Software developed by researchers in the US could help conservationists keep a watchful eye on the black rhino, one of the world’s most critically endangered species.
The interactive software, jointly developed by researchers at Duke University and analytics software specialist SAS, analyses the footprints left by black rhinos and can be used to monitor their movements, enabling conservationists help keep them safe from poachers.
The software, called the Footprint Identification Technique (FIT), runs on JMP software from SAS and uses advanced algorithms to analyse over 100 measurements of a rhino’s footprint.
Because each rhino’s footprint is as distinctive as a human fingerprint, the analysed images can be archived electronically in a global database of previously collected footprint images for matching.
“If you find a match, you can identify the individual animal who left the mark and, by plotting the locations of all the other places that mark has been seen, track its movements without disturbing it or coming into close enough contact with it for there to be a risk of animal-to-human viral transmissions,” said Zoe Jewell, adjunct associate professor at Duke University’s Nicholas School of the Environment.
“It’s a cost-effective approach that not only protects the health of the rhino and the human, but also brings a centuries-old tracking skill into the 21st Century,” she added.
Jewell and her colleagues are now working with Namibia’s Ministry of Environment, Forestry and Tourism to train wildlife conservationists, land managers, local guides and anti-poaching agents how to use FIT.
Namibia is home to an estimated 2,000 black rhinos, or about 90% of the species’ total population worldwide. Between 30 and 50 of the animals are still slain each year for their horns, which can sell for more than $60,000 a kilogram on the Asian black market.
FIT allows the animals to be monitored three different ways, allowing scientists, managers, guides or anti-poaching patrols to use it as best meets their individual needs and constraints, said Jewell.
In the simplest option, the heel pattern on a digital image of the footprint, is compared to images already in the FIT database to search for a match. This use is well-suited to situations where a random footprint is found in the wild.
The software can also do a survey of footprints throughout the protected area and take measurements from each print to estimate the number of rhinos in that area. This can be useful information for calculating resource needs – the number of patrol vehicles, for instance – to monitor the animals effectively.
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In the most advanced option, each individual rhino can be tracked and matched to its unique footprint using both FIT and heel-patterns. This creates an interactive library that anti-poaching patrols can use to search for animals at the highest risk, including those known to frequent areas under threat from poachers or those whose footprints haven’t been showing up in recent years.
A peer reviewed study describing the technology’s effectiveness for monitoring the endangered rhinos was published on August 14 in the open-access journal PeerJ – Life & Environment.