Pipa Elias, Director of Agriculture, North America at The Nature Conservancy, comes on the show to tell us about the progress with OpTIS, The Operational Tillage Information System, and how this intersection of data science and agtech could affect agriculture and food systems in the United States.
Full Transcript
Ross Kenyon: Hello and welcome to Carbon Removal Newsroom. I’m Ross Kenyon. I’m the lead strategist with the Nori Carbon Removal Marketplace. Today I have with me Pipa Elias, Director of Agriculture for North America for The Nature Conservancy, saw an article that Pipa wrote called Optus, New Data Drives Conservation Solutions, and wanted to talk about what is happening in the world of remote sensing, ag tech, data science, all those good things, topics that we care a lot about at Nori. So thank you, Pipa, for being here.
Pipa Elias: Yeah, it’s great to be here with you today, Ross.
Ross Kenyon: Yes, I’m happy we were able to make it work. So I was wondering if you could tell our audience a bit about Optus and what is happening now in this space.
Pipa Elias: Sure. So OPTIS stands for Operational Tillage Information System, although it does a lot more than just that. And essentially, it uses remote sensing to look at the adoption of practices that improve soil health and in turn sequester carbon in the soil. So it’s run by a company that we worked with on this project, Dagan from New Hampshire. And we also did this project with some partners at CTIC, which is the Conservation Technology Information Center. And the idea behind this was to have some consistent and annual measurements of adoption of soil health practices.
In the past, CTIC actually worked through a government grant to Literally drive down country roads and use that as a way to do transect surveys of different conservation tillage practices that were happening. But around 2004, they stopped being able to do that. So we wanted to fill the data gap and look back starting from 2005 to today, how those practices have been adopted. So Optus allows us to look at adoption of conservation tillage, so different kinds of reducing tilling. And at the adoption of cover crops, looking at what was planted late in the season and then after harvest and persisted through the winter and then into the spring.
And then for this project, we also used USDA information to look at different crop rotation. So we put those three together. Those are three of the fundamental elements to building soil health and building soil carbon. So what we did in this project was map that from 2005 to 2018 for the Corn Belt, because that’s where we were really interested in filling that data gap.
Ross Kenyon: Interesting. What existed prior to Optus? Were people using some alternative system that wasn’t nearly as good or as integrated? What is this a leg up on?
Pipa Elias: Yeah, that’s a great question. And we really see it as complementary to other approaches. So in the past, there were, yeah, those kind of people driving country roads in the spring to see how people were tilling. And some people still do that in some states. There’s also a lot of surveys that USDA and others administer asking farmers to report on what their conservation practices are. And in a way, remote sensing can really be coupled with that. Remote sensing can’t get into why someone is doing something in terms of maybe planting cover crops.
Remote sensing can’t tell us about So someone tried planting cover crops, but it didn’t work. We cannot look at that. What remote sensing can do is provide consistency, provide annual data, and do it at an exponentially lower rate. And one of the things that we were excited about, Thank you so much. And so we can really couple this with that survey information, with other information people are finding on the ground, and have, when we put it all together, a really holistic and robust data set on practice adoption. And then on the outcomes related to that practice adoption.
So we’re going to take the OPTIS information, we’re going to model it and be able to see, for example, the sequestered carbon because of adoption of those practices compared to what it would be like if we didn’t see that practice adoption on the ground.
Ross Kenyon: That’s exciting. There’s so much there. Well, great. I know that there’s a number of more proprietary services that exist for farmers to collect their data, analyze it. Some of it uses satellite and remote imagery. Some of it does not. How does Optus interact with those other systems? Are they complementary to these proprietary data systems for farming? Is this supposed to be a replacement? Where does it fit into the tech stack of farmers?
Pipa Elias: Super interesting. And I think you started to get there about how complimentary this is. So the Optus data that are now available on CTIC’s website are part of the public domain. And in doing so, we did not provide any data at the field scale, at the farm scale, or even at the county scale. So the data that are up are at the watershed scale and at the crop reporting district scale. And that was largely to protect farmer privacy, which is really important. And really, when we think about the purpose of the data set that we created with Optus, it was really, again, to connect large-scale adoption of these practices with the environmental benefits that So to us, that’s really the purpose of Optus.
On the other hand, there are those proprietary solutions that, to be honest, are much higher tech. Optus uses publicly available remote sensing data, so there’s limitations to that. It’s largely 30 by 30 meter resolution. The proprietary sources can provide that kind of farmer decision making, you know, down to the field, down to even finer resolution than that. So they do provide kind of different services. We would not expect any kind of farmer decisions. Decision-making to be done using Optus. On the contrary, it’s more for that broader kind of conversation that’s happening, say, at the supply chain level as companies are looking at maybe the footprint of a mill shed or for the government to look at, you know, how is practice adoption ultimately going to lead to improvements in water quality in the Gulf of Mexico?
Because we know that takes time for that water quality to actually improve.
Unknown speaker: Interesting.
Ross Kenyon: I want to make sure that I understand this fully. So you’re able to get data at the field level, but it’s somehow anonymized into county or watershed level statistics. Is that correct?
Pipa Elias: Exactly. And not even county scale, although the technology could do that. So that’s exactly right, Ross. What the remote sensing gives is 30 by 30 meter pixels of information. And then And what Dagan did was scale that all up and just provide the data at a much higher scale, at a much coarser resolution, so that it wasn’t really looking at what any individual grower is doing. It could be used in that way, but that was really not what we built this current project to do.
Ross Kenyon: To what degree do you think problems like eutrophication and fertilizer runoff, water quality issues is the result of not having adequate data or the right platform to interact with this data? Do you think that’s been something that’s stopped action on some of these problems?
Pipa Elias: I think it depends whose action we’re talking about. So at the farmer level, I don’t think so. I think there are other reasons why there’s a lot of risk or uncertainty around adoption of practices at that scale. However, one of the reasons we did invest in this project was because a lot of the incentives that can help farmers overcome the costs and the risks of adoption of practices, there was a feeling that there wasn’t enough information. For example, we look at a lot of the companies that are putting money into this kind of practice adoption right now, and they felt like they weren’t really seeing enough change, right?
The water quality was still an issue. In part, that’s because maybe there wasn’t enough practice adoption. In part, it’s also because it takes a long time for water quality to improve even when practices are improving. So we wanted kind of that in between to say, look, there has been this significant uptick in adoption of cover crops. It is going to take some time to see those benefits in water quality. But we still have confidence that these investments from the supply chain, From cost share from government are actually helping. So that was really important to us.
Also, the Nature Conservancy had put out a goal of seeing 50% adoption of soil health practices by 2025. And we put the goal out there and then knew we need to be able to measure that. So this is one of the tools we’re going to use to measure our goal. I think it’s a little harder on nutrient management. So one of the limitations of Optus is that it cannot look at increased adoption of, say, better fertilizer efficiency. So that’s definitely a gap we recognize and know that we need to fill because that’s another key tool to improving water quality.
Ross Kenyon: Okay, yes, that’s very useful context. So my understanding, and feel free to correct me if I’m naive or uninformed here, but I know that groups like the NRCS and the USDA to some extent and extension agents have a fair So you’re asking there kind of how the Optus data can help them inform their selection of incentives and participants? Yes, I’m trying to pin down exactly where the locus of agency may take place with inside of a system where people are using Optus.
Pipa Elias: Yeah, so I think we envision a few different ways of kind of using Optus for decision making at the broadest scale. Although one of the reasons we put it out publicly is because that will probably create a lot of innovation and additional ideas that we haven’t come up with. But one of the additional pieces of work that we’re going to do is looking at spatialization. Can you look at a crop reporting district in northern Iowa and figure out why it might be different levels of adoption than in southern Iowa, for example?
And there’s obviously a lot to that question and a lot that cannot be mapped. But we also want to see if there are any trends that are mappable. So is there a higher rate of adoption of cover crops in warmer places, in places that receive more spring rain or less spring rain, in places that have certain soil types? And using that, I think we can really discern a lot more about drivers of adoption. And then we’ll also be able to see, are there places where we really need to invest more, where we could point different programs to, to say, here’s an area where adoption seems to be lower than what it should be.
So what’s happening? So that’s one of the things that we would like to do with the data. But again, we’re also really excited to see how other people take it and run with it and figure out what it means to help increase adoption of these practices across the country.
Ross Kenyon: Great. That answers my question. And I also appreciate that approach. Well, anyone listening to this show or reversing climate change knows how much we like that riffing on open tech that’s out there. There’s a lot of fun surprises when you open up like that. At least I hope you experience that. It seems like there’s a lot here. Well, Pipo, what should we expect for the future of, I don’t know, the combination of all these different fields within ag tech, like the amount of data that’s coming through, the ways that people are processing it and using it for both policy and personal economic decisions, making agronomic decisions on the farm level, and carbon sequestration?
I realize that’s a gigantic question, but...
Pipa Elias: Yeah, but I think that’s, you know, the state of play right now is that there’s a lot and it’s exciting. And, you know, to us, it is in part the importance of, you know, where these data can be made public and put out for people to, you know, riff off of and innovate with. We think that’s really important. You know, and I think there’s a lot of opportunity and it’s about helping people just to see what the options are and learning about how that can relate to, say, different incentive mechanisms or different decision making.
To me, it’s less about some people think there’s still a data gap. There’s still so much more that we need to know. I think there are a few of those. We went out with this project intending to fill a time series data gap. I think where the next revolution is going to be is just really in Understanding how to put different data sets together to help answer some questions. So I think that there’s less of an issue when not having the data, but there is a little bit of a challenge ahead of us in making sure that different decision makers, again, from farmers who are thinking about annual management decisions to the government is thinking about where to put investments to markets that want to pay for carbon sequestration, just figuring out how to arrange the data That helps people make decisions that help farmers put in place the practices that they want to do on the ground.
Ross Kenyon: Very exciting. There’s a lot of innovation happening here, and we watch it pretty closely at Nori. And it seems like not very much time goes by before the next milestone is reach on any of these things. So kudos. Also, I should let you know that I feel personally attacked by your proper use of the plural data. I still haven’t figured that one out. I’m a singular dataman.
Pipa Elias: Sorry.
Ross Kenyon: And I’m a nerd, so... I got to just drill that into my brain. I haven’t done that yet. Well, if someone wants to keep up with your work, they want to keep up with Optus, what might be the best way for them to do so?
Pipa Elias: Yes, there’s a number of options. The Optus data, again, are up on CTIC’s website. So I’m sure you can put that in the notes. It’ll be ctic.org slash Optus, O-P-T-I-S. And I’m on Twitter at Pipa Elias. So I tweet about this stuff a lot. I’m really passionate and excited about it.
Ross Kenyon: Get your hot takes there, people. That’s where they exist. Okay. Well, Pipa, thanks so much for being here with us. It was a fun time. We goof around more than normal.
Pipa Elias: I hope the audience will forgive. Well, I appreciate it, Ross. Always a pleasure to talk.
Ross Kenyon: Thank you. If you enjoy the show, please share it with your friends. Please let them know that exciting innovation is happening in agriculture. Carbon removal is an exciting industry with lots going on. Please direct them to the show, rate and review us on iTunes or Apple Podcasts or Stitcher. And thanks so much for listening.
