By Monica Jha
Photographs & Video by Sriram Vittalamurthy
Design: Rajesh Subramanian
By Monica Jha
Photographs & Video by Sriram Vittalamurthy
Design: Rajesh Subramanian
On the last day of March 2017, Shikha Bisht walked from her home on the idyllic campus of the Wildlife Institute of India (WII) in Dehradun to her office. The five-minute walk in the early summer felt pleasant amidst the pyramid-like buildings that complement the Mussoorie hills in the background far away.
She entered her office at 9 am and opened her official email. An email from her boss caught her eye immediately. The subject line read “Tiger skin seized in Dhanghari (Kailali) Nepal”.
Two days earlier, Nepal police had arrested a smuggling gang and found a tiger skin on them. The police arrested them in Dhangadhi, a sub-metropolitan city in Nepal. Dhangadhi was an ideal conduit for the tiger skin trade. It shares a border with Uttar Pradesh and is less than 100 km from several tiger reserves in both India (Dudhwa and Pilibhit) and Nepal (Bardiya and Shuklaphanta).
The Nepali authorities got in touch with India’s National Tiger Conservation Authority, or NTCA, a statutory body overseeing tiger conservation in India. The NTCA’s first order of business was identifying where the tiger came from. They sent a photo of the tiger skin to Yadvendradev Vikramsinh Jhala.
Yadvendradev Vikramsinh Jhala, one of India’s foremost experts on large carnivores.
Jhala is one of India’s foremost expert on large carnivores, and the man chosen to head the newly incubated Tiger Cell. The Cell was established in August 2016 and is jointly run by NTCA and WII.
Jhala forwarded the tiger skin photo to Bisht, a senior biologist at the Tiger Cell.
She sprung into action immediately.
The easiest way to distinguish tigers is by their stripe patterns. Just like human fingerprints, stripe patterns are unique to each tiger. Bisht’s task was to check if any tiger in her image library matched with the dead tiger.
But, the library had over 40,000 photos. Her team – with three members – would have taken over a month to match them with that of the dead tiger.
Instead, Bisht’s team uses ExtractCompare, a software program to find a match. The program was developed by Conservation Research Ltd, a UK based software firm. K Ullas Karanth, director of the Wildlife Conservation Society – India Program, was instrumental in developing this program.
The Tiger Cell was established at Wildlife Institute of India(WII) campus in August 2016 and is jointly run by NTCA and WII.
ExtractCompare extracts the stripe pattern of the dead tiger from the photo of the skin. The most useful information is in the stripes of a tiger’s flank, followed by its hind legs. “The picture of the tiger skin we received was a good quality one, showing the flank clearly,” recalls Bisht.
The software then compares it to patterns in the tiger photos in the library. Since the skin was found in Nepal, Bisht looked for a match from the Northern belt. This area comprised of the Shivalik range and the Gangetic floodplains.
It took two days for ExtractCompare to go through all the photos and throw up probable matches. After two days, a technical assistant called Bisht to check a potential match.
Bisht inspected the two images closely. She said nothing. She checked all other probable matches first, before coming back to the first one.
It’s a match, she announced.
The photo that matched the dead tiger was captured at Kishanpur Wildlife Sanctuary in Uttar Pradesh. It was taken in December 2013, as part of the 2014 tiger census. Tigers are territorial so it’s highly likely that the dead animal was from Kishanpur or around. “We didn’t have any other photos of this tiger from this or another location,” Bisht says.
From the photo, Bisht deduced that it was a healthy adult male and over four years old when it was photographed. Bisht guessed that the killing was meant for sale.
“The skin was very neat and had one clean bullet hole. So, my guess is that they (the arrested) wanted to sell the skin,” she explains.
Tigers killed in UP are often smuggled to China via Nepal. “Skin found in Nepal often turns out to be of tigers from Northern India (UP and Bihar). This has been established as a trade route,” explains Bisht.
On April 5, the Tiger Cell informed NTCA about the identity of the tiger.
The Tiger Cell has been identifying tigers in poaching cases since 2012. Bisht has received 31 skin images, of which she could work with 27 of them. “The other four images were of very poor quality,” she explains. In seven cases, the skins of dead tigers matched with the images in her library.
Some results have been revealing.
In a case in 2013, she established using ExtractCompare, that the skin caught in Nepal was of an adult female tiger from Pench in Madhya Pradesh.
“This was very surprising. We weren’t aware of any trade routes that traverse from central India all the way to Nepal. This was new information,” Bisht says.
Tracing a poached tiger to a specific geographical location or region helps understand hotspots of wildlife crime and trade routes, which is crucial to fight the crime, she explains.
Today, the Tiger Cell has over 40,000 photos of tigers captured in camera trap surveys. Each identified individual tiger is assigned a unique tiger identiﬁcation (UTID). Through this, the Cell has identified over 1,686 tiger individuals. This is over 70% of India’s total estimated 2,226 tigers.
This gives Bisht’s team a 70% probability to figure out the identity of a poached tiger and where it comes from. For the ongoing tiger census, the Tiger Cell is expecting photos from over 20,000 camera locations across the country.
In December 2004, a team from WII found that tigers at the Sariska Tiger Reserve in Rajasthan had gone extinct. The state forest department insisted there were 18 tigers. But the field data showed no signs. India was facing its biggest wildlife crisis since Project Tiger was launched in 1973.
The scientists panicked, but they were also puzzled. There were no warning signs. Sariska authorities reported around 25 tigers during censuses between 1995 and 2003. The census in 2004 reported 16 to 18 tigers.
Jhala was a member of the WII team. Along with his colleague Professor Qamar Qureshi, they dug out old registers. Forest guards, who patrol the reserve, enter every tiger sighting in the register on a daily basis.
They plotted the number of tiger sightings and the effort the guards put in patrolling. A picture of the evolving crisis began to emerge. Sightings had declined in Sariska since 1998. And in the last one year, there hadn’t been a single sighting. The authorities either ignored these signals or simply cooked up the census numbers.
The discovery was shocking. Despite rooms full of data being available, the extinction was missed. This happened due to lack of data analysis.
After the Sariska debacle, the union government set up a Tiger Task Force to review management of tiger reserves. Its tasks included providing a scientific basis to the tiger census.
The task force chose a system proposed by Jhala and Qureshi, by borrowing from what was published by different scientists on methods of population abundance estimation. This was an improvement over the existing pugmark technique. It recorded ecological signs of tigers, co-predators, and prey. It used camera traps and with the support of geographical information systems (GIS). And it enabled population estimation across vast landscapes.
The task force mandated NTCA and WII to conduct a tiger census across India every four years. Since then, tiger censuses have been held in 2006, 2010 and 2014, and the latest round is ongoing.
Even with a new census in place, Jhala and Qureshi hadn’t gotten over the Sariska shock. “Sariska was a jolt. What good is the data if not analysed and used to correct or improve the situation,” says Jhala.
Forest authorities needed to see the trends – decline or increase in sightings and crime – clearly and regularly, they realised.
In the same year, while supervising a student’s work in Nepal, Jhala and Qureshi met Rajan Amin. Of Indian origin, he was a senior wildlife biologist at the Zoological Society of London (ZSL). While working on rhinos in Kenya, Amin developed a system for patrolling rhinos. It recorded GPS coordinates and date and time of the crime.
“He had this wonderful system of patrolling – law enforcement aspects – in place. We already had the ecological aspects. So, it struck us that if we could amalgamate an ecological system, with a patrol system and geotagging, then it would be perfect,” recalls Jhala.
This was the beginning of M-STrIPES — the Monitoring System for Tigers Intensive Protection and Ecological Status (M-STrIPES). Jhala and Qureshi, who is a specialist in remote sensing and GIS, set about developing it. The NTCA agreed to fund it.
The initial concept was developed in collaboration with ZSL. The monitoring system combined data on tiger presence with wildlife crime. And all this was tagged with GPS data. Development began in 2010 with the initial versions were written in Delphi, the programming fraework. In the beginning, forest guards used GPS devices on patrols to record tiger sightings, deaths, wildlife crime and ecological observations.
Over the years, M-STrIPES has undergone several refinements. The system was shifted to the .NET platform two years ago. Besides the desktop and server applications, WII has developed three android apps in-house. Instead of GPS devices, forest guards are using the M-STrIPES app on their phones to record data.
Prof Qamar Qureshi of Wildlife Institute of India, Dehra Dūn
M-STrIPES has simplified and standardised data collection methods across India.
The Ecological app allows a beat guard to record direct and indirect signs of species: sightings as well as signs like paw marks, kill, and scat for tiger, leopard, sloth bear, wild dog, chital, and sambar, etc.
With the Patrol app, forest guards can record crimes. For instance, snares to trap animals, trees cut illegally, or trespassers.
GPS coordinates of each sign and crime are recorded and M-STrIPES has built-in safeguards to prevent fudging. The data entered in M-STrIPES app can’t be edited by anybody at any stage, without losing its geotag.
The Tiger Cell is about to launch an M-STrIPES app to record human-animal conflicts. Officials can document attacks on humans and livestock, crop raiding, or property damage. The app can record details such as GPS location, time of conflict, photos of the damage, and size and estimation of loss. This can be used to assess compensation to be paid, if any.
They have also added ‘SOS’ and ‘Live tracking’ tabs to the patrol app. These connect the patrol staff with the central office.
The Tiger Cell is about to launch an M-STrIPES app to record human-animal conflicts.
A forest guard on patrol can press the SOS tab in case of a crime, forest fire or another emergency. It would send an SMS to four higher officials. On receiving the alert, they can rush armed backup, help to extinguish a fire etc.
The app records the GPS coordinates of the areas a guard patrols. With live tracking, officers at higher levels can assign personnel to beats based on requirements on the ground.
But these features do have a shortcoming. “This is possible only where mobile network is available — a huge constraint in forests,” says Ninad Mungi, senior research biologist at Tiger Cell.
“One possibility is to make it work on walkie-talkies that every patrol guard carries,” he adds.
M-STrIPES data can also be used to resolve wildlife crime cases. Data with geotagging intact would be admissible as evidence in the court. But it’s still early days on this front since this year’s tiger census is the first time M-STrIPES is witnessing a large scale use.
Digitising the data has made analytics easier.
Using ecological data, M-STrIPES generates densities of each species on a spatial scale. A colour-coded map tells you population trends from season to season. Areas marked red show population decline while areas marked in yellow indicate a stable population. The areas where populations have increased are shown in green.
Scientists working at Tiger Cell, Dehradun
A manager can glance at this report and decide where she needs to focus her efforts.
Combined with data from the patrol module, she can correlate changes in animal densities with crimes. Using M-STrIPES, forest managers have a ready reckoner on all the happenings in their range.
Between 2011 and 2016, M-STrIPES has been piloted in six tiger reserves. Bhadra in Karnataka, Sariska in Rajasthan, Corbett in Uttarakhand, Anamalai in Tamil Nadu, Kanha in Madhya Pradesh, and Nagarjuna Sagar Srisailam in Andhra Pradesh and Telangana. The current app-based system, which runs on mobile phones, was developed in 2015; before that, it ran on GPS devices.
This year, the NTCA has mandated all 18 tiger states to collect data for the tiger census using M-STrIPES. “Digitising and cleaning up the data took us an entire year for the 2014 estimation. M-STrIPES has done away with that. Now, the data will be transferred electronically without human error,” says Jhala.
There are hurdles. Many states are yet to acquire mobile handsets with the app for staff. Staff also needs training to use the apps. In the interim, the Tiger Cell is allowing states to collect data by paper and GPS handsets. But they need to follow the M-STrIPES data format. This will be manually entered in the M-STrIPES database.
Jhala hopes that for the 2022 estimation, all states will collect data through the M-STrIPES app.
M-STrIPES received an early validation at the Bhadra Tiger Reserve in Karnataka. Between June 2012 and March 2014, the staff at the reserve collected data on illegal activities at the reserve. For the same period, they also had data on distance walked by the patrolling team.
The Tiger Cell measured how active patrolling was across the year. Combining data on patrolling efforts and number of crimes, they developed an index of crimes per unit effort. “It tells us that in case you walk a km of patrol, how many crimes you will detect,” says Mungi of Tiger Cell.
“Based on the total patrolling efforts and number of crimes across the year, we found that this rate was higher in monsoon. Even with the least effort, a higher number of crimes were encountered,” he added.
The data showed that crimes peaked during the monsoon. And the data also showed that during the monsoon, patrolling was the lowest since the incessant rains left certain parts of the forest inaccessible.
These graphs have helped in increasing patrolling efficiency, says H C Kantharaju, the Conservator of Forest at Bhadra. “We can clearly see which areas have not been patrolled by our guards. Depending on areas not covered and where incidents have occurred in the past, we assign patrolling duty and routes to our guards. Now, we generate monthly graphs for better decisions on patrolling.”
The best example of how people at Tiger Cell work together is the ongoing All India Tiger Estimation 2018, as the latest tiger census is called.
In Phase 1 of the estimation, forest departments collect data on signs of tigers, preys, other predators, and human impact, using M-STrIPES. Once the field data is in, the Tiger Cell knows where tigers are present.
In phase 2, this data is analysed. The cell looks at tiger distribution, habitat connectivity between tiger populations, and new potential habitats.
This information is put on a GIS map. Superimpose this on a vegetation map, and you can see how vegetation correlates to tiger populations. Similar techniques show how tiger areas are exposed to human presence, night light, roads, different climates, etc. These show how stressed or inviolate the tiger habitat is
These two phases help field biologists choose locations with a high probability of tiger presence. In Phase 3, camera traps are set up in these locations and photos of tigers are collected. Using ExtractCompare, they identify individual tigers from these images.
In areas where setting up camera traps is not feasible, genetic analysis is used. Using DNA samples, Tiger Cell has identified 158 unique tigers so far.
Next, data from tiger reserves is analysed separately. Ecological data collection and camera trapping are done in other areas every four years. But in tiger reserves, this is done every year. In Phase 4, phases 1, 2 and 3 are carried out specifically for the annual data from each tiger reserve.
From these four phases, individual tigers are identified. And the minimum tiger density in an area is calculated with the aid of a mathematical model.
Tiger population in India has increased at 5.8% per year between 2006 and 2014.
When NTCA asked us to collect data for 2018 Estimation using M-STrIPES, there was a lot of reluctance among the staff. My beat staff complained that they couldn’t understand how to use it properly. We didn’t have enough mobiles to do this either. We’ve used datasheets and GPS devices this time. By the 2022 tiger estimation, I hope my staff will be ready to collect data directly through the app. For this, we would need a lot of training and resources.
I see the best use of technology in generating automatic reports and trends, which makes monitoring and decision making easier for me. It also make data collection faster and free of human errors.
We were comfortable using M-STrIPES during the pilot project. But last year, they gave us an improved version of the software, this needs better mobile handsets and good network connectivity. Our forest guards have trouble understanding how to use it. For 2018 Estimation, the department gave us only 3-4 mobiles that were compatible with the updated version. We had to use our personal mobiles. We also had to hire a person, who was trained by Tiger Cell, to use M-STrIPES this time.
Camera traps have proved very useful in not just monitoring movement but also assessing animal numbers more accurately. M-STrIPES ecological module is very good for monitoring purposes. Patrol module is useful but hasn’t proved to be a major improvement from the GPS method that we earlier used. Also, our guards find it tough to fill data in this module during patrolling. M-STrIPES apps help eliminate human errors and the data is easy to analyse.
Technology is providing a very useful support tool but it can’t replace the traditional system of protection. There is a huge gap between science and fieldwork. As foresters, we’re trying to bridge this gap from our end.
With vast amounts of data generated, the Tiger Cell is looking for quicker ways to analyse it.
CaTRAT (Camera Trap Repository Analysis Tool) uses artificial intelligence and machine learning protocols to categorise camera trap images. This automates what was once a tedious and time-consuming process, riddled with human errors.
Plans are afoot to integrate CaTRAT with M-STrIPES and ExtractCompare.
Pictures from patrolling and camera traps (M-STrIPES) will be segregated using CaTRAT. ExtractCompare will identify unique tigers and assign an ID for each one. This information will then flow back to CaTRAT. So the next time it sees the same tiger, it recognises it.
“We initially fed over 5,000 tiger photos into the program,” says Kausik Banerjee, Project Scientist – Wildlife Biologist, Tiger Cell. “The program has shown about 95% accuracy in identifying tiger photos. It identified a tiger correctly even when it was behind bushes. To improve, it needs more training data sets.”
CaTRAT was developed by the Tiger Cell in collaboration with the Indraprastha Institute of Information Technology at Delhi.
Microsoft has also approached WII to share their photo repository, says Vinod B Mathur, Director of WII. “We haven’t decided to go ahead yet, considering concerns about leaks and intellectual property rights. But, I believe the more we share our data, the more useful it will become,” he adds.
The cell is also using game theory to design optimal patrol paths. For instance, a forest guard from a tiger reserve opens the app and enters that he wants to patrol 5 km. It’s a morning in July. The program looks at historical data: areas that have seen high crime rate in July or in morning hours, areas not patrolled recently, areas where animals have been sighted etc. The software then suggests a route where the likelihood of detecting crime is high.
“The software is ready and we’re waiting for one-year data from across the country to launch it. It will work within the M-STrIPES app,” says Mungi.
The Tiger Cell would like to keep a tab on what’s happening in the forest all the time. But without burdening the limited manpower of the forest departments.
There are a lot of sensors available that you can put underground so you can actually listen to animals and people, says Qureshi. “There are cameras available, small and not easily detectable. Using them, we can collect data about people trespassing or monitor animals,” he adds.
One interesting use would be in monitoring elephants. “A lot of elephants die on tracks. So using cameras as well as a geo sensor, you can actually sense vibrations and figure if elephants are on the move,” explains Qureshi.
Similarly, drones are making their foray into tiger conservation. Drones can play a crucial role in surveillance in sensitive areas or tough terrains, which forest department staff can’t access. They can gather data on animal presence, habitat quality, fires, etc., without putting lives at risk.
Scientists are looking at drones for multiple uses. For instance, collecting data from radio collars and camera traps.“Now, a person goes with a VHF antenna tracking a radio collared animal. Maybe a drone can do that,” says Vaibhav Mathur, Assistant Inspector General of Forests, NTCA. Maybe, a drone can also collect images and data from all camera traps through wireless sensors and report it back at the base station, he adds.
Survey work could be another area of usage. In riverine habitats in Assam, the banks of rivers in protected areas often get eroded. The NTCA is contemplating if a drone can aerially monitor the entire area, periodically over long stretches of time. From photos taken by drones over a period of time, it can be observed which areas have eroded.
Another area where drones can potentially help is human-animal conflict. When animals, especially cats, enter human habitation, it is not advisable for the staff to approach them directly. Using a drone to pinpoint the location of the animal would safeguard the staff managing the situation.
The NTCA is also trying out electronic eye (e-eye) in tiger areas. It uses long-range cameras with thermal sensors that can see up to 3 km and short-range infrared cameras that can see the activity directly below a watch tower to monitor animal and human movement during both night and day in all weather conditions. It uses mobile and satellite network to send alerts to the central server and control room, where officials of the tiger reserve can act upon it. The e-eye is particularly useful in monitoring tiger areas which are difficult to access or require continuous scanning due to high threat of poaching.
The Tiger Cell’s use of technology also finds application in reconciling development and conservation issues. When a project needs environmental clearance, they check if it would interfere with wildlife habitats.
The Tiger Cell overlays their spatial data on the map of the project plan. They check if it falls in any crucial habitat or corridor. If it does, the cell comes up with mitigation measures.
In 2017, Telangana government sought wildlife clearance for the Dr B R Ambedkar Pranahita Irrigation Canal project. The Rs 4,200 crore project had been cleared by the Expert Appraisal Committee for River Valley and Hydroelectric Projects.
But, the project cut across a crucial tiger corridor — one that links Kawal Tiger Reserve (Telangana) with Tadoba Andhari (Maharashtra) and Indravati (Chhattisgarh) tiger reserves. Construction of the canal requires diversion of 1,136 hectares of forest land.
A team from Tiger Cell visited the project site and submitted a detailed report on September 1, 2017. The Site Inspection Committee recommended construction of nine eco-friendly bridges. The cell has designed the eco-bridges keeping in mind passage of all large and small animals. The eco-bridges were designed to mimic adjacent habitats. The bridges wouldn’t be wide enough to allow movement of vehicles, nor would they be too narrow to hamper the movement of large animals.
The cell also recommended construction of six to eight meter wide ramps with a very gentle gradient. These would be built every 500 meters on both sides of the canal where it passes through forest lands and wildlife crossing areas. This would allow smaller animals access to canal water.
Taking the mitigation measures on board, the Standing Committee of National Board for Wildlife (NBWL), at a meeting on September 4, 2017, cleared the project.
In September, the NBWL rejected the proposal of Hubbali-Ankola rail line based on a similar report from Tiger Cell. The project – construction of the 168.28 km broad gauge line – requires diversion of 596 hectare land from three elephant corridors.
Going back, some of the most fundamental principles of tiger conservation in India today – for instance, core-buffer policy for tiger reserves – were shaped up by data collected over the years.
With data from past research involving radio telemetry, satellite GPS telemetry, annual camera trapping, etc., Jhala and his team established that 800 to 1,000 sq km area was required for a viable tiger population. They recommended this to be made into the core area of a tiger reserve — an inviolate space for tigers. Surrounding this, they suggested a buffer zone: a multiple use area, where conservation remains the primary goal of land use management.
This affected a change in the Wildlife Protection Act in 2006, mandating core and buffer areas. An incentivised voluntary relocation package to move forest dwellers out of the core areas followed.
Similarly, the concept of corridors as a crucial entity for conservation came from data analytics on the movement of tigers between protected areas. Jhala’s colleagues used the countrywide assessment data (historical data on locations, movement, and habitat of tigers) from 2006, 2010 and 2014 censuses to delineate corridors between tiger reserves across the country.
Fresh out of the Sariska crisis, India undertook for the first time in 2006, the All India Tiger Estimation.
There were a few surprising findings.
The estimation found that Corbett Tiger Reserve in Uttarakhand had a tiger density of 19.6 tigers per 100 sq km. This was the highest density of tigers anywhere in the world — unheard of previously.
They estimated the park had over 200 tigers. Over a 100 tigers were captured by camera traps, establishing the numbers beyond doubt.
Corbett had been famous for its gorgeous views, but it didn’t offer many tiger sightings. Unlike in Kanha or Bandhavgarh, you consider yourself lucky if you sight a tiger in Corbett.
“The entire scientific community was surprised; I was definitely surprised. We had no idea Corbett had so many tigers since sightings there weren’t common,” says Jhala. “In retrospect, we should’ve guessed this since it is an extremely productive terai habitat. But the tall grasses block sightings. The data on density pleasantly surprised me.”
Corbett became Jhala’s favourite data story.
It remained so till 2016.
In March 2016, the Uttarakhand police seized five tiger skins in Haridwar. The divisional forest officer of Haridwar called up Jhala’s colleague Bivash Pandav, who worked at the adjacent Rajaji National Park.
He was asked to check if the tigers were from Rajaji. Pandav got photos of the skins, and sat through the night checking images of tigers from Rajaji. None matched.
Next morning, he gave the images to the Tiger Cell. They checked for a match in their database. To Jhala’s surprise, four of them matched. All four tigers were camera captured in Corbett between 2006 and 2015. At least one was a breeding female.
“These tigers were residents of Corbett. The poaching could have happened anywhere. We pointed out where the poached tigers originated from,” says Jhala.
Following protocol, the Tiger Cell informed the member Secretary of NTCA, the Chief Wildlife Warden, and the Field Director of Corbett Tiger Reserve.
Jhala was relieved that the data proved useful to Corbett once again. But, he doesn’t know if the information was used to curb poaching in Corbett.
“Shortly after this incident, all our research work in Corbett was stopped. We were informed that our assistance was no longer required,” says Jhala.
Corbett was one of four research sites where the WII team was studying tiger demography. Research that even informed national policy. Now, they’re missing out on crucial data of a reserve with one of the highest tiger densities in the world.
“We have not had camera trap data sets from Corbett since 2016. And, here, we are talking about an international tiger database,” says Jhala. He is referring to the approval from the Convention on International Trade in Endangered Species of Wildlife Flora and Fauna (CITES) for housing a global tiger repository.
“A classic case of shooting the messenger,” says Jhala, referring to the Corbett reserve administrators’ decision to keep the Tiger Cell off limits.
This is not a one-off incident. Most officials hush up wildlife crime cases, says Jhala. “They feel that reporting a crime in their area would reflect badly on their reputation and efforts, which is untrue. Reporting is a good thing and helps fight crime.”
Jhala says that he even sees this in forest officials’ resistance to using M-STrIPES patrol app. He hopes that the use of patrol app will catch up and more crime incidents will be reported. He stresses that a culture shift is required. “And, that’s something technology can’t fix.”