Counting Tigers Reliably — Combining Information From Multiple Sources

by Krithi K. Karanth & Arjun Srivathsa

Authors Arjun M. Gopalaswamy, K. Ullas Karanth, Andy Royle, Mohan Delampady, James D. Nichols and David W. Macdonald demonstrate innovative approaches that integrate information from photographic capture-recapture and genetic data to derive more robust estimates of tiger densities in Bandipur Tiger Reserve, India. These are the highlights of their study published in the journal Ecology in 2012.

In landscapes where wildlife occurs in low densities, gathering information from a single method often does not allow accurate estimation of population densities and abundance. In such cases, using multiple data sources may allow us to overcome ecological and logistical difficulties to estimate densities of elusive carnivores.

Study Site

The study was conducted to estimate abundance and density of tigers (Panthera tigris) in the 871 sq km Bandipur National Park and Tiger Reserve located in Karnataka, South India. This dry deciduous reserve receiving an annual rainfall of 625-1250 mm with varying temperatures from 18-29°C supports high herbivore densities (35.2 animals/sq km) including sambar, chital, four-horned antelope, wild pig, gaur and elephant. Consequently it has a large population of tigers.


Data were collected using two field survey methods. Photographic camera trap surveys were used to collect data from November 2005 to January 2006. Tiger fecal samples (scats) containing DNA were also collected from the same area. The photographic survey involved setting up camera traps in 118 locations along forest road routes and trails. Covering a walk effort of 237 km, tiger scats were collected along 18 survey routes. Tiger scats were collected to extract DNA, using which individual tigers can be identified. The scats were collected over six successive days and repeated for six weeks. Models were constructed by combining data to identify ecological and sampling processes that produce the most reliable estimate of tiger densities.

The authors use models that can incorporate either a ‘direct’ approach where data are collected specifically for such analyses, or alternatively, a ‘step-wise’ approach, which can utilize estimates available from other studies and published literature.


  • The camera trap surveys resulted in 35 captures of 29 individual tigers.
  • The scat surveys resulted in 63 DNA samples from 24 individually identifiable tigers.
  • Analyses using combined information from two surveys produced more consistent and precise estimates of tiger densities (8.7 and 8.5 tigers /100 sq km) as compared to models where the data were analyzed separately (12.8 and 6.65 tigers/100 sq km).
  • Both ‘direct’ and ‘step-wise’ approaches produced similar estimates of tiger densities: 8.7 and 8.25 tigers/100 sq km.

Conservation Implications

The study suggests that using multiple sources of data is important and provides better and more reliable results than a single source. This can be particularly helpful when studying rare or elusive animals that occur at low densities, for which obtaining large amounts of data is a practical challenge. The authors recommend that future research efforts should focus on developing spatial models that can include information on specific geographic locations from where data were obtained to improve estimates of animal densities. The flexibility in the models proposed by the authors allows efficient utilization of previously published or available estimates, thereby aiding better assessments of population status for threatened and endangered species.

About the author

Krithi K. Karanth & Arjun Srivathsa
Krithi K. Karanth is an Associate Conservation Scientist with Wildlife Conservation Society (New York) and studies human-wildlife interactions and social dimensions of wildlife conservation. Arjun Srivathsa is a Research Associate with Wildlife Conservation Society-India, currently working on carnivore populations.


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