Open your phone and scroll back to the least interesting photo in your camera roll. A blurry parking lot, maybe, or the inside of a pocket.
Now picture an entire folder of nothing but that: thousands of near-identical frames of grass and wind, with the occasional tail disappearing out of the corner of the shot. Your job is to look at every single one and say honestly what you saw. Would you make it past the first hundred before giving up?
A very large number of strangers didn’t give up. Since 2010, a network of motion-triggered cameras strapped to trees and posts across Serengeti National Park in Tanzania has been firing at anything that moves, day or night, and the flood of photographs it produced has been sorted, frame by frame, by people who signed up for free from wherever they happened to be sitting that evening. The project is called Snapshot Serengeti, and the numbers behind it are worth sitting with for a minute.
Two hundred twenty-five cameras and a question nobody could answer fast enough
Researchers from the University of Minnesota began setting camera traps across the park in June 2010, starting with 200 of them and expanding the grid to 225 by 2012, the count that held for most of the years since and the one in the title above.
Spread across roughly 1,125 square kilometers of the park, home to more than 40 mammal species according to the study’s own published dataset, the cameras were built to answer a question that sounds simple and isn’t: how do lions, hyenas, cheetahs, and a long list of grazing animals actually share that ground without one group crowding out the rest? By the time the first three years of results were formally published, the cameras had captured 1.2 million distinct image sets, and roughly a third of a million of those actually had an animal in frame.
The project outlived the study that made it famous. More than a decade after the first camera clicked on, the Snapshot Serengeti team has kept running new rounds of the same survey, adding well over a dozen additional seasons of photos on top of those original three years.
The part no computer could do in 2010
How do you get through a million photographs before the grant runs out? In 2010, the honest answer was that you don’t, not with a research team of a handful of people, and not with the image recognition technology available at the time. “We needed to rely on the human eye,” said Margaret Kosmala, who was a graduate student at the University of Minnesota at the time and is now a postdoctoral fellow at Harvard.
So the team partnered with Zooniverse, a platform built for exactly this kind of crowdsourced pattern-matching, and opened the entire photo archive to anyone willing to click through it. No biology degree required, no application process, no plane ticket. Just patience, and a working pair of eyes.
What all that sorting actually turned up
At the University of Oxford, Alexandra Swanson now works as a postdoctoral fellow, but when this camera grid first went into the ground, she was the University of Minnesota doctoral student running it day to day. Her own read on the project’s size doesn’t undersell it: “This was the largest camera tracking survey conducted in science to date.”
That scale is what made a specific discovery possible a year later. A 2016 study led by Swanson, published in the journal Ecology and Evolution, drawing on the same camera network, expected to find lions, hyenas, and cheetahs carving the landscape into separate territories, the way ecologists usually assume weaker predators avoid stronger ones out of fear. That isn’t quite what the data showed. Instead of avoiding lion territory altogether, the study found that cheetahs are able to use patches of preferred habitat “by avoiding lions on a moment-to-moment basis,” slipping into prime hunting ground for a few hours at a time and clearing out before trouble arrived. It’s a pattern drawn from years of photographs, not a lab experiment, but it held up consistently enough across the dataset to publish.
None of that shows up in a single photograph. It only shows up once thousands of labeled images, tagged with species, time, and location, get stacked against each other across years of data. One photo tells you almost nothing. A few million of them, sorted patiently, tell you something real.
Camera traps aren’t the only tool turning up invisible patterns in the wild. GPS collars recently tracked one elephant’s two-year, 12,000-kilometer trek across four countries — and found something researchers didn’t expect: a wall the herds can see and we can’t. Space Daily channel explores what the data revealed in a recently published video, The Wall Only Elephants Can See.
More people wanted to look at wildebeest photos than you’d guess
By 2018, more than 140,000 volunteers worldwide had logged into the project to identify species, count animals, and flag behavior across the photo archive, according to the University of Minnesota. That figure is already several years old, and the project has run more seasons since, so the real total today is almost certainly higher. Most of these volunteers will never see the Serengeti in person. They did it from a laptop, in whatever country they happened to live in, for no pay and no public credit beyond a screen name in a database.
Go back to the camera roll challenge from the start of this piece. Multiply your own patience threshold by however many photos of grass it takes to reach one worth flagging, then multiply that by well over a hundred thousand people who decided to do it anyway, repeatedly, for years. That’s not a small ask of strangers, and enough of them said yes to build a dataset that outlived its original grant.
What I keep coming back to
I don’t know anything about lion ecology beyond what I read researching this, and I won’t pretend otherwise. What actually caught my attention here is the volunteers, not the cheetahs. I have a personal opinion I return to often, about opportunity more than ecology: people who want something seek it out, and people who don’t tend to find reasons it can’t be done. Well over a hundred thousand people found a real opportunity to contribute to actual wildlife research from their own couches, with no training and no travel budget, just a willingness to look closely and repeatedly at something most of us would scroll past in five seconds.
Nobody made them do it, and nobody paid them either. They decided that clicking through a folder of grass photos, on the chance a cheetah showed up two thousand frames later, was worth an evening. That opportunity sat in front of anyone with an internet connection for more than a decade. Well over a hundred thousand strangers picked it up anyway.
