- An android-based mobile application will make data gathering easy for the national tiger estimation of 2018.
- It reduces errors and the time taken for gathering the first level of data for the estimation.
- Though the app was used earlier in a few tiger reserves, this is the first time it will be used for the national estimation.
India’s upcoming All India Tiger Estimation 2018 is all set to go hi-tech. The plan is to digitise data records with the help of an Android mobile application (app) and eliminate the manual process of recording, which is prone to errors.
The Wildlife Institute of India (WII), Dehradun, developed the app named Monitoring System for Tiger-Intensive Protection and Ecological Status (M-STrIPES).
“M-STrIPES is designed to address many of the issues difficult to handle in patrolling survey,” said P. S. Somasekhar, inspector general of the National Tiger Conservation Authority (NTCA), Southern Region. “Data related to the carnivore’s signs, the relative abundance of prey, habitat and human impact in the area would be digitally recorded through the app. It is user-friendly and easy for information management.”
If procurement of the app goes according to plan, it will be used for the 2018 All India Tiger Estimation, added Somasekhar. The NTCA plans to provide one app-loaded smartphone for data logging in each of the beats (area covered by a forest guard) in the tiger reserves of the country.
The M-STrIPES app, when loaded on to an Android-based smartphone, can help the guard collect data along with pictures and GPS coordinates. If the guard is at a location where there is Internet connectivity, the data is transferred automatically to the server. However, since most parts of the tiger terrain are outside the reach of such connectivity, the data gets stored in the mobile phone and can be transferred at the forest manager’s office.
Training of trainers
“The Wildlife Institute of India is conducting a country-wide training of trainers,” said K. Sivakumar, a scientist at WII, Dehradun. “It is a mammoth task as the estimation is set to begin in January.”
The trainers will then go on to train forest officials, field staff and technical operators in the usage of the app, according to Ambadi Madhav, director of Bandipur Tiger Reserve in Karnataka. Training for field staff in the south Indian states will be held in December.
Sivakumar stated that the use of the app would help in reducing the time taken and make the estimation process easier. “We used to have a formulated data sheet in which patrolling guards recorded data manually. This would then be compiled and sent to the higher authorities. This is a slow and complicated process. But, with the M-STrIPES app, the data logged on the spot will be automatically transmitted to the main server. Those managing the estimation can immediately access the data.”
Besides recording information related to tigers, the app also has features designed to note unusual activities such as poaching and human-wildlife conflict. “If there are any issues, the software can quickly analyse it and the local managers can take relevant action. This will also help assess if current conservation measures are working,” explained Sivakumar.
According to him, tiger reserves in the states of Maharashtra and Madhya Pradesh have been successfully using the M-STRiPES app for close to five years now. There have been improvements in the app since the time they started using it first. Now it is more user-friendly, and provides instant analysis for the managers to take decisions related to surveillance, monitoring and patrolling.
Improves accuracy and reliability of data
“M-STrIPES will be used in the first phase of the tiger estimation in all forested areas,” said Y.V. Jhala, senior scientist at WII and nodal officer of the WII-NTCA Tiger Cell. In this phase, a beat forest guard covers 10 to 15 kilometres in each forest range, looking for signs related to the presence of tigers. By walking transects and recording pictures, the guard can also quantify the animals’ prey base.
“As the information of both tiger signs and prey is logged, the app automatically records the geographical co-ordinates. This improves the accuracy and reliability of the data,” added Jhala.
“Earlier, the data could be faked or there would be errors in manual recording of co-ordinates. This would make the data worthless or require a re-visit to the area. With the M-STrIPES app, such errors are minimised and effort is saved,” noted Jhala.
The entire national estimation is expected to take a year to cover about 400,000 sq. km of forested area in 18 states.
To inform tiger conservation measures, the Government of India started the national tiger estimation in 2006. The NTCA conducts the estimation once every four years and has established a protocol that is implemented in three phases as part of the procedure.
Phase I includes ground survey data collected by trained field personnel. Phase II involves habitat characterisation using satellite data. Phase III includes computation of tiger density using camera traps. In areas where it is difficult to conduct ground surveys or establish camera taps, genetic testing of tiger scat is used to obtain tiger density. Data from all three phases are then analysed together using statistical models to estimate tiger populations.
The problem is with the sampling
The last all India tiger estimation, conducted in 2014, noted a 30% increase in tiger numbers from 1411 to 2226. Experts have however contested these numbers citing discrepancies in the methodology.
Can M-STrIPES help in eliminating these discrepancies? “Shifting to app-based data collection has certainly helped us to minimise some of the human errors,” said Sanjay Gubbi, a scientist with the Nature Conservation Foundation (NCF) and a member of the Karnataka State Wildlife Board. “Using a smartphone app is only a change in tool for data collection, and is not a change in sampling methodology.”
Arjun Gopalaswamy, a scientist associated with the Wildlife Conservation Society (India), agrees with Gubbi. “The M-STrIPES app has not been designed to estimate wildlife numbers. It is essentially a data-recording device for patrolling staff. But the errors in India’s tiger estimation procedure are coming from more foundational problems which are not resolved by an app such as M-STrIPES.”
Gopalaswamy and his associates published a study stating that estimates of tiger abundance reported in India’s tiger estimation reports are more unreliable than previously thought, since these estimates are coming from unpredictable models.
The study states that the index-calibration method used by the Indian government to estimate tiger population numbers suffers from ‘overdispersion’. What this means is that there is greater variability in the data than would be expected.
Index calibration involves calibrating animal numbers obtained by accurate measures such as camera trapping and DNA sampling in a small region with animal densities obtained by approximate indicators such as survey of tiger signs. The calibrated-index is then used to extrapolate actual animal numbers over larger regions.
Using a mathematical model, Gopalaswamy’s study showed that the index calibration model had a high extent of noise and yielded irreproducible results. As a consequence, both the mean estimates of tiger abundance as well as the associated statistical upper and lower limits reported in India’s tiger estimation reports are unreliable.
A re-analysis of all these tiger data will help in assessing the number of tigers in India better,” Gopalaswamy concluded.