There were drones, there were boats. There were spotters on land. There was a hydrophone listening for suspicious sounds underwater. This past summer, crowds of people gathered in Scotland to hunt for any sign of a legendary creature: the Loch Ness Monster. This may have been the biggest search of its kind in 50 years.
Nearly 6,000 kilometers (3,700 miles) away, data scientist Floe Foxon emailed the event’s organizers. He wished them good luck. “I’m sure it’s going to be a fun weekend,” he wrote. Foxon wasn’t joining them. But from his home office in Pittsburgh, Penn., he has examined Nessie’s lore in his own way — with statistics.
Last July, Foxon published a study on the probability of finding a giant eel in the loch. That’s one of many hypotheses for sightings of the storied sea monster. The answer: Essentially zero. Even the chances of finding a 1-meter (about a yard) -long eel are low, about 1 in 50,000. Foxon reported this in JMIRx Bio. Once you get much longer than that — into monster-sized eel territory — the probability plummets further.
But don’t call Foxon a myth buster or a debunker. “Absolutely not,” he says. “I think you should approach these things with an open mind and let the data influence your decision making.”
Though monsters have captured Foxon’s imagination, his background is in physics. By day, he’s a data analyst for a health consulting firm. In his free time, he flits through far-flung fields of science. They include astronomy, paleontology and cryptology, the study of ciphers. “When you learn data science,” Foxon says, “you find that it can be applied to more or less anything.” Even monsters.
For his Nessie study, Foxon analyzed the mass distribution of eels caught in Loch Ness and other freshwater bodies in Europe. He converted that data to eel length and then calculated the odds of finding eels of different sizes.
Looking for monsters with math
In a separate monster study, Foxon looked at data on Bigfoot sightings and black bear populations across the United States and Canada. The study was posted online July 20 at bioRxiv.org. As the number of black bears in a region goes up, Bigfoot sightings tend to increase as well, he found. That doesn’t tell you whether Bigfoot is real, though, Foxon says. “You can’t answer that sort of question without a specimen.” Instead, he thinks about it from a probability standpoint. If you think you’ve seen a sasquatch, he says, it’s probably just a bear.
But people claiming glimpses of Bigfoot or other extraordinary beasts probably aren’t hoaxers, Foxon says. “Most people are very earnest and honest about having an experience that they personally cannot explain.” He thinks scientists should listen to them and take them seriously.
Off the top of his head, Foxon can rattle off the names of supernatural attractions he’s visited around the world. There was a museum of curiosities in London, England, and the Flatwoods Monster Museum in Sutton, W.Va. He’s even been boating on Loch Ness (though no sign of Nessie).
Foxon considers his study of sea monsters, sasquatches and other mythical beings folk zoology. He describes the field as the intersection between zoology and indigenous knowledge of animals in folklore. Foxon’s work has roots in cryptozoology. This field once used the tools of science to investigate mysterious animals. But it has since been “overrun by a lot of pseudoscience,” he says.
It’s not so much the monsters that pushed the field to the fringe, though. Foxon, for instance, investigates all sorts of cryptic creatures. These include giant snakes and a hypothetical aquatic animal dubbed Champy. It has been reported to live in North America’s Lake Champlain. But his quest for answers takes a strictly scientific tack that relies on established mathematical methods.
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“It’s not what you study, it’s how you study it,” says Charles Paxton. He’s a statistician and fish biologist at the University of St. Andrews in Scotland who has published papers on the Loch Ness Monster. Still, when people find out what Paxton studies, some assume he’s a pseudoscientist. “That’s quite frustrating, actually,” he says. “The methods of science can be more widely used than people might think.”
Foxon’s latest study posted online August 8 at bioRxiv.org. In it, he uses a statistical method to examine eyewitness sightings of a long-extinct bird, the New Zealand moa (Dinornithiformes). Scientists think the ostrichlike bird went extinct hundreds of years ago. But people have reported seeing moa as recently as the 1990s. The analysis factored in the reliability of 97 separate moa sightings. Foxon estimated that moa probably were extinct by 1770.
“I’m greatly disappointed by all of my findings,” Foxon says with a laugh. “I really wish that there was a giant eel in Loch Ness,” or a hairy apelike monster in North America’s woods or moa living in modern times, he says. But “there seems to be a very, very low probability.”