Food habits and prey selection of tiger and leopard in Mudumalai Tiger Re-serve, Tamil Nadu, India

J. Sci. Trans. Environ. Technov. J. Sci. Trans. Environ. Technov 01/2009; 2(2):170-181.

ABSTRACT Food habits and prey selection of tiger (Panthera tigris) and leopard (Panthera pardus) in Mudumalai Tiger Reserve, Tamil Nadu were assessed from January to August 2008. Chital, Axis axis was the most common prey species in the study area with a density of 55.3 ± 6.28 animals/km 2 followed by common langur Presbytis entellus with 25.9 ± 3.59 animals/ km 2 and gaur Bos gaurus with 11.4 ± 2.14 animals/km 2 .The estimated mean biomass of the potential prey species was 8365.02 kg/km 2 . A total of 179 tiger scats and 108 leopard scats were collected and the prey remains were analyzed. Sambar and chital were the principle prey species for tiger and leopard, respectively, as inferred from the relative biomass con-sumption of prey remains in tiger and leopard scats. The preferred prey species of leopard and tiger were sambar, common langur, wild pig and cattle. The dietary overlap between these two predators was 82% in terms of percentage frequency of occurrence of prey remains in the scats. In terms of biomass consumed, the estimated dietary overlap between tiger and leopard was 72%.

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    • "Prey biomass is seen to strongly influence tiger [51] and leopard [10], [52] density although other factors such as interspecific competition [44] and disease [53] also affect carnivore densities. Leopards in protected areas in India feed on small to medium sized wild prey such as cheetal (Axis axis), sambar (Rusa unicolor) and langur (Semnopithecus spp.) [54], [55]. Our study site contains no other apex predator and no wild ungulate prey species suitable for leopards. "
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    ABSTRACT: Protected areas are extremely important for the long term viability of biodiversity in a densely populated country like India where land is a scarce resource. However, protected areas cover only 5% of the land area in India and in the case of large carnivores that range widely, human use landscapes will function as important habitats required for gene flow to occur between protected areas. In this study, we used photographic capture recapture analysis to assess the density of large carnivores in a human-dominated agricultural landscape with density >300 people/km2 in western Maharashtra, India. We found evidence of a wide suite of wild carnivores inhabiting a cropland landscape devoid of wilderness and wild herbivore prey. Furthermore, the large carnivores; leopard (Panthera pardus) and striped hyaena (Hyaena hyaena) occurred at relatively high density of 4.8±1.2 (sd) adults/100 km2 and 5.03±1.3 (sd) adults/100 km2 respectively. This situation has never been reported before where 10 large carnivores/100 km2 are sharing space with dense human populations in a completely modified landscape. Human attacks by leopards were rare despite a potentially volatile situation considering that the leopard has been involved in serious conflict, including human deaths in adjoining areas. The results of our work push the frontiers of our understanding of the adaptability of both, humans and wildlife to each other's presence. The results also highlight the urgent need to shift from a PA centric to a landscape level conservation approach, where issues are more complex, and the potential for conflict is also very high. It also highlights the need for a serious rethink of conservation policy, law and practice where the current management focus is restricted to wildlife inside Protected Areas.
    PLoS ONE 03/2013; 8(3):e57872. DOI:10.1371/journal.pone.0057872 · 3.23 Impact Factor
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    • "Available studies in India reported high dietary overlap amongst leopard, wild dog and tiger (Johnsingh 1983; Karanth & Sunquist 1995; Ramesh et al. 2008). Similar to present study, the dietary overlap between leopard and tiger was observed 94% in Nagarhole Tiger Reserve (Karanth & Sunquist 1995) and 82% in Mudumalai Tiger Reserve (Ramesh et al. 2008). Evidences suggest that among large sympatric carnivores, the larger carnivores can prey on broader size ranges of prey classes due to Figure 8. Age and sex classes of large herbivores observed by kill records of leopard (n=29) and tiger (n=40) in Sariska Tiger Reserve, Rajasthan, India. "
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    ABSTRACT: After the extermination of tigers in Sariska Tiger Reserve, Western India in 2004, three tigers were re-introduced in Sariska during 2008–2009. The present study examined the prey selection and dietary overlap between leopard and tiger after re-introduction of tiger in the study area. Scat analysis revealed the presence of nine prey species in leopard scat (n = 90 scats) and five prey species in tiger scats (n = 103 scats). Percentage frequency of occurrence of sambar (45.5%) was found to be the highest followed by chital (15.2%) > nilgai (8.9%) > cattle (7.1%) > common langur (6.3%) > peafowl (6.3%) > rodent (5.4%) > wild pig (2.7%) and hare (2.7%) in leopard diet. In the diet of tiger, sambar contributed maximum (41.7%) followed by chital (26.2%), cattle (19.4%), nilgai (10.7%) and common langur (1.9%). The present study revealed that both the predator utilized and preferred prey species in similar way, though there was difference in selection of prey species in terms of sex and age class as observed by kill records. The dietary overlap between leopard and tiger was found to be 94%. The results suggested considerable overlap between the two carnivores along diet axis.
    Italian Journal of Zoology 12/2012; 79(4):1-10. DOI:10.1080/11250003.2012.687402 · 0.79 Impact Factor
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    • "They were stored in paper bags, individually labelled with date, location and species for further analysis. Hair of prey often remained undamaged in carnivore scats and hair identification became useful to determine the diet of carnivorous species (Ramesh et al. 2009) where, a combination of hair characteristics like hair width, medullary and cuticular structure was observed microscopically and later compared to reference slides using hair samples from kills of large carnivores and reference collection present at the Research Laboratory of Wildlife Institute of India, Dehra Dun. Data was recorded in terms of frequency of occurrence of individual prey species in scats by examining 20 hairs at random in each scat (Mukherjee et al. 1994). "
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    ABSTRACT: BioOne ( is a nonprofit, online aggregation of core research in the biological, ecological, and environmental sciences. BioOne provides a sustainable online platform for over 170 journals and books published by nonprofit societies, associations, museums, institutions, and presses. Abstract. We investigated dietary partitioning among tiger Panthera tigris, leopard Panthera pardus and dhole Cuon alpinus in Mudumalai Tiger Reserve, India between January 2008 and April 2010 based on scat analyses and prey surveys. Scat analysis revealed that though the diet of the three predators consisted of 15 to 21 prey species, wild ungulates formed a major portion of their diet (88.4 to 96.7%). The three predators exhibited high diet overlap (> 61%). Prey availability, estimated from an effort of 473 km of line transects (n = 33) revealed high density of chital Axis axis (43.8 ± 10.7 (mean ± SE) individuals/km 2), followed by langur Semnopithecus entellus (31.0 ± 3.8), gaur Bos gaurus (6.7 ± 1.5), giant squirrel Ratufa indica (6.4 ± 1.3), sambar Rusa unicolor (4.9 ± 0.96) and elephant Elephas maximus (4.9 ± 0.75). Mean biomass (kg/km 2) of chital, gaur and sambar was 2058.6, 3015 and 656.6 respectively. In terms of biomass, tiger consumed mostly large sized prey (> 50 kg). Although leopard and dhole selected mostly medium-sized (11–50 kg) prey (chital), the second most important prey was sambar for dhole and langur for leopard. The results suggest that high density of different-sized prey in Mudumalai Tiger Reserve helped facilitate coexistence of tiger, leopard and dhole, despite the high dietary overlap, although some dietary partitioning was apparent when considering prey size and prey selection.
    Mammal Study 12/2012; 37(4):313-321. DOI:10.3106/041.037.0405 · 0.53 Impact Factor
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