“For centuries forests have redeemed us humans. Now we must reciprocate that redemption”. Shannon Mattern does some tree thinking
From the exhibition Cambio, by Formafantasma, at the Serpentine Galleries, 2020.
Something of an epic essay on “tree thinking” in Places Journal by Shannon Mattern (we’ve done our share of tree thinking here on A/UK). It goes through how “decision trees” are a long-standing image in scientific thinking; the ways that trees have been core to philosophy and politics; how indigenous culture’s conception of the forest challenges our Northern definitions of truth and reality; and much, much more.
But Mattern starts with some enjoyable techno-farce about trees, and the measurement hubris of the big tech giants:
Last fall Google launched its Tree Canopy Lab, which uses artificial intelligence to examine aerial imagery and public data on population density, land use, and heat risk to estimate tree canopy coverage across Los Angeles — and eventually other cities. The expectation is that such visualizations will inform tree-planting efforts to reduce carbon emissions and enhance public health.
Around the same time, the conservation nonprofit American Forests partnered with Microsoft to introduce the Tree Equity Score, which grafts together data about neighborhood income, demographics, employment, and population density, as well as tree canopy and surface temperature, These will determine how the presence or absence of trees might map onto other forms of racial and socioeconomic inequity.
This summer American Forests revealed that to achieve tree equity, the United States would need to plant 522 million urban trees.
Similar technologies have allowed Canopy to deploy proprietary software called “ForestMapper” to help its fashion industry clients plot out more sustainable fiber supply chains. The U.K. tech startup Dendra will also use AI and aerial imagery to identify prime spots for planting, which in this case involves drones firing seed-filled pods into the ground.
Meanwhile NCX, a carbon credit exchange built on Microsoft AI, uses its own “precision forest management” tool so that landowners can “quantify the full value” of their wooded properties. As Zack Parisa, the CEO, says, “you can’t manage what you can’t measure.”
Microsoft’s Chief Environmental Officer, Lucas Joppa, also frames ecological management as a technological concern: our “wide range of environmental concerns … represent the world’s biggest data challenges, the world’s biggest compute [sic] challenges, and the world’s biggest algorithmic challenges.”
And he offers up an even more ambitious ecological-epistemological imaginary: “Imagine if we had a planetary computer that could tell us exactly what we needed to do to protect planet earth—a system that was capable of providing us with information about every tree, every species, all of our natural resources: how could we use all that data to build a better world?”
Just imagine! Wouldn’t that be grand? An algorithm that could calculate how many trees would atone for the historical and contemporary inequities of urban planning and environmental injustice?
That could undo processes of deforestation wrought through centuries of colonial violence? That could heal a landscape destroyed by clear cutting? A dashboard that grants us datafied dominion over all of creation?
A colossal computer that would model all living systems and allow us to turn some knobs and test the impact of design solutions: a windbreak here, a forest preserve there, a pollinator garden over yonder?
Or maybe not. As trees become data points, they are all too readily cast as easy fixes for profound problems. Trees as tools of carbon capture, tall timber as an instrument for sustainable construction, green barriers as sound buffers along roadways: sylvan solutions to systemic snafus.
The media scholar Jennifer Gabrys argues that such approaches are efforts to frame (and tame) hard problems—wicked problems —in computational terms. Forest data sets in particular, she writes, tend to “present the problem of environmental change through … metrics that in turn legitimate specific technological interventions to meet targets for averting environmental catastrophe.”
In other words, these technological tools promote techno-solutionist responses to problems that are simultaneously ecological, cultural, social, economic, and political.
It’s easier to plant a tree—and to allow a generative design dashboard to tell you precisely where to plant it—than it is to change our individual and collective consumption habits or to muster the political will to eliminate fossil fuels.
In 2019, a research team at ETH Zürich mapped the potential global tree canopy and discovered that the world could accommodate an additional 0.9 billion hectares of canopy cover, which could store over 200 gigatons of carbon; as a member of the team told The Guardian, “This new quantitative solution shows [forest] restoration isn’t just one of our climate change solutions, it is overwhelmingly the top one.”
Anyone can plant a tree, so the argument goes, and doing so doesn’t require difficult sacrifices or fundamental change. Hence the popularity of initiatives like the One Trillion Tree Campaign—even Donald Trump was a fan—which seem to promise that a billion people each planting a tree will cumulatively constitute a meaningful response to the climate crisis.
But at best this is magical thinking, a crowd-sourced form of techno-vegetal solutionism—and as such a distraction from the large-scale, systemic transformations that are required to counter the impacts of global warming.
”The notion that tree planting is an elixir for what ails the earth is as popular with polluters as it is with nations, a fact that spawned the ‘carbon offset industry,’” writes science journalist Ted Williams in Slate. For Google and Microsoft, tree projects amount to little more than slickly produced campaigns to greenwash their own extractive, energy-intensive operations.
The tech giants’ hubristic projects, with their satellite maps and interactive apps, not only serve to minimize the scale of the problem; they also risk impoverishing our understanding of trees. As Gabrys argues, such tools can render forests as mere timber stores or carbon sinks, rather than as “sites that sustain cultural narratives or indigenous cosmologies,” as systems and repositories of knowledge that resist algorithmization.
This is, in fact, a new version of an old problem. The rise of scientific forestry in Prussia and Saxony in the late 18th century brought about an abstracted and operationalized perspective of wooded landscapes.
As the political scientist James C. Scott argues in his influential book Seeing Like a State, the forest became “an economic resource to be managed efficiently and profitably,” while “the actual tree with its vast number of possible uses was replaced by an abstract tree representing a volume of lumber or firewood.”
Yet there are other, more capacious ways to think through trees. By recognizing the deep roots and copious branches of arboreal thinking, we can not only appreciate trees as foundational models in intellectual and social history; we can perhaps also graft those branches onto the evolving methodological tools that we are using to repair our damaged planet.
More here (see the original piece which is extensively footnoted). We would immediately point you to Richard Powers’ on his book The Overstory.