In August 2011, I climbed onto a small twin-propeller plane, crouching down to avoid smacking my head. The plane took off from Cusco, Peru, and was soon soaring over the Amazon rainforest. From the window, I could see a vast, unbroken layer of trees, greeting the horizon in every direction. It all looked the same—but it wasn’t. That seemingly uniform stretch of jungle contained many distinctive types of forest, each with its own distinctive climate and species. To the naked eye, the boundaries between these zones are invisible. We literally can’t see the forests for the trees.
The trio of devices in the back of the plane had no such problems. They were “probably the most advanced Earth-mapping system in the world,” according to their creator, Greg Asner, who sat behind me on the flight. One—a gray box—sent beams of light sweeping across the canopy, and used the rebounding beams to map the shape of every tree and branch. The others—another gray box and a golden cylinder—measured the various wavelengths of sunlight that naturally reflect from the canopy. Those reflections depend on the chemicals within the leaves; by measuring them, the devices could record the chemistry of the forest from afar.
For almost eight years, Asner has been using these instruments to map the world’s forests at an incredible scale. While traditional ecologists can spend months hacking through jungle, taping off quadrants, and counting species, Asner can fly over and get a lifetime of data in seconds. From several kilometers overhead, he can image trees down to individual branches, measure the carbon stored in the soil, and classify species based on their chemistry.
When I met him in 2011, Asner was just starting out, and the golden chemistry-mapping instrument had just been finalized. “It was my first year, and I was putting on my game face and saying: Hey, I can do this.”
And he did. He has now mapped all of the Peruvian Amazon—all 300,000 square miles of it.
He used that golden sensor to measure the density of the leaves, their levels of essential nutrients like nitrogen, water, calcium, phosphorus, and their levels of two defensive chemicals—lignins and polyphenols. And by using machine-learning algorithms to interpret these seven traits, he has shown that the Amazon can be divided into 36 distinctive types of forest, which fall into six major groups. “There’s a beautifully complex geography that’s been totally unknown to science till now,” Asner says.
Those 36 types of forest so far have been treated as if they were three: those growing on firm clay soils, those growing on floodplains, and those living on the sides of the Andes mountains. But each of these “is more biodiverse than anyone had thought,” says Asner. “If you fly over the Amazon rainforest, or look at it in Google Earth, it’s a lie of omission. It’s not just a green carpet.” Indeed, on his map, the Peruvian Amazon looks like a bad LSD trip, with 36 colors demarcating the various forest types.
It reveals the “variation in a highly complex ecosystem that is notoriously difficult to sample from the ground and where many species are poorly known or new to science,” writes Valerie Kapos, from the United Nations Environment Programme, in a related commentary.
Asner didn’t make the map for academic reasons. By overlaying it with government data on protected areas, deforestation, oil exploration, and more, he identified forest types that are reasonably safe, those that are in danger, and those that would benefit from more protection. “As land use continues to chew away at these forests, conservationists need to be more and more tactical as to where it puts their protection,” he says. “That ability totally depends on knowledge. Otherwise, you’d protect one type and miss 10 others, and you’d lose lots by omission.” In other words, if a tree falls in the forest, you want to know which kind of forest.
“The work is clearly pushing the boundaries,” says Nathalie Pettorelli, from the Zoological Society of London, “but I remain to be convinced that it would actually help guide conservation.” She argues that Asner measured seven traits because they were traits that could be measured from afar. But are they the most important ones? What if he only did five? Or had two more? Would the 36 types changes?
Not so much, says Asner. His orange sensor actually maps 20 traits, and he used that data to select the seven that are most informative. He and his field teams have also travelled to each forest type the old-fashioned way, to try and work out whether they are meaningfully different. And they are, he says; they vary in their elevation, soils, climate, water levels, and resident species. “I’ve been looking at this map for a few years to try and understand it,” he says. “It’s my first offering, and there’ll be a lot of nerdy papers that come out afterwards.”
In the meantime, he has bigger plans. He wants to take his approach into space.
He and his colleagues at NASA’s Jet Propulsion Laboratory have spent years tweaking that golden sensor that I saw on his plane, so that it would work from orbit. He tells me that he needs three more years, and around $200 million—a surprisingly low cost. “We’ve been engineering and reengineering to bring the price down and make this a no-brainer,” he says. “[Once in orbit], we can map the changing biodiversity of the planet every month. That’s what we need to manage our extinction crisis.”
“I can’t fly this plane around enough,” he adds.
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