Changes in Activity Patterns and Intergroup Relationships After a Significant Mortality Event in Commensal Long-Tailed Macaques (Macaca Fascicularis) in Bali, Indonesia.
Int J Primatol (2015) 36:548–566
DOI 10.1007/s10764-015-9841-5
Changes in Activity Patterns and Intergroup
Relationships After a Significant Mortality Event
in Commensal Long-Tailed Macaques (Macaca
Fascicularis) in Bali, Indonesia
Fany Brotcorne 1,2 & Agustín Fuentes 3 &
I. Nengah Wandia 4 & Roseline C. Beudels-Jamar 2 &
Marie-Claude Huynen 1
Received: 28 June 2014 / Accepted: 2 April 2015 / Published online: 24 May 2015
# Springer Science+Business Media New York 2015
Abstract Little is known regarding behavioral and social responses of free-ranging
primates to demographic changes emerging from significant mortality events. Here, we
report on the activity patterns and intergroup sociospatial relationships in a commensal
population of long-tailed macaques (Macaca fascicularis) in Bali, Indonesia, that
underwent a significant mortality event in summer 2012. During the period of interest,
we noted heightened mortality in three of the five social groups present in this
population, with adult females and juveniles experiencing higher mortality rates than
adult and subadult males. Limited diagnostic data regarding pathogen identification and
a lack of any conclusive etiology of the deaths prevent our ascertainment of the agent(s)
responsible for the observed mortality, but given the characteristics of the event we
assume it was caused by a transmissible disease outbreak. Comparing the pre- and postmortality event periods, we found significant differences in activity patterns, including
a decreased proportion of affiliation in adult females. This result is likely indicative of
enhanced social instability induced by the high mortality of adult females that constitute
the stable core of macaque social structure. A higher social tension between groups
after the mortality event was indicated by more frequent and intense agonistic
* Fany Brotcorne
fbrotcorne@gmail.com
1
Primatology Research Group, Behavioural Biology Unit, University of Liège, 4020 Liège,
Belgium
2
Conservation Biology Unit, Education and Nature, Royal Belgian Institute of Natural Sciences,
1000 Brussels, Belgium
3
Department of Anthropology, University of Notre Dame, Notre Dame, IN 46556, USA
4
Primate Research Center, Universitas Udayana, 80361 Denpasar, Bali, Indonesia
Activity of Long-Tailed Macaques After a Mortality Event
549
intergroup encounters. Intergroup conflict success was inversely proportional to the rate
of mortality a group suffered. Our results illustrate how changes in demographic
structure caused by significant mortality events may have substantial consequences
on behavior and social dynamics in primate groups and at the level of a population.
Keywords Anthropogenic habitat . Bali Monkey Forest . Behavioral impact . Intergroup
relationship . Significant mortality . Social dynamics
Introduction
Pathogens are proposed as a significant ecological force in primate social systems
and behavior, with important effects on survival and reproduction (Nunn 2012;
Nunn and Altizer 2006). In Old World monkeys, mass mortality episodes caused
by infectious disease outbreaks have been reported (Bermejo et al. 2006;
Hanamura et al. 2008; Kaur et al. 2008; Leendertz et al. 2006; Wallis and Lee
1999). Documenting the frequency of significant mortality in wild animals is of
paramount importance for long-term population viability analyses (Young 1994).
Yet the behavioral and social responses of primates to significant disease-related
demographic changes are still poorly documented. Sapolsky and Share (2004)
described the long-term effects of a tuberculosis outbreak in a troop of olive
baboons (Papio anubis) in Kenya, with the emergence of a particularly pacific
culture following the death of the most aggressive males. A study comparing the
pre-, ongoing, and post-Ebola outbreak periods in two gorilla populations (Gorilla
gorilla gorilla) showed that the immigrations and social dynamics were impacted
during the outbreak only to finally return to their initial state, suggesting a longterm resilience (Genton et al. 2014).
Commensal primates are those that live in close association with humans and whose
primary ecology is highly anthropogenic (Fuentes 2012; Wheatley 1999). There is a
growing body of evidence that anthropogenic disturbance and increased habitat overlap
of human and nonhuman primates influence primate behavioral ecology (Altmann and
Muruthi 1988; Gumert et al. 2011; Jaman and Huffman 2013) and disease ecology
through modifications of host–parasite relationship (Chapman et al. 2005; Lane 2011).
There is some support for increased prevalence of pathogen infection in primate
populations living in anthropogenic environments (Chapman et al. 2005; Hussain
et al. 2013; McLennan and Huffman 2012; Nunn and Altizer 2006). By contrast, a
recent study conducted in Bali (Indonesia) argued that the quality of food consumed by
long-tailed macaques (Macaca fascicularis) in anthropogenic context results in better
nutritional conditions, and in turn, lessens the impact of gastrointestinal parasite
infestation (Lane et al. 2011). Yet, in 1994, a wide disease outbreak occurred in Bali,
affecting farmed pigs and several populations of free-living long-tailed macaques, and
Streptococcus equi ssp. zooepidemicus was identified as the responsible infectious
agent (Soedarmanto et al. 1996; Wheatley 1999).
Primates, and particularly cercopithecines, tend to have cohesive social groups with
stable membership over time (Cords 2012). As a result, significant changes in group
demographic structure after a substantial mortality event are likely to affect activity and
social patterns. For example, death of group members can disrupt social relationships
550
F. Brotcorne et al.
among individuals (Capitanio 2012) and trigger period of social instability (Kaburu
et al. 2013). It is well established that affiliative activities, especially allogrooming,
serve an important social function of bonding and group cohesion (Dunbar 1991;
Lehmann et al. 2007). A decrease in affiliative activities may thus be an indicator of
group instability and lower social cohesion (Beisner et al. 2011). Similarly, agonistic
interactions occurring within and between primate groups inform on the social tension
at the group and population level, respectively (Schino et al. 1990). Demographic
changes can also impact home range use by neighboring groups as well as their
dominance relationships, by introducing temporary instability and leading to increased
aggressions during intergroup encounters, as reported in capuchins (Cebus apella
nigritus: Scarry and Tujague 2012).
The main goals of the present study were to document the demographic and
sociobehavioral impacts in long-tailed macaques (Macaca fascicularis) of a significant mortality event that occurred in a tourist Monkey Forest of Bali in 2012.
We provide 26-yr demographic trends for the macaque population and analyze
how changes in the demographic structure impacted activity patterns, intergroup
relationships, and home range use of this population. Within this population, we
contrasted affected groups in which many individuals died during the 2012
mortality event, and nonaffected groups in which virtually no monkeys died
during this event.
Methods
Study Site and Subjects
The Padangtegal Monkey Forest is located alongside the villages of Padangtegal, Nyuh
Kuning and Ubud, in south-central Bali (8°31 S–155°15 E) (Fig. 1). It is a famous
tourist site, visited by 205,000 tourists in 2012. The Monkey Forest consists of a Hindu
temple complex within a 9-ha fragment of secondary mixed forest, surrounded by two
rivers, roads, human habitations, and rice fields. Local people use the temples for
ceremonies and cross the site to travel between villages (Fuentes et al. 2011). The
Padangtegal village committee manages the Monkey Forest and provisions the macaques several times a day with sweet potatoes and various fruits and vegetables.
Tourists also provide them with bananas and other fruits (Fuentes et al. 2005). The
climate in Ubud District is tropical monsoonal, with a short dry season lasting from
May to September and a wet season lasting from October to April. The average annual
rainfall is 2244 mm (http://climate-data.org).
Long-tailed macaques (Macaca fascicularis fascicularis: Fooden 1995) have been
living in Padangtegal Monkey Forest for centuries (Fuentes et al. 2005; Wheatley
1999). Since 1986, the population has been the focus of a series of behavioral (Fuentes
and Gamerl 2005; Fuentes et al. 2011; Wheatley 1999), ethnoprimatological (Fuentes
et al. 2005; Lane-deGraaf et al. 2014; Lane et al. 2010; Loudon et al. 2006), and
pathogen-related studies (Engel et al. 2006; Fuentes 2006; Jones-Engel et al. 2008;
Lane et al. 2011). Since 2009, this population has been composed of five social groups
(Cemetery, East, Michelin, Central, and Temple groups) with highly overlapping home
ranges (Brotcorne et al. 2011).
Activity of Long-Tailed Macaques After a Mortality Event
551
Fig. 1 The study site Padangtegal Monkey Forest with the overall home range of the long-tailed macaque
(Macaca fascicularis) population in 2012 and surrounding landscape and villages. The small dark circles
represent the main food provisioning areas.
Data Collection
Demographic Patterns From 2009 to 2012, we conducted repeated demographic
censuses of the overall population (October and June, N = 8 censuses). Because of
the large groups at the site, we used procession counting (Kurita et al. 2008) to
ascertain individual group size (N = 68 group counts between 2009 and 2012), counting
the number of individuals during their collective travel across an open area. Population
sizes before 2009 were collected by other authors using a similar counting method
(Fuentes et al. 2011; Loudon et al. 2006; Wheatley 1999). To assess the fluctuations in
the composition of social groups, we assessed the representation of each of the five
age–sex classes in each group: adult male (>6 yr), adult female (>3.5 yr), subadult male
(4–6 yr), juvenile (sex unidentified, >1 yr), and infant (sex unidentified, < 1 yr). We
determined age–sex classes by visual assessment of body size and development level of
sexual organs. In addition to the overall population surveys, we kept track of the status,
e.g. disappearance, age–sex class, pregnancy, of a subsample of individually identified
macaques (N = 88).
Necropsy A significant mortality event occurred in the Padangetgal long-tailed macaque population in July–August 2012. Given the difficulty of encountering fresh
carcasses and the logistical limitations imposed by onsite circumstances, we were not
able to conduct a comprehensive diagnostic assessment on macaques that died during
this 2012 event period. We collected only two fresh carcasses and sent them to the
Veterinary Investigation Unit in Denpasar for necropsy in July 2012. To isolate the
infectious agents, we collected nasal exudates and swabs from brain, thoracic, and
552
F. Brotcorne et al.
abdominal organs; streaked them onto Columbia sheep blood agar plates; and then
incubated the plates at 37°C for one night. We then analyzed the morphology and
chemical properties of suspect colonies with Gram staining (Hutabarat et al. 1999).
Activity Patterns We conducted behavioral observations for two periods of 3 mo
each: 1) pre-event period corresponding to a 3-mo period of November 15, 2011–
February 15, 2012 before the significant mortality event of July–August 2012; and
2) post-event period corresponding to a 3-mo period of September 15, 2012–
December 15, 2012 subsequent to the mortality event. We followed each group for
a mean of 3 d/mo, from 07:00 to 18:00 h when possible (Npre = 36 d, Npost = 26
d), or for half-days due to meteorological or other conditions (Npre = 10 d, Npost =
13 d). The minimum daily follow length included in the analyses of the focal data
was ≥4 h (Harrison et al. 2009).
To compare the activity budget pre- and post-event, we used 20-min focal observations (Altmann 1974) collected on a total of 54 sexually mature individuals, i.e., focal
individuals (27 males and 27 females), belonging to the five social groups and present
for the two periods. We identified focal individuals by their physiognomy, body marks,
and behavioral features. During focal samples, we selected individuals on a first-seen
basis, avoiding resampling the same individual before all the other focal individuals of
the group had been sampled. The analyses included 162 h of focal data for the preevent period and 124 h for the post-event period. To give equal weight to all focal
individuals, the sampling effort was identical for each individual nested within each
period (Periodpre = 3 h per individual; Periodpost = 2.3 h per individual).
We defined eight general activity categories (Fuentes et al. 2011): 1) Resting:
individual inactive, sitting or lying alone including visual scanning of the environment;
2) Moving: solitary or collective (traveling) movement from place to place, excluding
foraging; 3) Feeding: looking for or handling food items including foraging, consuming, processing; 4) Affiliation: affiliative behaviors involving two or several individuals
including allogrooming (or social grooming), huddling, lip-smacking, playing, and
caring; 5) Agonism: agonistic behaviors involving two or several individuals including
threat, submission, displacement, physical assault with or without contact, agonistic
intergroup encounter; 6) Sexual behavior: copulation and sexual-related behaviors
including presenting genitalia and visual inspection; 7) Self-directed behavior: selfgrooming, object manipulation, solitary play; 8) Interaction with humans: human–
macaque interactions involving physical contact or not, including begging, grabbing
food, provisioning, agonistic interaction, and playing.
Agonistic Intergroup Encounters We defined intergroup encounters as agonistic
when the proximity of a neighboring group induced one of the following reactions in
members of the group under study: group displacement, chase, flight, collective fight,
barking, and screaming vocalization (Scarry 2013; Wheatley 1999). We recorded
intergroup encounters on an ad libitum basis (Altmann 1974) and noted the identity
of the opponent groups as well as the level of intensity of the agonistic encounter (lowintensity = when the encounter involved the displacement of a group without other
agonistic behavior vs. high-intensity = when any additional agonistic interaction
between the opponent groups preceded the final group displacement) (Sugiura et al.
2000). We determined the outcome of each intergroup encounter, i.e., the identity of
Activity of Long-Tailed Macaques After a Mortality Event
553
winners and losers, based on which group was ultimately displaced (Cooper et al. 2004;
Scarry 2013).
Ranging Patterns During the daily group follows, we recorded the GPS location of
the group at 20-min intervals (Npre = 1,056 GPS points, Npost = 623) to reconstruct the
daily ranging patterns, using a handheld GPS Garmin 60CSx (≤10 m error).
Data Analysis
Demographic Patterns To analyze population trends over the last three decades, we
combined data from previous studies (Fuentes et al. 2011; Loudon et al. 2006;
Wheatley 1999) and our own 2009–2012 data. We calculated the intrinsic rate of
increase (r) as a measure of the population growth rate over the surveyed years as
follows (Cowlishaw and Dunbar 2000):
r¼
lnðN t Þ−lnðN 0 Þ
t
where Nt is the number of individuals in the final year, N0 is the number of individuals
in the beginning year, t is the number of years between surveys.
To calculate mortality rates (m) induced by the July–August 2012 event, we used two
computational methods. For the first, we compared the number of individuals counted in
each age–sex class for each group of the population before (census June 2012) and after
(census October 2012) the event (excluding the infants born between both censuses).
However, in an attempt to control for potential over- or underestimates stemming from
using gross population census figures, we based the second mortality estimate only on
the subsample of individually identified macaques (N = 88 in June 2012): we calculated
the proportion of these that had disappeared after the event.
Activity Patterns For each focal individual we calculated the duration (in seconds)
spent in each of the eight activity categories, weighted by the total duration of time
recorded for that individual during each period. The percentage of time each individual
spent in an activity within each period was the unit of comparison (Harrison et al.
2009). We used a multivariate analysis of variance (MANOVA, type III sum of square)
to determine whether the overall activity budget varied between the pre- and post-event
periods. We included as control predictors group identity and sex class, as well as the
interaction of these predictors with the period, because they are likely to influence the
activity budgets. To reduce heterogeneity of variances and increase the normality of
residuals, we performed an angular transformation on the proportional activity data
(Sokal and Rohlf 1995). We checked model validity and stability (distribution of
residuals, Shapiro–Wilk test, Levene’s test, leverage values, Cook’s distance), and
the assumptions required for MANOVA techniques were respected (Quinn and
Keough 2002). We also performed univariate analyses of variance to analyze the
effects on each activity category taken separately and employed contrast planned
comparisons between sex classes and between groups (Sokal and Rohlf 1995). In
tables and graphs, we present the untransformed mean time percentages of activities
with their standard errors.
554
F. Brotcorne et al.
Agonistic Intergroup Encounters We used a Fisher exact test to compare the level of
intensity of agonistic encounters between both periods. For each group and for each
period, we calculated a win/loss ratio corresponding to the proportion of encounters
won by a group on the total number of encounters observed for that group during that
period, i.e., intergroup encounter success. We used a Spearman exact correlation test to
examine the relationship between the win/loss ratio during the post-event period and
the group’s mortality rate after the 2012 event.
Ranging Patterns We used the accumulated GPS location points to generate the home
range of each group for each period, by means of fixed kernel density estimates
(Worton 1989), implemented with Hawth’s Tools for ESRI ArcGIS 9.3.1. We calculated the reference bandwidth (href) with adehabitatHR for R 3.0.1 (R Core Team 2013).
We defined the spatial centrality of the group home ranges as the access to the main
provisioning areas within the study site (Fig. 1). To calculate this, we first overlaid a
grid of 5 × 5 m cell size on the study area and identified the cells that intersected the
provisioning areas. Second, for each day of group follow (minimum daily follow fixed
at ≥7 h: Npre = 936 GPS points, Npost = 546), we counted the number of GPS points
located within the cells of provisioning areas, divided by the total number of GPS
points available for that day. We obtained a value of spatial centrality per group and per
day. We compared this value for each group between periods using Mann–Whitney
tests. Finally, we compared the daily centrality values between the affected vs.
nonaffected groups for the post-event period, by means of a Welch’s t-test (cf. unequal
variances detected with an F-test) (Quinn and Keough 2002).
We performed all statistical analyses (two-tailed statistics) with a significance level
set at 0.05, using STATISTICA 10.0 and R 3.0.2 (R Core Team 2013).
Ethical Note
This research followed all Indonesian laws for foreign research. Our study was
conducted under research permission from the Indonesian Ministry of Research and
Technology (#03B/TKPIPA/FRP/SM/III/2011, #355/SIP/FRP/SM/IX/2012), the
Provincial Government of Bali, and the local authorities, and used protocols developed
by Universitas Udayana Primate Research Center (UNUD-PKP) and the University of
Notre Dame under University of Notre Dame IACUC (#07-001).
Results
Demographic Patterns
Population Demographic Trends over 26 yr. Between 1986 and 2012, the mean
annual growth rate of the macaque population in Padangtegal Monkey Forest was 11%,
increasing from 69 individuals in 1986 to 563 individuals in 2012 (Fig. 2) (Fuentes
et al. 2011; Loudon et al. 2006; Wheatley 1999). However, this dramatic growth has
not been constant over the 26 yr. The intrinsic rate of increase (r) was negative between
Activity of Long-Tailed Macaques After a Mortality Event
555
Fig. 2 Long-tailed macaque population size history in Padangtegal Monkey Forest: population size (bars) and
intrinsic rate of increase (r; solid line) from 1986 to 2012. No data for 1987–1989, 1993–1997, 2004–2006,
and 2008. 1986–1992: data from Wheatley (1999). 1999–2002: data from Fuentes et al. (2011). 2003: data
from Loudon et al. (2006). 2007: unpublished data from Wayan Gede Gunartha. The statement of the
significant mortality event in 1994 is based on Soedarmanto et al. (1996) and Wheatley (1999).
1992 and 1998 (r = –0.01) and in 2012 (r = –0.08), two periods corresponding to the
occurrence of significant mortality events assumed to be associated with disease
outbreaks (Fig. 2).
Characterizing the Mortality Events In 1994, a disease outbreak caused by
Streptococcus equi ssp. zooepidemicus affected long-tailed macaques in the
Padangtegal Monkey Forest, but no detailed demographic data and mortality rates
were available for that period (Soedarmanto et al. 1996; Wheatley 1999) (Fig. 2). In
summer 2012, several macaques at the same site showed clinical signs of illness
including lethargy, severe movement difficulty suggesting polyarthritis, and substantial
weight loss (indicated by observable body condition); and an unusual number of
macaques were found dead during that period (N = 65; Wayan Gede Gunartha, pers.
comm.). Bacteriological tests of swabs from two fresh carcasses of monkeys dead at the
site revealed the presence of Gram-positive colonies of beta-hemolytic streptococci.
Based on this result, the Denpasar Veterinary Investigation Unit diagnosed streptococcal infections (Streptococcus sp.) as cause of both deaths, but no further bacteriological
classification was conducted and no additional diagnostics were used to screen the
monkeys at the site. This diagnosis of streptococci was communicated to the management staff and veterinarians at Padangtegal Monkey Forest who decided to treat the
macaques with Amoxicillin (an antibiotic) delivered within a mixture of fresh eggs
deposited at several locations in the site (during 5 days in July 2012 and 9 days in
August 2012). Following this treatment, the overt signs of illness in macaques diminished. Despite the assertion of Streptococcus sp. infection in this case, the lack of
etiological, histopathological, and epidemiological data leave it unclear as to the
presence and exact identity of pathological agent(s) that may have triggered the 2012
mortality event.
In 2012, based on the pre- and post-event censuses, the mortality rate (m) was 12.5%
for the overall population (N = 77 missing individuals). This rate varied markedly
between groups and age–sex classes (Table I). Only three of the five groups suffered a
556
Table I Composition of the long-tailed macaque population in Padangtegal Monkey Forest, home range size (95 % kernel), and group density (total group size divided by the group’s
home range area), before (Pre-mortality event period) and after (Post-mortality event period) a significant mortality event in summer 2012
Group
Pre-mortality event period (census June 2012)
Post-mortality event period (census October 2012)
AM
SUB
AF
JUV
Total group
Home range (ha)
Density (ind/ha)
AM
SUB
AF
JUV
Total group
Home range (ha)
Cemetery
7
5
32
45
89
1.69
52.6
6
9
24
31
70
2.56
27.3
East
6
10
39
53
108
4.06
26.6
6
7
21
36
70
2.82
24.8
Michelin
7
8
38
60
113
2.85
39.6
8
11
28
46
93
2.03
45.8
Central
7
5
33
60
105
4.42
23.7
9
8
33
66
116
1.95
59.4
Temple
20
15
58
107
200
3.38
59.1
17
17
60
120
214
4.78
44.7
Total
47
43
200
325
615
8.7
70.6
46
52
166
299
563
10.16
55.4
Mortality rates per group
Based on overall population (%)
Based on known individuals (%)
Cemetery
24.7
31
East
37.9
29
Michelin
23.8
19
Central
0
0
Temple
0
0
Total
12.5
15.9
AM
2.1
8.8
SUB
0
11
AF
22
21.6
JUV
13.5
25
Density (ind/ha)
Mortality rates per age–sex class
F. Brotcorne et al.
Mortality rates per group (affected groups are in italic) and per age–sex class (AM = adult male; AF = adult female; SUB = subadult male; JUV = juvenile) computed via two methods:
1) based on the censuses of the overall population; 2) based on the censuses of identified individuals. The mortality estimation for juveniles excluded infants
DOI 10.1007/s10764-015-9841-5
Changes in Activity Patterns and Intergroup
Relationships After a Significant Mortality Event
in Commensal Long-Tailed Macaques (Macaca
Fascicularis) in Bali, Indonesia
Fany Brotcorne 1,2 & Agustín Fuentes 3 &
I. Nengah Wandia 4 & Roseline C. Beudels-Jamar 2 &
Marie-Claude Huynen 1
Received: 28 June 2014 / Accepted: 2 April 2015 / Published online: 24 May 2015
# Springer Science+Business Media New York 2015
Abstract Little is known regarding behavioral and social responses of free-ranging
primates to demographic changes emerging from significant mortality events. Here, we
report on the activity patterns and intergroup sociospatial relationships in a commensal
population of long-tailed macaques (Macaca fascicularis) in Bali, Indonesia, that
underwent a significant mortality event in summer 2012. During the period of interest,
we noted heightened mortality in three of the five social groups present in this
population, with adult females and juveniles experiencing higher mortality rates than
adult and subadult males. Limited diagnostic data regarding pathogen identification and
a lack of any conclusive etiology of the deaths prevent our ascertainment of the agent(s)
responsible for the observed mortality, but given the characteristics of the event we
assume it was caused by a transmissible disease outbreak. Comparing the pre- and postmortality event periods, we found significant differences in activity patterns, including
a decreased proportion of affiliation in adult females. This result is likely indicative of
enhanced social instability induced by the high mortality of adult females that constitute
the stable core of macaque social structure. A higher social tension between groups
after the mortality event was indicated by more frequent and intense agonistic
* Fany Brotcorne
fbrotcorne@gmail.com
1
Primatology Research Group, Behavioural Biology Unit, University of Liège, 4020 Liège,
Belgium
2
Conservation Biology Unit, Education and Nature, Royal Belgian Institute of Natural Sciences,
1000 Brussels, Belgium
3
Department of Anthropology, University of Notre Dame, Notre Dame, IN 46556, USA
4
Primate Research Center, Universitas Udayana, 80361 Denpasar, Bali, Indonesia
Activity of Long-Tailed Macaques After a Mortality Event
549
intergroup encounters. Intergroup conflict success was inversely proportional to the rate
of mortality a group suffered. Our results illustrate how changes in demographic
structure caused by significant mortality events may have substantial consequences
on behavior and social dynamics in primate groups and at the level of a population.
Keywords Anthropogenic habitat . Bali Monkey Forest . Behavioral impact . Intergroup
relationship . Significant mortality . Social dynamics
Introduction
Pathogens are proposed as a significant ecological force in primate social systems
and behavior, with important effects on survival and reproduction (Nunn 2012;
Nunn and Altizer 2006). In Old World monkeys, mass mortality episodes caused
by infectious disease outbreaks have been reported (Bermejo et al. 2006;
Hanamura et al. 2008; Kaur et al. 2008; Leendertz et al. 2006; Wallis and Lee
1999). Documenting the frequency of significant mortality in wild animals is of
paramount importance for long-term population viability analyses (Young 1994).
Yet the behavioral and social responses of primates to significant disease-related
demographic changes are still poorly documented. Sapolsky and Share (2004)
described the long-term effects of a tuberculosis outbreak in a troop of olive
baboons (Papio anubis) in Kenya, with the emergence of a particularly pacific
culture following the death of the most aggressive males. A study comparing the
pre-, ongoing, and post-Ebola outbreak periods in two gorilla populations (Gorilla
gorilla gorilla) showed that the immigrations and social dynamics were impacted
during the outbreak only to finally return to their initial state, suggesting a longterm resilience (Genton et al. 2014).
Commensal primates are those that live in close association with humans and whose
primary ecology is highly anthropogenic (Fuentes 2012; Wheatley 1999). There is a
growing body of evidence that anthropogenic disturbance and increased habitat overlap
of human and nonhuman primates influence primate behavioral ecology (Altmann and
Muruthi 1988; Gumert et al. 2011; Jaman and Huffman 2013) and disease ecology
through modifications of host–parasite relationship (Chapman et al. 2005; Lane 2011).
There is some support for increased prevalence of pathogen infection in primate
populations living in anthropogenic environments (Chapman et al. 2005; Hussain
et al. 2013; McLennan and Huffman 2012; Nunn and Altizer 2006). By contrast, a
recent study conducted in Bali (Indonesia) argued that the quality of food consumed by
long-tailed macaques (Macaca fascicularis) in anthropogenic context results in better
nutritional conditions, and in turn, lessens the impact of gastrointestinal parasite
infestation (Lane et al. 2011). Yet, in 1994, a wide disease outbreak occurred in Bali,
affecting farmed pigs and several populations of free-living long-tailed macaques, and
Streptococcus equi ssp. zooepidemicus was identified as the responsible infectious
agent (Soedarmanto et al. 1996; Wheatley 1999).
Primates, and particularly cercopithecines, tend to have cohesive social groups with
stable membership over time (Cords 2012). As a result, significant changes in group
demographic structure after a substantial mortality event are likely to affect activity and
social patterns. For example, death of group members can disrupt social relationships
550
F. Brotcorne et al.
among individuals (Capitanio 2012) and trigger period of social instability (Kaburu
et al. 2013). It is well established that affiliative activities, especially allogrooming,
serve an important social function of bonding and group cohesion (Dunbar 1991;
Lehmann et al. 2007). A decrease in affiliative activities may thus be an indicator of
group instability and lower social cohesion (Beisner et al. 2011). Similarly, agonistic
interactions occurring within and between primate groups inform on the social tension
at the group and population level, respectively (Schino et al. 1990). Demographic
changes can also impact home range use by neighboring groups as well as their
dominance relationships, by introducing temporary instability and leading to increased
aggressions during intergroup encounters, as reported in capuchins (Cebus apella
nigritus: Scarry and Tujague 2012).
The main goals of the present study were to document the demographic and
sociobehavioral impacts in long-tailed macaques (Macaca fascicularis) of a significant mortality event that occurred in a tourist Monkey Forest of Bali in 2012.
We provide 26-yr demographic trends for the macaque population and analyze
how changes in the demographic structure impacted activity patterns, intergroup
relationships, and home range use of this population. Within this population, we
contrasted affected groups in which many individuals died during the 2012
mortality event, and nonaffected groups in which virtually no monkeys died
during this event.
Methods
Study Site and Subjects
The Padangtegal Monkey Forest is located alongside the villages of Padangtegal, Nyuh
Kuning and Ubud, in south-central Bali (8°31 S–155°15 E) (Fig. 1). It is a famous
tourist site, visited by 205,000 tourists in 2012. The Monkey Forest consists of a Hindu
temple complex within a 9-ha fragment of secondary mixed forest, surrounded by two
rivers, roads, human habitations, and rice fields. Local people use the temples for
ceremonies and cross the site to travel between villages (Fuentes et al. 2011). The
Padangtegal village committee manages the Monkey Forest and provisions the macaques several times a day with sweet potatoes and various fruits and vegetables.
Tourists also provide them with bananas and other fruits (Fuentes et al. 2005). The
climate in Ubud District is tropical monsoonal, with a short dry season lasting from
May to September and a wet season lasting from October to April. The average annual
rainfall is 2244 mm (http://climate-data.org).
Long-tailed macaques (Macaca fascicularis fascicularis: Fooden 1995) have been
living in Padangtegal Monkey Forest for centuries (Fuentes et al. 2005; Wheatley
1999). Since 1986, the population has been the focus of a series of behavioral (Fuentes
and Gamerl 2005; Fuentes et al. 2011; Wheatley 1999), ethnoprimatological (Fuentes
et al. 2005; Lane-deGraaf et al. 2014; Lane et al. 2010; Loudon et al. 2006), and
pathogen-related studies (Engel et al. 2006; Fuentes 2006; Jones-Engel et al. 2008;
Lane et al. 2011). Since 2009, this population has been composed of five social groups
(Cemetery, East, Michelin, Central, and Temple groups) with highly overlapping home
ranges (Brotcorne et al. 2011).
Activity of Long-Tailed Macaques After a Mortality Event
551
Fig. 1 The study site Padangtegal Monkey Forest with the overall home range of the long-tailed macaque
(Macaca fascicularis) population in 2012 and surrounding landscape and villages. The small dark circles
represent the main food provisioning areas.
Data Collection
Demographic Patterns From 2009 to 2012, we conducted repeated demographic
censuses of the overall population (October and June, N = 8 censuses). Because of
the large groups at the site, we used procession counting (Kurita et al. 2008) to
ascertain individual group size (N = 68 group counts between 2009 and 2012), counting
the number of individuals during their collective travel across an open area. Population
sizes before 2009 were collected by other authors using a similar counting method
(Fuentes et al. 2011; Loudon et al. 2006; Wheatley 1999). To assess the fluctuations in
the composition of social groups, we assessed the representation of each of the five
age–sex classes in each group: adult male (>6 yr), adult female (>3.5 yr), subadult male
(4–6 yr), juvenile (sex unidentified, >1 yr), and infant (sex unidentified, < 1 yr). We
determined age–sex classes by visual assessment of body size and development level of
sexual organs. In addition to the overall population surveys, we kept track of the status,
e.g. disappearance, age–sex class, pregnancy, of a subsample of individually identified
macaques (N = 88).
Necropsy A significant mortality event occurred in the Padangetgal long-tailed macaque population in July–August 2012. Given the difficulty of encountering fresh
carcasses and the logistical limitations imposed by onsite circumstances, we were not
able to conduct a comprehensive diagnostic assessment on macaques that died during
this 2012 event period. We collected only two fresh carcasses and sent them to the
Veterinary Investigation Unit in Denpasar for necropsy in July 2012. To isolate the
infectious agents, we collected nasal exudates and swabs from brain, thoracic, and
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abdominal organs; streaked them onto Columbia sheep blood agar plates; and then
incubated the plates at 37°C for one night. We then analyzed the morphology and
chemical properties of suspect colonies with Gram staining (Hutabarat et al. 1999).
Activity Patterns We conducted behavioral observations for two periods of 3 mo
each: 1) pre-event period corresponding to a 3-mo period of November 15, 2011–
February 15, 2012 before the significant mortality event of July–August 2012; and
2) post-event period corresponding to a 3-mo period of September 15, 2012–
December 15, 2012 subsequent to the mortality event. We followed each group for
a mean of 3 d/mo, from 07:00 to 18:00 h when possible (Npre = 36 d, Npost = 26
d), or for half-days due to meteorological or other conditions (Npre = 10 d, Npost =
13 d). The minimum daily follow length included in the analyses of the focal data
was ≥4 h (Harrison et al. 2009).
To compare the activity budget pre- and post-event, we used 20-min focal observations (Altmann 1974) collected on a total of 54 sexually mature individuals, i.e., focal
individuals (27 males and 27 females), belonging to the five social groups and present
for the two periods. We identified focal individuals by their physiognomy, body marks,
and behavioral features. During focal samples, we selected individuals on a first-seen
basis, avoiding resampling the same individual before all the other focal individuals of
the group had been sampled. The analyses included 162 h of focal data for the preevent period and 124 h for the post-event period. To give equal weight to all focal
individuals, the sampling effort was identical for each individual nested within each
period (Periodpre = 3 h per individual; Periodpost = 2.3 h per individual).
We defined eight general activity categories (Fuentes et al. 2011): 1) Resting:
individual inactive, sitting or lying alone including visual scanning of the environment;
2) Moving: solitary or collective (traveling) movement from place to place, excluding
foraging; 3) Feeding: looking for or handling food items including foraging, consuming, processing; 4) Affiliation: affiliative behaviors involving two or several individuals
including allogrooming (or social grooming), huddling, lip-smacking, playing, and
caring; 5) Agonism: agonistic behaviors involving two or several individuals including
threat, submission, displacement, physical assault with or without contact, agonistic
intergroup encounter; 6) Sexual behavior: copulation and sexual-related behaviors
including presenting genitalia and visual inspection; 7) Self-directed behavior: selfgrooming, object manipulation, solitary play; 8) Interaction with humans: human–
macaque interactions involving physical contact or not, including begging, grabbing
food, provisioning, agonistic interaction, and playing.
Agonistic Intergroup Encounters We defined intergroup encounters as agonistic
when the proximity of a neighboring group induced one of the following reactions in
members of the group under study: group displacement, chase, flight, collective fight,
barking, and screaming vocalization (Scarry 2013; Wheatley 1999). We recorded
intergroup encounters on an ad libitum basis (Altmann 1974) and noted the identity
of the opponent groups as well as the level of intensity of the agonistic encounter (lowintensity = when the encounter involved the displacement of a group without other
agonistic behavior vs. high-intensity = when any additional agonistic interaction
between the opponent groups preceded the final group displacement) (Sugiura et al.
2000). We determined the outcome of each intergroup encounter, i.e., the identity of
Activity of Long-Tailed Macaques After a Mortality Event
553
winners and losers, based on which group was ultimately displaced (Cooper et al. 2004;
Scarry 2013).
Ranging Patterns During the daily group follows, we recorded the GPS location of
the group at 20-min intervals (Npre = 1,056 GPS points, Npost = 623) to reconstruct the
daily ranging patterns, using a handheld GPS Garmin 60CSx (≤10 m error).
Data Analysis
Demographic Patterns To analyze population trends over the last three decades, we
combined data from previous studies (Fuentes et al. 2011; Loudon et al. 2006;
Wheatley 1999) and our own 2009–2012 data. We calculated the intrinsic rate of
increase (r) as a measure of the population growth rate over the surveyed years as
follows (Cowlishaw and Dunbar 2000):
r¼
lnðN t Þ−lnðN 0 Þ
t
where Nt is the number of individuals in the final year, N0 is the number of individuals
in the beginning year, t is the number of years between surveys.
To calculate mortality rates (m) induced by the July–August 2012 event, we used two
computational methods. For the first, we compared the number of individuals counted in
each age–sex class for each group of the population before (census June 2012) and after
(census October 2012) the event (excluding the infants born between both censuses).
However, in an attempt to control for potential over- or underestimates stemming from
using gross population census figures, we based the second mortality estimate only on
the subsample of individually identified macaques (N = 88 in June 2012): we calculated
the proportion of these that had disappeared after the event.
Activity Patterns For each focal individual we calculated the duration (in seconds)
spent in each of the eight activity categories, weighted by the total duration of time
recorded for that individual during each period. The percentage of time each individual
spent in an activity within each period was the unit of comparison (Harrison et al.
2009). We used a multivariate analysis of variance (MANOVA, type III sum of square)
to determine whether the overall activity budget varied between the pre- and post-event
periods. We included as control predictors group identity and sex class, as well as the
interaction of these predictors with the period, because they are likely to influence the
activity budgets. To reduce heterogeneity of variances and increase the normality of
residuals, we performed an angular transformation on the proportional activity data
(Sokal and Rohlf 1995). We checked model validity and stability (distribution of
residuals, Shapiro–Wilk test, Levene’s test, leverage values, Cook’s distance), and
the assumptions required for MANOVA techniques were respected (Quinn and
Keough 2002). We also performed univariate analyses of variance to analyze the
effects on each activity category taken separately and employed contrast planned
comparisons between sex classes and between groups (Sokal and Rohlf 1995). In
tables and graphs, we present the untransformed mean time percentages of activities
with their standard errors.
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F. Brotcorne et al.
Agonistic Intergroup Encounters We used a Fisher exact test to compare the level of
intensity of agonistic encounters between both periods. For each group and for each
period, we calculated a win/loss ratio corresponding to the proportion of encounters
won by a group on the total number of encounters observed for that group during that
period, i.e., intergroup encounter success. We used a Spearman exact correlation test to
examine the relationship between the win/loss ratio during the post-event period and
the group’s mortality rate after the 2012 event.
Ranging Patterns We used the accumulated GPS location points to generate the home
range of each group for each period, by means of fixed kernel density estimates
(Worton 1989), implemented with Hawth’s Tools for ESRI ArcGIS 9.3.1. We calculated the reference bandwidth (href) with adehabitatHR for R 3.0.1 (R Core Team 2013).
We defined the spatial centrality of the group home ranges as the access to the main
provisioning areas within the study site (Fig. 1). To calculate this, we first overlaid a
grid of 5 × 5 m cell size on the study area and identified the cells that intersected the
provisioning areas. Second, for each day of group follow (minimum daily follow fixed
at ≥7 h: Npre = 936 GPS points, Npost = 546), we counted the number of GPS points
located within the cells of provisioning areas, divided by the total number of GPS
points available for that day. We obtained a value of spatial centrality per group and per
day. We compared this value for each group between periods using Mann–Whitney
tests. Finally, we compared the daily centrality values between the affected vs.
nonaffected groups for the post-event period, by means of a Welch’s t-test (cf. unequal
variances detected with an F-test) (Quinn and Keough 2002).
We performed all statistical analyses (two-tailed statistics) with a significance level
set at 0.05, using STATISTICA 10.0 and R 3.0.2 (R Core Team 2013).
Ethical Note
This research followed all Indonesian laws for foreign research. Our study was
conducted under research permission from the Indonesian Ministry of Research and
Technology (#03B/TKPIPA/FRP/SM/III/2011, #355/SIP/FRP/SM/IX/2012), the
Provincial Government of Bali, and the local authorities, and used protocols developed
by Universitas Udayana Primate Research Center (UNUD-PKP) and the University of
Notre Dame under University of Notre Dame IACUC (#07-001).
Results
Demographic Patterns
Population Demographic Trends over 26 yr. Between 1986 and 2012, the mean
annual growth rate of the macaque population in Padangtegal Monkey Forest was 11%,
increasing from 69 individuals in 1986 to 563 individuals in 2012 (Fig. 2) (Fuentes
et al. 2011; Loudon et al. 2006; Wheatley 1999). However, this dramatic growth has
not been constant over the 26 yr. The intrinsic rate of increase (r) was negative between
Activity of Long-Tailed Macaques After a Mortality Event
555
Fig. 2 Long-tailed macaque population size history in Padangtegal Monkey Forest: population size (bars) and
intrinsic rate of increase (r; solid line) from 1986 to 2012. No data for 1987–1989, 1993–1997, 2004–2006,
and 2008. 1986–1992: data from Wheatley (1999). 1999–2002: data from Fuentes et al. (2011). 2003: data
from Loudon et al. (2006). 2007: unpublished data from Wayan Gede Gunartha. The statement of the
significant mortality event in 1994 is based on Soedarmanto et al. (1996) and Wheatley (1999).
1992 and 1998 (r = –0.01) and in 2012 (r = –0.08), two periods corresponding to the
occurrence of significant mortality events assumed to be associated with disease
outbreaks (Fig. 2).
Characterizing the Mortality Events In 1994, a disease outbreak caused by
Streptococcus equi ssp. zooepidemicus affected long-tailed macaques in the
Padangtegal Monkey Forest, but no detailed demographic data and mortality rates
were available for that period (Soedarmanto et al. 1996; Wheatley 1999) (Fig. 2). In
summer 2012, several macaques at the same site showed clinical signs of illness
including lethargy, severe movement difficulty suggesting polyarthritis, and substantial
weight loss (indicated by observable body condition); and an unusual number of
macaques were found dead during that period (N = 65; Wayan Gede Gunartha, pers.
comm.). Bacteriological tests of swabs from two fresh carcasses of monkeys dead at the
site revealed the presence of Gram-positive colonies of beta-hemolytic streptococci.
Based on this result, the Denpasar Veterinary Investigation Unit diagnosed streptococcal infections (Streptococcus sp.) as cause of both deaths, but no further bacteriological
classification was conducted and no additional diagnostics were used to screen the
monkeys at the site. This diagnosis of streptococci was communicated to the management staff and veterinarians at Padangtegal Monkey Forest who decided to treat the
macaques with Amoxicillin (an antibiotic) delivered within a mixture of fresh eggs
deposited at several locations in the site (during 5 days in July 2012 and 9 days in
August 2012). Following this treatment, the overt signs of illness in macaques diminished. Despite the assertion of Streptococcus sp. infection in this case, the lack of
etiological, histopathological, and epidemiological data leave it unclear as to the
presence and exact identity of pathological agent(s) that may have triggered the 2012
mortality event.
In 2012, based on the pre- and post-event censuses, the mortality rate (m) was 12.5%
for the overall population (N = 77 missing individuals). This rate varied markedly
between groups and age–sex classes (Table I). Only three of the five groups suffered a
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Table I Composition of the long-tailed macaque population in Padangtegal Monkey Forest, home range size (95 % kernel), and group density (total group size divided by the group’s
home range area), before (Pre-mortality event period) and after (Post-mortality event period) a significant mortality event in summer 2012
Group
Pre-mortality event period (census June 2012)
Post-mortality event period (census October 2012)
AM
SUB
AF
JUV
Total group
Home range (ha)
Density (ind/ha)
AM
SUB
AF
JUV
Total group
Home range (ha)
Cemetery
7
5
32
45
89
1.69
52.6
6
9
24
31
70
2.56
27.3
East
6
10
39
53
108
4.06
26.6
6
7
21
36
70
2.82
24.8
Michelin
7
8
38
60
113
2.85
39.6
8
11
28
46
93
2.03
45.8
Central
7
5
33
60
105
4.42
23.7
9
8
33
66
116
1.95
59.4
Temple
20
15
58
107
200
3.38
59.1
17
17
60
120
214
4.78
44.7
Total
47
43
200
325
615
8.7
70.6
46
52
166
299
563
10.16
55.4
Mortality rates per group
Based on overall population (%)
Based on known individuals (%)
Cemetery
24.7
31
East
37.9
29
Michelin
23.8
19
Central
0
0
Temple
0
0
Total
12.5
15.9
AM
2.1
8.8
SUB
0
11
AF
22
21.6
JUV
13.5
25
Density (ind/ha)
Mortality rates per age–sex class
F. Brotcorne et al.
Mortality rates per group (affected groups are in italic) and per age–sex class (AM = adult male; AF = adult female; SUB = subadult male; JUV = juvenile) computed via two methods:
1) based on the censuses of the overall population; 2) based on the censuses of identified individuals. The mortality estimation for juveniles excluded infants