Just a few decades ago, bee enthusiasts across much of North America could count on spotting one of the continent’s most common bumblebee species buzzing from flower to flower.
Today the American bumblebee is in trouble. Its numbers have dropped sharply, and it has vanished entirely from large swaths of its range.
Yet the fact that biologists even know of this pollinator’s plight marks a key step toward helping it, because population trends steer conservation efforts.
By contrast, scientists remain in the dark about how most of the other estimated 4,000 bee species in North America are handling habitat loss, pesticides, global warming and other challenges.
A new smartphone app called BeeMachine harnesses artificial intelligence to tackle a key hurdle to figuring this out: Right now, experts struggle to tell many species apart.
“It’s a huge problem,” said entomologist Brian Spiesman, the app’s creator and a professor at Kansas State University. “We bring back a few hundred specimens (from fieldwork) and we spend much longer identifying them in the lab than we do actually collecting them.”
Bee ecologists mail tricky specimens — many species are nearly identical and tiny as gnats — to specialized taxonomists.
But these taxonomists are in short supply, so Spiesman and his collaborators are training artificial intelligence to help. As an added bonus: The app lets the public participate in documenting bees, too, by snapping photos when they spot one.
“This type of citizen science has the potential to get more eyes out there sighting bees than any single study could ever hope for,” Spiesman said. “Better tools for crowdsourcing are really important.”
The public’s sightings can offer valuable intel on which bees live where.
In the Midwest, for example, a hiker wandering trails or a gardener scouting their flower beds could find a Southern Plains bumblebee or an American bumblebee, both of which are currently under review by the U.S. Fish and Wildlife Service for potential listing as threatened or endangered.
A separate project from Cornell University, E-Bird, has already proven the power of large-scale public participation by turning passionate birdwatchers into a wellspring of data for avian research and conservation efforts.
So far, BeeMachine can distinguish between more than 350 kinds of bees at the species or genus level.
The goal: teaching it to identify all of the estimated 20,000 bee species worldwide.
That will require international collaboration, though, because Spiesman and his colleagues need high-quality photos of accurately identified specimens to train BeeMachine.
