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Fruit availability has a complex relationship with fission-fusion dynamics in spider monkeys


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Understanding the ecological and social factors that influence group size is a major focus of primate behavioural ecology. Studies of species with fission-fusion social organizations have offered an insightful tool for understanding ecological drivers of group size as associations change over short temporal and spatial scales. Here we investigated how the fission-fusion dynamics of spider monkeys (Ateles geoffroyi) at Runaway Creek, Belize were affected by fruit availability. When males and females were analyzed together, we found no association between fruit availability and subgroup size. However, when females were analyzed separately, we found that when fruit availability increased, so did subgroup size. In all analyses, higher fruit availability did not influence subgroup spatial cohesion. Our results point to the complexity of understanding grouping patterns, in that while ecological factors make groups of specific sizes advantageous, social factors also play an important determining role.
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Fruit availability hasacomplex relationship withssion–fusion
dynamics inspider monkeys
KaylaS.Hartwell1· HughNotman1,2· UrsKalbitzer3,4 · ColinA.Chapman5,6,7 · MaryM.S.M.Pavelka1
Received: 3 September 2019 / Accepted: 30 August 2020
© Japan Monkey Centre and Springer Japan KK, part of Springer Nature 2020
Understanding the ecological and social factors that influence group size is a major focus of primate behavioural ecology.
Studies of species with fission–fusion social organizations have offered an insightful tool for understanding ecological driv-
ers of group size as associations change over short temporal and spatial scales. Here we investigated how the fission–fusion
dynamics of spider monkeys (Ateles geoffroyi) at Runaway Creek, Belize were affected by fruit availability. When males
and females were analyzed together, we found no association between fruit availability and subgroup size. However, when
females were analyzed separately, we found that when fruit availability increased, so did subgroup size. In all analyses,
higher fruit availability did not influence subgroup spatial cohesion. Our results point to the complexity of understanding
grouping patterns, in that while ecological factors make groups of specific sizes advantageous, social factors also play an
important determining role.
Keywords Subgroup· Group size· Food resources· Ateles geoffroyi
Animal social groups vary along a continuum from highly
cohesive (low fission–fusion dynamics) to highly fluid
(high fission–fusion dynamics; Aureli etal. 2008; Strier
1989). Group-living animals tend toward cohesiveness,
forming social groups in which members synchronize their
movements and activity, but species with a high degree of
fission–fusion dynamics do not. Species in this latter type of
grouping pattern include Tursiops spp. (Dolphins, Connor
and Wells 2000), several species of bats (Altringham and
Senior 2006; Bradbury and Vehrencamp 1976), chimpan-
zees (Pan troglodytes), and Ateles (spider monkeys, Chap-
man etal. 1995; Symington 1990). Group members often
leave (fission) and join (fusion) others, and thus subgroups
are frequently changing their size, composition, and spatial
Theory predicts that high fission–fusion dynamics
mitigates the costs of group living by adjusting subgroup
size to changes in the spatial and temporal availability of
food resources (Chapman 1990a; Chapman and Chapman
2000; Klein and Klein 1977; Wrangham and Smuts 1980).
Researchers argue that by foraging in smaller subgroups,
individuals can reduce feeding competition and time spent
travelling between food resources (Chapman and Chap-
man 2000; Korstjens etal. 2006; Lehmann etal. 2007).
Consequently, larger food patches or high food density
should be able to support larger subgroups, and vice versa.
While current theory focuses on the spatial and temporal
variation in food supply as the primary factor influenc-
ing variation in grouping patterns, other parameters, such
as group demographic structure (Altmann and Altmann
* Colin A. Chapman
1 Department ofAnthropology andArchaeology, University
ofCalgary, Calgary, AB, Canada
2 Centre forSocial Sciences (Anthropology), Athabasca
University, Athabasca, AB, Canada
3 Department fortheEcology ofAnimal Societies, Max Planck
Institute ofAnimal Behavior, Radolfzell, Germany
4 Department ofBiology, University ofKonstanz, Konstanz,
5 Department ofAnthropology, Center fortheAdvanced Study
ofHuman Paleobiology, The George Washington University,
Washington, DC20037, USA
6 School ofLife Sciences, University ofKwaZulu-Natal,
Scottsville, Pietermaritzburg, SouthAfrica
7 Shaanxi Key Laboratory forAnimal Conservation, Northwest
University, Xi’an, China
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1979), neighboring group number and composition (Aureli
etal. 2006; Chapman etal. 1989), and climatic conditions
(Schaffner etal. 2012), likely play a role, but here we focus
on food availability.
The actual relationship between food availability and
subgroup size, however, is not clear, and research in this
area has yielded conflicting results (Aguilar-Melo etal.
2018; Asensio etal. 2009; Pinacho-Guendulain and Ramos-
Fernández 2017). In chimpanzees and spider monkeys, for
example, some studies have found a positive correlation
between temporal variation in habitat-wide fruit availability
and the size of subgroups (Chapman etal. 1995; Mitani etal.
2002; Shimooka 2003; Symington 1990), while others have
found little or no correlation (Hashimoto etal. 2003; Hohm-
ann and Fruth 2002; Newton-Fisher etal. 2000; Wakefield
2008). A study on spider monkeys (A. hybridus) living in a
small fragment in Colombia revealed that subgroups were
smaller when fruit availability was high compared to when
it was low; the opposite to what would be expected (Rim-
bach etal. 2014). While the authors of this study concede
that the fragmented habitat may have affected subgrouping
patterns in this population, the conflicting results between
this research and other studies indicate that factors other
than fruit availability affect subgroup size, or that there are
other aspects to fruit availability affecting subgroup size to
be understood. The conflicting results of studies on both
primate genera may also be due to different methodology
and/or the difficulty of quantifying fruit availability.
Spider monkeys are ripe fruit specialists, and ripe fruit
typically constitutes > 75% of their diet, supplemented with
young leaves, flowers, seeds, and sometimes decayed wood,
insects, and other small prey items during periods of fruit
scarcity (reviewed in Di Fiore etal. 2008; González-Zamora
etal. 2009). Those populations living in highly seasonal
forests (Stevenson etal. 2000; Wallace 2005), small for-
est fragments (Chaves etal. 2012; Rimbach etal. 2014), or
areas damaged from hurricanes or fires (Champion 2013;
Schaffner etal. 2012) cope with periods of fruit scarcity
by increasing their consumption of leaves and including a
greater variety of food items in their diet (Chapman 1987;
González-Zamora etal. 2009).
Here we quantify the feeding ecology of spider monkeys
(Ateles geoffroyi yucatanensis) at Runaway Creek, Belize to
examine the relationship between fruit availability and sub-
grouping dynamics using behavioural and ecological data
collected over five and a half consecutive years. Our objec-
tives are, first, to quantify the diet of this spider monkey pop-
ulation; second, to evaluate the effect of fruit availability on
diet; and third, to build on these data to examine the theory
that proposes a relationship between fruit availability and
two important aspects of fission–fusion dynamics: subgroup
size and subgroup spatial cohesion. In the middle of our
study, a Category 2 hurricane passed over the area, causing
substantial habitat damage, providing a unique opportunity
to examine grouping dynamics under extreme conditions.
Socio-ecological theory predicts that greater fruit avail-
ability will lead to larger group size; thus we expect that
spider monkeys will follow this general theoretical pattern
(Asensio etal. 2009; Chapman 1990a, b; Shimooka 2003;
Wrangham etal. 1993). In addition, we anticipate that peri-
ods of high fruit availability will lead to more cohesive
subgroups, as individual monkeys tolerate closer inter-indi-
vidual proximity as contest competition is reduced (Asen-
sio etal. 2009; Chapman 1988; Symington 1988a, 1988b).
Since the reproductive strategies of males and females dif-
fer, with females trying to maximize access to food while
males first try to increase mating opportunities (Wrangham
1980), we considered how subgroup size and subgroup spa-
tial cohesion varied as a function of fruit availability for
females separately.
Study site andstudy group
Runaway Creek Nature Reserve is a 2469-ha private reserve
in central Belize, located 11km inland from the Caribbean
coast. The reserve has two main vegetation zones: pine
savannah and low broadleaf, semi-deciduous tropical for-
est. The forest comprises steep karst hills with caves, low
valleys, and seasonal swamps and is connected to approxi-
mately 58km2 of similar habitat to the west but is otherwise
surrounded by pine savannah and citrus plantations. This
area has a dry season from December to May and a wet sea-
son from June to November and receives 2000–2200mm of
rain annually (Meerman 1999).
Between 2008 and 2014, we studied the behaviour and
ecology of spider monkeys at Runaway Creek. All indi-
viduals in the community were habituated to researchers’
presence and individually recognizable. Over this time, the
community ranged in size from 31 to 37 individuals (5–7
adult males, 12–14 adult females, and 12–18 immatures)
due to births, immigrations, disappearances, and immatures
maturing to adulthood.
Behavioural data collection
Behavioural data were collected in full- or part-day follows
by KH with the help of trained graduate students and field
assistants. Individual identification of spider monkeys is a
difficult task and typically must be made by subtle differ-
ences in coat colour, freckling patterning around the eyes,
and characteristic of the genitalia unless there are obvious
scars or injuries; thus KH was responsible for individual
identification, which removed inter-observer error. We
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defined a subgroup using a “chain-rule” (Ramos-Fernán-
dez 2005; we followed the same procedure, but obtained a
slightly larger cut-off point) and considered any individual
seen within 50m of another individual as part of the same
subgroup. “Fissions” occurred when an individual or group
of individuals moved more than 50m from any other sub-
group member, and “fusions” occurred when an individual
moved within 50m of another subgroup member. When
subgroups are more than 50m apart, it is unlikely that they
can efficiently visually track each other, and it is not possible
for an observer following one subgroup to also monitor the
second subgroup.
During a subgroup follow, we conducted an instantaneous
scan sample every 30min to record the subgroup size and
composition, the subgroup spread (defined below), and the
identity and behaviour of each monkey. The 30-min interval
was used to ensure that the observer could be with the sub-
group in the difficult terrain and adequately evaluate compo-
sition, and to partially ensure the independence of the obser-
vations. When a monkey was feeding, we recorded the plant
part [ripe and unripe fruit, young and mature leaves, flowers,
other (insect, limestone, and soil)]. Our identification was
aided by considerable efforts made by previous research-
ers who have worked in the area and who had sought the
help of botanists and local plant experts (Behie and Pavelka
2005; Behie and Pavelka 2013; Griffin 2013; Hartwell 2016;
Hartwell etal. 2014), but if the taxonomic identity of a tree
was unknown, it was flagged for later identification with the
assistance of a botanist, including Drs. Steven Brewer and
Colin Young. This was an ongoing process throughout the
five and a half years of study and was aided by a local veg-
etation expert and the assigning of common names to start
the identification process. Vines are particularly difficult
to identify because voucher specimens are hard to obtain,
but we were able to identify all the major vines used by
the spider monkeys to species (n = 7) or genus level (n = 3).
We monitored a phenology trail twice a month, but for the
analysis of fruit availability, we included one phenology
sample per month to calculate a monthly fruit availability
score (n = 52), as this is how data of this nature are typically
reported. This score was analysed in relation to size and
spread of subgroups drawn from 1week before and 1week
after the date of the phenology sample used to determine the
fruit availability score.
Our data comprise 4770 subgroup scans collected over
67months on 1033days from January 2008 to September
2013. A total of 6428h were spent in the forest searching,
while 2686h were spent in visual contact with monkeys; this
difference is due to the difficulty in following fast-travelling
spider monkeys over the steep karst hills and cliffs that char-
acterize the terrain, and the density of the animals. On 25th
October 2010, in the middle of the study, a Category 2 hur-
ricane (Hurricane Richard) passed over the area, causing
extensive habitat damage, which was exacerbated 6months
later by forest fires (Champion 2013). The tree falls after
the hurricane made it even more difficult to follow these
fast-moving animals.
Measures ofssion–fusion dynamics
For the following measures of fission–fusion dynamics
(described below), we used data on independently travelling
individuals; thus, we treated adults and subadults (approxi-
mately 5years of age—the age was estimated based on
observing animals in this population grow, maturity was
based on when individuals started to reproduce and on body
size) as independent individuals and excluded immatures
(< 5years of age). Subgroup spatial cohesion is sometimes
measured directly using subgroup spread; however, spread
is likely not independent of subgroup size, as larger sub-
groups are likely to occupy more area. To account for dif-
ferent subgroup sizes, we therefore built models with the
spread of the subgroup, measured in meters between the
two individuals furthest apart, as the outcome variable, and
included the number of individuals in addition to fruit avail-
ability as predictor variable (see below). Thus, this model
tests whether fruit availability affects the spread of a sub-
group after accounting for the effect of subgroup size. This
approach estimates how fruit availability is associated with
the space available to each individual (i.e., subgroup spatial
cohesion), assuming they are spaced evenly within a sub-
group. In contrast to the investigation of subgroup sizes,
we here included only subgroups containing at least two
Vegetation data
We sampled twenty-one 40 × 40m (total 3.36ha) vegetation
plots in the group’s range and in all habitats used, which
include swamp, low valley, karst hilltop, ridge side, and the
vegetation that is transitional between forest and savanna.
We identified and measured the diameter at breast height
(DBH) of all trees over 10cm DBH. If a tree species was
unknown, we flagged the tree for later identification with
the assistance of a botanist (see above). A tree’s DBH is an
indicator of the size of the tree and has been shown to reflect
the tree’s fruit production (Chapman etal. 1992). We then
calculated species basal area (sum of the area for each tree of
species A) and species dominance (total basal area of species
A/total area sampled).
To track temporal variation in ripe fruit availability, we
monitored a phenology trail monthly from January 2009 to
July 2013. The trail included 225 trees from 15 food tree
species, each represented by 15 individual trees. We chose
species for the phenology trail based on the tree species
that constituted greater than 2% of the population’s diet
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(Table1). Each phenology tree was scored with an estimate
of ripe fruit as 0, 25, 50, 75, or 100%. We then took the mean
proportion ripe fruit coverage score for each tree species and
multiplied it by the dominance value for that species. To
provide a monthly ripe fruit availability score, we summed
all scores across the 15 species for each month. Hereafter,
fruit availability refers to ripe fruit availability score.
Data analysis
We quantified the diet composition as the proportion of feed-
ing records devoted to the different plant parts (ripe fruit,
unripe fruit, immature leaves, mature leaves, flowers, and
“other”). We then describe the general changes in the diet
of spider monkeys across years. To investigate how diet is
affected by environmental factors, we first explore the rela-
tionship between fruit availability, season, and the occur-
rence of the hurricane. To do so, we calculated a Bayes-
ian model with fruit availability as the outcome variable
and either season or hurricane as the categorical predictor
variable. For the effect of the hurricane, we calculated two
separate models: First, we compared the availability of fruit
between the entire period before versus the entire period
after the hurricane (pre- vs. post-hurricane). Then, we com-
pared the 12months directly following the hurricane with
all other months (post 12months vs. other periods). Because
each month should be similar to the same month in other
years, we included month as a grouping variable (similar
to a random effect in a model using a frequentist approach).
However, because of the high variability in fruit availabil-
ity within and across years (see “Results”), and because we
assume that the availability of ripe fruit is more important
for the composition of the diet and behaviour of spider mon-
keys than season or the occurrence of the hurricane per se,
we use fruit availabilityas predictor variable in all of the
following models.
To investigate how fruit availability is linked to diet, we
calculated a Bayesian multinomial (or categorical) model,
with records of eaten plant parts (see above) as the outcome
variable and the availability of ripe fruit as predictor vari-
able. We used such a multinomial model to account for the
dependence of the different proportions of eaten food parts
(i.e., a larger proportion of one food part makes lower pro-
portions of the other food parts more likely). To account for
the dependence of records collected during the same month
and linked to the same monthly fruit availability score, we
also included the month in combination with the specific
year (e.g., January 2010; hereafter year-month) as a group-
ing variable.
To investigate the fission–fusion dynamics in relation to
fruit availability, we calculated a Bayesian model with the
outcome variable subgroup size and the predictor variable
fruit availability. Because subgroup size is a count variable,
and first model attempts indicated that this model was over-
dispersed, we used a model with a negative binomial like-
lihood function. Furthermore, we specified that the value
of the outcome variable group size was limited to values
larger than 0 (because subgroups with a size of 0 do not
exist). We included the date of data collection as grouping
variable to account for the dependence of different group
scans recorded on the same day. Furthermore, we included
the date of phenology data collection linked to the 2-week
period of behavioural data as grouping variable because all
behavioural data within these 2weeks were linked to the
same fruit availability score.
Finally, to investigate how fruit availability affects the
cohesion of subgroups, we calculated a model with subgroup
spread (in meters) as the outcome variable, and the size of
the subgroup and fruit availability as predictor variables. As
outlined above, this model tests whether fruit availability
affects the spread of a subgroup after accounting for the
effects of subgroup size, which reflects the cohesion of a
subgroup. We considered the spread in meters as a count
variable and fitted a model with a Poisson distribution. As
for the model for subgroup size, we included date of data
collection and the associated phenology date as grouping
As male and female reproductive strategies and competi-
tive regimes differ (Chapman etal. 1995; Wrangham 1980),
the two analyses for subgroup sizes and spread were con-
ducted both for all adults and just for subgroups with female
members only.
All models were fitted with the brms package v. 2.13.3v
(Bürkner 2017, 2018) in R v. 4.0.2 (R-Core-Team 2020).
We used the default priors, four chains and 2000 iterations,
Table 1 List of phenology tree species monitored in this study and
their percentage in the spider monkey diet at Runaway Creek, Belize
Family Genus Species % Diet
Moraceae Ficus insipida 14
Sapotaceae Manilkara staminodella 10
Moraceae Ficus pertusa 8
Arecaceae Attalea cohune 8
Burseraceae Protium copal 8
Anacardiaceae Metopium brownei 7
Anacardiaceae Spondias radlkoferi 6
Moraceae Pseudolmedia spuria 5
Arecaceae Sabal yapa 4
Moraceae Brosimum alicastrum 4
Ulmaceae Ampelocera hottlei 3
Caesalpiniaceae Dialium guianense 3
Fabaceae Caesalpinia gaumeri 3
Moraceae Trophis racemosa 2
Simaroubaceae Simarouba glauca 2
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which resulted in stable models with relatively large effec-
tive sample sizes (Bulk_ESS and Tail_ESS all above 1000)
and Rhat values equal to 1.
Diet composition
The monkeys fed on 121 plant species from 83 genera and
47 families. Three families (Moraceae, Anacardiaceae, and
Arecaceae) represented over half of their diet, and most nota-
bly, Moraceae constituted 39% of all plant items consumed.
Their overall diet was composed of 60% fruit (48% ripe and
12% unripe fruit), 30% young leaves, 8% flowers, and 0.5%
“other” items (limestone, soil, and insect eggs). The remain-
ing 1.5% of their diet were items that were unknown and/or
could not be identified. The diet composition varied over the
five and a half years of study (Fig.1).
Seasonal dierences indiet
There were two fruiting peaks in an annual cycle: one
smaller peak at the very end of the dry season (May) and a
larger fruiting peak toward the end of the wet season (around
October; Fig.2a). However, there was considerable variation
within and across years, and differences in fruit availability
between the wet and dry season were not consistent (Table2,
model a). With regard to the occurrence of the hurricane,
the model indicated that fruit availability tended to be lower
during the months following the hurricane (Table2, model
b; Fig.2b and c), and this difference was more pronounced
when only considering the 12months directly following
Fig. 1 Yearly variation in dietary composition of spider monkeys at
Runaway Creek from 2009 to 2013. The dashed line indicates Hur-
ricane Richard, which occurred on 25th October 2010
Fig. 2 Temporal changes in monthly fruit availability scores across
2009–2013. Changes are shown for the entire study duration (a), and
the period before (b) and after (c) the hurricane. Each line repre-
sents a single year, and the grey shaded area in a denotes the monthly
mean ± SE. The dark blue horizontal line in each of the plots indi-
cates the wet season
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the hurricane in comparison to all other periods (Table2,
model c). However, as for season, there was considerable
variation within and across years. Therefore, fruit availabil-
ity scores seem to be a more meaningful predictor variable
for behavioural variables than either season or hurricane,
and we therefore use monthly fruit availability scores in the
following models.
Diet andfruit availability
The multinomial model indicated that as fruit availabil-
ity increased, the proportion of fruit in the diet increased,
whereas the proportion of leaves, unripe fruit, and flowers
decreased [Table3; for an easier interpretation of these coef-
ficients, which are on a logit-scale and in relation to the
Table 2 Results of the models
testing for an effect of season
and hurricane on monthly fruit
In addition to the median of the estimate, the boundaries of the 95% credibility interval of the posterior dis-
tribution are shown in the table (CI95 low and high). Fruit availability was scaled to a mean of 0 and a SD
of 1 before calculating the models
Model Parameter Estimate (median) CI95_low CI95_high
a. Season Intercept −0.09 −0.55 0.42
Season (wet) 0.21 −0.51 0.96
b. Hurricane (pre vs. post) Intercept 0.31 −0.14 0.79
Hurricane (post) −0.51 −1.06 0.02
c. Hurricane (within 12months
post vs. other periods)
Intercept 0.17 −0.19 0.55
(12months post)
−0.68 −1.28 −0.03
Table 3 Results of the multinomial model testing for an effect of fruit
availability on the proportion of ripe fruit, unripe fruit, leaves, and
flowers in the diet of spider monkeys
The parameter estimates for the intercepts and the effects of fruit
availability for the different food items are in relation to the propor-
tion of eaten flowers (the pivot in this model). Fruit availability was
scaled to a mean of 0 and a SD of 1 before calculating the model
Parameter Estimate (median) CI95_low CI95_high
Ripe fruit—Intercept 2.17 1.76 2.6
Unripe fruit—Intercept −0.07 −0.76 0.51
Leaves—Intercept 1.97 1.56 2.38
Ripe fruit—Fruit avail-
1.07 0.63 1.55
Unripe fruit—Fruit avail-
0.14 −0.56 0.84
Leaves—fruit availability 0.46 0.02 0.89
Fig. 3 Proportion of ripe fruit,
unripe fruit, leaves, and flowers
in the diet of spider monkeys
in relation to monthly ripe fruit
availability. The circles show
the observed proportion of
different food items in the diet,
combined for four different
intervals of ripe fruit avail-
ability. The area of the circles
is proportional to the number
of feeding events included. The
lines illustrate the model predic-
tions of the multinomial model
shown in Table3, with the
shaded areas showing the 95%
credibility intervals
1 3
pivot, flowers in this case, the effects are illustrated in Fig.3;
see (McElreath 2020)].
When fruit availability was low, the spider monkeys
increased their consumption of flowers (primarily from Bro-
simum alicastrum, Pseudobombax ellipticum, and the vine
Combretum fruticosum) and preyed on the seeds of unripe
fruit from Brosimum alicastrum, Pseudolmedia spuria, and
Caesalpinia gaumeri.
Fruit availability andssion–fusion dynamics
The calculated model indicated no clear evidence for a rela-
tionship between the availability of ripe fruit and the size
of the subgroups (Table4, Fig.4a) or fruit availability and
subgroup cohesion (Table5, Fig.5a).
To assess how fruit availability might affect female sub-
grouping patterns when males were not present, we re-ran
the analyses on all-female subgroups, omitting all-male and
mixed-sex subgroups. Here, fruit availability was positively
related to the size of subgroups consisting of only females
(Table4; Fig.4b). However, there was no such relationship
for fruit availability and the spread of female-only subgroups
(Table5; Fig.5b).
Our study of the spider monkeys at Runaway Creek
revealed a complex set of relationships between food avail-
ability, diet, and subgroup dynamics. Diet was variable
from year to year, but consistently contained a large pro-
portion of fruit. Fruit availability positively predicted the
amount of fruit in their diet. Spider monkeys are typically
characterized as ripe fruit specialists, and between roughly
Table 4 Results of the negative binomial models testing for the rela-
tionship between fruit availability and size of spider monkey sub-
Fruit availability was scaled to a mean of 0 and SD of 1 before calcu-
lating the models
Included indi-
Parameter Estimate
CI95_low CI95_high
All individuals Intercept 0.99 0.91 1.08
Fruit availability 0.05 −0.03 0.13
Females only Intercept 0.76 0.66 0.86
Fruit availability 0.10 0.00 0.19
Fig. 4 Relationship between fruit availability and the size of spider
monkey subgroups for all individuals (a) and for females only (b).
The circles indicate the observed size of subgroups, and the line the
predicted relationships from the models shown in Table4, with 95%
credibility intervals indicated by the shaded area
Table 5 Results of the Poisson models testing for the effect of fruit
availability and subgroup size on the spread of spider monkey sub-
Fruit availability and subgroup size were scaled to a mean of 0 and
SD of 1 before calculating the model
Included indi-
Parameter Estimate
CI95_low CI95_high
All individuals Intercept 26.03 24.08 27.95
Fruit availability 1.37 −0.51 3.35
Group size 6.57 5.65 7.45
Females only Intercept 26.51 24.13 28.74
Fruit availability 1.3 −1.02 3.63
Group size 6.14 4.79 7.52
1 3
75% and 90% of their diet is fruit (Di Fiore etal. 2008;
Wallace 2005). In our study, ripe fruit consumption never
exceeded 75%, but when unripe fruit is included, the cat-
egory of “fruit” accounts for 48–82% of their annual diet.
Ripe fruit consumption was highest before the hurricane,
as fruiting trees ceased fruit production in many parts of
the forest that sustained the most severe wind damage
(Champion 2013). Given this, our results are consistent
with previous studies demonstrating that spider monkeys
typically show a strong preference for fruit (Dew 2005;
Stevenson etal. 2000). However, our results also show that
spider monkeys can substitute leaves and flowers for fruit
when fruit availability is low (see also Chapman 1987).
In fact, leaf consumption approached 50% in 2012 after
the hurricane. In the post-hurricane years, both leaf and
flower consumption increased. A study of Ateles geoffroyi
in the Yucatan similarly found that the animals increased
the time spent feeding on leaves after a hurricane, and in
the dry seasons both pre- and post-hurricane, the mon-
keys spent more time eating leaves (Schaffner etal. 2012).
Similarly, Ateles belzebuth in Bolivia is highly frugivo-
rous, except for 1 or 2months during the dry season when
Fig. 5 Relationship between the spread of spider monkey subgroups
and subgroup size for all individuals (a) and for female-only sub-
groups (c), and between subgroup spread and fruit availability for all
individuals (b) and female-only subgroups (d). The circles indicate
the observed spread of subgroups, combined into regular intervals
for fruit availability and subgroup spread with the area proportional
to the number of scans. The lines indicate the predicted relationship
between the different variables from the models shown in Table5,
with 95% credibility intervals indicated by the shaded area. These
effects are conditional on a mean effect of the omitted variables; thus
a, c show the effects of subgroup size on subgroup spread conditional
on a mean value for fruit availability, and vice versa for b and d
1 3
leaves constitute up to 36% of their diet (Wallace 2005).
Spider monkeys did consume more fruit when fruit was
more abundant.
Our investigation of fission–fusion dynamics revealed
theoretically interesting complexities. High fission–fusion
dynamics is hypothesized to result from contest competi-
tion over patchily distributed and temporally unpredictable
fruit resources (Aureli etal. 2008; Janson 1988; Schaffner
etal. 2012). Accordingly, we predicted that larger subgroups
would occur during periods of higher fruit availability, and
we expected that subgroup spatial cohesion would increase
during periods of fruit abundance. When males and females
were analyzed together, we found no link between fruit
availability and subgroup size. However, when females
were analyzed separately, fruit availability did affect sub-
group size in the predicted direction. There are several ways
to interpret these results. One possibility is that males and
females associate at random with respect to fruit availabil-
ity, so male membership in subgroups was not affected by
fruit availability, but rather by social factors (see also Aureli
etal. 2006; Chapman etal. 1995). Interestingly, our prior
research has shown that this population of spider monkeys
are significantly sexually segregated for most months of the
year, and that males and females are more often segregated
during periods of higher fruit availability (Hartwell etal.
2014). This might explain why, when males were included in
this analysis, subgroup size did not increase with fruit avail-
ability, because it was during periods of relatively lower fruit
availability that larger, mixed-sex subgroups were formed,
possibly because they were attracted to the same few fruit-
ing trees. As female reproductive fitness is limited by access
to food, females are predicted to distribute themselves to
best take advantage of food resources and minimize contest
competition, thus rendering their behavioural patterns more
sensitive to ecological pressures, such as food availability
(Snaith and Chapman 2007; Wrangham 1979). In other
words, changes in fruit availability may be more accurately
reflected by variation in female subgrouping patterns than by
variation in all-male or mixed-sex subgroups, which could
reflect other factors, such as the availability of reproduc-
tively available females, the need for territorial defense, or
more consistent rates of association among males (Ramos-
Fernandez etal. 2009).
Higher fruit availability did not influence subgroup spa-
tial cohesion, and this result did not change when females
were analyzed separately. We expected higher fruit avail-
ability to lead to higher spatial cohesion, as closer inter-
individual proximity between subgroup members might be
tolerated when contest competition is potentially reduced;
however, we did not find this. It is possible that our measure
of spatial cohesion was too crude to capture the effects of
fruit availability. However, in a recent study by Aguilar-Melo
etal. (2020), the authors used inter-individual distances as
a measure of spatial cohesion and found a minimal effect of
fruit availability on proximity patterns. These authors con-
clude that social factors are more important than fruit avail-
ability in determining spatial cohesion within subgroups.
Similarly, for our study group, non-ecological factors such
as social preferences likely have a larger effect on spatial
cohesion, even for female subgroup members.
A growing body of evidence suggests that demographic
and social factors interact with ecological drivers in deter-
mining the spatial arrangement of group members (Fury
etal. 2013; Murray etal. 2007). Thus, examining such vari-
ables may help to refine our understanding of spider mon-
key subgrouping dynamics. Furthermore, future studies of
subgrouping dynamics may benefit from incorporating other
ecological measures of fruit availability that can influence
travel costs and food competition, such as patch size and
fruiting tree density and distribution throughout the home
range, and by considering the temporal dependency of the
variables [e.g., what is the temporal time scale over which
food items of each species are available (see also suggestions
in Asensio etal. 2009; Asensio etal. 2012a, b)]. In addition,
a consideration of foods less frequently consumed, but which
nonetheless are nutritionally important (e.g., sources of salt
Fashing etal. 2007; Rode etal. 2003; Rothman etal. 2012,
2006), will help understand fission–fusion dynamics more
Acknowledgements Thanks to Dr. Gil and Lillian Boese, Larry and
Cindy Law, the Foundation for Wildlife Conservation, and the Zoologi-
cal Society of Milwaukee for permission to work in the Runaway Creek
Nature Reserve. Thanks to Birds without Borders for their cooperation
and help. We are grateful to the following people who contributed to
data: Stevan Reneau, Brittany Dean, Kayley Evans, Jane Champion,
Gilroy Welch, Colin Dubreuil, and Meredith Brown. Furthermore, we
are grateful to the editor and two anonymous reviewers for their highly
valuable feedback. Our research was supported by the University of
Calgary, Athabasca University, and the Natural Sciences and Engineer-
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Some social species exhibit high levels of fission-fusion dynamics (FFD) that improve foraging efficiency. In this study, we shed light on the way that FFD allows animal groups to cope with fluctuations in fruit availability. We explore the relative contribution of fruit availability and social factors like sex in determining association and proximity patterns in spider monkeys. We tested the influence of fruit availability and social factors on the association and proximity patterns using three-year data from a group of spider monkeys in the Yucatan Peninsula of Mexico. We identified subgroup members and estimated their Interindividual distances through instantaneous scan sampling. We evaluated fruit availability by monitoring the phenology of the 10 most important food tree species for spider monkeys in the study site. Social network analyses allowed us to evaluate association and proximity patterns in subgroups. We showed that association patterns vary between seasons, respond to changes in fruit availability, and are influenced by the sex of individuals, likely reflecting biological and behavioral differences between sexes and the interplay between ecological and social factors. In contrast, proximity patterns were minimally affected by changes in fruit availability, suggesting that social factors are more important than food availability in determining cohesion within subgroups.
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