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Flawed research method puts 30 per cent tiger rise in doubt


                                                                                                                                 Mumbai Mirror, Mumbai, 24th February, 2015



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.

Amongst 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.

A report of the research is published this week in the journal Methods in Ecology and Evolution.

Index-calibration often relies on measuring animal numbers accurately in a relatively small region using reliable, intensive and expensive methods (such as camera trapping) 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 approach has been popular among wildlife conservation agencies to generate animal numbers at a regional and national level. These numbers are then used to inform conservation efforts and direct resources worth millions of pounds.

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.

"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. Our empirical test with data from Indian tiger survey efforts proved that such calibrations yield irreproducible and inaccurate results," said Arjun Gopalaswamy, lead author of the report.

The team say that the aim of the study is to help ecologists and conservationists to address the global challenge of counting rare and elusive animals.

The good news is that the mathematical model created by the team provides the crucial 'link' between some of the older methods (which don't estimate detection rates) with some of the newer methods (which do estimate detection rates).

The findings will help in the reanalysis of raw data from wildlife research. MM