, Volume 59, Issue 2, pp 163–171 | Cite as

Small-scale variability in a mosaic tropical rainforest influences habitat use of long-tailed macaques

  • John Chih Mun Sha
  • Siew Chin Chua
  • Ping Ting Chew
  • Hassan Ibrahim
  • Hock Keong Lua
  • Tze Kwan Fung
  • Peng Zhang
Original Article


Pristine habitats have generally been considered to be the most important ecological resource for wildlife conservation, but due to forest degradation caused by human activities, mosaics of secondary forests have become increasingly prominent. We studied three forest types in a mosaic tropical forest consisting of short secondary forest (SS), tall secondary forest (TS) and freshwater swamp forest (SF). These forests differed in stand structure and floristic composition, as well as phenological productivity of fruits, flowers and young leaves. We examined habitat use of long-tailed macaques (Macaca fascicularis) in relation to indices of phenological activity. The macaques used the SS for feeding/foraging more than the TS and the SF. This was because the SS had higher productivity of fruit, which is a preferred food resource for macaques. Stem densities of young leaves in the SS and the TS also influenced habitat use, as they provided more clumped resources. Use of SF was limited, but these forests provided more species-rich resources. Our results showed that M. fascicularis responded to small-scale variability in phenological activity between forest types found in a heterogeneous mosaic forest, with young secondary regrowth forests likely providing the most important food resources. Mosaic landscapes may be important as they can buffer the effects of temporal food resource variability in any given forest type. In our increasingly human-altered landscapes, a better understanding of the role of secondary forest mosaics is crucial to the conservation and management of wildlife habitats and the animals they support.


Floristic composition Macaca fascicularis Phenology Stand structure Secondary forest 


Tropical rainforests are some of the most diverse and productive ecosystems on earth (Corlett and Primack 2011). Their high primary productivity includes a diverse assemblage of fruits, flowers and young leaves, which serve as important food sources for many primates with diverse feeding adaptations (Lambert 1998). In general, plant resources in tropical forests undergo temporal variations, with pronounced within-year and between-year variations, resulting in periods of resource abundance and scarcity that are often patchily distributed in space and time (van Schaik et al. 1993; Chapman et al. 1997).

The landscape of tropical forests is rapidly changing. Between 1990 and 2015, approximately 129 million ha of forest was lost and only 30.6% of the world’s land area is now made up of forest (FAO 2015). In humid tropical regions, about half of remaining forests contained 50% or less tree cover (Asner et al. 2009). Due to high rates of forest degradation and deforestation, mosaics of secondary forests of varying successional stages have become increasingly prominent. In such heterogeneous forest landscapes, successional forests with different plant communities would further affect food availability (van Schaik et al. 1993).

Primates have to adapt to both natural and human-induced changes to their environments by modifying their foraging strategies through diet shifts, changes in their movement and activity patterns or incorporating new areas into their home ranges. Indeed, many primate species have been shown to be highly adaptable to, for example, seasonal resource and temperature fluctuations (Peres 1994; Hanya 2004; Hemingway and Bynum 2005; Wallace 2006). They also respond to stochastic events like supra-annual flowering and fruiting events (Corlett 1990; Lucas and Corlett 1991; Hill and Agetsuma 1995), and to local differences in plant floristic compositions and species richness (Chapman and Chapman 1999; Ellwanger and Gould 2011). In human-impacted landscapes like fragmented or degraded forests, primates adapt to generally lower availability of quality food resources by exploiting mature leaves of lower nutritional quality (Donati et al. 2011), increase their diversity of food plant species (Cristóbal-Azkarate and Arroyo-Rodríguez 2007; Chaves et al. 2012), switch between more frugivorous and folivorous diets (González‐Zamora et al. 2009; Dunn et al. 2009; Tesfaye et al. 2013), exploit alternative resources like insects (Tutin 1999), or increase the consumption of fallback foods, i.e., food items from non-preferred species (Constantino and Wright 2009).

Singapore is located in the biodiversity hotspot of Southeast Asia, which is also a region experiencing rapid changes in forest land use (Sodhi et al. 2010). Most of Singapore was covered by forest before the arrival of the British in 1819, but by the late 1800s, only about 10% of the original forest remained (Cantley 1884). The original vegetation was cleared mainly for agriculture and rubber plantations (Corlett 1991b). By the early 1900s, many of the cultivated areas were abandoned as the nation was gradually urbanized and the forests were left to regenerate naturally (Corlett 1992). The remaining forested areas in Singapore are concentrated within the Central Catchment Nature Reserve (CCNR), which is legally protected. Vegetation based on aerial photographs in this area consisted of secondary forest regrowth and freshwater swamp forests since at least the 1950s. Early successional secondary forests were at least 60 years old and late successional forests could be at least 100 years old (Corlett 1991a). Aside from past agricultural activities, the construction and expansion of reservoirs had been the only anthropogenic impact, which changed the distribution of freshwater swamp forests (Turner et al. 1996). The current forests consist of small isolated patches of freshwater swamp forests along the margins and stream inlets of the reservoir, which are scattered amongst differently regenerating secondary forest stands.

Existing literature on the influence of forest food resources on primate ecology in Singapore largely considered their habitats as an entirety within their home ranges (e.g., Lucas and Corlett 1991; Ang 2011; Sha and Hanya 2013a, b). However, due to historical changes in forest cover in Singapore, the home ranges of these species now comprise forest mosaics with different floristic composition and plant communities. The influence of small-scale differences in forest characteristics on resource availability for macaques, as well as other mammal species in Singapore, has not been studied.

In this study, we examined floristic composition, stand structure and phenology of three different forest types within the home range of a group of long-tailed macaques (Macaca fascicularis) in a tropical rainforest in Singapore. We hypothesize that within this small forest area, considerable variability in forest productivity exists between forest types of different successional stages of regrowth, and that these food resource factors influence the habitat use of the macaques. We discuss the conservation value of secondary and mosaic forests and the implications for primates and other mammalian herbivores.

Materials and methods

Study site

We conducted our study at a site in Singapore which is adjacent to the Upper Seletar Reservoir Park within the CCNR (1°24′4″N, 103°48′14″E) (Fig. 1). For forest classification, we modified those from Wong et al. (1994) and Yee et al. (2011) for our study site. The secondary forests are dominated by native species with differences in stand structure and species composition occurring along a successional gradient that can be clearly identifiable at the extreme ends (Yee et al. 2016). We classified the secondary forest as short secondary forest (SS) and tall secondary forest (TS), to reflect differences according to their stage of succession. TS are generally more dense and have multistoried closed canopies whereas SS consists of patchy and simpler single-canopy forest stand structures. We also ground truthed and improved the accuracy of the extent of freshwater swamp forest (SF).
Fig. 1

Map of study area showing forest types, phenology plots and core forested home range of the study group

Data collection

We set up thirteen 20 × 20-m plots in an area of 0.52 ha, with five plots set up in the SS, five plots in the TS and three plots in the SF. The number of plots for each forest type corresponded approximately to the area of the different forest types within the study area. In all plots, we tagged all trees above 5-cm diameter at breast height. We identified all tagged trees to species level and monitored the trees once a month over 12 months from June 2011 to May 2012, and checked for the presence of fruits, flowers, and young leaves. We defined the different phenophases according to USA National Phenology Network National Coordinating Office (2012). Fruits included ripe or unripe fruit; flowers included fresh open or unopened flowers or flower buds; and young leaves included leaves before they had reached full size or turned the darker green or had the tougher texture of mature leaves. We considered trees as phenologically active when at least one of the reproductive phenophases were observed. In total, 392 individuals of 111 tree species were surveyed.

Forest type characteristics

Stand structure and floristic composition

We examined differences between the forest types. To take into consideration differences in stem density among the forest types, we calculated the expected species richness of 107 trees, subsampled randomly using trees in all plots from each of the forest types; 107 was the lowest number of trees in the three forest types. We also generated species accumulation curves for each forest type by random sampling of all individual stems within that forest type.

To describe the floristic similarity between the forest types, we calculated the Jaccard community coefficient of similarity (CCJ) between any pair of forest types (Mueller-Dombois and Ellenberg 1974): CCJ = c/S × 100, where c is the number of species common to two forest types and S is the total number of species sampled in the two forest types. We analyzed plot dissimilarities in species composition using ordination of plots by nonmetric multidimensional scaling (NMDS), with the Chao dissimilarity distance used to compute distance matrices. This analysis provides a visualization of the level of similarity in species composition between plots in different forest types.

Forest type indices

For each phenophase (flower, fruit and young leaf) we created an index of monthly phenological activity by totaling the basal stem area of phenologically active trees in each forest type. For comparison of forest characteristics between forest types, we calculated basal area and stem density, according to methods by Hédl et al. (2009), and species richness as the number of species per number of stems, for (1) all trees, and (2) phenologically active trees. These indices represent different characteristics of primate food resources produced by these forests. Basal area is used to measure resource abundance as it is a function of tree cover (Cade 1997) and fruit crop size (Chapman et al. 1992). Stem density is used to measure resource distribution, i.e., high and low stem densities represent clumped and dispersed resources, respectively, which have profound effects on primate foraging ecology (Altmann 1979; Oates 1987). Plant species richness is used to measure resource diversity, as more varied forest resources are beneficial to primate dietary diversity and can provide fallback foods (Cristóbal-Azkarate and Arroyo-Rodríguez 2007; Constantino and Wright 2009; Chaves et al. 2012).

Habitat use

Data on habitat use were from a larger study conducted on two groups of long-tailed macaques (Sha and Hanya 2013a, b). In this study, we used the dataset from one group that used all three forest types found at the study site. The group was observed over a period of 1 year for a total of 410 observation h (mean 31.6 ± 3.4 h/month). We used scan sampling (Altmann 1974) with 15-min intervals to record general activity (rest, locomotion, and forage/feed). During each scan, we recorded group location using a geographic positioning system (Trimble Recon; Trimble Navigation). To calculate habitat use, for the purposes of this study, we focused on data of feeding/foraging, which were defined as any activity that involved eating or manipulation of food items. We extracted global positioning system (GPS) locations which corresponded to scan data whereby at least 50% of the group was recorded as feeding/foraging. We calculated the percentage use of different forest types by dividing the total number of GPS locations recorded in each forest type by the total locations recorded in all forest types.

Statistical analysis

A χ2-test of goodness-of-fit was performed to determine whether the observed habitat use by the macaque group significantly deviated from expected use based on the percentage of each forest type within its home range. Using the Kolmogorov–Smirnov test, we verified that data were normally distributed. We used one-way ANOVA to test statistical differences between forest indices (basal area, stem density and species richness) of food resources (fruit, flower and young leaf) in different forest types.

Where ANOVA showed significant results, we used post hoc Tukey’s honest significant difference test to examine significant differences between pairs of forest types. We used general linear models (GLM) with Poisson distribution to examine the effects of independent variables of forest type indices (basal area, stem density and species richness) on macaque habitat use (dependent variable). Analyses were performed with the R statistical package, version 3.1.2 (R Development Core Team, R Foundation for Statistical Computing, Vienna;, with: (1) the vegan package, with the specaccum function for species accumulation curves, the metaMDS function for NMDS and the vegdist function for the dissimilarity test; (2) the chisq.test function for the χ2 goodness-of-fit test; (3) the car package with aov and TukeyHSD functions for ANOVA and post hoc analysis; (4) the MASS package using the glm function for GLM analysis; (5) the psych package, with descriptive statistics using the describe and summary functions.


Forest type characteristics

The three habitat types within the home range of the macaque group differed in stand structure, floristic composition and species diversity (Table 1). Mean stem density was highest for the SF followed by the TS and the SS. Mean basal stem area was highest for TS, followed by SS, and SF. Species accumulation curves by plot and by individual stems both showed that SF had the highest expected species richness as compared to TS and SS, which had similar estimates for species richness (Fig. 2). NMDS ordination showed distinct groupings of plots by forest type with a Chao dissimilarity distance of 0.93, suggesting a low number of shared species between forest types (Fig. 3). The CCJ was highest between SS and TS secondary forest (23.4%, or 15 of 64 species), and much lower between these two forest types and SF (7.4%, or seven of 94 species) and between SS and SF and (8.1%, or seven of 86 species between TS and SF).
Table 1

Characteristics of the short secondary (SS), tall secondary (TS) and freshwater swamp forests (SF)


Short secondary forest

Tall secondary forest

Freshwater swamp forest

For all trees

 Basal area (m2/ha)

17.4 ± 4.1

19.4 ± 16.4

14.5 ± 10.1

 Stem density (no./ha)

650.0 ± 230

775 ± 206

891.7 ± 317

 Species richness

12.00 ± 1.22

14.60 ± 1.52

23.00 ± 5.29


Short secondary forest

Tall secondary forest

Freshwater swamp forest




Young leaf



Young leaf



Young leaf

For phenologically active trees

 Basal area (m2/ha)

9.6 ± 4.7

8.9 ± 4.5

17.0 ± 4.2

3.5 ± 1.5

1.0 ± 0.6

17.0 ± 11.6

3.9 ± 5.0

4.8 ± 3.2

11.9 ± 7.3

 Stem density (no./ha)

225.0 ± 46.8

205.0 ± 32.5

600.0 ± 207.5

125.0 ± 72.5

65.0 ± 37.5

735.0 ± 210.0

167.5 ± 95.0

192.5 ± 80.0

757.5 ± 275.0

 Species richness

3.6 ± 1.8

4.6 ± 1.1

11.8 ± 2.1

4.0 ± 2.4

2.0 ± 0.7

13.8 ± 1.9

4.7 ± 1.2

6.7 ± 2.5

20.3 ± 7.6

Basal area, stem density and species richness were calculated from a mean of 20 × 20-m plots (±SD). There were five plots each in SS and TS, and three plots in SF. Phenologically active trees were observed over a period of 1 year

Fig. 2

Species accumulation curves by a plots and b individual stems for the three forest types: short secondary (SS), tall secondary (TS) and freshwater swamp forests (SF)

Fig. 3

Ordination of plots by non-metric multidimensional scaling (NMDS) with Chao distance, showing similarities in species composition between phenology plots in different forest types of SS, TS and SF. For other abbreviations, see Fig. 2

Variability of indices of food availability between forest types

We compared the indices of food resources (basal area, stem density and species richness) of the availability of food resources (fruit, flower and young leaf) between forest types.

There was a significant difference in basal area of fruiting trees between forest types [F (2,33) = 5.914, p < 0.001], where SS was significantly higher than TS (p < 0.01). Basal area of flowering trees similarly differed between forest types [F (2,33) = 6.753, p < 0.01], where SS was significantly higher than TS (p < 0.01). Basal area of trees with young leaves was significantly different between forest types F (2,33) = 16.74, p < 0.001, where TS was significantly higher than both SS (p < 0.01) and SF (p < 0.001).

There was a significant difference in stem density of fruiting trees between forest types [F (2,33) = 12.74, p < 0.001], where SS was significantly higher than both TS (p < 0.001) and SF (p < 0.001). Stem density of flowering trees similarly differed between forest types [F (2,33) = 39.0, p < 0.001], where TS was significantly lower than SS (p < 0.001) and SF (p < 0.001). Stem density of trees with young leaves was not significantly different between forest types [F (2,33) = 1.391, p = 0.263].

There was no significant difference in species richness of fruiting trees between forest types [F (2,33) = 3.192, p = 0.054]. Species richness of flowering trees was significantly different between forest types [F (2,33) = 34.73, p < 0.001], where TS was significantly lower than SS (p < 0.001) and SF (p < 0.001) and SF significantly higher than SS (p < 0.001). Species richness of trees with young leaves was significantly different between forest types [F (2,33) = 31.23, p < 0.001], with SS higher than TS (p < 0.001) and SF (p < 0.001), and TS higher than SF (p < 0.05).

The total production of fruits, flowers and young leaves varied across months in different forest types (Fig. 4). Fruit production was particularly variable across the year, with dips from September to December. During this period, flowering and young leaf flushes were, however, relatively high, suggesting that total resource availability within the mosaic forest was rather stable across the year.
Fig. 4

Monthly phenological index of fruits, flowers and young leaves over a period of 1 year

Resource predictors of macaque forest type use

The core forested home range of the macaque group included approximately 30% of SS, 50% of TS and 20% of SF. For feeding, the macaques used the SS 52.2 ± 14.9%, the TS 41.3 ± 14.6% and the SF 6.5 ± 3.0% of the time. The observed use of forest type significantly deviated from expected use based on the percentage of forest type within the macaque home range (χ2 goodness-of-fit, χ 2 = 13.702, df = 2, p < 0.001). We examined the effects of forest characteristics (basal area, stem density and species richness) of resource type (fruit, flower and young leaf) on macaque use of each forest type (Table 2).
Table 2

The effect of basal area, stem density and species richness

Independent factors





Fruiting trees on the proportion of time spent in SS (R 2 = 0.91, df = 11, p < 0.001)






 Basal area





 Stem density





 Species richness





Trees with young leaves on the proportion of time spent in SS (R 2 = 0.82, df = 11, p < 0.001)






 Basal area





 Stem density





 Species richness





Trees with young leaves on the proportion of time spent in TS (R 2 = 0.86, df = 11, p < 0.001)






 Basal area





 Stem density





 Species richness





Fruiting trees on the proportion of time spent in SF (R 2 = 0.86, df = 11, p < 0.001)






 Basal area





 Stem density





 Species richness





For abbreviations, see Table 1

Forest characteristics of fruiting and flushing trees had significant main effects on macaque use of SS forest (Table 2) with a significant positive relationship between forest use and basal area of fruiting trees (t = 2.698, p = 0.027), and between forest use and stem density of flushing trees (t = 1.892, p = 0.018). Forest characteristics of flowering trees had a non-significant main effect on macaque use of SS (R 2 = 0.52, df = 11, p = 0.318).

Forest characteristics of flushing trees had a significant main effect on macaque use of TS (Table 2), with a significant positive relationship between forest use and stem density (t = 3.963, p = 0.004). Forest characteristics of fruiting trees had non-significant main effects on macaque use of TS (R 2 = 0.71, df = 11, p = 0.241). Forest characteristics of flushing trees similarly had a non-significant main effect on macaque use of TS (R 2 = 0.62, df = 11, p = 0.122).

Forest characteristics of fruiting trees had a significant main effect on macaque use of SF (Table 2), with a significant positive relationship between forest use and species richness of fruit (t = 3.198, p = 0.013). Forest characteristics of flowering trees had a non-significant main effect on macaque use of SF (R 2 = 0.65, df = 8, p = 0.181). Forest characteristics of flushing trees similarly had a non-significant main effect on macaque use of SF (R 2 = 0.76, df = 8, p = 0.073).


The mosaic rainforest we studied consisted of three forest types that could be clearly distinguished by floristic composition, community and stand structure. The SS and TS forests were rather distinct in their floristic composition even after more than 60 years of natural regeneration, with relatively low species overlap; the secondary forests were even more floristically distinct from the SF, which had the highest species richness. More importantly, the three forest types showed differences in their flower, fruit and young leaf phenology. Indeed, significant variability in food availability between forest types was observed, with fruit availability generally higher in SS, young leaf availability higher in TS and more species of flowers and young leaves in SF. Thus past land use had left behind a legacy of heterogeneous forest landscape with different plant communities and stand structure, which in turn caused differences in tree phenology.

These forests were found within the home range of a group of long-tailed macaques which showed differential use of the forest types. Of the three forest types, the SS likely provided the most important food sources for the macaques. They spent more time feeding/foraging in this forest type than expected from the distribution of forest types within their home range. The macaques are predominantly frugivorous and the SS provided the highest productivity of fruit. Although total stem density of fruiting trees was also highest in the SS, this index did not predict macaque use of SS forest. Instead, higher macaque use of the SS was predicted by higher stem density of trees with young leaves. This could reflect the flexible foraging strategies employed by the macaques. They minimize foraging time when high-quality fruits are abundant, which is similar to the situation with high-quality anthropogenic food (Sha and Hanya 2013a). For lower quality foods like leaves, they minimized foraging effort and maximized food intake by using habitats where these resources were more clumped, i.e., where stem densities were higher. When productivity of fruits was high and availability of leaves was clumped, the SS could support larger groups of these social animals in a smaller area, thus reducing the energy cost for foraging and food competition (Chapman et al. 1995). Secondary forests could, in some instances, provide more food resources for generalist frugivores than old-growth forests, as also shown in other studies, e.g., DeWalt et al. (2003).

The macaques spent a relatively high percentage of time in the TS forest, although fruit resources were lowest here. The basal area of young leaves in TS was comparable to that in the SS, but this index did not predict use of the TS. Instead, the TS use by macaques was predicted by higher stem density of trees with young leaves. Indeed, this index was the highest amongst the different forest types. Total basal area and stem density in this forest type was also the highest, thus theoretically producing the largest biomass of total food resources (if we do not restrict our definition of food resources only to fruits, flowers and young leaves), as macaques have also been observed to feed on mature leaves (Sha and Hanya 2013a). As high-quality fruit resources are more temporally variable when compared to leaf resources, and macaques generally having rather flexible diets, the TS may provide a more stable food base of leaves throughout the year.

Although the two secondary forests had relatively low species similarity, the species that do occur in both forest types were important food resources. These included Rhodamnia cinerea, Knema malayana, species of the genus Syzygium, as well as Prunus polystachya. These secondary forests are also important for more folivorous mammals that use these forests, e.g., the Malayan flying lemur (Galeopterus variegatus) is known to feed on young leaves of Syzygium spp. and R. cinerea (Agoramoorthy et al. 2006; Lim et al. 2013). In addition, the young leaves of several abundant species in the TS, such as K. malayana and Nothaphoebe umbellifora, are also important food sources for the banded leaf monkey (Presbytis femoralis femoralis), which occurs predominantly in freshwater swamp forest and has a highly folivorous diet (Ang 2011).

The macaques’ use of the SF was limited, likely because absolute fruit and leaf resources were comparatively low. However, high fruit species richness predicted higher use of SF, which could indicate a role of the SF as a fallback habitat for high-quality fruit resources when preferred fruits in other forests are not available. There could also be some preferred food resources in the SF, e.g., fruits of Elaeocarpus petiolatus, which is an abundant species in this forest and regularly fed on by the macaques (but not found in other forest types).

Different reproductive plant parts of different forest types in this study showed high variability across the year. In general, the peak production of flowers, fruits and young leaves in these three forest types occurred at different times of the year, and could provide a continuous source of food for mammalian herbivores, particularly the long-tailed macaques that have highly flexible diets and can feed on a variety of plant parts. In addition, despite temporal variability in resource productivity amongst habitat types, total productivity of fruits, flowers and young leaves within the mosaic forest appeared to be relatively stable across the year. Mosaic forest likely benefits the long-tailed macaque and other mammalian herbivores that include heterogeneous habitats within their home range, as the staggered phenology events provide continuous and varied food sources throughout the year and can buffer the effects of temporal food resource scarcity during times of low resource conditions in any given forest type.

The destruction of old-growth forest and subsequent changes in forest structure and composition are generally regarded as detrimental to the conservation of wildlife species (Aleixo 1999; Gibson et al. 2011). Thus, conservation efforts have largely focused on the preservation and restoration of old-growth forest, while the potential conservation value of secondary forests is largely neglected. Indeed, secondary forests have been suggested to be important for the persistence of forest species, particularly in tropical, human-modified landscapes (Chazdon et al. 2009). In general, the value of regrowth forests increases with successional age. For example, regrowth forests that are at least 20 years old can resemble mature forest in some structural characteristics important for wildlife habitats (Herrera-Montes and Brokaw 2010); within 70 years following the cessation of active management, many structural aspects of secondary forests resembled those of old-growth stands (DeWalt et al. 2003). However, not all forest regenerate quickly or as expected, e.g., in heavily logged forests, the regeneration rate was consistently slower than in unlogged areas (Chapman and Chapman 1997). The potential of secondary forests of different successional stages should be given more priority for conservation management planning.

Intensive human modification of natural habitat has caused many primate species to live in matrix landscapes of fragmented forests interspersed amongst various human land-use areas for agriculture and habitation (Meijaard 2016). Studies have shown that matrixes in human-modified landscapes can provide habitat continuity, and the flexibility of some primate species to traverse and utilize such landscapes to supplement their diets is critical to their survival (Pozo-Montuy et al. 2013; Arroyo-Rodríguez et al. 2017). Examining such primate responses to small-scale landscape heterogeneity can improve our understanding of the importance of mosaic forest for wildlife species, which is crucial to the conservation and management of wildlife habitats in our increasingly human-altered landscapes.



We thank all the assistants who took part in this project. We express our sincere gratitude to Chong Kwek Yen, Alex Yee, Shawn Lum, Ali Ibrahim and Gwee Aik Teck for their assistance in plant identification. We thank the National Parks Board Singapore (NParks) for their support, in particular Jeremy Woon, for coordinating the permit procedures for this project (NParks permit NP/RP10-022). We appreciated the assistance of Nobuo Imai for the NMDS analysis. We thank Colin Chapman and an anonymous reviewer for their valuable comments during the review process.


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Copyright information

© Japan Monkey Centre and Springer Japan KK 2017

Authors and Affiliations

  • John Chih Mun Sha
    • 1
  • Siew Chin Chua
    • 2
  • Ping Ting Chew
    • 3
  • Hassan Ibrahim
    • 3
  • Hock Keong Lua
    • 3
  • Tze Kwan Fung
    • 4
  • Peng Zhang
    • 1
  1. 1.School of Sociology and AnthropologySun Yat-Sen UniversityGuangzhouChina
  2. 2.Ridge View Residential CollegeNational University of SingaporeSingaporeSingapore
  3. 3.National Parks BoardSingaporeSingapore
  4. 4.School of Biological SciencesNational University of SingaporeSingaporeSingapore

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