Climate Conversations S1E11: Climate, Food Security and Water: Interdisciplinary Insights

[00:00:00:09] RAJESH KASTURIRANGAN: From MIT'S Office of Digital Learning, this is Climate Conversations by ClimateX.

[00:00:06:07] ERWAN MONIER: And I want to make it clear when I talk about uncertainty. Because this is a term that I think is sometimes misunderstood. I don't mean uncertainty in the sense that we're not certain that climate change is taking place and that climate change will continue to take place. But how much, to what magnitude, and exactly what region will be most affected?

[00:00:29:21] RAJESH KASTURIRANGAN: Welcome to Climate Conversations. I'm Rajesh Kasturirangan here in Cambridge. And with me--

[00:00:35:25] LAURA HOWELLS: Hi, Rajesh. I'm Laura here from ClimateX.

[00:00:38:08] DAVE DAMM-LUHR: Hey, Rajesh. Dave Damm-Luhr, ClimateX.

[00:00:40:25] LAURA HOWELLS: How are we, everybody?

[00:00:42:02] RAJESH KASTURIRANGAN: Climate modeling. It seems to be the MIT thing to integrate as many different variables, and then work some magic.

[00:00:52:02] LAURA HOWELLS: Play around with some big data.

[00:00:53:21] RAJESH KASTURIRANGAN: Exactly.

[00:00:54:16] DAVE DAMM-LUHR: Right. Put it all together in one coherent, comprehensive framework.

[00:00:58:21] RAJESH KASTURIRANGAN: And today, we are going to interview Elodie and Erwan, who, put together, are bringing data and climate modeling and impacts on food systems in the southwestern United States, among other places.

[00:01:13:00] DAVE DAMM-LUHR: One of the things that I found really exciting about their work is that they're putting together the economic development side with the climate, Earth systems side. That's really very helpful to move forward.

[00:01:27:06] RAJESH KASTURIRANGAN: Well, let's take a listen and see what happens. So welcome to Climate Conversations. I'm Rajesh Kasturirangan, and I'm here in the studio with my partner in crime--

[00:01:39:11] DAVE DAMM-LUHR: Dave Damm-Luhr. Welcome, everybody.

[00:01:41:25] RAJESH KASTURIRANGAN: We have two wonderful guests in our studio today. We have Elodie Blanc.

[00:01:48:08] ELODIE BLANC: Hello.

[00:01:49:18] RAJESH KASTURIRANGAN: And Erwan Monier.

[00:01:51:26] ERWAN MONIER: Good morning.

[00:01:53:08] RAJESH KASTURIRANGAN: Thank you so much for joining us. You guys have done some fantastic work and we want to ask you lots of questions about it.

[00:02:02:03] ERWAN MONIER: Well, I'm going to say, first, thank you for reading our work. This comes as a very nice surprise. And thank you for inviting us. This is great.

[00:02:12:28] DAVE DAMM-LUHR: We're glad you're here.

[00:02:14:15] RAJESH KASTURIRANGAN: So Elodie--

[00:02:16:13] ELODIE BLANC: Yes.

[00:02:17:06] RAJESH KASTURIRANGAN: You've been here at MIT for a while. Right? Tell us how you got here.

[00:02:24:10] ELODIE BLANC: I was doing my PhD in New Zealand and I got the opportunity to work at the Joint Program. I first came as a visiting student when I was still doing my PhD, and then I got the opportunity to stay as a postdoc, and then as a research scientist.

[00:02:38:05] DAVE DAMM-LUHR: And how about you, Erwan? How did you arrive in Cambridge, Massachusetts?

[00:02:43:05] ERWAN MONIER: So originally, I'm from France. I came to the US for a PhD 14 years ago. So I did my PhD in UC Davis. And I started looking for a postdoc position, trying to stay in the US. And I had this amazing opportunity to come to the Joint Program. I was very excited because of the type of work that's being done, very multidisciplinary, a unique program. And I jumped on the opportunity and I haven't left since.

[00:03:14:01] DAVE DAMM-LUHR: Right. So what was your original discipline? UC Davis is famous for agricultural studies and that sort of thing.

[00:03:20:13] ERWAN MONIER: It is famous for agricultural study. I was actually focusing on atmospheric science.

[00:03:25:02] DAVE DAMM-LUHR: Oh, I see.

[00:03:25:23] ERWAN MONIER: And I did, actually, a lot of work which I felt was very theoretic and not very useful, in a way, to look at the major issue of climate change. And so being able to reposition myself and focusing on climate change, climate modeling, was really what excited me a lot about coming to MIT.

[00:03:47:10] RAJESH KASTURIRANGAN: Fantastic. You know, we interviewed John Reilly not too many weeks ago, and it's wonderful to have more people from the Joint Program come visit us. What do you guys actually do?

[00:04:00:02] ELODIE BLANC: So I actually work on all the topics of water and crops. So modeling water allocation in the US and competition for water resources. And also the impact of climate change on crops. And this aspect of the work uses, generally, more statistical methods to look at different impacts. For example, typhoons, biodiversity, or many different aspects that could impact crop productivity.

[00:04:30:09] RAJESH KASTURIRANGAN: What about are, Erwan?

[00:04:32:25] ERWAN MONIER: So I'm a climate modeler. I would say that's really my main hat. But I'm also involved in a lot of climate impact assessments, so understanding how climate change will impact various ecosystems, or various sectors of the economy. And so we do that by linking climate models that provide us projections of how temperature and precipitation will change in various regions of the world with models that are going to focus on, for example, you know, crop or crop productivity or agriculture or water resources.

[00:05:09:09] And so that's why I'm teaming up with Elodie, who is really an expert on agriculture and water resources, and I'm bringing up the expertise in the climate modeling. So how would you design a study to understand how climate change, and the large uncertainty there is in future projection of climate change, can impact those sectors. And I want to make it clear when I talk about uncertainty, because this is a term that I think is sometimes misunderstood. I don't mean uncertainty in the sense that we're not certain that climate change is taking place, and that climate change will continue to take place. But how much?

[00:05:51:03] We're uncertain about how much, to what magnitude, and exactly what regions will be most affected. So we try to really take that into account. The fact that we don't always know. We don't have perfect foresight. Our models are not perfect.

[00:06:05:23] And so we need to understand, where do we have, really, confidence in our projections and where do we lack that confidence? And so we have various methods to deal with that. I don't know if you want to get technical there.

[00:06:19:10] DAVE DAMM-LUHR: Well, our colleague Kurt Newton, when interviewing John Reilly, said, in his view, models were our crystal ball. Because we really can't know, as you're saying, we just simply can't put our fingers on all the variables. We can't specify them. We can't get perfect data. So there's a little bit of guesswork. But it's better than just putting your fingers up to the wind and see which way it's blowing.

[00:06:43:23] ERWAN MONIER: Well, yes. I mean, if we didn't have models, I think we would be clueless. We would not be able to really make any projections, make any decisions, or be prepared. At the same time, it's true that our models are not perfect. We cannot just run the model once and be completely sure that what we're getting out of the model is going to be useful. And so that's why we run a lot of simulations.

[00:07:07:18] So for example, as a society, will we take climate change seriously, and are we going to have strategies to limit emissions of greenhouse gases? Or will we just let those emissions go as they have been in the last 30, 40, 50 years? Will there be technologies, breakthrough in technologies that will allow us to reduce emissions of greenhouse gases without having that much effort, without needing international coordination? We don't really know that.

[00:07:40:11] So that's why we'll usually run scenarios. A scenario where we assume that the world is going on a very dangerous path with a lot of emissions, and another scenario where we're really assuming that there will be collaboration, coordination efforts around the world, and we'll be able to limit emissions of greenhouse gases.

[00:07:57:20] DAVE DAMM-LUHR: So how do you pick the-- how do you develop or design those scenarios?

[00:08:01:16] ERWAN MONIER: So there is a lot of scenarios that already exist. So we can use scenarios that have been designed internationally under the umbrella of the IPCC. So that's the well-known UN effort to investigate climate change. We can develop our own, depending on whether we believe that those scenarios are still relevant. I mean, most of those scenarios were developed a long time ago.

[00:08:25:17] And as things happen, like the Paris Agreement, we have the capability at the Joint Program to develop our own scenarios. And so those are scenarios that take into account changes in population, changes in the economy, and what that means for emissions of greenhouse gases and the management of the land system, like land use change, and so forth.

[00:08:48:05] DAVE DAMM-LUHR: So climate modeler, crop modeler, how do you trade models with each other? You know, these are modeling quite different things.

[00:08:58:09] ELODIE BLANC: So we don't trade models, we just integrate them. So Erwan's climate model output, I'll input into my water model, for example.

[00:09:07:15] DAVE DAMM-LUHR: Oh, so when you were talking about an integrated approach, that's really what it means. You're not smushing together the two atmospheric science and economic development models, but you're joining them in some meaningful way. Like you were saying, output of one is an input to the other. Is that right?

[00:09:23:14] ELODIE BLANC: Yeah. So our integrated framework, for the moment, yeah, assembles all these different models representing the earth and human system. And making them interact with each other.

[00:09:34:00] DAVE DAMM-LUHR: That sounds really innovative to me. Is anybody else doing that, or are you all the first on the block?

[00:09:39:26] ERWAN MONIER: Well, so the Joint Program has been around for, I believe, 20-- now, probably, 26 years-- so it is one of the first groups around the world to really take that integrative approach. There is now a lot of newer groups that are seeing the value in having multi-disciplinary approach with natural scientists and social scientists trying to understand how different systems-- the Earth system and the human system-- interact.

[00:10:08:09] But I would argue that is still, surprisingly, not the majority of the research that is done around climate change. You don't have that systematic approach of, we need to have people who understand how humans behave. We need to have people who understand how the earths behave-- the climate, the land, different ecosystems. That's not necessarily what you see. But I think there's a realization that this is where we need to move toward.

[00:10:35:16] RAJESH KASTURIRANGAN: Elodie, as someone who is, in a way, a consumer of climate modeling, are there other things besides climate models that you incorporate into your work that are outside your own core specialty?

[00:10:48:10] ELODIE BLANC: So for example, for the water model that we use in the study, we also use input from a land use model, CLM, Community Land Model. We also use output from economic models. So that comes from another model developed by other researchers in our department.

[00:11:06:27] RAJESH KASTURIRANGAN: So you were mentioning the uncertainties associated with modeling, which I think, is true of every kind of model. But when you have different types of models that are all being integrated, you're multiplying uncertainties.

[00:11:23:00] ELODIE BLANC: Yeah.

[00:11:23:19] RAJESH KASTURIRANGAN: Right? So how do you correct for that?

[00:11:26:10] ERWAN MONIER: Now, this is a major issue that we face. There is issues where, as information is passed along from one model to another, one component to another, you have uncertainty that is propagating throughout the system. You have new uncertainties that arise as you add new components.

[00:11:45:19] So we have various methods. We have methods where we know that, in different models, we have particular parameters or numbers that we know are not certain. And so what we'll do is we'll look at those particular numbers or parameters and we'll vary them, and we'll run very large ensembles. Very large ensemble simulations, so that means hundreds of simulations, where the only thing we change is going to be that parameter. Because we know that it's an important parameter and we know that it will have impacts throughout the entire modeling system.

[00:12:24:09] So that's why a lot of the work that we do is designing those large ensembles, understanding where are the key uncertainties, what we don't know, what we know more. And this is quite complex. And I'm not saying that we have it figured out, as there's more and more data available, as there is more computational power, we have those very large clusters-- computer clusters.

[00:12:51:15] We end up having this big issue of just running and running and running simulations, and trying to make sense of exactly what we're doing. So we can combine these issues with machine learning techniques, which is something that now is becoming a lot more important, really, to design models that are able to make sense of all this data in a very systematic way. And so that's really where we're moving toward.

[00:13:20:07] RAJESH KASTURIRANGAN: I mean, and of course, every probabilistic scenario has this problem. Right? That if there are independent events whose uncertainties you're adding, then at some point, it's not good. And again, I also want to reemphasize what you mentioned. This is not uncertainty about the existence of climate change.

[00:13:42:15] It's uncertainty about the specific trajectories it might take, which really brings me to my next question. So I want to move up a little bit and ask a more general question. Are we going in the direction of greater collaboration? And if we are not, what might be coming our way?

[00:14:03:16] ERWAN MONIER: So I think we are going toward more integrated and collaborative research. I mean, you can see that in various aspects. You can see that also in the way funding goes now. I mean, I'm still a fairly junior researcher, so I cannot tell you how it used to be 40 years ago. But I remember, at least, when I was a grad student, when you were applying for funding-- when my advisor was applying to funding, it was for a very specific project for one person.

[00:14:30:00] Now, it's very difficult to actually get funding for a very narrow problem where you don't bring in multiple researchers, multiple institutes. So I think that already shows that there is, at least from a strategic point of view of how research is funded, this realization that we need to have collaborative research that includes multiple disciplines. Now, does that translate in how we do research?

[00:14:59:20] We are, for example-- we're not a department at MIT. We're a Joint Program. We're an independent center. And that's, to me, the evidence of-- there is a lack of understanding that maybe the structure of universities may have to change. You cannot just have a Department of Economics, a Department of Atmospheric Science.

[00:15:21:08] We also need to have ways to collaborate and to understand that this is not just one discipline at a time. There's also this integrated vision of how research should be done. And as far as I know, you don't have those types of departments in most universities, departments that really integrate all sorts of disciplines and expertise.

[00:15:43:25] DAVE DAMM-LUHR: They're all kind of working in parallel.

[00:15:45:19] ERWAN MONIER: They're working in parallel, and usually, they'll be some sort of initiative that will bridge around those departments.

[00:15:50:28] DAVE DAMM-LUHR: For a time.

[00:15:51:26] ERWAN MONIER: For a time. And it may or may not be very successful. I mean, that's unclear.

[00:15:56:17] DAVE DAMM-LUHR: I wanted to shift a little bit to the specific study that caught our eye when we were scanning the MIT news a few weeks back. And that is the study that you did-- water shortages and irrigated crops, that sort of thing. So I'm thinking that's a particular instance where you were trying to bring disciplines together.

[00:16:17:22] You combined the atmospheric science and the economic science, economic development folks, and you were really looking at a particular case that illustrated the larger point that speaks, I think, to what Rajesh is talking about. Can you tell the listeners a little bit about the study?

[00:16:35:08] ELODIE BLANC: About the study? Yeah. So we wanted to know if irrigation, as a way of ensuring food security, if it's actually a sustainable strategy in the future, especially in the context of climate change. Because yields are much higher for crops that are irrigated because they are not affected by the lack of water.

[00:16:54:07] But if you don't have the water available in the place where you are currently irrigated, then we wanted to study where these regions are, where would there be hotspots of water stress, and where, for the most commonly grown plants in the US. So we wanted to integrate all the aspects of the human system and the earth system. So looking at economic activity, how it will impact demand for water, in terms of industry for industrial activity, for economic activity for cities, for all the different users of water on top of agriculture.

[00:17:26:18] And this economic activity will have consequences, in terms of emissions, CO2 emissions, and greenhouse gases. And how that will affect climate and how this climate will affect water resources, in terms of how much precipitation there will be, how much runoff that we'll induce, and then, how much water will be available for these different sectors, specifically for irrigation.

[00:17:49:21] RAJESH KASTURIRANGAN: So Erwan, how did you bring your climate modeling into this exercise?

[00:17:56:18] ERWAN MONIER: Yeah, so as Elodie mentioned, this is a fairly complex study with a lot of elements. So what we did is we brought together economic models, models of the world economy, a model of the US economy that's a lot more disaggregated, a climate model, a model that allows us to look at how much water will crop need in the future as climate changes. A water model that allows us to represent that competition from the different sectors.

[00:18:30:01] So the way it works is, at the beginning, I mentioned scenarios. So we design scenarios. Scenarios of how will the world economy change in the future, and what are going to be the climate mitigation efforts? So we had three scenarios.

[00:18:46:27] One scenario where I assume there's really no efforts whatsoever to curb emissions of greenhouse gases. And then two scenarios that are really a lot of mitigation at different levels. One mitigation with the aim to limit the increase in temperature to two degrees, which is sort of the aspirational goal of the Paris Agreement. And another one that's more intermediate between the two of those.

[00:19:09:03] And so once we're able to model under those scenarios how the world economy is going to develop and how emissions of greenhouse gases will move forward, we can bring those emissions into our climate model, and that allows us to determine what will be the impact for temperature and precipitation and other key variables over the entire world, but also for that particular study, focusing on the US.

[00:19:33:25] DAVE DAMM-LUHR: So why would decision makers, politicians, care about your results?

[00:19:37:18] ERWAN MONIER: I would hope that they'll care because they'll realize that if we just work as nothing is happening, and we don't prepare for the impact of climate change, we'll end up being in a very difficult situation. And in particular, there'll be basins in the US where specific crops will not be able to grow well. And that will affect the livelihood of farmers in those particular basins. And that's usually what we found in our study in the southwest of the US.

[00:20:10:22] RAJESH KASTURIRANGAN: So can you give us an example of a specific location and a specific crop that's going to suffer?

[00:20:17:21] ELODIE BLANC: So for example, if you're a farmer in the Gila Basin in Arizona, then your cotton will only produce about 10% of the yield that it could produce if it was fully irrigated.

[00:20:29:06] RAJESH KASTURIRANGAN: So how soon is this going to happen? When will the D-day come for the Arizona farmer?

[00:20:38:06] ELODIE BLANC: So in our study, there is already some water stress at the moment, but our study goes to 2050.

[00:20:44:01] RAJESH KASTURIRANGAN: So by 2050, I mean, nobody is going to get to 90%, because at that time-- if there's a 90% reduction, you're going to be unsustainable much before that, right?

[00:20:56:15] ELODIE BLANC: Yes. And so there is a high chance that it will just grow something else that doesn't require as much water, or they will pack up and go somewhere else.

[00:21:05:14] ERWAN MONIER: What we really wanted to look at is the way irrigation is used right now in the US. Is it sustainable? If we just continue doing everything the way it's done now, is it going to work out? And so I just want to point out that when we look at the entire US, the effect is not really big.

[00:21:25:20] It's really important for specific locations. And usually, in those specific locations, those specific basins, it's not where you have the most production. Because it's areas where there's already water stress. So obviously, that's not where you have--

[00:21:40:08] DAVE DAMM-LUHR: Oh, the marginal places.

[00:21:41:16] ERWAN MONIER: Correct. Right. But it's important, at least we believe it's important, because this means, for some people, their livelihood is going to be drastically impacted. And so there's ways you can adapt. I mean, you can be more efficient about how you use water or you can just stop.

[00:21:57:25] You just stop farming there and you move somewhere else. But when you look at the scale that we're looking at, we don't know what it will actually mean for a lot of farmers, how many will be affected. So this is really unknown territory about how will we respond to it.

[00:22:14:07] And so what we really wanted to do is to point out that those issues are likely going to take place in a few decades. And we need to be prepared. We need to have strategies. The system is so complex, we have to make simplifications. We cannot take into account everything. But at least what we want to convey is we need to do this integration. We need to understand how economic development, climate change, how that interacts with water resources.

[00:22:43:25] What does that mean for agriculture, for crop production, and essentially, for food security? And pointing out that there is a problem. We don't yet have all the solutions because we haven't designed strategies yet. You have a lot of people right now, decision makers, who don't even realize that those issues are coming and they're coming fast.

[00:23:06:26] RAJESH KASTURIRANGAN: So if you want to take this research into the public sphere, that may mean decision makers, that may mean new technologies and companies and perhaps even new agricultural practices, how would you go about it?

[00:23:23:24] ERWAN MONIER: Well, now that's a very good question. And I think that something that we struggle with is, as Elodie said, we do all this research and we feel it would be a waste if it actually did not result in anything concrete. But it's difficult. I don't think we can just see one person in particular and say, you need to care about your county or your state. We don't have that power. We cannot just called the governor of Arizona--

[00:23:48:28] RAJESH KASTURIRANGAN: Really?

[00:23:49:08] ERWAN MONIER: --and get an appointment.

[00:23:50:02] RAJESH KASTURIRANGAN: No? No?

[00:23:52:25] ERWAN MONIER: But I think what we're hoping is-- first of all, MIT is a great platform. There's a lot of visibility that comes from MIT research. The Joint Program, also, has done a lot of work with decision makers and has, I believe, had an impact. What we want to do is, first, make people aware that they need to think about those problems.

[00:24:18:03] And I think it would be great if every decision maker in every state thought, maybe I should determine whether or not my state will be impacted and how it will impact it and what it will mean for businesses in my state. I don't think that's what's happening and I don't think you can just convince one person with-- even if we got a one-hour meeting with the governor of Arizona, I don't think we would be able to convince him to change the way they think about the future. It's also a very difficult problem because we're looking at multiple decades. And most politicians, I think they care about being re-elected for, maybe, four, eight, 10 years.

[00:24:55:18] DAVE DAMM-LUHR: You've noticed a pattern here, right?

[00:24:58:03] ELODIE BLANC: I think so. So it's difficult and I don't know.

[00:25:03:08] RAJESH KASTURIRANGAN: Sadly, I think we're all facing the same problem, right? Which is we are looking at a major, major catastrophe waiting to happen. And we are all looking for ways to get more attention.

[00:25:20:08] DAVE DAMM-LUHR: Everybody has to eat.

[00:25:21:17] RAJESH KASTURIRANGAN: Right.

[00:25:22:01] DAVE DAMM-LUHR: Right? So that's the food security piece.

[00:25:26:03] RAJESH KASTURIRANGAN: Talking about everybody has to eat, we are running out of time and we usually end our podcast with what we call a Magic Wand question. So if you could wave a magic wand, both you, Elodie, and you, Erwan, and you could change one thing about the world, ideally to get the world or the aspects of the world that you care about, to pay more attention to climate change, what would that magic wand be?

[00:25:58:20] ERWAN MONIER: I just wish that climate change was not a divisive issue that is just divisive, in terms of the political spectrum. And that people just realized there's no conspiracy. We're not millionaires riding a gravy train-- a gravy boat train, whatever the expression is. We're researchers. I think we work pretty hard.

[00:26:23:20] We just see that there's a major issue there and we're trying to understand what it is and how do you go at solving it. That's all we're doing. And I think until this is resolved and people understand that this is science, and whether you believe or not that we know everything or whether you understand that there's a lot of uncertainty, just being able to work together, regardless of what party you're from, that's what I wish could happen. Because I think that would really change everything. That would be a game changer.

[00:26:54:29] ELODIE BLANC: Yeah. And related to what Erwan was saying is that, I would say that if the decision maker could actually read and base their decision based on the research-- the very good research that a lot of people around the world are making, and that point to solutions like, for climate change, for example, putting a price on carbon emission, such as a cap and trade system that many studies have shown would be the most efficient way of pricing emission and reducing overall emissions. If they could just listen to the research and follow the recommendations, that would be--

[00:27:37:00] RAJESH KASTURIRANGAN: So if I may try to capture, politicians should work with each other and they should listen to reason.

[00:27:44:04] [LAUGHTER]

[00:27:45:11] DAVE DAMM-LUHR: That's a pretty high bar.

[00:27:47:10] RAJESH KASTURIRANGAN: OK.

[00:27:48:07] ERWAN MONIER: Which has been the trend, I feel, in the last few years, right? It's really been the trend.

[00:27:52:12] RAJESH KASTURIRANGAN: Yes. Absolutely. Absolutely. So thank you so much.

[00:27:58:14] DAVE DAMM-LUHR: Merci bien.

[00:27:59:25] ELODIE BLANC: Merci beaucoup.

[00:28:00:18] ERWAN MONIER: Merci beaucoup.

[00:28:01:08] RAJESH KASTURIRANGAN: And I hope that all your wishes are granted, that the minute we leave this room, the governor of Arizona calls you. And in the meantime, we would love to have you back in a little while to tell us what's next and how these models are going.

[00:28:18:28] ERWAN MONIER: Thank you so much for having us. This was really great.

[00:28:23:07] RAJESH KASTURIRANGAN: Thank you.

[00:28:23:17] ELODIE BLANC: Thank you. Thank you very much.

[00:28:24:20] DAVE DAMM-LUHR: OK. Bye bye. Bye

[00:28:26:09] ELODIE BLANC: Bye.

[00:28:28:09] RAJESH KASTURIRANGAN: Boy, that was a fascinating conversation, and I hope the governor of Arizona is listening to us and ready to call Elodie and Erwan and find out everything that they do.

[00:28:38:07] LAURA HOWELLS: Let's hope so.

[00:28:39:09] RAJESH KASTURIRANGAN: Talking about people listening to us.

[00:28:41:11] LAURA HOWELLS: Yeah. We love all of you listeners out there, so please do reach out to us on Facebook and Twitter. You can get in touch with us directly if you have anything you want to share, anything you'd like us to do in the future. You can reach out to us at climatex_feedback@mit.edu. And please do rate and subscribe to us on iTunes. We'd love to hear feedback from you and it really helps us grow this wonderful community.

[00:29:02:24] DAVE DAMM-LUHR: So until the next time--

[00:29:04:12] LAURA HOWELLS: Thanks for listening.

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