense are collective benefits, i.e., they are shared not only by active defenders, but by the whole group, including individuals which did not participate, natural selection should favor the emergence of free-riders. These free-riders would reap benefits without incurring the costs of producing them, and free-riding is expected to become more prominent with increasing number of individuals of the larger sex in a group (Willems et al. 2013 ). Indeed, in a large comparative study across primates, increased home range overlap, after controlling for economic defendability, was associated with larger group size, the presence of multiple males and females, groups having multiple individuals of the larger sex, and habitual dispersal by the larger sex; all these findings can be interpreted as evidence for a collective action problem hampering range defense (Willems et al. 2013 ). Assamese macaques meet all these criteria, so it is conceivable that their non-territoriality is related to the collective action problem. The current study did not replicate the earlier finding that home range size increases with the number of males (Richter et al. 2016 ), so the Assamese macaques fit the general expectations of the collective action problem. Regardless of the collective action problem, Assamese macaques exhibit most of the traits that have been associated with high home range overlap in other studies. In a comparative study across 100 primate species, home range overlap was shown to be higher for larger-bodied species living in large home ranges at high population densities, where annual rainfall is low, and was higher for arboreal than terrestrial species (Pearce et al. 2013 ). Assamese macaques are arboreal, relatively large-bodied, and the home ranges at our study site were relatively large, in the upper quartile of the dataset of Pearce et al. ( 2013 ) (219 ha, home range size in our study: 266–848 ha). In accordance with this, the mean home range overlap of 69% observed in our study puts Assamese macaques above the upper quartile of the overlap range reported for primates (Willems et al. 2013 ; Pearce et al. 2013 ). It is also close to the mean overlap observed in other macaque species (63% in Willems et al. ( 2013 ); 51% in Pearce et al. ( 2013 )). While the absence or presence of territoriality tends to be a fixed species trait, home range overlap, in contrast, was shown to be very plastic (Pearce et al. 2013 ). The degree of overlap is influenced not only by conserved species traits, such as body size or social organization (Pearce et al. 2013 ; Willems et al. 2013 ), but also by traits that can show variability within species or population, such as home range size, population density, rainfall, resource availability, or social factors (Carpenter and MacMillen 1976 ; Maher and Lott 2000; Morrell and Kokko 2005; Mcloughlin et al. 2000 ; José-Domínguez et al. 2015). The wide range of home range overlap observed at our study site (30–100%), as well as among study sites in many other species (Pearce et al. 2013 ; Willems et al. 2013 ) further supports the idea of a gradient between non-territoriality and territoriality (Seiler et al. 2017 ; Morrell and Kokko 2005). Exclusive use of an area can be achieved not only by active defense of a territory but also by space partitioning and mutual avoidance (Börger et al. 2008; Brown and Orians 1970 ). Therefore, even non-territorial species with high home range overlap can maintain some degree of exclusivity in their use of space, as demonstrated by this and other studies (e.g., Seiler et al. 2017 ; Markham et al. 2013 ; Wartmann et al. 2014 ). Ultimately, the degree of territoriality and exclusivity are influenced by intraspecific competition for food and mates. For example, animals having access to abundant food resources and exhibiting low competition for mates may have no reasons to maintain neither territoriality nor exclusivity (e.g., Guinea baboons: Ohrndorf et al. 2025 ). By contrast, animals feeding on limited resources, with high competition for breeding opportunities, may be highly territorial and exhibit no overlap of home ranges (e.g., common marmosets, Callithrix jacchus : Lazaro-Perea 2001 ). The absence of territoriality combined with some degree of exclusivity in Assamese macaques puts them in the middle of a gradient between non-territoriality and territoriality. Patterns of space partitioning and avoidance demonstrated in our study further suggest that Assamese macaques do experience intraspecific competition for food and/or mates and actively avoid their neighbors to lower the competition. Declarations Acknowledgements We thank the National Research Council Thailand and the Department of National Parks Thailand for permission to conduct research in a protected area. We are grateful to K. Kreetiyutanont, M. Kumsuk, N. Kanjana and J. Prabnasuk (PKWS) for their cooperation, support, to all field assistants, D. Bootros, N. Bualeng, H. Drew, R. Intalo, N. Juntuch, S. Jumrudwong, M. Karlstetter, T. Kilawit, B. Klaewklar, W. Nueorngshiyos, N. Ponganan, K. Srithorn, W. Wisate, J. Wanart and coordinators A. Ebenau and M. Swagemakers for their excellent help. Funding Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – GRK2906 – project number 254142454 / GRK 2070. Contributions SD: Conceptualization, Formal analysis, Visualization, Writing – original draft SMe: Project administration, Writing – review & editing SMa: Project administration, Writing – review & editing PS: Investigation, Data curation, Writing – review & editing OS: Conceptualization, Resources, Supervision, Writing – review & editing JO: Conceptualization, Resources, Supervision, Writing – review & editing Ethics approval We adhered to the guidelines for the ethical treatment of nonhuman animals in research and teaching of the Association for the Study of Animal Behaviour (ASAB Ethical Committee/ABS Animal Care Committee 2023). 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Behavioral Ecology and Sociobiology 32 (3). https://doi.org/10.1007/BF00173778. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 04 May, 2026 Reviewers agreed at journal 14 Jan, 2026 Reviewers invited by journal 12 Jan, 2026 Editor assigned by journal 02 Jan, 2026 Submission checks completed at journal 02 Jan, 2026 First submitted to journal 23 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8432416","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":601330139,"identity":"61b8660e-2817-47f8-8329-d4d6ad71c567","order_by":0,"name":"Sofya 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(50%) for each group\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/25826e4262ac0e0ab1d0b28b.png"},{"id":104403594,"identity":"4171ffe4-06ad-4e24-b392-477d9757cd66","added_by":"auto","created_at":"2026-03-11 12:18:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":201303,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationships between 3-monthly 95% kernel home range size and (a) group size excluding dependent infants, and (b) the number of resident males, separately for each group (solid lines) and for all groups combined (dashed line)\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/4c7bfda9ccf528cd75d566ac.png"},{"id":104263712,"identity":"0c464494-bbd7-471d-9f72-f216e94770d5","added_by":"auto","created_at":"2026-03-09 19:12:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":201303,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationships between 3-monthly 95% kernel home range size and (a) group size excluding dependent infants, and (b) the number of resident males, separately for each group (solid lines) and for all groups combined (dashed line)\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/b633c591f6d435e191af9a34.png"},{"id":104403574,"identity":"98d1f89f-8bdd-4127-9f4a-df3767d606ba","added_by":"auto","created_at":"2026-03-11 12:18:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":81491,"visible":true,"origin":"","legend":"\u003cp\u003eMean monthly daily travel distance as a function of mean monthly group size (excluding dependent infants). 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The lines depict the fitted model (based on other predictors at their average), and blue areas correspond to 95% confidence intervals\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/94b996b6a66c13c2c9f154e4.png"},{"id":104102918,"identity":"7b54b262-c951-4c14-9aca-ad6e5f7a6a30","added_by":"auto","created_at":"2026-03-06 20:29:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":257489,"visible":true,"origin":"","legend":"\u003cp\u003eOverlaps between annual home ranges (95% kernel) and core areas (50% kernel) of neighboring groups, shown for years when data for all four groups were available\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/56f869ed0aaf39ccf9f5969f.png"},{"id":104403271,"identity":"f186927b-77f7-419b-b601-2e186c112ac5","added_by":"auto","created_at":"2026-03-11 12:17:53","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":152220,"visible":true,"origin":"","legend":"\u003cp\u003ePer cent overlap of annual home ranges (95% kernel) and core areas (50% kernel) of neighboring groups. 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Shown are percentages of home range/core area shared with home ranges or core areas, respectively, of neighboring habituated groups, for years when data for all four groups were available\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/f99674165ba8e1d9977f3b9a.png"},{"id":104403281,"identity":"846da820-4401-4788-a104-12c73af1f579","added_by":"auto","created_at":"2026-03-11 12:17:55","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":137451,"visible":true,"origin":"","legend":"\u003cp\u003ePer cent overlap of annual home ranges (95% kernel) and mean per cent of overlap of 3-month home ranges (95% kernel) calculated for the same year. Shown are percentages of home range shared with home ranges of neighboring habituated groups, for years when data for all four groups were available\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/e6e313226f42e552f6341cb2.png"},{"id":104263762,"identity":"82f5e367-b22a-4f6b-af16-e7c3cda7b14d","added_by":"auto","created_at":"2026-03-09 19:15:09","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":137451,"visible":true,"origin":"","legend":"\u003cp\u003ePer cent overlap of annual home ranges (95% kernel) and mean per cent of overlap of 3-month home ranges (95% kernel) calculated for the same year. Shown are percentages of home range shared with home ranges of neighboring habituated groups, for years when data for all four groups were available\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/febd69b71a9e60c4a4753734.png"},{"id":104102915,"identity":"e7fde28f-aa82-49b1-bbeb-43a49a8ee80f","added_by":"auto","created_at":"2026-03-06 20:29:11","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":375418,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of between-group distances throughout the day, shown for two group dyads with attraction spatial relationships (see Table 4)\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/9d8c8abed023178777a8fa73.png"},{"id":104102919,"identity":"aab2079a-e767-4853-9acf-e0149206e678","added_by":"auto","created_at":"2026-03-06 20:29:11","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":332863,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Shared use of sleeping trees. Trees used exclusively by a group are highlighted by corresponding colours, trees shared by two or more groups are shown as white dots. (b) Location of top five most popular trees for each group. Trees are highlighted by corresponding colors, the trees that appear in the top five for more than one group are shown as dots filled with colors of corresponding groups. 95% kernel home ranges and 50% core areas are calculated for all study years combined. Blue lines mark larger creeks\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/8de288875eb7ffa61605778e.png"},{"id":106401660,"identity":"c02e4da6-0ad5-49c3-8104-f2eeb1262d16","added_by":"auto","created_at":"2026-04-08 09:08:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3309272,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/4435d6d5-70c0-4abc-8ef0-d1cbd7d7db8a.pdf"},{"id":104403514,"identity":"bae368d9-721a-463d-969d-e20a4506c150","added_by":"auto","created_at":"2026-03-11 12:18:28","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":72554,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8432416/v1/c226b0b8921c85b508c184d3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Shared space use and avoidance among groups of wild non-territorial Assamese macaques","fulltext":[{"header":"Significance Statement","content":"\u003cp\u003eIn non-territorial animals, home ranges are shared with neighbors, leading to increased between-group competition. To investigate how this competition affects space use, we examined ranging patterns and spatial relationships between neighbors in four groups of wild Assamese macaques. Despite considerable home range overlap, groups used spatial and temporal partitioning to maintain some exclusivity in their space use. This suggests that even in the absence of territorial behaviors, between-group competition can be reduced by avoiding neighbors.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eSpace use in group-living animals is influenced by both resource availability and patterns of within-group and between-group competition (Brown and Orians \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1970\u003c/span\u003e; Macdonald \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Morrell and Kokko 2005; Maher and Lott 2000). In many territorial species, where residents aggressively defend parts of their home range and the limited resources therein (Brown \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1964\u003c/span\u003e; B\u0026ouml;rger et al. 2008), space use is mainly determined by between-group contest competition, with bigger groups gaining access over larger areas (e.g., African lions, \u003cem\u003ePanthera leo\u003c/em\u003e: Mosser and Packer 2009; blue monkeys, \u003cem\u003eCercopithecus mitis\u003c/em\u003e: Roth and Cords 2016; dwarf mongooses, \u003cem\u003eHelogale\u003c/em\u003e parvula: Arbon et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, neither group size nor home range size can grow indefinitely, as both are constrained by various factors.\u003c/p\u003e \u003cp\u003eBenefits of larger group size can be counter-balanced or even outweighed by increasing within-group feeding competition and resulting increases in foraging effort and daily travel length (McNab \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1963\u003c/span\u003e; Carbone et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), as shown in a variety of vertebrates (e.g., carnivores: Gittleman and Harvey \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Wrangham et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Arbon et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; primates: Wrangham et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Majolo et al. 2008; fish: Grand and Dill \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), or in longer feeding times and reduced food quality (Sch\u0026uuml;lke and Ostner \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). At some point, energy spent exceeds energy obtained, thus constraining both maximum group size and home range size \u0026ndash; a relationship formalized in the ecological constraints model (Chapman et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Chapman and Chapman, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2000a\u003c/span\u003e; \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2000b\u003c/span\u003e). Acting together, within- and between-group feeding competition can promote intermediate groups with small home ranges that can be exploited with short day journeys if food resources are limited (Markham et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Teichroeb et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Stevenson and Castellanos 2001).\u003c/p\u003e \u003cp\u003eBeyond feeding competition, social factors may affect the costs and benefits of living in larger groups. Group coordination becomes increasingly difficult the more members are involved in decision making, which decreases movement speed and may result in shorter daily travel distances and smaller home ranges in larger groups relative to intermediate-sized groups (e.g., guinea fowls, \u003cem\u003eAcryllium vulturinum\u003c/em\u003e: Papageorgiou and Farine 2020). Furthermore, cooperative home range defense may become less efficient with the higher number of individuals of the larger/dominant sex, resulting from the 'collective action problem' (Willems et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). With weaker defenses, the proportion of home range overlapping with neighboring groups increases (Pearce et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Willems et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), leading to increased between-group competition and diminishing foraging returns in overlap areas (Grant et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Jetz et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo manage competition with neighbors, animals may use different strategies. First, individuals might actively defend their home range or parts of it from conspecifics, preventing their intrusion, which leads to territoriality (B\u0026ouml;rger et al. 2008; Burt \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1943\u003c/span\u003e; Brown and Orians \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1970\u003c/span\u003e; see also Maher and Lott (1995) for a review of definitions of territoriality). Territory defense, however, carries costs that increase with territory size, because more time and energy are required to patrol it and expel intruders (Schoener \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Grant et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). The basic economic approach suggests that the emergence of territoriality is ultimately dependent on the 'economic defendability' of resources, i.e., it will only evolve when limited resources within a sufficiently small area can be economically defended from conspecifics (Carpenter and MacMillen \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Jensen et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Maher and Lott 2000; Schoener \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). When this is not feasible, home ranges are left undefended, and varying proportions of home ranges, including resources they contain, are shared with neighbors. This, in turn, can lead to loss of resources to neighbors (Grant et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Jetz et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and to increased risks of injuries from fighting with competitors over resources (Wrangham et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Sillero-Zubiri and Macdonald \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo mitigate these risks, animals with undefended home ranges might actively avoid their neighbors by partitioning a shared landscape. Partitioning may be spatial, with certain parts of the home range used more exclusively, and temporal, with animals avoiding other groups while moving within their home ranges. One mechanism of spatial partitioning is to maintain core areas (i.e., most intensively visited areas within the home range) with largely exclusive use by one group, as shown, e.g., in primates, rodents, and lizards (Seiler et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wartmann et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Pierro et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Kerr and Bull 2006). Another mechanism is to avoid the areas of overlap, as shown, e.g., in wolves, primates, and birds (Wrangham et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Sillero-Zubiri and Macdonald \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Mech \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1977\u003c/span\u003e; Gibson and Koenig 2012; Wakefield et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Even when all parts of a home range overlap extensively with the home ranges of neighboring groups, animals may still use temporal landscape partitioning, where different groups actively avoid each other and use the same area sequentially, so that the ranges overlap less when assessed over shorter time scales (e.g., yellow baboons, \u003cem\u003ePapio cynocephalus\u003c/em\u003e (Markham et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); gray-cheeked mangabey, \u003cem\u003eCercocebus albiqena\u003c/em\u003e (Waser \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e1976\u003c/span\u003e)). Finally, in some cases,, if crucial resources are over-abundant, home ranges of neighboring groups may overlap extensively not because of high defense costs, but because of low defense benefits (Carpenter and MacMillen \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Mcloughlin et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Ohrndorf et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Maher and Lott 2000).\u003c/p\u003e \u003cp\u003eOne of the critical resources for which neighboring groups might compete are safe sleeping sites. As animals usually do not choose sleeping trees randomly and show sleeping-site preferences, the availability of suitable sleeping sites can influence space use and social interactions, as shown in various species of mammals and birds (Day and Elwood 1999; Lutermann et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kalko et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Du Plessis 1992; Doncaster and Woodroffe 1993). In non-territorial animals, sleeping sites in overlapping areas may be shared by neighboring groups, simultaneously or successively. While in some taxa, several groups may share sleeping sites on the same night (vulturine guineafowl: Papageorgiou et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; olive baboons, \u003cem\u003ePapio anubis\u003c/em\u003e: Loftus et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), in other taxa, groups may maintain some exclusivity in the use of sleeping sites by preference for sleeping sites located in non-overlapping parts of home ranges or by avoiding sleeping near other groups (e.g., in colobus monkeys: Teichroeb et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Von Hippel 1998). As sharing of sleeping trees may affect competition over nearby food resources and exposure to predators or parasites (Loftus et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Barclay \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Chapman et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1989\u003c/span\u003e), patterns of the shared use constitute an important part of inter-group dynamics.\u003c/p\u003e \u003cp\u003eIn this study, we investigated space use in a non-territorial species with large home range overlap between neighboring groups, Assamese macaques, \u003cem\u003eMacaca assamensis\u003c/em\u003e, living in their natural environment in Phu Khieo Wildlife Sanctuary in Thailand. Assamese macaques live in multimale-multifemale groups characterized by female philopatry and male dispersal (Heesen et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Sch\u0026uuml;lke et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Home range overlap between neighboring groups is large, and sleeping trees are shared by neighboring groups (Sch\u0026uuml;lke and Ostner, unpublished data), but patterns of shared space use have not yet been quantified. In an earlier study on changes in space use in one group over multiple years, home range size increased with decreasing rainfall and with an interaction of food abundance and distribution (Richter et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Controlling for these ecological factors, the number of males, but not the total group size, positively affected home range size (Richter et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Here, we extended this earlier analysis to four groups, studied over six years, to additionally examine shared use of space and of sleeping sites by neighboring groups.\u003c/p\u003e \u003cp\u003eWe aimed to: (1) quantify group ranging patterns, focusing on identifying demographic and ecological factors influencing home range size and daily travel distances; and (2) investigate spatial relationships among neighboring groups by examining the extent and patterns of shared space use. To address objective 1, we analyzed the effects of demographic (total group size, male group size) and ecological (fruit availability, rainfall, day length) factors on home range size and daily travel distances. In addition, we calculated an index of economic defendability, introduced and tested on primates by Mitani and Rodman (1979), that uses the ratio of daily travel distances to the size of the home range to assess the ability of a group to monitor the boundaries of its home range in order to defend it. To address objective 2, we first compared annual home range and core area overlap between neighboring groups to assess spatial partitioning and test whether core areas were more exclusive. We then calculated home range overlap at two temporal scales: annual and 3-month periods, to assess temporal partitioning and to test whether overlap decreased when assessed over shorter intervals. While these \u0026ldquo;static\u0026rdquo; measures (sensu Doncaster \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1990\u003c/span\u003e) reflect the extent of shared space, they do not capture simultaneous movements and the nature of spacing behavior (i.e. avoidance, attraction, or neutrality) between groups. To examine these \"dynamic\" interactions, we compared the observed encounter rates between groups with the expected rates if groups moved independently from each other. Observed encounter rates higher than expected would indicate attraction, whereas lower rates suggest avoidance. Finally, to gain further insight into shared resource use, we investigated the degree of exclusivity and re-use of sleeping trees.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eStudy site and study groups\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study is part of a long-term research project on a population of fully habituated Assamese macaques living in their natural environment at Phu Khieo Wildlife Sanctuary in northeastern Thailand (PKWS, 16\u0026deg;050 \u0026minus;350 N, 101\u0026deg;200 \u0026minus;550 E). The sanctuary is part of the \u0026gt; 6500 km\u0026sup2; protected forest of the Western Isaan Forest Complex (Borries et al. 2002). The climate is characterized by a cold dry season from November through mid‐March and a warm rainy season with peak precipitation in May and September (Richter et al. 2016).\u003c/p\u003e\n\u003cp\u003eThe study population inhabits hill evergreen forest with bamboo stands and breeds seasonally, with a mating season spanning from October to February and births spread from March to August (F\u0026uuml;rtbauer et al. 2010; Shivani et al. 2025). This study is based on data collected on four groups from October 2013 until September 2019, i.e., the years following the previous study (Richter et al. 2016). Each study group was composed of adult females, adult males, and immatures, with a total group size between 20 and 86 animals, with fluctuations resulting from male immi- and emigration, births, deaths, and group splits. Groups Mst, Sst, and Mot existed since the beginning of the study period. Group Sot was established in May 2014 after splitting off from group Mot.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eSpatial data\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study groups were followed on average 9 days per month (range: 1-23 days) from sleeping tree to sleeping tree by various observers. The monkeys emerged from sleeping trees on average at 05:59 (range: 04:50 - 07:37) and retired to sleeping trees on average at 17:08 (range: 15:00 - 18:40). GPS coordinates were recorded for the sleeping trees and, as part of behavioral data collection, at the beginning and at the end of each 30-min (until October 2014) or 40-min (from October 2014) focal sampling session (GPS device: Garmin GPSMAP 64s). When multiple observers followed different animals in the same group, we averaged coordinates with timestamp differences of less than 10 min. This resulted in an average of 28 (range 2-57) GPS points per day/group. The number of GPS points varied because the number of animals followed on a given day differed, not all protocols lasted 30 or 40 min (e.g., focal animal was out of sight), and sleeping tree coordinates were sometimes missing (i.e., if the group was lost during the day). It was not possible to record data blind because our study involved focal animals in the field.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eEcological factors\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eClimate data were recorded throughout the study period. Precipitation data were taken daily using a HOBO Event data logger. At the middle of each month, we assessed fruit availability based on phenological scores from a sample of more than 650 macaque food trees and tree species abundance scores from 21 ha (0.21 km\u0026sup2;) of botanical plots and calculated a monthly fruit availability index (see details in Anz\u0026agrave; et al. 2025). Daily day length data was downloaded from www.timeanddate.com for Bangkok, as it was the closest location for which data were available (situated about 320 km SSW of the study area). Mean monthly day length varied between 11 h 20 min (December) and 12 h 55 min (June).\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eDemographic factors\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe presence or absence of every individual was recorded every day. Group size was calculated from the total group size excluding unweaned infants up to the age of 1 year as they are not independent foragers yet. This measure of group size varied between 17 and 78 individuals; the number of resident males varied between 1 and 14. Average group size and number of adult males per month and per 3-month intervals, used for statistical analysis (below), were calculated from these daily counts. \u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eHome range sizes and site fidelity\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe estimated the home range and core areas of each group using the fixed kernel density method (Erran Seaman and Powell 1996) in the R package adehabitatHR (Calenge 2006). We chose this technique because it is less sensitive to outliers and to differences in sampling effort than minimum convex polygons and is more suitable for comparisons between groups (B\u0026ouml;rger et al. 2006). We defined home ranges as the area within the 95% fixed kernel contour and the core areas as the are within the 50% fixed kernel contour (Asensio et al. 2012; Holzmann et al. 2012). To avoid oversmoothing the data, we first selected the lowest smoothing factor \u003cem\u003eh \u003c/em\u003ethat did not create discontinuity in the 95% isopleth, except for gaps already present in the corresponding isopleth when using the reference smoothing factor. As the lowest \u003cem\u003eh \u003c/em\u003ewas equal to reference \u003cem\u003eh\u003c/em\u003e, we continued the analysis with the reference \u003cem\u003eh\u003c/em\u003e. Annual home ranges were calculated from October (beginning of mating season) until September the following year (mean number of GPS fixes per year/group = 2575, range = 770 - 4530). These home ranges were then used to draw maps and calculate overlaps in QGIS 3.28 (QGIS Development Team, 2022). To assess site fidelity (home range stability over the years), we calculated home range overlap between years for each group in QGIS 3.28, defined as the percentage of an annual home range area (95% kernel estimates) which was used in the previous year.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eDaily travel distance\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe calculated daily travel distances as the sum of distances between consecutive GPS locations. We used only days with complete observations (from sleeping tree to sleeping tree) and omitted days with time gaps \u0026gt;3 h, resulting in 1134 days in total (mean = 283.5 days per group).\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003ePredictors of home range size and daily travel length\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate which factors influenced the home range size, we calculated 95% kernel home ranges over 3-month intervals. This interval was chosen because it was the shortest interval providing at least 100 GPS fixes for most group-intervals. We used 100 GPS fixes as a minimum sample size because the 95% kernel home range size reached asymptote around 100 fixes; moreover, 100 relocations were recommended as a minimum sample size adequately representing home range size for spread data (spanning over at least 5 weeks) (Jacobson et al. 2024). After excluding 3-month blocks which had \u0026lt; 100 GPS points, the sample size was 72 3-month blocks, with a mean of 703 GPS points per 3-month block/group (range = 116-1400). We then used a Generalized Linear Mixed Model (GLMM; Baayen 2008) with the size of 3-month home ranges as response variable and mean group size, mean fruit availability index, and the mean amount of rainfall calculated for a given 3-month period as predictor variables. To investigate potential non-linear relationship between home range size and number of males, we additionally included squared group size as a predictor variable. To account for repeated observations, we used group identity as a random effect. Prior to fitting the model, all predictors were z-transformed to a mean of zero and a standard deviation of one to make model convergence more likely. To rule out collinearity, we checked Variance Inflation Factors (VIFs (Quinn and Keough 2002)) using R package car (version 3.1-3). The original model also included the mean number of resident males as a response variable. However, as this variable was strongly correlated with the group size, and VIFs indicated problematic levels of collinearity (VIF = 6 for both variables), the number of males was excluded from the analysis. The assumptions of normality and homogeneity of residuals were checked and met, and the model was stable for all estimates. To test the effect of the individual predictors, we applied likelihood ratio tests using R function drop1. We ran the model using R package lme4 version 1.1-36 (Bates et al. 2015).\u003c/p\u003e\n\u003cp\u003eTo identify ecological and demographic factors affecting daily travel distances, we used a Generalized Linear Mixed Model (GLMM; Baayen 2008) with mean monthly daily travel distance as response variable. We only included months with at least 7 data points, resulting in a sample size of 82 months. As predictor variables, we included the mean monthly group size, monthly fruit availability index, mean monthly day length, and the amount of rainfall per month (mean: 100.1 mm, range: 0 - 282.4 mm). Group identity was used as a random effect. The model was fit and tested in the same way as the model described above.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eHome range and core area overlap between neighboring groups\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo compare overlap between annual home ranges (95% kernel) and core areas (50%) of neighboring groups, we calculated for each group the percentage of the respective group\u0026rsquo;s annual home range (or core area) overlapped by the home ranges (or core areas) of neighboring habituated groups in QGIS 3.28 (QGIS Development Team, 2022). We included only years for which data for all four groups were available, which included October to September in 2014-2015, 2015-2016, and 2016-2017.\u003c/p\u003e\n\u003cp\u003eTo assess the overlap of home ranges and core areas on a shorter time scale, we followed the same procedure using 3 months instead of full years and including only 3-months intervals with \u0026ge;100 GPS points (Mot, Mst: 23 3-month intervals, Sot: 10, Sst: 18).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDefendability index\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the economic defendability of the home ranges, we calculated the D-index (Mitani and Rodman 1979), which is specified as the ratio of the average daily travel length to the diameter of the (idealized) home range. We calculated D-index for each study group on both time scales: annually and 3-monthly. D-index was calculated as follows: DI = d/ , where d = mean daily travel distance (km) in a given time unit and A = the area of the annual home range (km\u003csup\u003e2\u003c/sup\u003e) for that time unit.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eBetween-group dynamics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate how neighboring groups move throughout their home ranges relative to each other, we examined whether groups were in proximity to one another more or less often than expected by chance. As there were no occasions when all four groups were followed on the same day, we examined pairwise spatial relationships between two groups. We first selected the days when any two groups were followed and when both groups had at least 10 GPS points, resulting in the following sample sizes for groups dyads: Mst/Mot: 89 days; Mst/Sst: 37 days; Mot/Sot: 12 days; Sst/Sot: 16 days; Mst/Sot: 9 days; Mot/Sst: 3 days. We then tested for attraction and avoidance within each dyad using MoveMine, a program for mining movement databases (Li et al. 2013, https://faculty.ist.psu.edu/jessieli/MoveMine/). In this analysis, the observed rates at which two groups encountered each other were compared to rates that would be expected to occur if groups moved independently through their home ranges, generated for each dyad by repeatedly permuting the locations in the movement sequence of one group (1000 permutations). The statistical significance of the observed number of encounters was obtained by comparing the observed number to the tails of the null distribution. As a threshold for what constitutes an encounter we first used 50 m, as this was a minimum group spread shown in an earlier study (Heesen et al. 2015). To confirm robustness of our findings, we additionally considered proximity thresholds of 100 m, 150 m, and 200 m, which are distances over which groups can still hear each other. \u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eSleeping tree usage\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo quantify the usage of sleeping trees and the extent to which they are shared between groups, we mapped the locations of 85 sleeping trees used in the study period onto the 95% kernel home ranges and the 50% kernel core areas calculated for all study years combined and examined the frequency of use of the trees by all study groups. To test whether sleeping trees are concentrated in core areas of the home ranges, we compared the observed and expected numbers of sleeping trees in the core area vs. in the rest of the 95% kernel home range using Fisher\u0026rsquo;s exact tests (two-tailed), for each group separately. We calculated expected values under the null hypothesis of sleeping trees being evenly distributed across the home ranges, taking into account the size of each area. To test whether monkeys preferred to sleep in trees located inside their core areas, we conducted a similar analysis, comparing the observed number of nights spent in the core area vs. in the rest of the home range with the numbers expected if nights were distributed evenly throughout the home range, for each group separately. In total, we analyzed 2011 group-nights.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eHome range sizes and site fidelity\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe size of an annual home range (95% kernel) varied between 266 and 848 ha (mean = 463 ha), the size of an annual core areas varied between 73 and 205 ha (mean = 128 ha) (Table 1). The annual home ranges were stable in location, with mean overlap between the ranges for consecutive years of 87% for Mot, 81% for Mst, 80% for Sot, and 77% for Sst (Table 1, Fig. 1). The most prominent shift of the home range location occurred for Sot between 2014/2015 and 2015/2016, after Sot split from Mot in May 2014; the largest annual home ranges of all (848 ha) was observed for Sot in the same year.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 Yearly home range (95% kernel) and core area (50% kernel) sizes for each group in ha, and the annual overlap of home ranges (percentage of yearly 95% kernel home range area used in the previous year)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"945\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 215px;\"\u003e\n \u003cp\u003eMot\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eMst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eSot\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003eSst\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003eHome range size (ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eCore area size (ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eOverlap with previous year (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eHome range size (ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eCore area size (ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eOverlap with previous year (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eHome range size (ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eCore area size (ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eOverlap with previous year (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eHome range size (ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eCore area size (ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eOverlap with previous year (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2013/2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e540.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e173.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e434.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e108.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2014/2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e632.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e156.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e78.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e412.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e93.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e75.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e848.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e204.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e358.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e109.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2015/2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e607.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e185.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e87.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e523.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e131.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e70.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e512.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e153.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e83.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e380.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e96.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e77.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2016/2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e567.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e180.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e92.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e408.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e113.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e85.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e444.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e110.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e76.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e266.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e72.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e95.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2017/2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e557.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e163.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e86.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e435.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e115.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e85.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e355.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e107.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e62.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2018/2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e371.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e83.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e89.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e327.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e79.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e89.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e357.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e76.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e72.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ePredictors of home range size and daily travel length\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe size of a 3-month home range (95% kernel) varied between 116 and 741 ha (mean = 368 ha). None of the predictors included in the GLMM model (group size, squared group size, fruit availability index, amount of rainfall) influenced the size of 3-month home ranges (Table 2). As the number of males was strongly correlated with the groups size, we could not include both these variables in the model. Multiple regression models ran for each group separately (using the same set of predictors as in the GLMM) did not reveal consistent associations either; there was a trend for non-linear associations between home range size and group size, U-shaped for Mot and Sst and bell-shaped for Sot (Fig. 2a), as well a trend for a U-shaped non-linear association between home range size and number of males for Mot and Sst (Fig. 2b), although none of these associations reached statistical significance.\u003c/p\u003e\n\u003cp\u003eTable 2\u0026nbsp;Estimates of factors influencing home range sizes based on a GLMM and standardized (z-transformed) predictor variables. Group size excludes dependent infants\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eTerm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eEstimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ez-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e374.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e34.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eGroup size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eGroup size\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e-5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e-0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRainfall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e17.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eFruit availability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e-1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMean distance traveled per day was 1778 m (range = 474-6949 m). The mean monthly daily travel distance was significantly influenced by group size and daylength, increasing in months with higher average group size (an increase of 4.7 m per group member) and longer average daylength (an increase of 3.9 m per minute) (Table 3, Fig. 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3 Estimates of factors influencing mean monthly daily travel distance based on a GLMM and standardized (z-transformed) predictor variables. Group size excludes dependent infants\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eTerm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eEstimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ez-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e1738.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e27.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e63.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e58.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.045\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDaylength\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e129.1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e37.6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eFruit availability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e-41.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e29.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e-1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRainfall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e12.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e38.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eDefendability index\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe annual D-index, i.e., the ratio of average daily travel distances to the diameter of the home range, was less than 1 for all groups in all years (mean = 0.75, range 0.58-0.93; Table S1, Electronic Supplementary Material). The mean D-index for 3-month intervals was slightly higher (mean = 0.84, range 0.47-1.2), in some cases exceeding 1 (Table S1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSpatial partitioning\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe annual core areas of neighboring groups overlapped less than the annual home ranges in all groups in all years (Fig. 4, Fig. 5; Table S2, Electronic Supplementary Material). While the mean per cent of home range shared with other groups was 69% (range 30 - 100%), the mean per cent of core area shared with other groups was only 30% (range 11-76%), driven to some degree by very low values for Sst. Group Mst shared the highest percentage of both home ranges and core areas with neighboring groups, because of its central position among the four study groups. Due to the substantial range shift of group Sot after its split from Mot in 2014, the percentage of space shared with the neighbors decreased each year for all groups except Sst, as Sot shifted its range mostly towards the range of Sst.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTemporal partitioning\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo compare home range overlap on two temporal scales, annual and 3-month, we first calculated the percentages of 3-month home ranges shared with neighboring groups and then averaged these values for corresponding group/years. When these averaged overlaps at the 3 months scale were compared with overlaps of annuals home ranges for corresponding years, the overlap of annual home ranges was higher in all cases but three cases (Fig. 6; Table S3, Electronic Supplementary Material).\u003c/p\u003e\n\u003cp\u003eDistance between neighboring groups, when two were simultaneously followed throughout the day, varied from 32 m to 4526 m (mean = 1319 m, sd = 409 m; Table 4). Using 50 m as the criterion for an encounter, we assessed whether groups met more or less often than expected from independent movements. Sot had avoidant relationships with Mot and Mst, i.e., they encountered each other less often than by chance. Sst had neutral relationships with Mot and Sot. Group Mst had attraction relationships with groups Sst and Mot, i.e., the encounters with these groups were more frequent than expected. Except for one case, these patterns were consistent when we increased the encounter thresholds up to 200 m.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4 Mean between-group distances and significance value for attraction-avoidance relationship analysis for each group dyad for four proximity threshold distances, 50 m, 100 m, 150 m, and 200 m. Values close to 0 (in bold) indicate a significant avoidance relationship between the groups, values close to 0.5 (normal font) indicate neutral relationship between groups, values close to 1 (in italics) indicate a significant attraction relationship between the groups. The number of follow days represent the number of days both groups were followed simultaneously\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"601\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eGroup 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eGroup 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eN follow days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMean distance (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e50 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e100 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e150 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e200 m\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003esot\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003emot\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.32\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.05\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003esot\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003emst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.08\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003esst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003esot\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.88\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003esst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003emot\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003emst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003emot\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.99\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003emst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003esst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTo examine whether attraction relationship between Mst and Mot, as well as between Mst and Sst, could be explained by unavoidable encounters at certain times of day, e.g., around sleeping trees, we then explored the distribution of between-groups distances throughout the day in these two dyads. The distances, however, were evenly distributed throughout the day and were not lower around the time when monkeys emerged from sleeping trees in the morning (05:59 on average) or when they retired to sleeping trees in the evening (17:08 on average) (Fig. 7).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eUsage and sharing of sleeping trees\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAcross 2011 group-nights, macaques used a total of 85 individual sleeping trees. These trees were not concentrated in core areas, but were evenly distributed between core and other parts of the home range based on the size of the areas (Fisher\u0026apos;s tests: Mot: p = 1.00, N = 65 trees; Mst: p = 0.47, N = 44 trees; Sot: p = 0.41, N= 60 trees, Sst: p = 0.44, N = 36 trees). Of the 85 sleeping trees, 37 were shared by two or more groups (yet never on the same night), while 48 trees were used exclusively by only one of the study groups. Exclusively used trees were not concentrated in the core area of the respective group but rather located in the areas least overlapping with neighboring groups\u0026apos; ranges (Fig. 8a).\u003c/p\u003e\n\u003cp\u003eAll groups spent more nights in shared trees than in \u0026apos;exclusive\u0026apos; trees (Mst: 99% of nights spent in shared trees, 20 of 22 trees are shared; Mot: 80% of nights spent in shared trees, 24 of 54 trees are shared; Sst: 76% of nights spent in shared trees, 22 of 29 trees are shared; Sot: 68% of nights spent in shared trees, 24 of 40 trees are shared). When we identified five most popular trees for each group separately (i.e., trees a group used most frequently), all these trees except one (tree \u0026apos;Nga\u0026apos;, used by Sot) were shared with one or more neighboring groups. Moreover, two trees appeared in the list of five most popular trees for all four groups, and one tree appeared in the list of five most popular trees for three groups (Fig. 8b).\u003c/p\u003e\n\u003cp\u003eDespite the high degree of shared use of sleeping trees, all groups preferred to sleep inside their core areas. Comparison of number of nights spent in the core area vs. in the rest of the home range showed that all groups spent more nights in the core areas than would be expected if nights were distributed evenly throughout the home range (Fisher\u0026apos;s exact test p-value \u0026lt; 0.001 for all groups, N = 679 nights for Mot, 825 for Mst, 171 for Sot, 336 for Sst). Moreover, all most popular five trees for each group, with the exception of only one tree, were located within these groups\u0026apos; core areas (Fig. 8b).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn territorial species, between-group competition is often evident in inter-group fights over contested territories, and in patrolling and avoidance behaviors once territories are established (Wrangham et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Mech \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1977\u003c/span\u003e; Roth and Cords 2016; M\u0026uuml;ller and Manser 2007). In non-territorial animals, where parts of home ranges are shared by neighboring groups, signs of between-group competition may be more subtle. Our study brings new insights into how intraspecific competition affects space use in a non-territorial species, Assamese macaques. We showed that, despite considerable home range overlap between neighboring groups, groups maintained some degree of exclusivity in their space use employing both spatial and temporal landscape partitioning. Patterns of avoidance and attraction in the daily movements of neighboring groups indicated that between-group spatial dynamics are further influenced by demographic history of the groups and possibly by the distribution of food resources. Finally, we found that daily travel distances of our study groups increased with group size, suggesting that Assamese macaques may also experience within-group competition for food. Below, we discuss mechanisms by which macaques may avoid neighbors in the absence of territorial defense to decrease within- and between-group competition, and possible evolutionary reasons for the absence of territoriality in Assamese macaques.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003eSpace partitioning\u003c/h2\u003e \u003cp\u003eThe observed annual home range overlap represents the whole range reported for other macaque species (37\u0026ndash;85%: Willems et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The actual overlap between neighboring groups is likely even higher, as our analysis included only habituated groups, which were surrounded by unhabituated groups on all sides. Not only space, but also sleeping trees were shared to a high degree. Although more than half of the sleeping trees were used only by one group, all groups preferred to sleep in trees shared with other groups. For all groups, five most popular trees were shared with neighbors, with the exception of only one tree, and groups spent 68\u0026ndash;99% of nights in the shared trees. Moreover, some of the trees were among the most preferred for more than one group.\u003c/p\u003e \u003cp\u003eAlthough both space and sleeping trees were shared to a high degree, we found evidence that neighboring groups used spatial and temporal space partitioning to avoid each other. Spatial partitioning was indicated by comparing the core area and the home range overlap. The annual core areas of neighboring groups overlapped on average only at 30%, which is less than half of the mean overall annual home range overlap of 69%. Temporal space partitioning was indicated by comparing home range overlap at different temporal scales. Home ranges overlapped less when assessed over shorter temporal scale, suggesting that neighboring groups limited simultaneous use of shared areas by sequential occupation of shared space. The same spatial and temporal effects were evident from sleeping tree usage data. Many sleeping trees were used by more than one group, but never simultaneously. Although sleeping trees were evenly distributed throughout the home range, all groups preferred to sleep in their core areas. This pattern of sleeping trees use is in line with the risk avoidance hypothesis, that suggests animals select sleeping trees located in the parts of their home range least shared with the neighbouring groups to decrease the risk of intergroup encounters (Wrangham et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The preference for sleeping in central, more exclusive areas of the home range was shown for several other non-territorial macaque species (Albert et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Rismayanti et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Del Castillo et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), as well as for some territorial primates (e.g., Heymann \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Teichroeb et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Phoonjampa et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Taken together, our findings indicate that Assamese macaques actively avoid each other, suggesting they may experience between-group competition for resources.\u003c/p\u003e \u003cp\u003eHow this avoidance is achieved remains unclear. One possibility is that macaques are able to locate neighboring groups through auditory or visual cues to avoid them during their daily ranging. This mechanism was suggested for other two non-territorial species where active avoidance of neighbors has been demonstrated, mountain gorillas (avoidance using chest beats; Seiler et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and baboons (avoidance using visual cues in the relatively open and flat savannah habitats; Markham et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, Assamese macaques do not advertise their location by loud calls, and visibility in the habitat is low. It is also possible that macaques avoid the areas where encounters happened earlier or, alternatively, avoid the areas previously used by neighbors by visually inspecting signs of foraging, as suggested for mountain gorillas (Seiler et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). To test this, future studies should investigate movement decisions of the macaques after the intergroup encounters and in relation to foraging patterns.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eDaily between-group spatial dynamics\u003c/h2\u003e \u003cp\u003eThe analysis of simultaneous movements of neighboring groups showed that, within most group dyads, groups either avoided each other, being in proximity less often than expected by chance, or had neutral relationships, neither avoiding nor being attracted to each other. The avoidant relationships are to be expected if groups try to minimize between-group competition. Competition may also explain that dyads composed of one small (SSt or Sot) and one large group (Mst or Mot) had avoidant or neutral relationships, with only one exception (SSt/Mst). Avoidance also may have underlain the home range shift of Sot. After group Sot split off from Mot in 2014, their home ranges overlapped almost entirely. Then Sot gradually shifted towards the Northeast of the study area, reducing overlap with Mot and Mst. This avoidance movement may have been facilitated by human observes pushing unhabituated groups in the east aside when following Sot.\u003c/p\u003e \u003cp\u003eContrasting this pattern of avoidance, two pairs of groups (Mst/Sst and Mst/Mot) moved into close distances more often than expected. This attraction might reflect unavoidable (non-intentional) encounters around limited resources, such as sleeping or feeding trees. Such pattern was observed, e.g., in yellow baboons, where groups avoided each other during the day but had a higher encounter rate in the evening around sleeping sites (Markham et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In Assamese macaques, most sleeping trees in the areas of home-range overlap are shared by several groups, so one may expect frequent intergroup encounters around them. However, the distribution of between-group distances throughout the day did not reveal any temporal patterns, and the distances were not lower in the evening or in the morning, when the animals are around their sleeping sites. It is possible that the observed attraction relationships are caused by groups' driven to shared feeding trees. Because of the creek located in the area of overlap between these three groups, this area has an unusually high density of feeding trees (Sch\u0026uuml;lke and Ostner, unpublished data) and represents a center of attraction for all the groups.\u003c/p\u003e \u003cp\u003eAnother possibility is that some groups might intentionally seek out intergroup encounters. Young males in Assamese macaques can use the encounters as an opportunity to assess dispersal opportunities (Sch\u0026uuml;lke and Ostner, unpublished data). Dispersal decisions of males can be influenced by home range overlap and availability of females (Janmaat et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Olupot and Waser 2001). It is conceivable that macaque groups with many young males intentionally seek proximity with the neighbors. Resident males, on the other hand, might use avoidance tactics to reduce competition from immigrants (Markham et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The patterns of attraction-avoidance relationships between groups, therefore, might be shaped by their demographic characteristics, in addition to the distribution of food resources and group fission history. To investigate this further, systematic quantitative data on behavior during and after intergroup encounters and in relation to feeding data and demographic history are needed.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eFactors affecting ranging behavior\u003c/h2\u003e \u003cp\u003eFurther evidence for intraspecific feeding competition in Assamese macaques comes from our finding that daily travel distances were positively associated with total group size. Among other factors that we tested, only the day length had a significant positive effect on daily travel distances. The positive relationship between daily travel distances and group size is in line with the general principle of bigger groups increasing their foraging effort and hence their travel distances in search for food because they deplete food patches faster (McNab \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1963\u003c/span\u003e; Chapman et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Chapman and Chapman, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2000a\u003c/span\u003e; \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2000b\u003c/span\u003e). Within-group feeding competition was also demonstrated in earlier studies on the same study population, where the animals were shown to adjust their foraging behavior to reduce contest competition (Heesen et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These adjustments included lower ranking individuals occupying peripheral positions within the group, apparently to avoid direct competition for food by spacing out, entering food patches after higher ranking individuals, and using their cheek pouches more to reduce risks of co-feeding with dominant individuals (Heesen et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In another, mainly folivorous, population of Assamese macaques inhabiting limestone forests, larger groups did not increase day journey length, an effect presumably related to a high abundance and perhaps more even distribution of leaves as food in their habitat (Chen et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In our study population, variation of food availability was indeed shown to influence individual energy intake, physical condition, and female fecundity (Heesen et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile the effect of within-group feeding competition is evident in the increased travel distances in bigger Assamese macaque groups, larger groups may be favored in between-group contest competition so that the resulting relationship between home range size and group size is U-shaped. The smallest groups may need larger areas because they are often displaced by larger groups, which have to travel over larger areas to meet their energetic needs (\u003cem\u003eAngolan colobus\u003c/em\u003e, \u003cem\u003eColobus angolensis\u003c/em\u003e: Teichroeb et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; baboons: Markham et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; wooly monkeys, \u003cem\u003eLagothrix lagothricha\u003c/em\u003e: Stevenson and Castellanos 2001). In cases when the smallest groups are those that recently split off from a larger one, the large home ranges of these small groups may also be explained by reduced foraging efficiency in unknown areas. This was shown, e.g., in blue monkeys, \u003cem\u003eCercopithecus mitis\u003c/em\u003e, where small post-fission groups, which tended to move to new areas after fission, spent less time feeding on preferred food (fruit) compared to pre-fission (Wakeford and Cords 2025). Post-fission groups were also shown to increase time spent moving and, in some cases, to expand their newly established home ranges (blue monkeys: Cords \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; red-tailed monkeys, \u003cem\u003eCercopithecus ascanius\u003c/em\u003e: Windfelder and Lwanga 2002). Our smallest group Sot indeed had the largest home range right after splitting off from Mot, and in the following years it shifted the home range away from Mot and shrunk it. However, despite the evidence suggestive of between-group contest competition presented above, we did not find medium-sized groups to have the smallest home ranges in our overall analysis, and within-group analysis revealed inconsistent patterns.\u003c/p\u003e \u003cp\u003eIn an earlier study in our study population, home range size, examined for one group (a group that split into Mst and Sst later) over six years, was positively affected by the number of males, but not the total group size, after controlling for ecological factors (home range size also increased with decreasing rainfall and with an interaction of food abundance and distribution: Richter et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This result was not replicated in the current study, with data collected in later years on more groups. In contrast to the earlier study, strong collinearity between the number of adult males and group size did not allow us to disentangle the variance between the two. It is possible that the absence of demographic effects in our study is related the fact that the data were collected around several group splits: Mst and Sst had split in 2012, Mot and Sot in 2014, and Mst split again in 2020. These changes could have disrupted the associations between demographic factors and ranging patterns. Data density also differed between studies, with 75 data points per group in the previous study and 19 data points per group on average in the current study. Finally, a potentially relevant difference between the two studies is that the group examined by Richter et al. (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) was the only habituated group at that time. This could have allowed less constrained home range expansion, compared with four groups examiend in the current study, which were all habituated to the presence of human observers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003ePossible reasons for non-territoriality in Assamese macaques\u003c/h2\u003e \u003cp\u003eTaken together, our findings provide evidence for the existence of both within- and between-group competition in Assamese macaques. This, in turn, raises the question of why the macaques do not defend their home ranges from neighboring groups to decrease the competition. It has been suggested that a pre-requisite for the evolution of territoriality is the economic defendability of resources. In a comparative study across primates, territorial species were all found to present a D-index larger than 1, whereas most non-territorial species presented a D-index less than 1, indicating that their daily travel distances were not long enough to cross the home range, which suggests that the D-index reflects aspects of economic defendability (Mitani and Rodman 1979). Our finding of D-index sometimes exceeding 1 in Assamese macaques when calculated for 3-month home ranges may help explain the pattern of temporal partitioning we observed, where home ranges overlapped less when assessed over the shorter temporal scale (annual vs. 3-months).\u003c/p\u003e \u003cp\u003eWhile mobility around the range is required for territorial defense, high mobility itself is not a sufficient condition for the evolution of territoriality (Mitani and Rodman 1979). Indeed, the fit between economic defendability and range defense is far from perfect, and there are taxa where territoriality is absent, although it would be expected from the perspective of defendability (Willems et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Mitani and Rodman 1979; Grant et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). One explanation suggested for the absence of territoriality in such taxa invokes a collective action problem (Willems et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Willems and Van Schaik 2015; Nunn \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Willems et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Because benefits gained from collective range defense are collective benefits, i.e., they are shared not only by active defenders, but by the whole group, including individuals which did not participate, natural selection should favor the emergence of free-riders. These free-riders would reap benefits without incurring the costs of producing them, and free-riding is expected to become more prominent with increasing number of individuals of the larger sex in a group (Willems et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Indeed, in a large comparative study across primates, increased home range overlap, after controlling for economic defendability, was associated with larger group size, the presence of multiple males and females, groups having multiple individuals of the larger sex, and habitual dispersal by the larger sex; all these findings can be interpreted as evidence for a collective action problem hampering range defense (Willems et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Assamese macaques meet all these criteria, so it is conceivable that their non-territoriality is related to the collective action problem. The current study did not replicate the earlier finding that home range size increases with the number of males (Richter et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), so the Assamese macaques fit the general expectations of the collective action problem.\u003c/p\u003e \u003cp\u003eRegardless of the collective action problem, Assamese macaques exhibit most of the traits that have been associated with high home range overlap in other studies. In a comparative study across 100 primate species, home range overlap was shown to be higher for larger-bodied species living in large home ranges at high population densities, where annual rainfall is low, and was higher for arboreal than terrestrial species (Pearce et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Assamese macaques are arboreal, relatively large-bodied, and the home ranges at our study site were relatively large, in the upper quartile of the dataset of Pearce et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) (219 ha, home range size in our study: 266\u0026ndash;848 ha). In accordance with this, the mean home range overlap of 69% observed in our study puts Assamese macaques above the upper quartile of the overlap range reported for primates (Willems et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Pearce et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). It is also close to the mean overlap observed in other macaque species (63% in Willems et al. (\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); 51% in Pearce et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2013\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eWhile the absence or presence of territoriality tends to be a fixed species trait, home range overlap, in contrast, was shown to be very plastic (Pearce et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The degree of overlap is influenced not only by conserved species traits, such as body size or social organization (Pearce et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Willems et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), but also by traits that can show variability within species or population, such as home range size, population density, rainfall, resource availability, or social factors (Carpenter and MacMillen \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Maher and Lott 2000; Morrell and Kokko 2005; Mcloughlin et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Jos\u0026eacute;-Dom\u0026iacute;nguez et al. 2015). The wide range of home range overlap observed at our study site (30\u0026ndash;100%), as well as among study sites in many other species (Pearce et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Willems et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) further supports the idea of a gradient between non-territoriality and territoriality (Seiler et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Morrell and Kokko 2005). Exclusive use of an area can be achieved not only by active defense of a territory but also by space partitioning and mutual avoidance (B\u0026ouml;rger et al. 2008; Brown and Orians \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1970\u003c/span\u003e). Therefore, even non-territorial species with high home range overlap can maintain some degree of exclusivity in their use of space, as demonstrated by this and other studies (e.g., Seiler et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Markham et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Wartmann et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Ultimately, the degree of territoriality and exclusivity are influenced by intraspecific competition for food and mates. For example, animals having access to abundant food resources and exhibiting low competition for mates may have no reasons to maintain neither territoriality nor exclusivity (e.g., Guinea baboons: Ohrndorf et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). By contrast, animals feeding on limited resources, with high competition for breeding opportunities, may be highly territorial and exhibit no overlap of home ranges (e.g., common marmosets, \u003cem\u003eCallithrix jacchus\u003c/em\u003e: Lazaro-Perea \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The absence of territoriality combined with some degree of exclusivity in Assamese macaques puts them in the middle of a gradient between non-territoriality and territoriality. Patterns of space partitioning and avoidance demonstrated in our study further suggest that Assamese macaques do experience intraspecific competition for food and/or mates and actively avoid their neighbors to lower the competition.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the National Research Council Thailand and the Department of National Parks Thailand for permission to conduct research in a protected area. We are grateful to K. Kreetiyutanont, M. Kumsuk, N. Kanjana and J. Prabnasuk (PKWS) for their cooperation, support, to all field assistants, D. Bootros, N. Bualeng, H. Drew, R. Intalo, N. Juntuch, S. Jumrudwong, M. Karlstetter, T. Kilawit, B. Klaewklar, W. Nueorngshiyos, N. Ponganan, K. Srithorn, W. Wisate, J. Wanart and coordinators A. Ebenau and M. Swagemakers for their excellent help.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) \u0026ndash; GRK2906 \u0026ndash; project number\u0026nbsp;\u003c/strong\u003e254142454 / GRK 2070.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD: Conceptualization, Formal analysis, Visualization, Writing \u0026ndash; original draft\u003c/p\u003e\n\u003cp\u003eSMe: Project administration, Writing \u0026ndash; review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eSMa: Project administration, Writing \u0026ndash; review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003ePS: Investigation, Data curation, Writing \u0026ndash; review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eOS: Conceptualization, Resources, Supervision, Writing \u0026ndash; review \u0026amp; editing\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJO: Conceptualization, Resources, Supervision, Writing \u0026ndash; review \u0026amp; editing\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe adhered to the guidelines for the ethical treatment of nonhuman animals in research and teaching of the Association for the Study of Animal Behaviour (ASAB Ethical Committee/ABS Animal Care Committee 2023). All methods used in the study were strictly non-invasive, i.e. the animals were never caught or fed. The study was approved by the Department of National Parks, Wildlife and Plant Conservation Thailand (permit numbers 0002/17 Jan. 2\u003csup\u003end\u003c/sup\u003e 2013, 0002/2424 April 23\u003csup\u003erd\u003c/sup\u003e 2014, 0002/47026 Jan. 26\u003csup\u003eth\u003c/sup\u003e 2016, 0002/4137 June 9\u003csup\u003eth\u003c/sup\u003e 2017) under a benefit sharing agreement. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData supporting the findings of this study are available in the Supplementary Material and on https://doi.org/10.25625/O2ZIJ2.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlbert, Aur\u0026eacute;lie, Tommaso Savini, and Marie‐Claude Huynen. 2011. \u0026lsquo;Sleeping Site Selection and Presleep Behavior in Wild Pigtailed Macaques\u0026rsquo;. \u003cem\u003eAmerican Journal of Primatology\u003c/em\u003e 73 (12): 1222\u0026ndash;30. https://doi.org/10.1002/ajp.20993.\u003c/li\u003e\n\u003cli\u003eAnz\u0026agrave;, Simone, Michael Heistermann, Julia Ostner, and Oliver Sch\u0026uuml;lke. 2025. \u0026lsquo;Early Prenatal but Not Postnatal Glucocorticoid Exposure Is Associated with Enhanced HPA Axis Activity into Adulthood in a Wild Primate\u0026rsquo;. \u003cem\u003eProceedings of the Royal Society B: Biological Sciences\u003c/em\u003e 292 (2039): 20242418. https://doi.org/10.1098/rspb.2024.2418.\u003c/li\u003e\n\u003cli\u003eArbon, Josh J, Amy Morris-Drake, Julie M Kern, Luca Giuggioli, and Andrew N Radford. 2024. \u0026lsquo;Social and Seasonal Variation in Dwarf Mongoose Home-Range Size, Daily Movements, and Burrow Use\u0026rsquo;. \u003cem\u003eBehavioral Ecology\u003c/em\u003e 35 (6): arae082. https://doi.org/10.1093/beheco/arae082.\u003c/li\u003e\n\u003cli\u003eASAB Ethical Committee/ABS Animal Care Committee. 2023. \u0026lsquo;Guidelines for the Ethical Treatment of Nonhuman Animals in Behavioural Research and Teaching\u0026rsquo;. \u003cem\u003eAnimal Behaviour\u003c/em\u003e 195 (January): I\u0026ndash;XI. https://doi.org/10.1016/j.anbehav.2022.09.006.\u003c/li\u003e\n\u003cli\u003eAsensio, Norberto, Colleen M. 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Chapman. 1993. \u0026lsquo;Constraints on Group Size in Primates and Carnivores: Population Density and Day-Range as Assays of Exploitation Competition\u0026rsquo;. \u003cem\u003eBehavioral Ecology and Sociobiology\u003c/em\u003e 32 (3). https://doi.org/10.1007/BF00173778.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"behavioral-ecology-and-sociobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"beas","sideBox":"Learn more about [Behavioral Ecology and Sociobiology](http://link.springer.com/journal/265)","snPcode":"265","submissionUrl":"https://www.editorialmanager.com/beas/default.aspx","title":"Behavioral Ecology and Sociobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Between-group competition, group size, home range overlap, territoriality, space partitioning, macaques","lastPublishedDoi":"10.21203/rs.3.rs-8432416/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8432416/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBetween-group competition in territorial taxa is evident in patrolling and avoidance behaviors. In non-territorial animals, signs of competition are more subtle, and little is known about how neighbors use their shared space. We investigated space use in four groups of wild, non-territorial Assamese macaques (\u003cem\u003eMacaca assamensis\u003c/em\u003e). Using locational data collected over six years, we quantified group ranging patterns to identify factors influencing home range size and daily travel distances, and investigated spatial relationships among neighboring groups by examining the patterns of shared use of space and sleeping trees. We found that daily travel distances were positively affected by group size and day length, but not fruit availability, while home range size was not influenced by any of the examined variables. Despite considerable home range overlap between groups, we found evidence for spatial and temporal landscape partitioning. Groups used their core areas more exclusively than entire home ranges and preferred to sleep within the core areas. Additionally, home ranges overlapped less when assessed over shorter time scale (annual vs. 3-month intervals). The analysis of spatial dynamics between simultaneously tracked groups demonstrated that patterns of avoidance or attraction were influenced by demographic history and possibly by the distribution of food resources. These findings show that space use in Assamese macaques is influenced by between-group competition and feeding needs. Our study suggests that even in the absence of territoriality, non-territorial species can maintain some exclusivity in their space use via avoidance behaviors to reduce competition with neighbors.\u003c/p\u003e","manuscriptTitle":"Shared space use and avoidance among groups of wild non-territorial Assamese macaques","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-06 20:29:06","doi":"10.21203/rs.3.rs-8432416/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"326305468052654560305369058061149660871","date":"2026-05-04T14:08:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324668950914871910392761445284277463824","date":"2026-01-14T10:26:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-12T07:52:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-02T09:42:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-02T06:39:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Behavioral Ecology and Sociobiology","date":"2025-12-23T10:34:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"behavioral-ecology-and-sociobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"beas","sideBox":"Learn more about [Behavioral Ecology and Sociobiology](http://link.springer.com/journal/265)","snPcode":"265","submissionUrl":"https://www.editorialmanager.com/beas/default.aspx","title":"Behavioral Ecology and Sociobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"81882cb2-49e9-4d6d-bfc8-a4321a8dab69","owner":[],"postedDate":"March 6th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"326305468052654560305369058061149660871","date":"2026-05-04T14:08:22+00:00","index":34,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-06T20:29:06+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-06 20:29:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8432416","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8432416","identity":"rs-8432416","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}