Tiger numbers in India may not be accurate: study
India's claim of a robust revival in its tiger population may have been premature and the result of a flawed research method, a new Oxford-led study suggests
London: India's claim of a robust revival in its tiger population may have been premature and the result of a flawed research method, a new Oxford-led study suggests.
Flaws in a method commonly used in censuses of tigers and other rare wildlife put the accuracy of such surveys in doubt, researchers said.
A team of scientists from the University of Oxford, Indian Statistical Institute, and Wildlife Conservation Society exposes, for the first time, inherent shortcomings in the 'index-calibration' method that means it can produce inaccurate results.
Among recent studies thought to be based on this method is India's national tiger survey (January 2015) which claimed a surprising but welcome 30 per cent rise in tiger numbers in just four years.
The survey showed that tiger population in the country had risen to 2,226 in 2014, a 30 per cent jump since the last count in 2010.
"Our study shows that index-calibration models are so fragile that even a 10 per cent uncertainty in detection rates severely compromises what we can reliably infer from them," Arjun Gopalaswamy, lead author of the report from the Wildlife Conservation Research Unit at University of Oxford, said.
"Our empirical test with data from Indian tiger survey efforts proved that such calibrations yield irreproducible and inaccurate results," said Gopalaswamy.
Index-calibration often relies on measuring animal numbers accurately in a relatively small region using reliable, intensive and expensive methods and then relating this measure to a more easily obtained, inexpensive indicator (such as animal track counts) by means of calibration.
The calibrated-index is then used to extrapolate actual animal numbers over larger regions. "This study exposes fundamental statistical weaknesses in the sampling, calibration and extrapolations that are at the core of methodology used by the government to estimate India's numbers, thus undermining their reliability," said Dr Ullas Karanth, a co-author from the , Wildlife Conservation Society, and a member of India's National Tiger Conservation Authority.
"We are not at all disputing that tigers numbers have increased in many locations in India in last 8 years, but the method employed to measure this increase is not sufficiently robust or accurate to measure changes at regional and country wide levels," said Karanth.
To investigate index-calibration the team created a mathematical model describing the approach and then tested its efficiency when different values, representing variations in data, were inputted. Under most conditions the model was shown to lose its efficiency and power to predict. The team then tested this mathematical model on a real world example: attempting to derive tiger numbers from fieldwork data.
The index-calibration model was shown to be unreliable again, with any high degree of success shown to be down to chance, rather like being dealt a single incredibly 'high value' poker hand, that could not be replicated.
"Index-calibration relies on the assumption that detection rates of animal evidence are high and unvarying. In reality this is nearly impossible to achieve. Instead, there are many flexible approaches, developed over the past decade by statistical ecologists, which can cut through noisy 'real world' data to make accurate predictions," Gopalaswamy added.
"The findings have wider consequences for several applied sciences where sampling and direct extrapolation is involved, especially when sampling errors are influenced by unknown detection probabilities," said Professor Mohan Delampady, a co-author from the Indian Statistical Institute.
The team urges conservation practitioners to guard against these sources of error, which could mislead even the best conservation efforts, and suggests a constructive way forward using alternative methods of counting rare animals that avoid the pitfalls of the index-calibration approach.
The research was published in the journal Methods in Ecology and Evolution.