Feb 25 2015 : The Times of India (Delhi) India's tiger census method flawed, says Oxford study Kounteya Sinha & Amit Bhattacharya LondonNew Delhi: TNN   Experts Hit Back, Say Univ’s Research Poorly Designed Reigniting the debate over India’s tiger census, which has shown a 30% rise in the big cat’s population in four years, a British-Indian team of scientists has said the exercise mostly likely suffers from a measuring error — a finding rebuffed by experts involved in the census exercise.At the heart of the row is the ‘index calibration model’ which measures animal numbers when they can’t all be seen, using data from camera-traps, radio-collars etc. The technique is commonly used in the census of tigers and other rare wildlife across the world. In the study, published in Methods in Ecology and Evolution, scientists from the University of Oxford, Indian Statistical Institute and Wildlife Conservation Society brought out inherent shortcomings in the model and said it could produce inaccurate results. However, experts involved in India’s tiger census said the study was poorly designed and the datasets used to develop the theoretical model suffered from low reliability. “It is not surprising that they haven’t found a strong relationship of tiger density with tiger signs or any other variable for that matter. No amount of statistical sophistication can compensate for poor study design,” said Yadvendra D Jhala and Qamar Qureshi from Wildlife Institute of India, in an email response. Both experts are principal investigators of the estimation exercise. Index-calibration relies on measuring animal numbers accurately in a relatively small region using relia ble, intensive and expensive methods (such as camera trapping) and then relating this measure to a more easily obtained, inexpensive indicator by means of calibration. The calibrated index is then used to extrapolate actual animal numbers over larger regions. To investigate index-calibration, the study team created a mathematical model describing the approach and then tested its efficiency using different values, even attempting to derive tiger numbers from fieldwork data. Under most conditions, the model was shown to lose its efficiency and power to predict.