Excel, drones, and the measurability of forest carbon — Theo Stanley

Today, Eric has been hired to fly a DJI M300 airframe drone, fitted with a 45-megapixel camera, over a Highland estate. The drone takes high-resolution images of the estate’s canopy from above, which are combined with laser imagery taken from the forest floor, to produce a 3D-visualisation of every tree growing on the estate. This effectively creates a landscape-scale model of the estate’s above-ground biomass, which can be used to calculate how much carbon is stored in the estate’s vegetation. Eric explains how the digital technologies he uses have generally “found 300% more biomass than the Woodland Carbon Code had suggested,” across a range of forests, from commercial plantations of Sitka spruce to dense native woodlands.

 

Eric, and the estate owner employing him, are exemplars of a growing group of business-minded entrepreneurs, investors and landowners, who are developing and employing new technologies to measure ecosystems in the Scottish Highlands. These technologies, which include drones, satellites, lasers, artificial intelligence, robotics and eDNA sampling, measure carbon storage, carbon sequestration, biodiversity abundance, or other ecosystem services in forests, peat bogs and grasslands.

Technologies such as these, that measure ecosystems in fine-grained detail, are widely heralded as critical for ecosystem restoration. As the world warms and society races towards ‘net zero’, there is a growing discourse promoted by conservationists, governments, and corporations, that society needs to improve its technological capacity to measure and know ecosystems (Huff & Brock, 2017; Nost & Goldstein, 2022). Access to more detailed and accurate environmental data about ecosystems, known through improved digital technologies, is assumed to be essentially good for the ecosystems being measured – more accurate data can inform more rational conservation policy and help channel investment into ‘nature-based solutions’ to climate change and biodiversity loss (Büscher & Fletcher, 2020; Seddon et al., 2019, 2020; Turnhout et al., 2014).

However, as Nost and Goldstein (2022, p. 3) highlight, “it is increasingly clear that environmental data does more than simply offer a better view of the planet.” Environmental data does not just appear but is always produced by specific assemblages of humans and nonhumans (Taffel, 2019). Within the neoliberal conservation paradigm, the standardized measuring of ecosystems can be used to forge connections between conservation organisations and organisations with technocratic and economic interests (Turnhout et al., 2014). Jennifer Gabrys (2021) highlights how digital ‘green’ technologies are often put to work within the logics of extractive capitalism and ‘green growth’. These technologies facilitate the entrenchment of class and wealth divides, as people without digital access are excluded from decision-making and knowledge production. Meanwhile, these technologies often fail to address the environmental change they purport to fix.

Informed by this growing body of critical scholars researching how ‘digital ecologies’ are produced, governed and shape the material world (for an in-depth overview, see von Essen et al., 2021), my research investigates how and why ‘nature-based solutions’ are measured and digitised in the Scottish Highlands. This involves hanging out in forests and peatbogs with all sorts of folk – entrepreneurs like Eric, soil scientists, commercial foresters, rewilders, community forestry groups and conservationists – and trying to piece together how environmental data is being produced, and what effects this is having. What is being measured (or not) in ‘nature-based’ carbon calculations? How is it being done? And who is benefitting from these measurement processes?

 

WHEN EXCEL SPREADSHEETS AREN’T ENOUGH

There are many ways to measure an ecosystem. The IPCC categorises different mechanisms for estimating carbon removals into different ‘Tiers’. ‘Tier 2’ measurement involves inputting macro-level, abstracted data on land use or forest cover. ‘Tier 3’ measurement is more in-depth, and involves modelling and measuring carbon over time, using fine-scale, high resolution data, and is largely reliant on GIS technology.

In the UK, land-based carbon sequestration is largely measured using a ‘Tier 2’ mechanism, the Woodland Carbon Code (WCC). The WCC calculates how much carbon a reforestation or afforestation project will sequester, and therefore determines how many ‘independently verified carbon units’ (aka carbon credits) the project can be attributed. Calculations of tree growth are based on numbers from the ‘Blue Book’, a forestry handbook that estimates the amount of timber (ie, a tree’s trunk) that will grow.

To calculate carbon credits using the WCC, a project manager inputs data about the trees they plan to plant (species, spacing between trees, etc.) and landscape-specific details (relief, steepness etc.) into the WCC’s Excel spreadsheet. An algorithm produces a number: the amount of carbon the scheme is expected to sequester in the following 100 years. This determines how many carbon credits a scheme is worth.

 

Several of my research participants were, at best, ambivalent towards the WCC. Some acknowledged its flaws but told me it was the “best approximation or model that we have,” and how it was “okay… one of the first carbon codes and it is good enough.” But the majority of my research participants were critical of the WCC, for a range of reasons. Here, I pick out three.

Firstly, commercial foresters and entrepreneurs were frustrated that the WCC models are “really conservative.” They told me that the WCC was “deeply flawed” and “dated.” As one carbon accountant suggested, “maybe the WCC is modelling 70-80% less carbon than is in those ecosystems.” Some foresters argued that this was stifling profits, as forests weren’t accredited a correct financial value.

Secondly, accusations of fraud, data fudging and imprecision were commonplace. One forester told me the WCC’s ‘additionality’ clause, which specifies that carbon credits are only attributed to schemes that would not be financially viable without carbon finance, could easily be “tinkered with in the spreadsheets.” Another forester told me how data can be easily “cooked”, to make a scheme look like it will sequester more carbon compared to “business-as-usual.” She told me how data about an estate’s ‘alternative land use’ can be easily “played with,” which inflates the ‘additional’ amount of carbon a scheme can claim to sequester. To compound the issue, “…the data is only checked once! And the evidence you need to provide is minimal. So unless they check the evidence at that first point, you are validated and you can make as much money as you want!” She provided an example. “…when I was working at [a large forestry company], they were putting through a Sitka plantation [a non-native monocrop] into the WCC… and the landowner would just say, ‘what do you want the figures to say?’ They’ll come up with a budget for the ‘alternative land use’ that will just make it work.”

Thirdly, many conservationists, ecologists, and ‘progressive’ foresters told me how the WCC suits commercial forestry. Several interviewees argued that the linearity of tree growth needed for commercial forestry can easily be folded into the WCC’s spreadsheet. Contrastingly, the messiness of a naturally regenerating native woodland could not easily be calculated by the WCC because of its chaotic growth pattern.

 

EVERYONE WANTS MORE DATA…

Concerns with the limitations of the WCC are diverse. Yet a belief uniting many people and organisations, ranging from commercial foresters to rewilders, who often disagree on topics relating to environmental management, is that a more reliable, up-to-date, accountable system of measurement to measure and monitor ecosystems is much-needed. Drones, satellites and lasers – and the ecosystem data these technologies produce – were widely heralded as being necessary for improving carbon calculations.

Repeatedly in interviews, conservationists, native woodland specialists and rewilders argued that improved measurement and quantification of ecosystems might tip the balance in favour of more ecologically sound practices. Better data could highlight how ecosystem restoration provides more ecosystem services and natural capital than commercial forestry, thus attracting investment and informing conservation policy. For example, a native woodland expert, who works for a consultancy specialising in producing ‘ecological carbon’, argued, “If we can just find a way to measure ecological benefits and explain it to people, we can tell the stories because we know these things. It’s basically about taking carbon and creating a story around it and making it interesting.” Likewise, a senior rewilding executive told me how “we believe in habitat restoration,” but his rewilding organisation needs to develop metrics to “prove that there are measurable benefits to ecological restoration.”

 

Commercial foresters also argued that better technology for measuring ecosystems will help the forestry industry. As ecosystems are measured with more rigour and accuracy, the natural capital credits produced within commercial forests will be more robust and trustworthy. As one commercial forester explained, “We need to get better at remote sensing, satellite data and machine learning… The Woodland Carbon Code is good for telling us what to expect but these technologies tell us what is happening on the ground.” He argued that improving ecosystem measurement technology can bring more robust verification to carbon credit schemes, which should facilitate an expansion of the carbon credit industry. Other commercial foresters and carbon entrepreneurs – who were often the same people – echoed his claim, telling me that improved technology can help in “unlocking the environment through technology” and “unleash” funding into natural capital.

 

… BUT WHO CAN ACCESS IT?

I’m chatting to Matthew, the ‘carbon and biodiversity accountant’ for a small estate in the Central Highlands, which has been using ‘Tier 3’ carbon measurement techniques. I ask him about a report published recently, in which every private company undertaking ‘Tier 3’ measurement of carbon (and biodiversity) found more of what they were looking for (such as carbon sequestration or biodiversity). I ask, “it seems that by using ‘deeper’ methods, [the forester or landowner] always find more of whatever it is they are looking for. Is that problematic?”

Matthew chuckles wryly. “I don’t think so. Fundamentally, if they didn’t, they [the companies doing the measurement] wouldn’t have a business model!” Matthew continues,

“The ‘Tier 3’ stuff asks, do I want to spend extra to do this modelling, to prove that extra value. I.e., is it worth doing the [Tier 3] measurement, because I am going to get 40% more income from my carbon later down the line. That’s fundamental to the business model to those companies: can you measure stuff more accurately and therefore identify more volume and therefore identify more income.”

Matthew’s comment highlights a tension in improving measurement technologies. In a sense, ‘Tier 3’ modelling attends closer to the material reality of a forest, and the complicated growth patterns in which it develops. For example, unlike the WCC, drones and lasers do not only measure tree trunks but also twigs and limbs, and the scrubby undergrowth that could not easily be integrated into an Excel spreadsheet. ‘Tier 3’ measurement techniques can also measure forests that are not growing in linear rows, which the WCC struggles to do.

Yet in the Highlands, where the digitisation of forests is determined by and constrained by access to finance, measuring ecosystems is not economically or politically disinterested. The digital measurement technologies that are developed by private companies are specifically designed to find more carbon or biodiversity and therefore increase the amount of natural capital that a landowner or forester can claim. Crucially though, as many interviewees told me, there is no limit on the types of landscapes where these technologies can be employed. These measurement technologies are not solely bounded to measuring rewilded or regenerating woodlands or peatbogs – they can also ‘find’ more carbon or biodiversity in a wide-range of ecosystems, including landscapes commonly assumed to be degraded, such as monocrop Sitka spruce plantations or overgrazed farmland. As such, these measurement technologies facilitate the expansion and profitability of offsetting logics, as more nonhumans within a wide range of ecosystems are rendered knowable and therefore made value-able (Mackenzie, 2009). Borrowing the term from Morgan Robertson (2006, p. 367), through these technologies, there is more “nature that capital can see.” Yet these technologies do not necessarily further ecological restoration or social justice agendas.

Moreover, in the Highlands, the ‘Tier 3’ measurement of forests is expensive, and currently, exclusive. As Matthew says, “We don’t want lots of estates spending 100,000 grand a year on monitoring stuff.” Access to ‘Tier 3’ tools and technologies is reserved for organisations and individuals with large financial backing, such as private companies, rather than community-owned forestry organisations or cash-poor conservation groups. The measurement tools and technologies which rewilders and conservationists speculate will facilitate a science-led transition towards ecosystem restoration might exist but are not necessarily available to them.

 

CONCLUSION

The production and adoption of new ecosystem measurement tools and technologies is largely presented by their developers, such as carbon entrepreneurs and environmental consultancies, as value-neutral, helping to “create solutions” to climate change and biodiversity loss. ‘Big Data’ helps to inform and scale-up ‘nature-based solutions’. However, in the Highlands, more accuracy in measuring ecosystems is largely being developed to find more value. Whilst rewilders and conservationists speculate that new digital technologies will encourage investment into nature restoration, currently, improved technologies accommodate for landowners with liquid capital to produce more value from their privately-owned natural assets.

Clearly, then, the digitisation of ecosystems is not necessarily and unquestionably ‘good’, for people and nature writ-large. Environmental data and technologies are always produced within specific socio-political contexts. As we enter the new economic age of ‘net zero’, where natural capital and ecosystem services become the dominant frameworks for sustainable business and conservation NGOs, might ecosystems increasingly be seen by how they are quantified and measured? Might we be seeing a shift, from seeing that nature-has-carbon, to seeing nature-as-carbon? And if so, what other elements of an ecosystem might be overlooked as carbon measurement technologies improve?

 

REFERENCES

Büscher, B., & Fletcher, R. (2020). The conservation revolution: Radical ideas for saving nature beyond the Anthropocene. Verso.

Gabrys, J. (2021). Programming Nature as Infrastructure: In the Smart Forest City. Digital Ecologies Conference.

Huff, A., & Brock, A. (2017). Intervention – “Accumulation by Restoration: Degradation Neutrality and the Faustian Bargain of Conservation Finance.” Antipode. https://doi.org/10.1111/ANTI.12335

Mackenzie, D. (2009). Making things the same: Gases, emission rights and the politics of carbon markets [Article]. Accounting, Organizations and Society, 34(3), 440–455. https://doi.org/10.1016/j.aos.2008.02.004

Nost, E., & Goldstein, J. E. (2022). A political ecology of data. Environment and Planning E: Nature and Space, 5(1), 3–17. https://doi.org/10.1177/25148486211043503

Robertson, M. M. (2006). The nature that capital can see: Science, state, and market in the commodification of ecosystem services. Environment and Planning D: Society and Space, 24(3), 367–387. https://doi.org/10.1068/d3304

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Seddon, N., Turner, B., Berry, P., Chausson, A., & Girardin, C. A. J. (2019). Grounding nature-based climate solutions in sound biodiversity science. Nature Climate Change, 9, 84–87. https://doi.org/10.1038/s41558-019-0405-0

Taffel, S. (2019). Digital Media Ecologies: Entanglements of Content, Code and Hardware. Bloomsbury.

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