Technology a changer for game under threat
Software system gives rangers an earlier warning about poachers or other dangers in remote areas
If he has his way, Paul Allen, the world’s 10th-richest software developer, will cover 150,000km² of African territory with smart sensors and drones by the end of 2017 to bring hyper-connectivity to the most remote, wildlife-packed corners.
It’s the biggest, tech-focused conservation project to date, a command-and-control system for rangers to record and respond to poaching threats.
Allen is funding the project— called the Domain Awareness System (DAS) — through his company Vulcan and it’s as simple in concept as it is complex in execution. The software is the key to what may be one of the sexiest philanthropic causes of our time.
The basic idea: studying the movements of endangered animals to get ahead of poachers on a scale that allows Big Data to predict threats to the animals across entire regions.
For years, African rangers have protected wildlife with boots on the ground and sheer determination. Armed guards spend days and nights surrounding elephant herds and rhinos, while on the lookout for rogue trespassers.
Allen’s DAS uses technology to go the distance humans cannot. It relies on three funnels of information: ranger radios, animal-tracker tags and a variety of sensors such as camera traps and satellites.
It sends everything back to a centralised computer system which projects threats onto a map of the monitored region, displayed on large screens in a closed-circuit security room.
For example, if a poacher breaks through a geofence sensor set up by a ranger in a highly trafficked corridor, an icon of a rifle would flag the threat, as well as microchipped elephants and radio-carrying rangers in the vicinity.
When alerts strike, help is dispatched to help save one of 352,271 estimated remaining elephants, or one of 30,000 surviving rhinoceroses.
"By nature, I am attracted to tough problems — problems that, by definition, require innovative and dramatic solutions," says Allen from his office in Seattle, where his philanthropic company, Vulcan, is based.
"[The DAS project] is the ideal combination of two of my interests — technology and the preservation of [the savannah elephant], one of Africa’s most iconic species."
DAS was first put into the wild in October 2016, when Ted Schmitt, lead programme manager at Vulcan, and his team deployed the technology at the Lewa Conservancy in Kenya.
It was then brought to Odzala National Park, founded in 1935 and one of Africa’s oldest national parks in the Republic of the Congo.
In partnership with Save the Elephants, African Parks Network and Wildlife Conservation Society, six other conservation sites soon followed.
Its most high-profile partner is Singita, the network of luxury safari lodges run by conservation guru Luke Bailes. It has 12 properties spread across Tanzania, Zimbabwe and SA — with the most sumptuous design, the largest wine collection and often the highest price tag among its competitive set.
DAS was installed at the five-lodge Singita Grumeti reserve in March, using sensors to illuminate a key corridor for poachers intent on crossing to the neighbouring Serengeti.
Bailes calls the system a "game-changer". He says the "layered approach of technology and boots on the ground enables Singita Grumeti to significantly enhance its effectiveness in dealing with poaching".
Part of the success is Vulcan’s holistic approach: Schmitt’s team developed the software and provided capital for equipment and hardware, and they’ve also invested in training, technical input, support, set-up, mentoring and guidance. Although the partnership is just two months old, "the impact has been significant", Bailes says.
Schmitt says DAS happened almost by accident. In 2014, the Vulcan team had been dispatched to Kasane in Botswana to help launch the first pan-African elephant census in more than 40 years. "We had all the best ... scientists that do wildlife research and census-taking come together, trying to address a common problem," he says.
The group decided to systematically fly in grid-like patterns over 17 African countries, carefully threading and weaving above the continent, photographing herds and carcasses, and counting the old-fashioned way.
There was talk of using drones, but the area’s scope was too large for the devices and researchers feared the technology wasn’t consistent enough. The situation was too urgent for any technological mishaps, Schmitt says.
In the end, his team came away with two major insights. The population of savannah elephants has declined by 30% in the past seven years, primarily due to ivory poaching. And having tons of data on elephant poaching is useless unless conservationists can make sense of it in real time.
Schmitt’s first instinct was to harness as much data as possible, casting a wide net across the African savannah. "But what a lot of [park managers] were telling us was that they were already overwhelmed by the information they had. They couldn’t use it effectively."
What they needed was a way to aggregate and visualise data. They needed software.
"All of the tools that are out there are designed for the military," Schmitt says.
"They’re very expensive, for highly trained individuals, and not suited to the wildlife and conservation domains."
Rangers were instead using a decades-old system.
Building DAS took about 12 months and the partnership of many organisations that gave feedback. Threats differ by location: in Tanzania, wildlife snares and bush-meat hunters are a big problem, while ivory poaching is a more common issue in Kenya. There are also less malicious issues, such as fires or a cow that has wandered from a farm to big game predators.
Schmitt and his team designed a system capable of recognising all these factors. Some can be reported by rangers over radio; others can be picked up by seismic sensors, satellites, drones, camera traps and speed detectors.
"With every type of enforcement, the most urgent task is figuring out where the bad guys are," Allen says. "You might have the best people and equipment money can buy, but unless you know where to direct your response, you’re essentially powerless. The intel this system provides will help conservancies use their limited resources much more effectively."
It will take two to five years to get real measurements from conservationists, but the feedback for DAS has been promising. Though no animals have yet been saved as a direct result of DAS, rangers in two separate cases were able to use DAS alerts to intercept poachers who had already made a kill.
The system has also helped rangers in Kenya prevent human-wildlife conflict by identifying which farms’ cattle are most likely to roam into conservation areas. By working with locals to rein in the livestock, rangers can prevent retaliatory killings by farmers that happen when, say, a lion preys on that wandering cow.
What has been surprising to the Vulcan team is how the new system has unified conservationists who had previously been focused only on their individual reserves.
"All of these groups are now sharing best practices with each other, more now than they ever had been. They’d all been doing the best they can in their regions, but stepping back and exchanging information has proved to have tremendous value in itself," says Schmitt.
The next hurdle is bringing connectivity to places that still don’t have it, such as the jungles and forests of the Congo.
Enhancing connectivity where it exists but is low will also be key; it’s what will allow DAS to show alerts in real time (rather than on a delay).
Then, Schmitt says, comes the exciting part: "Once you have more and better data, you get to this place where we have real expertise. Where you can ask, ‘How do you analyse data and call up patterns and proactively identify threats?’."
Allen is happy to let his team run wild. "I’ve spent time with these park rangers, so I’m familiar with how difficult their work is. Providing this kind of tool to help them defend endangered species is incredibly fulfilling," he says.