A recently released report from the Yale Applied Science Synthesis Program and the Environmental Defense Fund offers practical ways to generate more high-quality evidence to increase confidence that the effects of soil carbon farming represent real carbon accrual or avoided greenhouse gas emissions.
Soil carbon sequestration through sustainable farming practices could lock up 5 billion metric tons of CO2 equivalent per year until 2050, which is comparable to roughly 10% of annual emissions, according to a recent estimate in Bloomberg NEF. Yet, despite its potential for sequestration, soil carbon farming — which refers to a variety of methods to sequester atmospheric carbon in soil and plants or reduce farm greenhouse gas emissions — currently accounts for a minor proportion of carbon market activity due to a lack of standards, regulation, and scalable measurements. “Agricultural Soil Carbon: A Call for Improved Evidence of Climate Mitigation,” a report recently released by the Yale Applied Science Synthesis Program, a joint initiative of the Yale School of the Environment and the Yale Center for Natural Carbon Capture, and the Environmental Defense Fund, details the need to expand and improve soil Measurement, Monitoring, Reporting and Verification (MMRV) to increase confidence that the effects of carbon farming represent real carbon accrual or avoided emissions.
YSE News recently spoke with two of the report’s co-authors, Mark Bradford, the E.H. Harriman Professor of Soils and Ecosystem Ecology at YSE and YASSP faculty director, and Emily Oldfield ’19 PhD, 11 MESc,'05 BA, Environmental Defense Fund senior scientist and YSE associate research scientist, about why the current approach to testing falls short and the practical ways to generate high-quality evidence that would help to validate GHG outcomes. Bradford and Oldfield say that adapting more systematic approaches to gathering high-quality evidence would help identify and improve agricultural and farming practices with the greatest climate adaptation and mitigation benefits.
Bradford: This is a great question and undergirds the primary motivation for the workshop, class, and ultimately the white paper that came out of those efforts. Our central motivation was to communicate the ‘evidence gap’ that can be filled by adopting MMRV approaches and datasets that approach the higher standards of evidence used in other fields, such as healthcare, before policy or practice decisions are made. While this gap remains unfilled, we argue that it is not possible to rigorously assess the effectiveness of soil carbon farming. We provide ways forward to fill the evidence gap. What we did not stress in the report is that we think the causal approaches we share are significant beyond soil carbon farming, suggesting ways forward to build quantitative evidence that interventions are effective for other purposes, such as for improving soil health, food security, and forest resilience.
Oldfield: I would also add that soil carbon sequestration and its effectiveness as a climate mitigation strategy is somewhat of a contentious topic with a lot of disagreement about the magnitude of mitigation that we can expect from carbon farming efforts. We did not want to wade into this debate but focus on the standards of evidence we think are really necessary to address the impact of these agricultural management interventions.
Bradford: The analogy originated because I was finding it hard to get our points across even to other soil and agricultural scientists. When I’d say that we needed studies that accurately quantify the effects of agricultural practices on change in soil carbon stocks, folks would tell me that we already had a lot of long-term experimental field trials to show that effect. But those trials are typically done on small plots. When I started likening those small plots to mice and said that to know if a human vaccine was effective you want to also test it on people to get definitive data, people grasped that a person was equivalent to a farmer’s field, and the human population under study equivalent to all the farm fields being managed for specific crops in a region. It seems obvious, but there is wide appreciation in our science that small experimental plots are managed in a way that is very different to how a farmer manages a commercial field. Once folks connected mice with small plots, they readily grasped that to quantify the effects of climate smart practices, we need to measure at the scale at which farmers work, just as we need to measure vaccine effectiveness at the scales at which they are delivered.
Oldfield: I would say a primary concern around soil carbon sequestration as a climate mitigation strategy is that it is not permanent, so getting back to the fact that soil carbon cycles continuously and any carbon gained could be lost for any number of reasons related to management decisions, uncontrollable climate related events, and land use change impacts. The MMRV framework in the paper does not necessarily solve this problem, but it can help ground our expectations around what is possible in terms of magnitude of expected soil carbon accrual, timeframes over which we can expect to see any gains and how practices like no and reduced tillage and cover cropping play out on working farms.
What we’re doing is translating their thinking to tackle questions in agriculture, forestry, and ecosystems, and, by doing so, we’re coming back to those deep-rooted beliefs and finding the basis for them to be wanting.”
Bradford: Everything always links to finance at some level but, in this instance, I’d say that deep-rooted beliefs in soil carbon science are the impediment. Just like nearly everyone else in this scientific field, I’ve been trained to believe that it is not feasible to quantify change in soil carbon stocks, attributable to management practices, because the carbon stocks are too large, too variable, and change too slowly. I’ve written and spoken that justification numerous times. This is where there is a huge advantage to working in a multi-disciplinary school: Many of my colleagues, particularly in the quantitative social and health sciences, face similar challenges to quantification. What we’re doing is translating their thinking to tackle questions in agriculture, forestry, and ecosystems, and, by doing so, we’re coming back to those deep-rooted beliefs and finding the basis for them to be wanting.
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Bradford: Although I just spoke about deep-rooted beliefs, it is fair to say that work at the scale we are proposing will take cooperative approaches. Not surprisingly, multiple federal, academic, and corporate attendees at the workshop we ran in October highlighted this need for cooperation and Emily has been working on thinking about how to realize such cooperation. But instead of looking forward, I first encountered calls for this approach by diving back into the history of agricultural and statistical sciences. I spent time in the Guinness Archive in Dublin looking at the large-scale science they co-funded and led across the 1900s to 1930s. Through cooperative work, for example at the scale of the barley growing region of Ireland, they conducted studies that more than paid for themselves by returning improved earnings to them, farmers, suppliers and the government. Much of the science we are calling for now arose from the close link between agricultural experimentation and what became modern applied statistics that was prevalent at the start of the last century. For whatever reasons, that link disintegrated in the post-WWII era, and we see a lot of value of reconnecting to that work.
Oldfield: As Mark mentioned, my team at EDF has been thinking for a while about how to implement and accelerate this kind of cooperative approach. Given the diverse array of agricultural production systems and growing conditions, much of our thinking rests on taking a regional approach to this cooperation and engaging various stakeholders along the way. Efforts involving food companies, academic researchers, ag-tech start-ups, federal agencies, local ag extension, and other NGOs are underway, and we hope this white paper provides important guidance and a path forward on research design and data collection to help spur these efforts along!
