Predicting preferred prey of Sumatran tigers Panthera tigris sumatrae via spatio-temporal overlap
M AXIMILIAN L. ALLEN,MARSYA C. SIBARANI and M IHA K ROFEL
Abstract Encounter rates of carnivores with prey are Introduction dependent on spatial and temporal overlap, and are often highest with their preferred prey. The Critically Endangered nterspecific interactions are important aspects of com- Sumatran tiger Panthera tigris sumatrae is dependent on Imunity ecology, affecting the functional ecology of eco- prey populations, but little is known about its prey prefer- systems and dictating the ecological niches inhabited by ences. We collected camera-trap data for years (–) species (Begon et al., ). Such interactions can be diffi- in Bukit Barisan Selatan National Park, Sumatra, to investi- cult to assess, however, particularly for cryptic species such gate spatial and temporal overlap of tigers with potential as wild carnivores (Allen et al., ; Saggiomo et al., ). – prey species. We also developed a novel method to predict Carnivore prey encounter rates are dependent on spatial predator–prey encounter rates and potential prey preferences and temporal overlap, and high encounter rates are often in- from camera-trap data. We documented at least individual dicative of prey preference (Holling, ; Fortin et al., ). tigers, with an overall detection rate of . detections/ Data on spatio-temporal overlap of carnivores with poten- trap nights. Tigers exhibited a diurnal activity pattern and tial prey species may thus facilitate inference of prey prefer- had highest temporal overlap with wild boar Sus scrofa and ences and patterns of interspecific interactions, providing pig-tailed macaques Macaca nemestrina, but highest spatial insights into ecosystem functions that can inform effective overlap with wild boar and sambar deer Rusa unicolor.We conservation. Camera trapping is a non-invasive method created a spatial and temporal composite score and three that is increasingly being used to monitor wildlife and additional composite scores with adjustments for the spatial provides data on species richness, behaviour, and spatio- overlap and preferred prey mass. Wild boars ranked highest temporal activity (Swanson et al., ; Rich et al., ; for all composite scores, followed by sambar deer, and both Allen et al., ). are known as preferred tiger prey in other areas. Spatial and The tiger Panthera tigris is categorized as Endangered temporal overlaps are often considered as separate indices, throughout its range, with four subspecies probably extinct but a composite score may facilitate better predictions of en- in the wild (Seidensticker, ; Goodrich et al., ). counter rates and potential prey preferences. Our findings sug- The Sumatran tiger Panthera tigris sumatrae is Critically gest that prey management efforts in this area should focus Endangered (Linkie et al., ), as are many other species ’ on wild boar and sambar deer, to ensure a robust prey base for on the Indonesian island of Sumatra (O Brien & Kinnaird, this Critically Endangered tiger population. ; Pusparini et al., ). Prey abundance can have strong effects on the abundance and population density of tigers Keywords Activity patterns, composite score, Panthera (Karanth et al., ; Barber-Meyer et al., ), and tiger tigris, prey preference, spatial overlap, Sumatra, temporal declines have been linked to declines of prey in Russia and overlap, tiger India (Miquelle et al., ; Ramakrishnan et al., ). The Supplementary material for this article is available at prey preferences of tigers are unknown in many areas, but doi.org/./S such knowledge is important to inform conservation planning and ensure sufficient prey is available in areas critical to tiger conservation. Information about the Sumatran tiger’s diet is limited (e.g. O’Brien et al., ; Linkie & Ridout, ), and data on spatial and temporal activity patterns and overlap between tigers and potential prey could improve our under- standing of the subspecies’ prey preferences. Bukit Barisan Selatan National Park is one of the largest
MAXIMILIAN L. ALLEN (Corresponding author, orcid.org/0000-0001-8976- protected areas on the island of Sumatra, and is critical 889X) Illinois Natural History Survey, University of Illinois, 1816S. Oak for the conservation of the Sumatran tiger and other Street, Champaign, Illinois 61820, USA. E-mail [email protected] species of conservation concern, including the Critically MARSYA C. SIBARANI Wildlife Conservation Society—Indonesia Program, Bogor, West Java, Indonesia Endangered Sumatran rhinoceros Dicerorhinus sumatren- sis and Sumatran elephant Elephas maximus sumatranus MIHA KROFEL ( orcid.org/0000-0002-2010-5219) Department of Forestry, ’ Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia (O Brien & Kinnaird, ; Pusparini et al., ). The Park Received January . Revision requested April . provides relatively abundant tiger habitat, but threat levels Accepted May . are moderate to high because of inadequate conservation
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measures (Sanderson et al., ). Given the Park’simportance for tiger conservation, it is important to understand the spe- cies’ ecology in this area. Previous studies of activity patterns of Sumatran tigers in the Park produced conflicting results; O’Brien et al. () reported tigers had a diurnal activity pattern, whereas Pusparini et al. () reported a crepuscular activity pattern with highest activity levels near dawn. The tigers’ prey preferences and prey abundance in the area are also unknown. To inform conservation efforts, we investigated tiger spatio-temporal overlap with potential prey species, using years of camera-trap data from an area of the Park with little human activity. Our objectives were to () document the minimum number of individual tigers in the area, () deter- mine the temporal and spatial overlap of tigers with six po- tential prey species, and () create a composite score from the indices of temporal and spatial overlap as a novel method to predict predator–prey encounter rates and determine poten- tial prey preference. In our analyses we included all potential tiger prey species present in the study area, based on a review of tiger dietary studies (Hayward et al., ). In line with known prey preferences of tigers across their range, we ex- pected sambar deer Rusa unicolor and wild boar Sus scrofa to have the highest composite spatio-temporal score. FIG. 1 The study site with camera-trap locations of both arrays within Bukit Barisan Selatan National Park on the island of Sumatra, Indonesia. Study area
Our study site is in Bukit Barisan Selatan National Park, in designed our survey to monitor multiple species effectively the South Barisan Range ecosystem on the Indonesian is- (Rich et al., ). We set two arrays of camera traps, land of Sumatra (Fig. ). The Park is the third largest pro- using the Network’s protocols (TEAM Network, ), in tected area (, km ) on Sumatra (O’Brien & Kinnaird, sites chosen for accessibility for long-term repeated surveys, ), spanning two provinces: Lampung and Bengkulu. all in lowland forests at – m altitude. We placed camera Topography ranges from coastal plains and lowland rain- traps in each array at a density of per km (Fig. ), and forest at sea level in the southern peninsula of the Park the arrays covered a total of . km . We deployed the to mountains up to , m in the central and northern camera-trap arrays in the dry season (April–July) of each parts (Pusparini et al., ). The Park contains montane, year during –, with array in operation during lowland tropical, coastal and mangrove forests. Annual April–May and array during June–July, with the aim to rainfall is ,–, mm, most of which falls in the mon- complete at least sampling days for each camera trap. soon season (November–May), and annual temperatures We positioned camera traps near animal trails and/or are – °C (O’Brien et al., ). The Park contains a high places used regularly by wildlife, to maximize detections. diversity of wildlife, with tigers and other species listed We placed camera traps – cm off the ground, with no in the CITES Appendices and categorized as Endangered refractory period between images. or Critically Endangered on the IUCN Red List.
Statistical analyses Methods To avoid pseudo-replication, we considered consecutive Camera trapping photo captures of the same species as independent events only if they occurred after an interval of . min We set camera traps in the Park as part of the Tropical (Rovero & Zimmermann, ). We calculated the number Ecology and Assessment Monitoring Network, which col- of independent captures for each species, but combined lects long-term biodiversity data in tropical environments both mouse deer species (greater mouse deer Tragulus globally to guide conservation actions. Our goal was to napu and lesser mouse deer Tragulus kanchil) in one cat- monitor the terrestrial vertebrate community, and we egory because they share similar characteristics as potential
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tiger prey and it was difficult to distinguish between them on potential prey species. The upper right quadrant of the plot camera-trap images (O’Brien et al., ). (high spatial and temporal overlap) indicates the most en- We used a relative abundance index as a proxy for tiger countered and potentially most preferred prey species, where- abundance, because this is a more accurate proxy for as the upper left (high temporal but low spatial overlap) and abundance than occupancy values (Parsons et al., ). lower right (low temporal but high spatial overlap) quadrants We calculated the index as: would indicate potential alternative prey that were encoun- tered opportunistically in space or time. The lower left quad- relative rant (low spatial and temporal overlap) would indicate species = (detection events/trap nights) × 100 abundance index rarely encountered and probably not preferred. Finally, we calculated the mean of the spatial and tem- for each camera trap, to determine detection events per poral overlap values for each prey species to create a spa- trap nights (e.g. Allen et al., ), and averaged the values tial and temporal composite score (Song et al., ). This from all camera traps to determine an overall mean for the allowed us to rank the potential prey species, with higher study area. We used the stripe patterns of individual tigers to scores indicating higher encounter rate and potentially high- identify the minimum number of individuals, separately for er preference. photographs of the right and left flanks. We expected that this simple composite score could be We used kernel density estimation to determine activ- improved by giving additional weight to some variables or ity patterns and quantify overlap among species (Ridout & including other variables in the score. We therefore calcu- Linkie, ). We reviewed potential prey species for tigers lated three additional composite scores to determine how (Hayward et al., ) and analysed those in our study area different weighting of overlap scores or the inclusion of ad- with . detection events, which included the greater and ditional variables affect the preference rankings of potential lesser mouse deer (n = ), Malay tapir Tapirus indicus prey. (n = ), pig-tailed macaque Macaca nemestrina (n = ), Firstly, we assigned more weight to the spatial overlap red muntjac Muntiacus muntjac (n = ), sambar deer value, because spatial overlap with prey is an important as- (n = ), and wild boar (n = ). We first converted the pect of niche selection and resource partitioning for carnivores time of each event into a radians measurement for analysis. (Schoener, ; du Preez et al., ) and may better reflect We then used the overlap package (Meredith & Ridout, ) prey species being sought out, compared to temporal overlap. in R .. (R Core Team, ) to fit the data to a circular We calculated the spatial adjusted composite score as: kernel density, and estimated the activity level at each time × . + period from the distribution of the kernel density using a spatial adjusted = (spatial overlap 0 6) composite score (temporal overlap × 0.4) Δ overlap value based on our sample sizes. We used the overlapEst function to estimate the degree of overlap in activ- Secondly, we considered a composite score that also in- ity patterns between tigers and the potential prey species. We cluded prey mass, with a higher mass adjustment value (spa- calculated confidence intervals (CI) by bootstrapping , tial and temporal composite score × .) for prey within the estimates of activity for each species, and then using the preferred size range of tigers (– kg; Hayward et al., bootEst and bootCI functions to estimate the %CIforthe ) and a lower value (spatial and temporal composite overlap between tigers and each potential prey species. score × .) for potential prey outside this range. We ob- To determine spatial overlap with potential prey species tained prey mass values from Nowak () and used % we used the methods of Ngoprasert et al. (). We first cal- of the mean weight of adult females to account for young culated the relative abundance index for each prey species, animals being eaten (Hayward et al., ). We then calcu- as for tigers, and then scaled the index for each prey spe- lated the mass adjusted composite score as: cies at each camera-trap site to continuous probability values – × × of (Ngoprasert et al., ). We then created a logistic mass adjusted = (spatial overlap temporal overlap) regression for each prey species using data from each composite score mass adjustment camera-trap location. In the logistic regression we used tiger presence as the dependent variable and prey probabil- Thirdly, we calculated a spatial and mass adjusted com- ity values as the independent variable. We then compared posite score as: spatial overlap of prey species using the area under the ((spatial overlap × 0.6) + curve (AUC) of receiver operating characteristic plots spatial and mass = (temporal overlap × 0.4)) × (Fielding & Bell, ), and quantified the spatial overlap adjusted composite score of tigers with individual prey species as the AUC values, mass adjustment which range from . (random) to . (perfect fit). We then ranked potential prey species based on each To determine which prey species may be preferred we composite score, with higher scores indicating higher en- plotted the spatial and temporal overlap of tigers with each counter rate and potentially higher preference.
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TABLE 1 The indices of potential prey species of tigers Panthera tigris sumatrae in Bukit Barisan Selatan National Park, Sumatra, including relative abundance (detection events/ trap nights), temporal overlap, spatial overlap, and composite scores. Higher composite scores indicate greater encounter rates and potential prey preference. Species are listed in order of their spatial and temporal composite score.
Composite scores Relative Temporal Spatial Spatial & Spatial Prey mass Spatial & prey Species abundance overlap overlap temporal adjusted adjusted mass adjusted Wild boar Sus scrofa 3.15 0.80 0.71 0.76 0.77 0.83 0.84 Sambar Rusa unicolor 1.02 0.70 0.66 0.68 0.67 0.75 0.74 Pig-tailed macaque 4.32 0.76 0.60 0.68 0.66 0.61 0.60 Macaca nemestrina Red muntjac 7.10 0.68 0.57 0.63 0.62 0.56 0.56 Muntiacus muntjac Mouse deer1 3.39 0.62 0.53 0.58 0.57 0.52 0.51 Tapir Tapirus indicus 0.85 0.43 0.52 0.48 0.48 0.52 0.53
Greater mouse deer Tragulus napu and lesser mouse deer Tragulus kanchil.
Results score, the prey mass adjusted score and the spatial and prey mass adjusted score, with scores –% higher than – We had camera traps operating during for a the next species (Table ). As for the spatial and tempo- total of , trap nights. We obtained , photographs ral composite score, sambar and pig-tailed macaques also of species, including mammals. We documented all six ranked second and third, respectively, for these additional potential tiger prey species in all years of the study. We composite scores. The spatial adjusted composite scores captured photographs of people times in study years for sambar and pig-tailed macaque were similar (sambar ( = , = , = , = ), and one domestic scored .% higher than pig-tailed macaque), but the differ- dog in . ence was greater for the prey mass adjusted score and the We recorded a total of tiger captures ( = , = , spatial and prey mass adjusted score (sambar scored % = , = , = , = , = ), with an overall higher for both of these scores). relative abundance of . ± SE . detections/ trap nights per camera trap. We identified at least individual tigers in left flank photographs and eight individuals in right flank Discussion photographs (Supplementary Material ). We documented , captures of potential prey species, The tiger is an important flagship species for conservation, with red muntjacs being recorded most frequently, followed but remains threatened throughout its range (Seidensticker, by pig-tailed macaques and mouse deer (Table ). Tigers ; Walston et al., ; Sibarani et al., ). Sumatran exhibited a diurnal activity pattern (Fig. ) and had the high- tigers are categorized as Critically Endangered (Linkie et al., est temporal overlap with wild boar, followed by pig-tailed ) and tiger populations in Bukit Barisan Selatan Na- macaques and sambar (Fig. , Table ). The highest spatial tional Park and other areas are threatened by encroach- overlap was also with wild boar, followed by sambar and ment and habitat destruction (O’Brien & Kinnaird, ; pig-tailed macaques (Table ). Pusparini et al., ), and by poaching of tigers and/or When plotting the values indicating spatial and temporal their prey (Linkie et al., , ). Effective conservation overlap of tigers with potential prey species, wild boar and is dependent on collaboration between countries, govern- sambar deer fell in the upper right quadrant, suggesting they ment agencies, local communities, and scientific organiza- are potentially preferred prey. Tapirs were in the lower left tions. The Tropical Ecology and Assessment Monitoring quadrant, indicating they were probably not preferred, and Network is focused on open sharing of scientific data and the other prey species were in the upper left (high temporal can be used as a model for data sharing amongst scientists but low spatial overlap), indicating potential alternative prey and other stakeholders for conservation. (Fig. ). We found tigers exhibited diurnal activity patterns, and Tigers had the greatest spatio-temporal overlap with wild we created a composite score of spatial and temporal overlap boar, with a spatial and temporal composite score of ., with potential prey species to provide insights into tiger prey which is % higher than the species with the second highest preferences, which can inform conservation (e.g. Karanth scores (sambar and pig-tailed macaques, both .; Table ). et al., ; Barber-Meyer et al., ). Previous studies in The additional composite scores produced a similar the study area suggested tigers have a diurnal activity pat- ranking to the spatial and temporal composite score. Wild tern (O’Brien et al., ), or a crepuscular pattern with boar ranked highest for the spatial adjusted composite highest activity near dawn (Pusparini et al., ). The
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FIG. 2 The temporal activity (including % confidence intervals) and overlap of the kernel activity density of tigers and potential prey species: (a) mouse deer (including greater mouse deer Tragulus napu and lesser mouse deer Tragulus kanchil), (b) pig- tailed macaque Macaca nemestrina, (c) red muntjac Muntiacus muntjac, (d) sambar deer Rusa unicolor, (e) tapir Tapirus indicus, (f) wild boar Sus scrofa. Tiger activity is represented as solid lines and prey activity as dotted lines, with their temporal overlap shown as the shaded area.
behaviour, or varying degrees of interactions with humans or other species in different parts of the Park. For example, Pusparini et al. () reported high rates of illegal human activity (photographic captures of humans with guns) and relative tiger abundances (relative abundance index = .) that were an order of magnitude higher than in our study (relative abundance index = .). This may have caused ti- gers to change their activity patterns to avoid threats posed by humans (e.g. Clinchy et al., ). Further research is re- quired to ascertain reasons for these conflicting results from the same Park and subpopulation. A high degree of spatio-temporal overlap does not necessarily indicate prey preference but it suggests po- tential for high encounter rates between carnivores and their prey, which is a key component of prey preference (Holling, ; Fortin et al., ). Temporal overlap has been posited as a way of determining prey preferences FIG. 3 The spatial (area under curve; AUC) and temporal (kernel (Linkie & Ridout, ), but probably provides an incom- density) overlap of tigers with potential prey species plotted ’ together (with axes scaled to the reported values for ease of plete picture if spatial overlap is not included (e.g. O Brien comparison). et al., ). Other factors to be considered include prey body size and potential avoidance strategies by prey species. We created four composite index scores that included both sample size of tiger captures in our study was lower than in temporal and spatial overlap. Each composite score appears both previous studies, but our findings appear to confirm to accurately rank prey preference of tigers in Bukit Barisan the diurnal activity pattern observed by O’Brien et al. Selatan National Park, with wild boar and sambar deer (). Reasons for the observed differences could be being the most preferred, as predicted based on the find- different sampling techniques, variation in individual tiger ings of Hayward et al. (). The spatial and temporal
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composite score was effective, but the scores including pre- should be conducted in other systems with known prey pre- ferred prey mass better separated sambar and pig-tailed ferences of carnivores (e.g. from dietary analyses) to further macaques as potential prey species for tigers. We used small evaluate the accuracy of this method, assess general applic- (%) adjustments to create the adjusted composite scores, ability of the method, and further interpret the observed and future studies in areas with known prey preferences relationships. could conduct sensitivity analyses to determine ideal weight- ing adjustments for spatial and temporal composite scores Acknowledgements All data used in this study were collected by the Tropical Ecology Assessment and Monitoring Network, a collab- to determine prey preference. oration between Conservation International, the Missouri Botanical The different composite scores indicated mostly the same Garden, the Smithsonian Institution and the Wildlife Conservation ranking amongst potential prey species, with the only excep- Society. The work was partially funded by these institutions, the tion being tapirs ranking slightly higher than mouse deer in Gordon and Betty Moore Foundation, the Illinois Natural History the spatial and mass adjusted composite score. Wild boar Survey, the Slovenian Research Agency (P4-0059), and other donors. Monitoring activities were managed by the Wildlife Conservation ranked highest in all cases, followed by sambar deer, and Society in collaboration with the Bukit Barisan Selatan National Park these two species are frequently the preferred prey of tigers and the Ministry of Environment and Forestry, Republic of Indonesia. throughout their range (Seidensticker & McDougal, ; We thank all field staff and forest rangers involved in camera-trap Hayward et al., ; Basak et al., ). The greater overlap deployment, and W. Marthy for help in the field and coordination. and composite scores for wild boar in this study site could be a result of wild boar having a relative abundance Author contributions Study concept: all authors; data collection: MCS; statistical analyses: MLA; writing: MLA; revisions: all authors. c. three times greater than sambar deer. Species with higher abundance are probably more widely distributed across Conflicts of interest None. the landscape, which could inflate their spatial overlap with predators and potentially overestimate prey preference. Ethical standards This research abided by the Oryx guidelines on Red muntjac, pig-tailed macaque and mouse deer were ethical standards. The research was based on passive monitoring, and did not involve human subjects, experimentation with animals indicated as potential alternative prey species with inter- and/or collection of specimens. mediate composite index scores and a position in the upper left quadrant on the spatial and temporal overlap plot (Fig. ), which indicates high temporal but low spatial References overlap with tigers. Tapirs had low spatial and temporal overlap with tigers, which corresponds to published data ALLEN, M.L., WILMERS, C.C., ELBROCH, L.M., GOLLA, J.M. & and suggests they may be non-preferred prey of tigers WITTMER, H.U. ( ) The importance of motivation, weapons, and foul odors in driving encounter competition in carnivores. (Hayward et al., ). Based on these results we suggest Ecology, , –. that conservation efforts in the area should be focused on ALLEN, M.L., GUNTHER, M.S. & WILMERS, C.C. () The scent of wild boar and sambar deer, to ensure a robust prey base your enemy is my friend? The acquisition of large carnivore scent by for this tiger population. We found evidence of illegal snares a smaller carnivore. Journal of Ethology, , –. set for sambar deer in the Park, suggesting conservation ALLEN, M.L., PETERSON,B.&KROFEL,M.( ) No respect for apex carnivores: distribution and activity patterns of honey badgers in the actions may be necessary. Serengeti. Mammalian Biology, , –. Prey preference is usually assessed using the ratio of prey BARBER-MEYER, S.M., JNAWALI, S.R., KARKI, J.B., KHANAL,P., killed to prey available, and our study shows a potential al- LOHANI, S., LONG, B. et al. () Influence of prey depletion and ternative method to predict prey encounter rates and pref- human disturbance on tiger occupancy in Nepal. Journal of Zoology, – erence. Determining the number of prey of different species , . BASAK, K., MANDAL, D., BABU, S., KAUL, R., ASHRAF, N.V.K., SINGH, killed by tigers, or numbers of prey available, can be costly A. & MONDAL,K.() Prey animals of tiger (Panthera tigris tigris) and time-intensive compared to using camera traps to col- in Dudhwa landscape, Terai Region, North India. Proceedings of the lect relative abundance data. Our method of plotting spatial Zoological Society, , –. and temporal overlap between predator and prey species and BEGON, M., TOWNSEND, C.R. & HARPER, J.L. () Ecology: From creating composite index scores from camera-trap data could Individuals to Ecosystems. th edition. Blackwell Publishing, Oxford, be useful for inferring the encounter rates of carnivores UK. CLINCHY, M., ZANETTE, L.Y., ROBERTS, D., SURACI, J.P., BUESCHING, with prey and appears to have correctly ranked the prey pre- C.D., NEWMAN,C.&MACDONALD, D.W. () Fear of the human ferences for Sumatran tigers. The inclusion of prey mass ap- ‘super predator’ far exceeds the fear of large carnivores in a model peared to improve upon the spatial and temporal composite mesocarnivore. Behavioral Ecology, , –. score, and including mass or other variables such as abun- DU PREEZ, B., PURDON, J., TRETHOWAN, P., MACDONALD, D.W. & dance or habitat preference may facilitate more effective LOVERIDGE, A.J. ( ) Dietary niche differentiation facilitates coexistence of two large carnivores. Journal of Zoology, , –. inference in future studies, which could also fine-tune the FIELDING, A.H. & BELL, J.F. () A review of methods for the values used in the adjusted composite scores. Further test- assessment of prediction errors in conservation presence/absence ing of a similar composite score for spatio-temporal overlap models. Environmental Conservation, , –.
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