Key points of convergence amongst Day 1 groups: 

  1. Hybrid approaches (e.g., activity-based and modeling) that are optimally cost-effective and accurate.
    1. Hybrid approaches should also help reduce uncertainty.
    2. Low- and middle-income countries are far behind on data, models, and measurement capacity and present more challenges related to smallholdings, farmer-based monitoring etc.

  2. For the finance community, the level of uncertainty is not always as important as identifying what the uncertainties are.  Methods should be good enough to provide evidence that greenwashing is not occurring. Precision can be improved over time.

  3. Using land use activity data as a proxy for SOC should help reduce cost (the major barrier). Improve how to put together robust data on land use history to define what is eligible for SOC stock measurements. 
  4. Observing co-benefits in tandem with soil C increases the value of the C credit. 
  5. As relationships improve with the farmers in certain projects, the synergy in data collection improves. 
    1. Must engage farmers across scales. 
    2. Companies can help engage farmers by encouraging them to collect data and, in turn, begin to promote behavior changes. However, data collection by farmers can impose an additional cost and be inaccurate. 


Requirements of the finance community

How to design MRV:

  1. Finance community wants to make payments based on results. 
  2. Receive payments upfront to support baseline measurements. 
  3. Identify uncertainties. 


How to deal with risk: 

  1. Managing risk of impermanence:
    1. Discounted carbon credits to account for impermanence and accuracy risks. 
    2. Accounting performed at the landscape scale to spread risk over large areas. 
  2. Reducing uncertainty: 
    1. Direct measurements (e.g., soil sampling). 
    2. Model outputs. 
    3. More measurements at deeper depths (> 30 cm). 
  3. Reducing cost of data collection:
    1. Hybrid approach: complement direct measurements with modeling/remote sensing. Detect the optimal measurement strategy based on region and resources available. 
    2. Detect C stock changes by measuring bulk density, in addition to SOC.