A great article about Regenerative Ag


A major reason the RFC is doing what it’s doing is to address skepticism around certain practices, and to provide sufficient data to clearly say what is working as what isn’t.

As we often get stuck in our little bubbles, I want to share an article I find thoughtful while also somewhat contrary to some of BFA’s work –

If the goal is to understand why ideas don’t scale, there are some clear roadblocks that he’s identifying here which are probably preventing regenerative ag from scaling. In most cases, it’s a lack of data - a place that we can clearly provide useful insights. I think it would be wise to invite someone like this (inclined to skepticism but clearly thoughtful and smart) to take part in the RFC discussions and process! @david.n.forster @DanT @BHck what do you think? Reading the discussion at the bottom is also quite good.


A unique scale experiment carried out at the MSU KBS farm (involving 27 fields over 6 years, compared to plot scale experimentation testing the same crop management systems) provided insights into why biological based, regenerative ag is difficult to scale. The high level of weed control that is possible through intensive management on experimental plots (and through eyes to the acre and lots of tillage and care on small scale farms), it is often not achievable on larger fields without chemical inputs. Biology can support nutrient cycling, at least to support 80-90% of crop yield potential (and does the world really need the highest yields everywhere given the inefficiencies elsewhere in the system, low conversion of crop grain when fed to animals and waste in the system, low yields in developing countries,etc), but weed control is a more complex and challenging issue, one that may require complex rotations (which are rarely profitable in the current economic set up). Check out attached: Kravchenko, A. S.S. Snapp, G.P. Robertson. 2017. Field-scale experiments reveal persistent yield gaps in low input and organic cropping systems. PNAS doi:10.1073/pnas.1612311114


Super useful reference… a good reason why we should be trying to collect real world data from fields, rather than intensive plot-level work. Also a cautionary tale. Here’s the working link to that paper also - https://par.nsf.gov/servlets/purl/10039402.


thanks for adding the link - I agree that this is part of the compelling evidence why we need farm observatory networks (tip of the hat to Dorn and colleagues), citizen science monitoring via Aps like LandPKS, and panel survey data (check out the description of the last on our Africa ag learning lab website http://globalchangescience.org/eastafricanode)