A rhino's distinctive footprint. Image © WildTrack

Rhino tracks are relatively easy to identify if you know what to look for. A big middle toe forms the curved edge at the front of the footprint, flanked on either side by two smaller lobes. The bulk of the spoor is created by the rhino’s heel which produces a “W” shape at the base of the track. If a rhino happens to trudge through soft substrate, a delicate network of wrinkled lines may be visible in the centre of the footprint it leaves behind – a criss-crossed pattern much like a human fingerprint, and just as unique.

This distinctive pattern, along with the size and shape of rhino prints, makes them perfect for a non-invasive tracking technique that allows field workers to accurately monitor the behemoths using just the marks they leave behind in the sand. A team of Duke University researchers have developed interactive software that "reads" and analyses rhino footprints to keep tabs on the animals' movements in the wild. They hope that the software, known as FIT (Footprint Identification Technique), will help conservationists observe rhino populations without incurring huge costs or interfering with the animals' natural behaviour. 

Darting and collaring wild species is dangerous work that can be stressful for the animals (and humans) involved. After recognising the problems with this monitoring technique, wildlife conservationists Zoe Jewell and Sky Alibhai founded WildTrack in 2004 – a nonprofit organisation that's behind the FIT software. "We would go out with local game scouts, who were often expert trackers, and they would often laugh at us as we were listening to these signals coming from the [tracking] collars,” Jewell told Time last year. “They would say to us, ‘all you need to do is look on the ground.”

The FIT software aims to help conservationists observe rhino populations without incurring huge costs or interfering with the animals' natural behaviour. Image © Tania Kühl Photography

More recently, the team has been testing the tech at a handful of private game reserves in Namibia. There are three ways in which FIT can be used to benefit guides, scientists, managers or anti-poaching units depending on their specific needs, according to Jewell who co-led a recent study published in PeerJIn its simplest form, a digital image of a rhino's heel pattern can be compared to records already in the FIT database to determine if there's a match. This is useful if a random print is spotted in the wild and field workers need to know which individual it belongs to. Of course, this only works if a substantial rhino-print database already exists for the area.

FIT software can also be used to estimate the number of rhinos in a particular area using a survey of footprints – individual tracks can be identified to give an indication of how many different rhinos are roaming the landscape. Reserve managers can then use this info to allocate appropriate resources such as how many rangers or vehicles are needed to patrol the area.

In its most comprehensive usage, individual rhinos are tracked and matched to their footprints to create an interactive database that anti-poaching teams can use to assess threats and establish if any animals are missing in action. "FIT is a distillation of the traditional ecological skills of the expert trackers who have lived and worked within Africa for many years," said Alibhai. "Using FIT allows their skills to be used effectively in conservation. This can benefit whole communities."

As long as rhinos are leaving tracks, they can be monitored. Image © Tania Kühl Photography

The software is not restricted to rhinos and has been used to track everything from big cats to polar bears. In more recent years, FIT has been used in conjunction with AI and aerial drones to more easily track prints and help speed up processing – a development that drew interest and funding from the US military. It's a partnership that may raise a few eyebrows, but if it helps save endangered rhinos, then Jewell and Alibhai are all for it.

Top header image: Matthew Rogers, Flickr