Academics spar over tiger census methods

Academics spar over tiger census methods

India's latest tiger count has sparked a bitter debate among two groups of wildlife conservationists over the methods adopted in calculating the number of big cats in the wild.

The National Tiger Conservation Authority (NTCA) on Sunday fired the latest salvo by trashing the claims of a group of academicians, including noted conservationist Ullas Karanth, who had published a research study questioning the government methodology used in the recent tiger survey.

“The study (by Karanth and other academicians) has no relevance in the context of the 2014 tiger population and status estimation,” said the NTCA.

Several scientists from the Wild Life Institute of India, Dehradun, and foresters are associated with the NTCA survey. The government had announced in January an increase in India's tiger count by 30 per cent in four years, claiming the presence of 2,226 of them in the wild.

As it was an estimate, the range was 1,945 on the lower side and 2,491 on the higher. The exercise was carried out over four years using a methodology that was first used by the government in 2006, replacing the traditional pug-mark-based system.  Data was collected through 9,735 camera traps, besides scat DNA analysis.

Within weeks, scientists from the University of Oxford, Indian Statistical Institute, and Wildlife Conservation Society, challenged the “index-calibration” method used in the survey.

In a research paper published in the journal “Methods in Ecology and Evolution”, they claimed inherent shortcomings of the NTCA method. “We do not believe this method can yield sufficiently refined results to accurately measure changes in tiger numbers at landscape or countrywide scales, as is being attempted. We have demonstrated and published alternative superior methods,” Karanth, director for Science in Asia at the WCS, had said.

The NTCA said, “The published study is based on data of 2005 and 2011, and has deliberately ignored methods used in the recent estimation which are currently the most advanced and robust spatial models, and address all concerns.”

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