Spatio-Temporal Correlations of Large Predators and Their Prey in Western Thailand

Home , Malayan tapir, Western Forest Complex, Western Thailand

Vinitpornsawan & Fuller: Predator and prey behaviours in Thailand Conservation & Ecology RAFFLES BULLETIN OF ZOOLOGY 68: 118–131 Date of publication: 8 April 2020 DOI: 10.26107/RBZ-2020-0013 http://zoobank.org/urn:lsid:zoobank.org:pub:ABF4C425-5FAA-40F9-A4EC-C4DF0DAB51C6

Spatio-temporal correlations of large predators and their prey in western Thailand

Supagit Vinitpornsawan1,2 & Todd K. Fuller1*

Abstract. The coexistence of predators with similar morphology can be achieved by avoidance through behavioural, temporal and spatial segregation, which separates niches and reduces competition. Partitioning of space and time can reduce competition by decreasing the frequency of interspecific encounters that exploit a common resource base. We investigated temporal and spatial partitioning of tigers (Panthera tigris), leopards (Panthera pardus), dholes (Cuon alpinus), and their ungulate prey in Thung Yai Naresuan (East) Wildlife Sanctuary in western Thailand from April 2010 to January 2012. We collected camera trap data from 106 locations over 1,817 trap nights. Kernel density estimation and Spearman’s rank correlation were used to quantify temporal and spatial activity patterns. Pianka’s index was used to investigate the temporal and spatial overlap for each species pair. Tigers (crepuscular activity pattern) showed no temporal correlation with leopards (mostly diurnal) or dholes (strongly diurnal), but leopard activity appeared to correlate positively with dhole activity. Tigers exhibited temporal overlap with larger gaur (Bos gaurus) and sambar (Rusa unicolor); leopards did so with barking deer (Muntiacus muntjak) and wild boar (Sus scrofa); and dholes did so with barking deer and wild boar. The spatial correlations of tigers, leopards, and dholes did not significantly overlap, though numerically overlap was higher between felids than with the canid. None of the three predators significantly correlated with prey distribution, except for dholes with sambar. Our findings suggest that tigers, leopards, and dholes co-occur with spatial and temporal partitioning due to differences in prey activity and low overlap in space use correlated to prey preference. The partition in space and time between tigers and leopards can minimise their competition-associated prey activity, while leopards and dholes seem to be more generalist and not spatially correlated with each other.

Key words. activity, tiger, leopard, dhole, gaur, sambar, Malayan tapir, barking deer, wild boar, camera trap

INTRODUCTION Predators affect prey populations and communities by direct and indirect effects on prey behaviours and life histories Interaction between species and the distribution of resources (Bolnick & Preisser, 2005). Selective predation on prey characterise ecological systems and provide essential may result from predators preferring prey of a certain size, information needed to understand the roles of species in behaviour, time, encounter rate, vulnerability, and predation communities (Schoener, 1974; Thompson, 1982). Spatial risk (Emlen, 1966; Polisar et al., 2003; Creel et al., 2005; and temporal partitioning is a viable strategy for minimising Jenny & Zuberbühler, 2005). This can cause prey to exhibit resource competition between species and increasing predator-avoidance behaviour by shifting to other food coexistence (Pianka, 1967; Thompson, 1982; Ramesh et patches or feeding times, or even aggregating into groups al., 2012). In general, activity patterns and spatial use for to repel the predators (Abrams, 1984; Overdorff, 1988; each species are influenced by several factors, which include Palomares & Caro, 1999; Eccard et al., 2008). Over time, physiological adaptations, food availability, distribution these interactions can result in the evolution of physical and pattern, human disturbance, and life-history strategies behavioural traits (Dawkins & Krebs, 1979). (Karanth & Sunquist, 2000). However, several predatory species hunting in the same area Interaction between carnivores and herbivores are can increase the pressure on prey populations (Johnsingh, characterised in terms of predator and prey interactions. 1992). The coexistence of predators with similar morphology can be achieved by avoidance through behavioural, habitat, temporal, and spatial segregation (Schaller, 1972; Malcolm & van Lawick, 1975; Ramesh, 2010; Ramesh et al., 2012). Accepted by: Norman Lim T-Lon Such differences in activities separate niches and reduce 1Department of Environmental Conservation, University of Massachusetts, Amherst, competition, presumably allowing the coexistence of * MA 01003 USA; Email: [email protected] ( corresponding author) sympatric living species (Bekoff et al., 1984; Sunquist & 2Wildlife Conservation Office, National Parks, Wildlife and Plant Conservation Department, 61 Paholyathin Rd., Chatujak, Bangkok 10900 Thailand Sunquist, 1989).

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Fig. 1. Thung Yai Naresuan (East) Wildlife Sanctuary (TYNE), Thailand.

119 Vinitpornsawan & Fuller: Predator and prey behaviours in Thailand

Tigers (Panthera tigris), leopards (Panthera pardus), and Data collection. Data were recorded by 106 camera traps dholes (Cuon alpinus) selectively kill prey types of different (Stealth Cam I590 with 5.0 megapixels, Grand Prairie, TX; species, size, and age-sex classes, facilitating their coexistence and Bushnell Trophy Cam infrared with 8.0 megapixels, through ecological separation (Johnsingh, 1992; Karanth Overland Park, KS) for a total of 1,817 trap days from April & Sunquist, 1995, 2000). Ramesh et al. (2012) found that 2010 to January 2012. Cameras were set to operate 24 hours dholes were temporally segregated from tigers and leopards, per day with three images per trigger, with a one-minute delay while spatial overlap occurred with leopards but not with for Stealth Cams (minimum setting) and a 30-second delay tigers. Partitioning of space and time can reduce competition for Bushnell Trophy Cams to maximise animal detection. All by decreasing the frequency of interspecific encounters that camera trap stations contained a pair of cameras, one of each exploit a common resource base (Kronfeld-Schor & Dayan, type to control for detection biases inherent in the different 2003; Ramesh et al., 2012). In Thailand, diet and habitat camera models at the location. The units were installed facing partitioning between these three main predators and their prey each other on both sides of wildlife trails. Each camera trap have previously been reported (Rabinowitz, 1989; Rabinowitz was placed 0.4–0.5 m from the ground and secured to a tree. & Walker, 1991; Grassman, 1999; Ngoprasert et al., 2007; All vegetation and debris were cleared from the field of view Simcharoen et al., 2008; Jenks et al., 2012), but less is known so that both medium and large animals had the opportunity about the behavioural mechanisms underlying temporal and to be photographed. Cameras were deployed in the field spatial partitioning within this group. These large carnivores for 15–20 days before batteries and memory cards were are also known to occupy Thung Yai Naresuan (East) Wildlife replaced. We ensured spatial and temporal independence by Sanctuary, but the activity patterns of predator and prey within minimising trap spacing between camera stations to 2 km the sanctuary are poorly understood. Thus, this study aims to (Fig. 2). No baits or lures were used with the camera traps. enhance our understanding of the coexistence of carnivores Each trap location was checked on a weekly basis to reduce and their prey in the sanctuary, by using camera traps to: 1) their down time from the risks of interference (from humans investigate spatial and temporal activity patterns, 2) compare and large mammals) and to replace batteries and the memory spatial and temporal activity overlap, and 3) evaluate the card when necessary. We selected camera sites based on the avoidance among species through the diel cycle. presence (scats, scrapes, pugmarks, and urination sites) of tigers, leopards, and dholes, and their main prey signs (dung, footprints, calls, and sightings). We placed each camera trap MATERIAL AND METHODS where trails merged or where no alternative trails existed to increase the probability of capturing our target species. Study site. This study was conducted in Thung Yai Naresuan (East) Wildlife Sanctuary, located in the Western Forest Activity patterns were extracted from the camera data for three Complex (WEFCOM) along the Thailand-Myanmar border. predators (tigers, leopards, and dholes) and their five major The sanctuary is adjacent to Huai Kha Khaeng Wildlife prey species: gaur (Bos gaurus), sambar (Rusa unicolor), Sanctuary, which is located at the core of the WEFCOM barking deer (Muntiacus muntjac), wild boar (Sus scrofa), and was designated as a Natural World Heritage Site in 1991 and Malayan tapir (Tapirus indicus), based on an earlier food (Buergin, 2001; WEFCOM, 2004) (Fig. 1). The Thung Yai habits study in the adjacent protected area (Phetdee, 2000). Naresuan Wildlife Sanctuary contains a variety of forest Each photograph was stamped with the time and date. To types, including mixed deciduous (45%), dry evergreen avoid pseudo-replications, we considered the first capture of forest (31%), and hill evergreen forest (15%) (Nakhasathien the animal as an independent record (Yasuda, 2004; Ramesh & Stewart-Cox, 1990). Secondary forest of varying stages of et al., 2012). Any species captured at both cameras in each regeneration covers 4% of the sanctuary, and the remaining camera location at the same time was counted as only one 5% consists of savanna, deciduous dipterocarp forest, and record for analysis. Independence of detections was defined grassland (Nakhasathien & Stewart-Cox, 1990; Duengkae as: 1) consecutive (each continuously following) photographs et al., 2006; Steinmetz et al., 2006). The sanctuary has of different individuals of the same (that is, individually long been inhabited by the indigenous minority known as distinguishable because of identifying marks) or different “Karen” (Emphandhu, 2003). The vegetation is still largely species; 2) consecutive photographs of individuals of the undisturbed as little logging or shifting cultivation has been same species (not individually identifiable) when separated practised (Buergin, 2003; Steinmetz et al., 2006). Major rivers by more than 30 min; or 3) non-consecutive photographs of in the Thung Yai Naresuan Wildlife Sanctuary are the Mae individuals of the same species (e.g., a photograph of one Klong and the Mae Chan, which feed the Si Nakharin Dam. species, then of a different species, then of the first species) The sanctuary is characterised by rugged mountainous terrain (O’Brien et al., 2003; Yasuda, 2004; Gray & Phan, 2011). with elevations rising up to 2,000 m. The lowland zone is Only tigers and leopards were individually identified, based found in the western part of the sanctuary (Nakhasathien on unique patterns on the body (Miththapala et al.,1989; & Stewart-Cox, 1990; Steinmetz et al., 2006); a moderate Karanth, 1995). Poor quality photographs in which the altitude zone is located mainly in the centre; and a high, species could not be confidently identified were excluded steep zone consisting of mountains ranging from 1,000 to from the analysis. Independent photographs were regarded 2,000 m is found in the east (Steinmetz et al., 2006). The as a random sample from the underlying distribution that climate of this region is monsoonal with a dry season from describes the probability of a photograph being taken within November to May, and a wet season from May to October any particular interval of the day (Linkie & Ridout, 2011). (Duengkae et al., 2006; Steinmetz et al., 2006). The probability density function of this distribution was

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Fig. 2. Camera trap locations in Thung Yai Naresuan (East) Wildlife Sanctuary. then referred to as the activity pattern, and we presumed quantifying the temporal activity patterns between predator that an animal was equally likely to be photographed at all and prey (Ridout & Linkie, 2009; Linkie & Ridout, 2011). times when it was active (Ridout & Linkie, 2009; Linkie The kernel density estimation was used to estimate the & Ridout, 2011). probability density function of the activity patterns of main predators (tiger, leopard, and dhole) against their main and Data analyses. First, we identified prey species most likely potential prey (gaur, sambar, tapir, barking deer, and wild utilised by the predators of concern. Previous studies have boar) (Sillero-Zubiri, 2009; Wang & MacDonald, 2009). indicated that tigers are often found to be associated mainly Then, we applied a smoothing parameter (bandwidth = 1.2) with medium to large mammalian herbivorous prey species, to generate the temporal predator-prey activity patterns as including gaur (Bos gaurus), sambar (Rusa unicolor), barking per Ridout & Linkie (2009). Analyses were performed in deer (Muntiacus muntjak), and wild boar (Sus scrofa) the software R and the package Overlap (R Development (Karanth & Sunquist, 1995; Phetdee, 2000; Bhattarai & Core Team, 2017). Kindlmann, 2012). The largest ungulates, gaur and sambar, contribute the greatest biomass consumed by tigers, whereas To examine the temporal correlation between each pair of medium-sized barking deer and wild boar contribute the predator and prey, we summed all independent photographs largest portion of the leopard diet (Karanth & Sunquist, 1995; for each species by hourly bins over a 24-hour period. We Hayward et al., 2006). Prey preferred by dholes is generally then calculated the percent of photographic captures for each medium-sized (Karanth & Sunquist, 2000) but can include species with the 24-hour cycle (Azlan & Sharma, 2006; deer, gaur, banteng (Bos javanicus) and other large bovids Harmsen et al., 2009; Ramesh et al., 2012). We tested the (Grassman et al., 2005; Andheria et al., 2007; Sillero-Zubiri, correlation between each predator-prey pair using Spearman’s 2009; Kamler et al., 2012). For each species, we used a rank correlation coefficient using the programme SPSS 16.0 non-parametric kernel density estimation procedure for (SPSS Inc., Chicago, Illinois, 2007). Then, we evaluated

121 Vinitpornsawan & Fuller: Predator and prey behaviours in Thailand the probability of temporal overlaps for each pair between and a minor peak between 2200 and 0000 hours (Fig. 3A). predator and prey by using Pianka’s index, Leopards and dholes had peaks of activity during the day (Fig. 3D). Most leopard activity (63%) was between 0600 n 2 2 1/2 Ojk i =1 P1i P2i P1 i P2 i ) and 1800 hours, with a major peak between 0900 and 1100 hours, a minor peak around midnight between 2300 and 0000 where= ∑ Pi is the/(∑ frequency ∑ of occurrence of species 1 and hours, and very low activity after midnight (0000 to 0300 2 at location i. Pianka’s index (O) varies between 0 (total hours) (Fig. 3B, C, D). Dholes showed bimodal activity with separation) and 1 (total overlap). This index corresponds high diurnal activity (95% between 0600 and 1800 hours to the area of intersection of the utilisation histograms of and a major peak in activity from 0900 to 1100 hours) and the two species. We assessed Pianka’s indices through a minor peak in activity between 1600 and 1700 hours (Fig. Monte Carlo randomisations (5,000 iterations) of relative 3A, D). Tigers showed a crepuscular activity pattern, while abundance in each particular hour, to simulate possible leopards tended to be diurnal, and dholes showed a strongly overlaps using the programme EcoSim 7.0 (Pianka, 1967; diurnal activity pattern and had more activity during the Gotelli & Entsminger, 2004). day than both felids (Fig. 3A). Although temporal activity among the three predators significantly overlapped only We examined spatial overlap among predators and their between leopard and dhole (Table 2), activity of the tiger, prey by calculating the photographic rate of each camera leopard, and dhole overlapped for more than 10 hours of trap station as an independent spatial point to reflect the the day (Fig. 3A). relative abundance of target species, which was based on the assumption that there is an equal probability that all camera Gaur exhibited several peaks of activity throughout the 24- traps will capture an animal (Carbone et al., 2001; O’Brien hour day (i.e., cathemeral; Fig. 4A), with 59% of activity et al., 2003; Azlan & Sharma, 2006). The photographic rate between 0600 and 1800 hours, and a major peak between of each species for each camera trap station was defined as 1700 and 1800 hours. Sambar were predominantly nocturnal the total number of independent photographs divided by (only 25% of activity between 0600 and 1800 hours), with the total number of independent records from the total trap bimodal peaks between 1900 and 2000 hours, and between nights (Azlan & Sharma, 2006; Ramesh et al., 2012). The 0200 and 0400 hours (Fig. 4B). Tapirs had peaks of activity photographic rate provided an estimate of abundance of during the night similar to sambar (peaks between 0000 and each species, and hence facilitated comparison of spatial use 0200 hours and between 2000 and 2200 hours), but tapir between different species. We observed the relations between activity was more strongly nocturnal (only 4% between 0600 predators and prey at each camera trap station by applying and 1800 hours) (Fig. 4C). In contrast, activity of barking Spearman’s rank correlation coefficient as a measure of spatial deer and wild boar was strongly diurnal (78% and 93% correlation. We evaluated spatial overlap for each predator- between 0600 and 1800 hours, respectively). Barking deer prey pair by using Pianka’s index assessed through Monte had a major activity peak between 0700 and 1100 hours and Carlo randomisations (5,000 iterations) of relative abundance a minor peak from 1700 to 1900 hours (Fig. 4D), while wild in each particular location and using the programme EcoSim boar had high activity from 0900 to 1100 hours and again 7.0 (Pianka, 1967; Gotelli & Entsminger, 2004). from 1400 to 1600 hours (Fig. 4E).

Tigers showed no temporal correlation with leopards or RESULTS dholes, but exhibited a positive temporal correlation with gaur (0.44, P < 0.05; Table 2). Leopard activity appeared to A total of 2,027 photographs was obtained for the eight target correlate positively with that of dholes (0.46, P < 0.05) and species, which equated to 875 independent photographs. The also showed positive correlations with activity of barking number of independent photographs of each species varied deer (0.47, P < 0.05) and wild boar (0.48, P < 0.05), but from 22 for gaur to 408 for barking deer (Table 1). correlated negatively with tapir activity (− 0.49, P < 0.05). Dhole activity was positively correlated with that of barking Tigers, leopards, and dholes did not significantly overlap deer (0.55, P < 0.01) and wild boar (0.47, P < 0.05). Tiger spatially, though numerically overlap was higher between activity overlapped with activity of larger gaur (73%) and felids than with canid (Table 2). None of the three predators sambar (64%), but also with activity of barking deer (72%). significantly correlated spatially with prey, except for dhole Leopard activity overlapped with that of barking deer and and sambar (0.20, P < 0.05). However, tigers and leopards wild boar, while dhole activity overlapped only with activity appeared to have the highest spatial overlap with barking of smaller barking deer (80%) and wild boar (77%). deer, while dholes had the highest spatial overlap with sambar and tapir. DISCUSSION Tigers, leopards, and dholes showed activity patterns with minor and major peaks (Fig. 3A, B). Tigers were active Temporal activity correlation. We studied the temporal throughout the 24-hour period (48% between 0600 and activity patterns of large predators and prey in Thung Yai 1800 hours), but had peaks of activity around dawn, dusk, Naresuan (East) Wildlife Sanctuary (TYNE). We found and during the night (Fig. 3A, B). The major peak of tiger leopards and dholes to be strongly active during the day. activity was in the morning between 0700 and 0900 hours Tigers were active throughout the day, with major and minor

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Table 1. The number of photographs obtained of large predators and their principal prey in Thung Yai Naresuan (East) Wildlife Sanctuary, Thailand.

Species name Number of photographs

Common Scientific Total Independent Tiger Panthera tigris 57 27 Leopard Panthera pardus 72 43 Dhole Cuon alpinus 31 24 Gaur Bos gaurus 41 22 Sambar Rusa unicolor 450 182 Malayan tapir Tapirus indicus 84 30 Barking deer Muntiacus muntjak 745 408 Wild boar Sus scrofa 185 64

Table 2. Spatial and temporal correlations of large predators and their prey in Thung Yai Naresuan (East) Wildlife Sanctuary, Thailand. aP Correlation significant (P < 0.05); bP Correlation significant (P < 0.01).

Species pair Temporal Spatial

Correlation Overlap index Correlation Overlap index Tiger and leopard 0.04 0.58 0.09 0.18 Tiger and dhole − 0.06 0.37 − 0.02 0.02 Tiger and gaur 0.44a 0.73 0.03 0.17 Tiger and sambar 0.11 0.64 0.03 0.17 Tiger and Malayan tapir − 0.12 0.39 0.02 0.11 Tiger and barking deer 0.23 0.72 0.10 0.37 Tiger and wild boar − 0.03 0.49 0.13 0.25 Leopard and dhole 0.46a 0.76 − 0.12 0.01 Leopard and gaur 0.13 0.45 − 0.10 0.06 Leopard and sambar − 0.37 0.41 0.01 0.11 Leopard and Malayan tapir − 0.49a 0.17 − 0.02 0.08 Leopard and barking deer 0.47a 0.80 0.16 0.25 Leopard and wild boar 0.48a 0.77 0.01 0.21 Dhole and gaur − 0.12 0.22 0.17 0.04 Dhole and sambar − 0.43 0.12 0.20a 0.12 Dhole and Malayan tapir − 0.38 0.05 0.12 0.18 Dhole and barking deer 0.55b 0.63 0.03 0.09 Dhole and wild boar 0.47a 0.57 − 0.04 0.05

123 Vinitpornsawan & Fuller: Predator and prey behaviours in Thailand (A) (B)

Fig. 3. Kernel density estimates of daily predator activity patterns. A, tiger, leopard, and dhole; B, tiger and leopard; C, tiger and dhole; D, leopard and dhole. The shaded areas indicate the overlap coefficient; that is, the area under the minimum of the two density estimates. peaks of activity around dawn and dusk. Previous tiger studies Higher temporal overlap between tiger and leopard than also found similar patterns (Kawanishi & Sunquist, 2004; between tiger and dhole was also reported in Mudumalai Azlan & Sharma, 2006; Ridout & Linkie, 2009; Ramesh et Tiger Reserve, India (Ramesh et al., 2012). We found that al., 2012). Temporal segregation between tiger and leopard tigers and leopards had a temporal overlap of 58%, while the was reported by Rabinowitz (1989) and Azlan & Sharma similar study in India found this temporal overlap to be larger (2006); they found that an adult leopard was largely diurnal than 80% (Ramesh et al., 2012; Lamichhane et al., 2019), (66% and 70% of daily activity, respectively), concluding that reportedly owing to their similar morphology and hunting leopards were diurnal when tigers occurred in the same area. strategies (Karanth & Sunquist, 1995; Ramesh et al., 2012). We found the temporal activity of dholes to be exclusively diurnal (up to 95%), which gave them temporal partitioning Tigers had significant temporal overlap with gaur but not from tigers. Camera trap studies in Laos and Malaysia also with small prey such as barking deer and wild boar, perhaps found strong diurnal dhole activity (Kawanishi & Sunquist, because of a preference for large prey size, as reported 2004; Kamler et al., 2012; Ramesh et al., 2012), though elsewhere (Johnsingh, 1983; Karanth & Sunquist, 1995; studies in Thailand by Grassman et al. (2005) and Jenks et Bhattarai & Kindlmann, 2012), and a crepuscular activity al. (2012) found that dholes were primarily diurnal but also pattern (Prayurasiddhi, 1997; Steinmetz, 2004; Steinmetz active during crepuscular period. et al., 2010). The small temporal correlation between tigers and smaller prey could be due to both barking deer and wild boar having had highly diurnal activity, having decreased

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(E)

Fig. 4. Kernel density estimates of daily activity patterns of tigers and prey species. A, tiger and gaur; B, tiger and sambar; C, tiger and tapir; D, tiger and barking deer; E, tiger and wild boar. The dashed lines are kernel density estimates for tigers and the solid lines are kernel density estimates for the prey species. The shaded areas indicate the overlap coefficient; that is, the area under the minimum of the two density estimates.

125 Vinitpornsawan & Fuller: Predator and prey behaviours in Thailand (A) (B)

(E)

Fig. 5. Kernel density estimates of daily activity patterns of leopards and prey species. A, leopard and gaur; B, leopard and sambar; C, leopard and barking deer; D, leopard and tapir; E, leopard and wild boar. The dashed lines are kernel density estimates for leopards and the solid lines are kernel density estimates for the prey species. The shaded areas indicate the overlap coefficient; that is, the area under the minimum of the two density estimates.

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(E)

Fig. 6. Kernel density estimates of daily activity patterns of dholes and prey species. A, dhole and gaur; B, dhole and sambar; C, dhole and tapir; D, dhole and barking deer; E, dhole and wild boar. The dashed lines are kernel density estimates for dholes and the solid lines are kernel density estimates for the prey species. The shaded areas indicate the overlap coefficient; that is, the area under the minimum of the two density estimates.

127 Vinitpornsawan & Fuller: Predator and prey behaviours in Thailand their activity when tigers were active. However, a study in including some arboreal ones for leopards (Seidensticker, Malaysia found that tigers were more diurnal than nocturnal, 1976; Odden et al., 2010; Mondal et al., 2012). and that patterns of activity were more similar to those of crepuscular/diurnal species such as barking deer and wild Dholes also exhibited spatial segregation from both tigers boar (Kawanishi & Sunquist, 2004). Furthermore, a study and leopards, and showed significant spatial overlap with in Sumatra also found that tigers and barking deer exhibited sambar. Besides avoiding the other predators, dholes also peaks of activity around dawn and dusk and that temporal have a high proportion of sambar in their diet (Johnsingh, overlap between both species was strong (Linkie & Ridout, 1992; Karanth & Sunquist, 1995; Grassman et al., 2005; 2011). Based on camera trap records and abundance estimates, Andheria et al., 2007; Thinley et al., 2011; Kamler et al., their studies reported that the abundance of large prey such as 2012), therefore prey selection associated with habitat use gaur and sambar was low. The correspondence between the by the prey may be one of the primary factors influencing activity patterns of tigers and barking deer was suggested to their spatial activity pattern. be due to barking deer being an important tiger prey species in term of abundance, biomass, and occupancy (Kawanishi In summary, the spatial overlap among the three predators & Sunquist, 2004; Linkie & Ridout, 2011). was low and insignificant, indicating some characteristic differentiation in the use of spatial resources. A traditional The diurnal activity of leopards and dholes may be due to interpretation of low overlap suggests species do so to the fact that smaller prey such as barking deer and wild boar avoid sharing resources and reduce competition (Gotelli & were more active diurnally. This activity pattern could also Graves, 1996). have served to enhance temporal separation from tigers. Dholes had no temporal correlation with tigers but correlated Conclusions. In the period of our study in TYNE, tigers, temporally with leopards. In contrast, Ramesh et al. (2012) leopards, and dholes seemed to co-occur with a combination did not observe temporal correlations between dholes and of both spatial and temporal partitioning due to differences either tigers or leopards. Elsewhere, a correlation in activity in predator and prey activity and low overlap in space use between leopards and dholes could have resulted from correlated with their prey preferences. Moreover, this survey leopards and dholes consuming similar medium-sized prey demonstrated that coexistence between tiger and leopard in that were usually active during the day (Wang & Macdonald, TYNE was a result of low density (1.4–1.6 tigers per 100 2009; Ramesh, 2010; Bhattarai & Kindlmann, 2012) and also km2, 0.7–0.8 leopards per 100 km2, respectively, based on avoiding tigers, which mainly hunted larger, nocturnal prey maximum likelihood spatially-explicit capture-recapture; (Johnsingh, 1992; Karanth & Sunquist, 1995; Mondal et al., Vinitpornsawan, 2013). The partitioning in space and time 2012). Prey selection by leopards and dholes may also be between tigers and leopards could minimise competition associated with a preference for reduced risk of injury during associated with the activity of their major prey, while prey capture, which could then be an underlying reason for leopards and dholes seem to be more generalist predators the lower preference, by leopards and dholes, for large prey (Edgaonkar, 2008; Aryal et al., 2015; Gray, 2013; Hayward (Karanth & Sunquist, 1995). et al., 2014) and thus may not have been so influenced by spatial correlation with each other. This contrasts with We found negative temporal correlations between the three the study in Nagarhole National Park, India (Karanth & predators and tapirs. Tapirs were predominantly nocturnal, Sunquist, 2000), which reported that the three predator species while tigers were active primarily during twilight, and used the same areas and hunted in similar habitats (where leopards and dholes were predominantly diurnal. The camera prey densities were particularly high), but were similar in trap surveys by Lynam (1999), Holden et al. (2003), and partitioning of time and space as their counterparts in the Linkie & Ridout (2011) also supported our results. In fact, Royal Chitawan National Park and Bardia National Park, tapirs do not seem to be a principal prey species of tigers Nepal, and Sariska National Park, India (Seidensticker, 1976; when other prey species are present (Kawanishi & Sunquist, Odden et al., 2010; Mondal et al., 2012). Our results did 2004; Andheria et al., 2007; Linkie & Ridout, 2011). not allow us to conclude whether the spatial and temporal partitioning among tigers, leopards, and dholes were primarily Spatial activity correlation. We found no significant spatial associated with prey size, prey preference, prey density, or correlations among the three predators in the study area. even prey distribution. Other studies on prey selection and A similar study in India also found no significant spatial diet reported that predators selected the most abundant prey correlation between tigers and leopards (Ramesh et al., 2012). species within their preferred size range, which was related to Furthermore, Ramesh et al. (2012) reported greater spatial their body size (Johnsingh, 1992; Karanth & Sunquist, 1995, overlap between tigers and leopards than with dholes. Spatial 2000; Andheria et al., 2007; Bhattarai & Kindlmann, 2012). overlap between tigers and leopards was reported in Malaysia, where leopards sometimes used the same areas and trails Further temporal and spatial activity studies that include diet, as tigers (Azlan & Sharma, 2006). However, our tigers and seasonality, and habitat use are needed to better understand leopards did not appear to overlap much in terms of space inter-specific relationships and coexistence, which will help use (index = 0.18) as compared to the study by Ramesh et al. clarify the use of shared resources through the partitioning (0.71; 2012); other studies indicate that tigers and leopards of time and space among the large sympatric carnivore avoid competition by hunting in different forest types, with communities. Thung Yai Naresuan (East) Wildlife Sanctuary different activity patterns as well as different prey species, (TYNE) certainly provides a large and contiguous habitat for

128 RAFFLES BULLETIN OF ZOOLOGY 2020 the coexistence of tigers, leopards, dholes, and their prey. in the context of Thailand’s globalization and modernization. We suggest that the coexistence of predators in TYNE could Geoforum, 24: 375–393. be enhanced via the application of habitat management for Carbone C, Christie S, Conforti K, Coulson T, Franklin N, Ginsberg ungulates, such as the use of controlled burns to maintain JR, Griffiths M, Holden J, Kawanishi K, Kinnaird MF, Laidlaw R, Lynam A, Macdonald D, Martyr D, McDougal C, Nath L, grass-base for ungulate recovery, suppressing fires effectively O’Brien TG, Seidensticker J, Smith JDL, Sunquist ME, Tilson in evergreen forest areas, an ungulate reintroduction R & Shahruddin WNW (2001) The use of photographic rates to programme using ex situ bred species (i.e., Eld’s deer), estimate densities of tigers and other cryptic mammals. Animal creating artificial water sources for ungulates, and improving Conservation, 4: 75–79. the effectiveness of anti-poaching efforts through ground Creel S, Winnie J, Maxwell B, Hamlin K & Creel M (2005) Elk patrols. In our study area, local people and shifting cultivation alter habitat selection as an antipredator response to wolves. occupy the western part of the sanctuary, and these conditions Ecology, 86: 3387–3397. could restrict animal dispersal and movement. In these areas, Dawkins R & Krebs JR (1979) Arms races between and within zoning seems to be a good practice, but management actions species. 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