Ground-breaking study combines ecology, astrophysics and drone technology to track orangutans
Thermal technology works best in the morning and at early evening when the forest is at its coolest.
SABAH (Reuters) - Swinging through dense jungle and resting in nests by night, orangutans have proved difficult to track for scientists in Sabah, on the southeast island of Borneo.
Borneo s orangutan population has declined from 230,000 to an estimated 104,000 over the last century - making the species critically-endangered according to WWF.
Traditional methods of observing orangutan numbers have relied on rough estimates. Typically, scientists must trek through the jungle and count nests, which is costly and time-consuming.
However, this has changed with a ground-breaking study which combines ecology, astrophysics and drone technology.
In collaboration with Liverpool John Moores University, WWF and Borneo orangutan conservation group HUTAN, a team of scientists flew a drone over the Borneo jungle for six days in May 2018.
It was fitted with thermal-imaging cameras to detect the orangutans heat signatures. Such technology is often used by astronomers to study the luminosity of stars.
"The tropics are a very humid area, it s very hot, so we weren t sure if the heat signal of an orangutan in a nest would be visible from on the drone images but fortunately they are," explained Professor Serge Wich, expert in Primate Biology at Liverpool John Moores University.
"We ve found out, for instance, that even when orangutans are covered by a certain amount of vegetation we can still pick up their signal," he added.
According to Wich, the thermal technology works best in the morning and at early evening when the forest is at its coolest.
The field team conducted 28 flights and successfully spotted 41 orangutans from the air, which was later confirmed by a team on the ground.
Pygmy elephants and a troop of proboscis monkeys were also caught on camera during the study.
The findings are promising and show the viability of this technology as an alternative to traditional methods.
The team is also working on a machine-learning algorithm to help tell the species apart from their unique heat signature.
Their next destination will be in Madagascar where they will be testing the technology on Lac Alaotra bamboo lemurs.
