We chose process-based modeling because it’s grounded in real data, calibrated and validated by soil samples, and accessible. Growers can enlist in a carbon marketplace without expensive sampling or waiting long periods of time to understand soil carbon trends. Through the use of these models, we are able to understand ten year trends of soil carbon accumulation. A longer term view of the soil dynamics helps prevent us from overissuing carbon while ensuring farmers are receiving a fair number of credits.
Essentially, the modeling platform Nori uses collects multiple types of data—such as management data, weather, soil, and plant growth data—and uses crop, soil, and weather models to estimate plant growth, their effects on the ecosystem, and the amount of carbon stored in the soil.
Currently, Nori receives management data from farmers on things like their fertilizer rate and timing, crop cultivars, planting dates and density, and their harvest date. The process-based models Nori uses have already been calibrated and validated by soil samples. As a result, we’re able to trust the model to provide appropriate estimates of soil and plant growth data while simulating estimates of carbon sequestration.
Soil is complex, and not all soil carbon is the same. Soil carbon can be divided into particulate organic matter (i.e. partially decomposed fragments of leaves and roots) and mineral organic matter (i.e. microscopic byproduct of microorganisms that coat soil particles). Particulate and mineral organic matter also have different retention times in the soil. Particulate organic matter is more susceptible to disruption such as tilling, whereas mineral organic matter can last up to 1000 years.
Nori is a farmer forward and science forward company. We don’t ignore the hard science or facts of carbon permanence, because carbon removal is only useful if the carbon that’s removed stays out of the atmosphere. We aim to be the bridge that meets both the science and farmers where they currently stand.
Process-based modeling allows us to straddle that line. Farmers are primarily concerned with improving their soil health and productivity. Instead of asking farmers to sign an unwieldy contract, farmers in our marketplace agree to retain the recovered carbon in soils and root systems for a minimum of ten years.
Nori strives to be upfront and use the best science available in its decision making, and ten-tonne years of carbon storage provides an honest estimate of the carbon retention term.
Some carbon models may predict that implementing certain practices will guarantee soil carbon retention for 100 years. We aren’t comfortable guaranteeing that timeline because without continuous monitoring, reporting, and management; a carbon market cannot truly achieve carbon permanence.
We believe that using process-based models allows us to maintain a fair and equitable marketplace for suppliers while also being firmly rooted in science. Most significantly, process-based models produce high-quality carbon credits. The models we use meet the USDA bluebook standards, keeping us in line with our science forward values.
Soil carbon accumulation is not linear. Soil carbon accumulation can be high in the first few years, before dropping off. Process-based models are flexible, allowing us to build an appropriate ten-year trend line. As a result, we are not over-issuing payments to farmers and then clawing them back each year.
All carbon accounting takes a lot of work and resources. Process-based modeling, however, eliminates the necessity of yearly field by field soil sampling, and doesn’t require farmers to incur an additional cost, or perform an additional task to their routine. Generally speaking, process-based models also have lower verification costs and meet the USDA blue book standard.
Historically, carbon sequestration baseline comparisons are difficult to account for when doing soil sampling. A process-based model allows us to easily determine a baseline without requiring farmers to set aside land. By modeling various outcomes, process-based models mitigate the question of whether to reserve land for comparison tests of soil organic carbon stock change (SOCSC).
We acknowledge that measuring soil carbon is a young science and there is still a lot to learn around the way carbon moves through the soil. For example, the impact of tillage on soil carbon depends on the environment. We’re also aware that some argue that soil sampling depth affects the quality of soil carbon measurements, and soil sampling shallower than 30 cm could skew estimates of no-till’s climate benefits.
Despite this uncertainty, we chose process-based modeling for our carbon market because, unlike other sampling methods, process-based modeling gives us the flexibility to incorporate new science with past data as it becomes apparent and available. Additionally, it allows us to reevaluate carbon estimates with new, additional data without scraping previous work.
Nori strives to be upfront and honest with all of its stakeholders. To that end, we acknowledge that process-based modeling is not a panacea for estimating carbon sequestration and storage. We understand that process-based modeling is arguably too broad and lacks the specificity of more localized soil sampling. However, Nori believes that process-based models can be scientifically sound, directionally correct, and provide farmers the ability to enter the carbon marketplaces.
Farmers use many complex approaches to improving their soil health and retaining carbon, including precision farming and planting certain crop species and blends. We recognize that to reflect the diverse soils across the U.S. accurately, we will need to consistently input data into our process-based model so that it is calibrated and validated accurately.
As both time and monetary funding become increasingly robust, we expect the process-based models we use to improve over time by testing soil at deeper depths and in more locations across the country. It is our sincere hope that carbon markets will drive the necessary research to improve the tools available to us.
Nori intentionally chose process-based modeling for its practicality, accessibility, and accurate trendline projection. (In addition to the reasons we outlined earlier.) Our goal continues to be to serve a broad range of farmers. We know a lot of work is being done to progress other innovative methods including soil sampling and remote sensing. When these methods are robust enough, Nori looks forward to the day we can incorporate these as carbon quantification tools to address an even more diverse range of farmers.