New study uses ideas from string theory and quantum field theory to simplify calculations of transcendental numbers, like pi and Euler’s Zeta function.

How accurate are India’s tiger numbers?

Read time: 1 min
12 Feb 2020
How accurate are India’s tiger numbers?

Tiger, one of the charismatic megafauna and the national animal of India, is often used as the face of conservation worldwide. On 29th July 2019, which marks the International Tiger Day, the Indian Prime Minister Narendra Modi announced the results of the 2018 National Tiger Estimation (NTE) Survey. He stated that India had achieved its goal of doubling its tiger population four years before the proposed deadline. According to the survey, the number of tigers has surged to 2967, indicating a doubling of tiger numbers since the first survey conducted in 2006 under a revised monitoring methodology. Although this change may sound exciting to the layperson, some scientists have flagged concerns about accepting these claimed changes in tiger numbers.

In a recent study, published in the journal Conservation Science and Practice, researchers from India and Norway refer to important mathematical, statistical and ecological principles and highlight how India’s tiger survey results deviate from these principles. The researchers surmise that India’s claims of increasing tiger numbers may be the consequence of an underlying ‘political population’, referring to changes in large carnivore numbers that are largely exaggerated in comparison to actual findings in scientific research.

The first three National Tiger Estimation surveys, conducted in 2006, 2010 and 2014, have shown contrasting patterns of increase in tiger populations. During 2006 to 2010, the reports indicate a decrease in tiger range by 12.9% or 11,400 sq km with a corresponding rise in tiger abundance by 17.3%. Going by these changes, it implies that in India, tigers in vast, poorly‐protected landscapes with a low density of prey serve as ‘source populations’—a finding that contrasts with scientific understanding. However, during the period 2010 to 2014, this pattern completely reverses.

“These claims from the Indian tiger surveys stand in stark contrast to scientific understanding derived from the source‐sink theory in population biology,” say the researchers.

The ‘source-sink’ theory, a foundational theory followed worldwide for large carnivore conservation, states that conducive habitats (or sources) produce surplus individuals who may move to the surrounding, not-so-desirable habitats (or sinks) that may or may not sustain these individuals over time.  

The study also points out glaring gaps in the methodology adopted by the All India National Tiger Estimation Surveys. The NTE surveys claim to have utilized a method termed as ‘double-sampling’, a well-known approach used to estimate animal abundance over large areas. It involves two phases of sampling using a standardized design. However, during the implementation, these surveys have skipped the crucial “spatial sampling step” that estimates the numbers in a given geographical range.

“Hence, this modified approach now becomes completely untested,” says Dr Arjun M. Gopalaswamy, Science Advisor at the Wildlife Conservation Society and the lead author of the study.

The NTE surveys also depend heavily on models of tiger abundance derived from tiger signs from the field, like pug marks and tiger scats. These models are then used to extrapolate the tiger population size for the rest of the country. The researchers of the current study conducted two experiments involving tiger tracks and scats to assess the population and arrived at extremely contrasting results. They found that both were not representative samples of the larger population, indicating that the sample size selected for these experiments were too small.

“Ironically, the result from one of the index-calibration experiments were so good that it actually implied that we didn’t require further calibration of indices (tiger tracks and scats) with tiger density estimates anymore because only indices could have served as a monitoring tool. But, as the new survey results indicate, this earlier result was misleading,” says Dr Gopalaswamy.

Thus, due to high variability in tiger sign data, extrapolations based on these data are misleading. 

Concerns over the numbers stated in NTE survey reports are not new! Over the years, many scientists have flagged inconsistencies and questioned its accuracy. However, despite that, international conservation agencies, such as the Global Tiger Forum (GTF), Global Tiger Initiative (GTI), and the World Wide Fund for Nature (WWF), continue to endorse claims of India’s success, rue the researchers. As a result, there has been considerable money put into tiger conservation budget, which may be misdirected. Massive tiger surveys in thick jungles also need immense resources. The NTE Survey of 2018, for example, required an effort of 593,882 person-days. However, if inaccuracies creep in due to design flaws in such surveys, this will lead to paradoxical ecological inferences and wastage of resource investments.

So, what can we fix to estimate India’s tiger numbers accurately? The researchers recommend a shift in monitoring from tracking crude changes in abundance once in four years at a national level, to monitoring changes in the expansion and contractions in tiger ranges. They also urge for greater transparency in survey reports and methods for monitoring threatened species that are based on well‐defined scientific and management objectives. Such efforts assist conservationists in real-time and avoid iconic mammal populations from being stigmatized as political populations.

“It is my opinion that wildlife management should be based on the best possible science instead of being mixed up with politics to make the authorities look good,” comments Dr Nils Chr. Stenseth, an evolutionary biologist and Professor at the University of Oslo, Norway, who is the corresponding author of the current study.

This article has been run past the researchers, whose work is covered, to ensure accuracy.