 Hello, everyone. I would like to welcome you to the second day of the public information gathering session. Paving the way for continental scale biology, connecting research cross-scales. For those who are not here yesterday, I would like to mention that this is an organized effort under the auspices of the Consensus Study Committee of the National Academies. Research at multiple scale, a vision for continental scale biology. I'm Jack Liu, the committee chair. I will begin to acknowledge the wonderful committee members and outstanding staff members of the National Academies for their great hope in planning this webinar. Yesterday, we had a keynote presentation and also six other presentations by leading researchers from the US, Germany, and Sweden. The excellent speakers covered a wide range of topics, highlights progress that had been made in the last several decades, such as the integration of two grand challenges of our time, global change and biodiversity laws. Also, talked about the golden age of remote sensing, the power of remote sensing data used to generate information and useful knowledge across multiple scale. Also talked about the golden age of genomics and the integration of microbiology, epidemiology, and biogeography through citizen science approaches. And also explore a lot of other issues, such as the drivers of biodiversity with neon data and the patterns of change in biodiversity under globalization and urbanization. And of course, they also point out a lot of challenges and limitations, especially data availability and the lack of synthesis of existing data. Of course, the funding is always an issue and not just the lack of funding for some areas, but not long enough funding to ensure the data maintenance and the data use and integration. And then the speakers also point out a number of needs or solutions and to fill out sample gaps in many regions and more innovative use of artificial intelligence and other tools. And also talk about the resource networks and networks of networks of ideas, people and young structures and more integrated theories. So there are a lot of other issues discussed yesterday and due to the time limitation, I will not cover all this for those who are interested in, they can watch the video and so this webinar is being recorded. Also, today we will hear another keynote presentation and several other presentations by experienced program manager at several federal agencies supporting research across multiple scales. Following the presentation and we will take questions from both the committee and participants joining us via live stream. If you are audience members joining us via live stream, please submit questions through Slido and you can also upload the questions from the audience you like most to hear. And we encourage questions from the audience, but the question from the committee will be prioritized. And after the meeting anyone would like to submit the written comments and could contact Cliff, the study director, or provide feedback through the website of the project of the National Academy of Sciences. I would like to invite Stephanie, one of our wonderful committee members to moderate the next panel presentation. Thank you. Thank you, Jack. And thanks so much, Si. It was a really, it was a great talk. So I'm going to introduce the panel discussion that we have this afternoon, biology at multiple scales from the program managers perspectives. So as we're diving into the work of this committee we recognize that program managers across our, our agencies frequently yours really seeing the leading edge of research and you're also seeing what's not being proposed that you feel that there's a need for so we wanted to be here to sort of give us that that real overview of this landscape. And of course, in many cases you're, you're managing funding programs. You also have some of you have teams of researchers that that work within your agencies and so you really bring that breadth of perspectives that you've been here. So the panelists will have a total of 10 minutes each and are going to try to limit their, their comments to about eight minutes with a few minutes for questions in between if we can, if we can stay roughly on time. All right, so you have the, the bios for each of the speakers. And so I don't want to take away from their time by giving them a really lengthy introduction so I'll just briefly say first we're going to hear from Annika, Jerlinga from National Institutes of Health. And Annika is a program officer in the National Institute of Environmental Health Sciences in NIH, and so she will tell us more about the, this program and perspective from NIH. Excellent. Thank you. All right. Thanks so much for the introduction and I'm happy to be here to tell you a bit about what we have going on at the NIHS. Next slide. Just to orient you, the National Institutes of Health is made up of 27 Institutes and Centers of which NIHS is just one but carries a broad scope of work. Uniquely, NIHS is not focused on any one health outcome but is concerned with understanding the role of environment in driving disease outcomes with an overall mission of improving human health or preventing disease. For this presentation, I hope to cover the challenges in defining environment in the context of specific research questions, how our research by definition places us at the nexus of multiple disciplines and stress the overall need for clear synergy and collaboration with other funding agencies. Next slide. So most of this presentation will be through the lens of having overseen a portfolio of research awards related to the intersection of post microbiome, environmental exposures and human health. So typically for NIHS environmental exposure refers to a chemical exposure or natural toxin that one encounters in life and can be ingested through food or water inhaled or dermal exposure at many doses for any length of time. Our approach to the role of the microbiome has been several fold. It could be in and of itself a direct target of a chemical which mediates disease progression in some way. Taking the gut microbiome as an example, an exposure may elicit toxicity of microbes directly to impact the health of the GI tract, or it may alter the profile of microbial products which go on to communicate with other systems throughout the body, such as through the gut liver or gut brain axes. And interpretation is heavily context dependent as there are direct impacts of microbes on the host to influence health, irrespective of chemical interactions, and that can drive the quote unquote normal physiology. In some cases, the host microbiome contributes to bio transformation processes that render that exogenous chemical we're studying more or less toxic in its metabolite form. Thus, in that case, the microbiome could be considered a mediator of bio elimination, which is still crucial to understanding the overall process of toxicity for that exposure. It's important to point out in the overall framing of the NIHH mission, the microbiome is not considered to be an environmental exposure, but we examine the host microbiome as an additional organ system. However, as a research field broader than NIHH, it's important not to lose sight of the fact that the microbiome, both environmental and in various niches within the host are micro environments in their own right with their own interactions and communication systems, but often underappreciated in this space, just for the sake of designing a tighter study. So if we take this paradigm and look at the larger context of human health in the schematic on the right, you can see that viewing host microbiome as one of many sources of individual variability is critical to addressing the applications. So can microbial signatures predict toxicity, leave a fingerprint of exposure, or be the key to preventing or mitigating exposure related toxicities? Okay, next slide. So as an example of the complex interplay I just described, here's a schematic of the contribution of air pollutants to metabolic disorders. The air pollution is a complex mixture in and of itself with each type of particle boasting a unique toxicology profile and attributions. Secondly, there are direct impacts of pollutants on biological systems, which we know from animal and human studies. So this can come both from inhaled and ingested routes contributing to outcomes in the lung and the gut and beyond. In the schematic, the author describes multiple roles for the microbiome and facilitating this, including altered bio transformation of toxicants and changes in the microbiota composition and metabolites contributing to those secondary and tertiary effects. So in all, although I don't have time for multiple examples, I'm hoping that this slide conveys that elucidation of these pathways necessitates mechanistic biology, exposure science, and epidemiology approaches as each unique set of answers. Next slide. As alluded to you on a previous slide, NIHS needs to be somewhat specific in its definition of the environment when developing certain programs as it can be unwieldy and lofty to consider everything. But that doesn't mean that it should not be a goal. As a grant per se, I want to highlight the concept of the expo zone because I think it's relevant to the goals of this meeting. So I've borrowed a couple slides from my colleague you should sway who recently presented an update to our NHS Council in January about expo mix. Essentially the expo zone represents the combined exposures from all sources that reach the internal chemical environment and may influence human health. So this slide is a probably non exhaustive list of sources of exposures from various environments that may influence internal systems and this notably goes above and beyond that chemical toxicant or a natural toxin definition that I said earlier. Next slide. So this second expo zone slide is a schematic indicating the paradigm approaches and challenges for exposure science and the expo zone. Basically, how do we track external exposure from the source into into a host and into the biological systems with within the host and key in on relevant biological processes that are integral to health outcomes. So this involves leveraging tools and technologies that are already in place either within our discipline or without and developing integration approaches from determining overall exposure at say a geospatial level to individual or population level and taking an intentional look at which analyses are going to be the most powerful tools in determining exposure disease relationship. So with the direction of human microbiome work, moving toward leveraging more function based applications such as microbial metabolomics or metatranscriptomics. I see an important role for microbiome here, especially when one considers what we can learn from the environmental microbiome and translate it into a human microbiome context. Next slide. Although I am most certainly running out of time. In this last slide, I would be remiss and not to include a successful example we have of a program that successfully merges environmental science with health sciences. And that is the NIH NSF co funded centers for oceans and human health. So this is a 20 year collaboration to jointly fund marine related health research. The structure of the centers are three to four distinct research projects, a community engagement core and an administrative core, at least one research project addresses a biomedical question. One addresses oceanography or lack of stream related question and one research project examines the role of climate change, and then community partners are engaged to facilitate translation of data into policy dissemination of community level education, or communication strategies. Just importantly the center structure allows for scientists from distinct disciplines to engage their multifaceted tools and approaches to coherently tackle major environmental and health concerns. Next slide. So that's a very brief tour that I prepared to start this conversation and I'd be happy to take questions now or in the panel. Thank you. Erica, thank you so much. I think that we have time for one question. And I'm looking around I see Janine. Janine are you looking for your. Yeah, sorry. So, in the one health slide you just showed. I think that climate change is emphasized, but we also saw with the pandemic, the COVID pandemic that there are all these links to natural ecosystems and to biodiversity and I'm wondering if there is consideration on increasingly incorporating biodiversity into the one health paradigm. I can speak on behalf of all agencies involved in the one health paradigm but certainly that's a conversation that's that's being had, and especially I was teasing a little bit about what are we looking at in terms of environmental microbiome or the environment in the grand scheme of the conversation of the environment and I think talking more and more about climate change that has been and needs to be part of the conversation. Thanks, Sonika. So I think we should go ahead and move to our next panelist. So our next panelist is Katarina did mark from National Science Foundation, and I don't actually have to look at her bio to be able to introduce her I probably don't know, but although it would help me to see the great number of programs she's been involved with, but specifically she is working with ecology and evolution of infectious disease which is also a multi agency program predictive intelligence for pandemic prevention, and, and a really large number of other programs so I'll go ahead and hand it over to you Katarina. Thank you Stephanie. Good afternoon everyone. And it's a pleasure to be here and thanks for inviting me. I don't have any slides so I'm just going to talk and you just going to have to look at me and listen. So in the past years NSF has stood up various programs that are aimed at translating knowledge across scales, but I will focus my remarks on the context of fundamental infectious disease research. Now, we all just went through a pandemic, and a lot of the research in the infectious disease arena suddenly became science with a deadline. And those moments of crisis are always great to realize all the things that are missing not working and that we should have taken care of ages ago. The edges in terms of research that emerged early on in the pandemic stage relates to a particular point in the pandemic timeline, which we call the pre emergence stage. And the broader context here is essentially the prediction of rare events in multi scale complex dynamical systems. The dynamic of such systems is of course extremely complex, and we are seeing some increased attention to the development of innovative theoretical frameworks and modeling tools that aim to capture non linear complexity. There's also a recognition that in order to operationalize these models, we need not just any data, but the right data. This should be data at optimal granularity, meaning it should be relevant to the temporal and spatial scales in question. In the particular context of the pre emergent state of pandemics. The predictive framework should be informed by bio surveillance as a very necessary ground choosing step. Together with the integration of climate land use and other often remotely collected large scale data sets that can inform future scenarios of emergence or vulnerabilities and risks to animals plants the ecosystem, the environment with large or human populations. Of course, we all know there are millions of pathogens or microbes that have yet to be discovered. And in the face of this high and ever evolving biodiversity, it became clear that surveillance of emergent emerging threats is needed at a scale that is currently in practical with the existing technology. So to address this need for new technology. There's an increased interest in the research community that we are observing on our end to design wireless remotely operated sensor networks, combined with new sensors for rapid detection to enable identification of pathogens. Another area of activity and growth we have seen is what could be described as spatial temporal dynamics of pathogen dispersal in the context of different environments and climate processes. Eventually this relates to fundamental research into the synchronicity of outbreaks and examples here are renewed research into fundamentals of regional to continental and global dispersal of microbes, including pathogens, not just via hosts, but also through the atmosphere or aquatic environments and an interrogation of the physical processes that contribute to that dispersal. If we are considering dispersal of pathogens in the context of animal vectors and I'm thinking of vector-borne diseases here. There's increased research interest to harness autonomous sensing platforms and novel sensor modalities for large scale animal population monitoring and detecting movements also through trade and changes in disease states of hosts. Microbial diversity, climate change and pathogen emergence is another very big topic that we are seeing a lot of development in. And in order to better understand these processes related to pathogen emergence, we are seeing an uptick in basic research to into the ecological and evolutionary dynamics of microbes in general. The impact of environmental conditions on pathogenesis remains largely unknown and shifts in these abiotic factors will undoubtedly affect microbial metabolism and nutrient cycling, as well as microbial community assembly, which in turn, of course can impact colonization and virulence, and for instance, influence the frequency of certain diseases including zoonotic diseases. So in essence, research into the metabolic activities and enzyme functions at the microbial community level and how this scales up and affects not just individual hosts but possibly populations or ecosystems on a larger geographic scale could be very important in the future. From the pandemic there emerged a very clear recognition of the role that humans and human environments play in disease and pandemic dynamics, and there is an increased focus on the science of complex human behavior at different scales. And research that meaningfully incorporates social and behavioral processes in epidemiological models is particularly critical. And at NSF we have just started a program called incorporating human behavior in epidemiological models, which is a collaboration between bio, social behavioral and economic sciences and mathematical and physical sciences. For any research that crosses scales, there is a need to enhance and sustain data innovation and to ensure that modeling and forecasting are up to par with the questions. Now, we always have in mind an ideal state of data availability, but the pandemic very clearly showed that scarcity of data is actually the norm. And additionally, outside the lab environment, data streams are often very noisy, they're biased and inconsistent, leading to difficulty in subsequent processing and analysis, including for artificial intelligence and machine learning techniques. And so determining the most effective method to using limited and noisy data and overcoming gaps while quantifying uncertainty or bias, because those samples often are self selected communion samples is one of the primary challenges on the topic of predictive modeling across scales. With respect to machine learning and artificial intelligence methods, there remains the persistent need for improved knowledge representation, learning architecture design and efficient training frameworks. Now, new insights into the interconnected and independent systems at the necessary levels of complexity is only going to be achieved by careful integration and coordination across multiple scientific and engineering domains. And one way to successfully and sustainably do that is by developing and training a prepared workforce. This needs to be a diverse workforce that is able to capture diverse perspectives and translate research outcomes into effective interventions in the case of pandemics. Emphasis on team science also from NSF is critical and best practices are highly welcomed. Lastly, perhaps, pandemic research showed that more so than ever science cooperation and technological development activities at scale don't happen in a vacuum and issues of equity, fair access, transparency, ownership, intellectual property, and reproducibility are becoming increasingly important. And those issues scale with working across international borders. And that's, that's all I had. Thanks, Katarina. And we are doing well on time. So we've got a couple of minutes where we could let's try to take one question. And of course I will jump in if I don't see other hands up when you polite though. Okay. So, Katarina, I know that the in some of the programs that you've mentioned that these are are highly interdisciplinary and I think in, in the, in the pandemic at NSF we saw all of the disciplines basically focus their energy on this single problem which was extraordinary. And I wonder if you could speak to what some of the challenges were in or and still are in terms of integrating those incentives and perspectives across the different disciplines and what some of what some of those opportunities are for overcoming them. Yeah, thank you. So I think it's really important to what the pandemic showed how important it is that we all need to kind of reach across the aisle and cooperate across different fields and learn each other's language. And often, like this integrative science I know we've talked about this very, very long time everybody always says oh we need to reintegrate biology and so on, but we really need to reintegrate science on a much larger scale. For instance, the part of what I just talked about came out of the effort of the predictive intelligence of pandemic prevention program, which is a collaboration internally between the biological sciences, engineering, computer science and engineering social and behavioral and economic sciences and math and physical sciences. And all of these communities basically had to come come together and think about what are some of the concepts that we all use and perhaps have different words for it and what are the things that we think are the same but actually are different. And I know this sounds trivial, but at the very hard often is this very, very fundamental. Well, let's just listen to each other and understand what we all mean, and then go from there. Another point that I want to make is we all I mean we do live in an age of large data and big data and everybody is enamored with that. But it is really important to understand well what kind of data do we actually need to answer these questions. And how do we get this data for the biological sciences there's a lot of opportunity to reach into the engineering community. Especially within the context of the pandemic, it was mind blowing to me all the different ways that engineers had already thought about how you could sometimes remotely connect, you know, some some data and remote areas for instance where it's very difficult to access. And I suppose this, although I have talked about bio surveillance in the context of pandemics. Yes, all kinds of, you know, data that you can get in all kinds of things that could be monitored including plants or the microbiome with large and so on. The kind of interdisciplinarity at a core level is super important to addressing some of these big and outstanding questions that we all have heard in the last two days and we also would probably recognize that in principle we have talked about these problems for a long time already. So, what is it really that needs to come together here to push, push us to the next level. And I think the integration of different disciplines, we still have a long way to go. Great. Thanks, Katarina. All right, so I will go to our next panelist, and it's woody Turner, who is joining us from NASA where woody is involved with biological diversity and ecological conservation, working there at headquarters in the earth science division. So, I'll hand it over to you, woody. Hey, can you hear me okay Stephanie. Yes, and my camera seems to be there we go. Okay. Thanks very much thanks to Jack and the Academy for putting on this, these two days of fantastic discussions. Great to be here with everybody great to be on this panel with these great program managers and also just love that keynote talk thank you so much for that I as somebody who's been working on biodiversity on the research side of the house and conservation on the more applied side of the house here at NASA for a while. I had to deal with scale issues for a long long time and when I was getting started in these two programs. I came across pretty early on that classic 1992 paper by our keynote speaker and it just sort of helped me make the case with a group of other program scientists around NASA who are mostly, you know, physics, physics folks or chemists that you know this really could work and that it's all physics after all right so they gave me a lot of cover so really I thank you so much for that talk is very integrated loved it. I want to talk about a couple of things one I want to start with some history then go quickly into a good thing they talked about two challenges and then on a sort of a up note a good thing note again. If I could so next slide please. Thanks for the slide. NASA has been looking at the earth from space for a while and in doing that we've had some, I would say biologically relevant global and thus continental scale products for some time thinking about various vegetation indices, or land cover maps and these very indices about the transfer etc on land and the ocean chlorophyll a products organic carbon products etc as exemplified on this global view from 2017. I'll note however that all of these basically up to the up to the current day. The vast majority of our biologically relevant products I'll call them have been looking at green as a various levels stages we're supposed to land in the water. And as we've been here we heard yesterday and just going to repeat some of the today we're entering into a golden age of sensing, both from the satellite perspective as well as the Institute perspective. And so, very excited about the level of observations that are coming together across scales. The challenge though is, is avoiding the sort of the tower of Babel problem and making sense out of the all these observations the next slide. So briefly, I'm not going to Dave Schemmel know this touch on this yesterday, we're going from sort of multi spectral focus on greenest to hyper spectral imaging spectrometers that get us the full spectrum in the visual shortwave infrared, give us added dimensionality really letting us get down to finer levels of taxonomy in some cases is certainly phylogy that we've been able to do before. We've got active systems with lasers and radars in the microwave bringing back different types of data sets on structure and helping us find water, etc. Thermal data of higher resolutions getting us the key temperature variables that are so important for life. And of course we were also getting you know, industry is bringing out high spatial resolution data that we're accessing through agreements with them and making available to our funded investigators. And of course we've got a host of other systems well on the Institute side. There's a comparable I would say explosion in organismal level data, and as well as omics data below that the organismal level you've got camera traps, acoustic systems networks of these things coming together. You've got increasingly powerful tagging technologies are not only telling us where something is and when, but what it's doing there. It's physiology or it's behavior without the psalometry and things like that. So, as well as we've got, you know, tons of abundance and distribution data coming through from citizen science platforms, etc. So, in a sense we are now really awash in observations, but as at different scales. And as we're all out here sort of looking I think all of us are at or so looking for patterns. As we and as we know from that classic paper that I refer to earlier, the driver or the mechanisms behind the patterns that we're seeing either with satellite data or in situ data for that matter often are happening at scales different from the patterns we're recognized. And so that brings together back to what Katarina was saying that the foremost challenge for us in working at continental scales or any scales is bringing data together across the other integrating those data. We need this Rosetta stone, otherwise we truly are living in a time when it's just a bunch of different observations and different networks largely speaking different languages that one another observer can't understand and we can't make sense of the can't do the cross scale work that we need to do. Next slide please. So there I think so that's good news but a real challenge. I think the challenge may get addressed in two areas one is is one more technical the other more basic science. But technical one is just data systems and how we manage information, which we've been helped out in terms of phenomenon like Moore's Law over the past decades we can handle big data now in ways we couldn't handle it before. So our approaches, I would say, haven't really kept up with our compute power. From a NASA perspective, we're we build missions we build things launch in the space and our data systems and our science teams that use those data are largely very mission centric. So we're coming sort of late to this for the last few years we suddenly have the ah ha that oh my gosh we've got all these missions up there now we've got to start doing integrated data systems. So that data from one mission a radar say and talk to data from another mission LiDAR or some type of optical sensor passive optical sensor to make sense of it all and so we're doing this this activity called the Earth Information System or EIS which has tools like VEDA have to actually look these acronyms up to make crazy visualized exploration data analysis project or the maps the multi mission algorithm analysis project both in terms of trying to visualize data allows to analyze it play with it, but also to develop common algorithms, all in the cloud with common metadata that allow us to work data across our very missions now. We have to go beyond our multi mission in this case we've got to we've got to bring in in situ data set as well and bring them into this construct we're also doing that. I say we tend to be more national centric than perhaps we should be but we are doing in situ now and space data better it's still we're still a number of years behind where we need to be. And of course as we're doing this we're also trying to do it in the context of open source science, which I think compliments it a great deal but it also complicates just how you know, in terms of what we've done what we build what we use has to be more open than ever before. Yeah, I think that's good for a long term goal. Quickly, moving on to models. I'll say that a couple of things. One, global large scale and continental scale ecosystem or what I call biodiversity models are rare. We heard about DGVMs and the keynote talk and those are great. We've got Mattingly out of Cambridge which is doing some other interesting work. Most of these big scale models are built around guilds or traits for the course. The new data we have both top down from satellite and airborne systems and bottom up from in situ organismal and other systems is allowing us to sort of fill in the gaps and do more agent based type work as we heard about the keynote. But it's still a volume issue and a challenge to how to build the right model at scale to get us to what the way most biologists think about the world which is in terms of species and genera and taxonomic levels or perhaps phylogenetic tools but not so much in terms of traits which can be flexible and changing depending on who's doing the defining. So we need to work back toward that. We have the data to do it but it means building more sophisticated models that are simple yet somehow have the information that makes sense to a biologist. Another challenge here is that at least at NASA and this is probably two at other places. Our data management infrastructure and our modeling, particularly our large scale modeling infrastructure with the GCM folks and the guys who give the big top down with satellite are largely in separate silos, separate areas. So we've got to integrate literally and physically in terms of a place, maybe it's a virtual place but a place as well as bureaucratically and in terms of our science teams who we fund to do work. We've got to integrate the data management side of the house and the modeling research side of the house. That's not to say that, you know, science teams don't work with data systems, but they've been so mission focused in the past that it was very much a, you know, tunnel vision discipline, you know, mission only approach that didn't allow us to incorporate data from other missions or in-situ data sets of various types. Finally, I'll end on a positive note in which case I think maybe our technology and our science may be actually lagging for change, the policy world, which is hard to imagine in this case, in that over the last few years we've seen the development of a global mechanism to focus on biodiversity and its law, somewhat analogous to what the climate community did, I'd say about 20 years before the biodiversity folks got around to it. And by this I'm talking about global mechanisms for observations, for assessment and for policy on the observation front. We have the group on our first observations of geo, they have a biodiversity observation network, geo bond, which is coordinating global observations of biodiversity and relevant parameters. At the assessment level, we've got the IPVS, the intergovernmental policy, science policy platform on biodiversity needs and services, which may or may not be IPCC, but for biodiversity. And of course, at the policy level, there are various conventions, particularly the CBD, Commission on Biological Diversity, which just has big COP 15 last December. That's, again, like UN framework for climate change, sort of bringing that together and coming up with policies. I'll note that these are mirrored, at least on the policy side and on the assessment side with efforts in the U.S. where we've got an American beautiful executive order coordinating policy at the domestic level. We have a national nature assessment, think of the IPVS assessment at a national level. So things are happening. We had an increasingly robust, I think framework in which to put our improved models and data that incorporate cross scalar dimensions. So I'm going to end it there and hopefully I'll have some time for the questions of the next week. Thanks for that. You went all the way up to the end of the 10 minute slot. So we'll go ahead and move on to the next panelist. But then I think the agenda has time for questions at the end. Yes, we do. Okay. So our next panelist is Todd Anderson from Department of Energy. And Todd is the director of the biological systems science division within the office of biological and environmental research. And so this division has a wide diversity of programs, of course, and I will not show up anymore of Todd's time and let him take it over. I'm hoping to open to share my screen here. Shoot. Kat, I figured this would happen. I don't know if you have my PDF. There we go. All right. Well, thank you for the introduction and I'm happy to be here. I recognize some few faces on the committee and so what I have is I think some folks will be familiar with kind of a description of our efforts and the components that we have within a division. And I think I'll end on a couple examples that I think we can talk about. So I'm Todd Anderson. I'm from the DOE's Office of Science. Next slide please. If you don't know, we are a basic research entity. We have eight different program offices now within the Office of Science, and I'm representing the biological and environmental research office, of which we have two divisions that comprise the office. And I'm representing today the Biological Systems Sciences Division, which is home to DOE's major efforts in genomics research, tied more towards its energy mission. And Sally McFarland is currently an active director for Earth and Environmental Systems Sciences Division, which is home to DOE's major climate modeling efforts across several scales and environmental programs. And I'll touch on those programs towards the end of the talk. But let me focus on the Biological Systems Sciences Division. So next slide please. So we are primarily a genomics focused program focused on plants and microbes. We have a history going all the way back to initiating the human genome project. But we've branched out since then and are looking at a wide range of plants and microbial species from a genomic perspective, looking at ways to provide the necessary fundamental science to understand, predict, manipulate and design biological processes that underpin innovations for bioenergy and bioproduct production from plant biomass and also to enhance the understanding of the natural environmental processes of relevance to DOE. We have four major objectives in the portfolio. First is just understanding the information encoded in the genome sequence of plants and microorganisms and how does that explain the functional characteristics of cells, organisms and whole systems. We're also looking at interactions among cells that regulate the function and behavior of living systems and how can we understand those behaviors dynamically and importantly predictably. We're also very interested in how organisms from different kingdoms interact. For example, how plants, microbes and communities of organisms adapt and respond to changing environmental conditions and how can that behavior be manipulated for desired outcomes that feeds directly into our efforts in bioenergy. And lastly, primarily because of the enormous amount of genomic and omic and all kinds of biological data that we're generating in the program, we're also moving towards understanding what organizing biological principles need to be understood to facilitate the design and engineering of new biological systems. So we're heavily engaged in metabolic engineering and what could be called synthetic biology. Next slide, please. So to give you a visual of what the division looks like, we have major research efforts in bioenergy research, biosystems design research and environmental research. Our main effort right now is in bioenergy. We have a range of different projects from the very large, the bioenergy research centers down to single PI projects. Looking at the BRCs are focused at a more comprehensive level looking at how we convert plant biomass to a range of fuels and chemicals that we normally get from petroleum to individual complementary efforts in looking at microbial systems that could be adapted in that bioenergy mission looking at plant genomics to develop dedicated plant crops, bioenergy crops and sustainable bioenergy research that combines expertise in microbial systems with plant systems in the field to understand how we cultivate dedicated bioenergy crops. Our biosystems design portfolio is a nice way of saying again, synthetic biology or metabolic engineering. We're actually using the information that we're generating in our programs to design new functions in the organisms, microbes and plants. And our environmental research is home to our microbiome science, which has evolved over the years. We're still very interested in the activities of microbial communities and a wide ranging environments and their ability to control the flux of carbon and nutrients in the environment. It's also a major discovery element for the rest of the portfolio. You can imagine pulling out different microbes from different environments and plugging those into the other major research elements in the portfolio. Those big three main research efforts are supported by a range of enabling capabilities in computational biology, which is also a research component in and of itself. But we also host several online open access platforms to help make sense of all the only configuration that we're developing in the program. We also have a small biocharacterization and imaging science portfolio that's developing new imaging technologies, both classical and quantum science-informed imaging technologies like entanglement for biological samples. We're part, if you can believe it, part of the larger quantum information science effort, but we have a very focused part of that portfolio on adapting quantum science efforts to bioimaging. And then, of course, DOE is home and we're home to a couple of DOE user facilities. We are the administrative home to the Joint Genome Institute. Our larger office is home to the Environmental Molecular Sciences Laboratory, and we have access to the structural biology resources at the Synchrotron Light and Neutron sources and other DOE user facilities. The research is complemented by our efforts in SBIR, Early Career Awards, the Office of Science, Graduate Student Research, and EPSCOR Awards. Next slide, please. Just another visual with three main elements to the portfolio. The Genomic Science Program is two-thirds of our budget. That's where the bulk of our research is. And you're seeing an overlaid image because there was a two-part in my PowerPoint that didn't come up. But you see a lot of effort in, if you look down through the Genomic Sciences Program, you see our efforts in bioenergy. How do we convert plant biomass to fuels and products, microorganisms, looking at our range of different microorganisms for bioenergy applications, plant genomics, understanding plant gene function, with the goal of developing dedicated bioenergy crops, sustainability research, looking at how to grow those crops in the field, our biosystems design work, synthetic biology and metabolic engineering for a wide range of manufacturing purposes. Our environmental microbiome science, looking at principles of microbial ecology, and our computational biosciences, looking at computational capabilities and developing out of a variety of different platforms. Our imaging capabilities, I mentioned earlier, and of course our facilities and infrastructure with the Joint Genome Institute being a central source of genomic and omic information, but also analysis capabilities for interpreting that information. And all of that portfolio is guided towards multiple aspects of the DOE mission, including bioeconomy research, biotechnology development, synthetic biology, biosecurity, and quantum information science. Next slide. I wanted to just mention the resources that are available both within the division and the larger DOE Office of Science. I mentioned our user facilities, the Joint Genome Institute, the Environmental Molecular Sciences Laboratory, but also through the BER structural biology resources. There's beamline time or beamline and other kinds of imaging and analytical capabilities at the DOE Synchrotron and Synchrotron-like neutron sources for a variety of capabilities. But I think you've already heard about some of the computational platforms that I think would feed into a larger view of biology, a continental view of biology. Our DOE Systems Biology Knowledge Base is an analysis platform, again, open access. It's tailor made for researchers bringing genome sequence to the platform and turning that genome sequence into metabolic models in which to develop hypotheses for further bench testing or using those metabolic models in a variety of different environmental models for predicting the activity of microbial communities in the environment. I think you already heard a presentation from Emily Ella Fraderos about the National Microbiome Data Collaborative, a source for microbiome data and all the metadata that goes with a microbiome data set. We're also home with, we also have the advantage of having significant computational resources available at the National Energy Research Supercomputing Center at Berkeley. And our colleagues in the Earth and Environmental Systems Sciences also run an environmental database, the Environmental Systems Sciences Data Integrative Virtual Environment or ESS-Dive. Next slide, please. So I want to just tell you just a brief overview of the division and its activities, but I wanted to end with these two examples that I think are relevant to a continental scale biology. One of these is a project led out of Pacific Northwest National Lab. This is out of our Earth and Environmental Systems Sciences Portfolio. It's called the Wonders Project. It's a worldwide hydro-biogeochemistry observation network for dynamic river systems. This is a burgeoning global effort to provide samples of primarily aquatic systems and sampled and analyzed in a standard way and providing a growing database, including genomic database of a snapshot of microbial communities at different environments. It's an interesting concept that I think could be a step stool to build on if we're looking at larger constructs or larger aspects of biological or continental biology. And the second one here is something out of our bioenergy portfolio and it's looking at common gardens that host a range of native species of switchgrass across quite a latitude across the breadth of the country. And so these native grasses have been sequenced and to the level that we can now correlate changes in the genomic structure of switchgrass species in these common gardens with perhaps geographic changes, climate change, climate adaptations, or various biogeochemical conditions at those sites. And that opens up a whole lot, I think, of larger scale genomic experimental work that we could do that could combine with larger, more macroscopic understanding of these systems. Again, I'm picking up on what Simon was talking about, about taking patterns in microscopic elements and moving them to the macroscopic. And in this format with at least in plant biology, we have a couple of examples of plants that have been sequenced in this way where we could build on that. So I would just like to leave you with those two examples for discussion and I'll stop there. Great, Todd, thank you. So we are just up against the time slot and so I'll go ahead and move on to our next panelists and we can save any questions for our session just after that. So our next panelist is Scott Hagerty, who is the Interim National Director of EPA Sustainable and Healthy Communities Research Programs in the Office of Research and Development. And again, the speaker's full bios are in your briefing book so I'll let you explore that and we'll go ahead and just turn it over to Scott now. Thank you, Stephanie. It is indeed a pleasure to be here today to talk to you about how EPA incorporates scale into its applied research to support the agency and protecting human health in the environment. One of our primary mandates of ORD is to provide the science to support statutory mandates. One of the things I believe in thinking about this presentation is what is our connection to continental scale biology. And I believe it really lies with our work and using an integrated systems approach to protecting human health in the environment. SHC, the Sustainable Healthy Communities is one of six national research programs that identifies the applied research required to fulfill the agency's mission and its strategic goals and objectives. Many of you are probably well familiar with the other national programs, including air, climate and energy, chemical safety for sustainability, health and environmental risk assessment, homeland security, safe and sustainable water resources. You may also be familiar that we've just completed the strategic research action plans, which is our four year plan of research that will be conducted to achieve the agency's mission. One of the unique things about this strategic research action plan was that the national program directors work together to combine efforts on six cross cutting priorities that are looking to conduct research that advances science that informs public and ecosystem health decisions and community efforts. And these six priorities are environmental justice, cumulative impacts, climate change, community resilience, children's health, contaminants of immediate and emerging concern. From one of the founding paradigms for EPA in its use and regulatory decisions is the source to exposure to effects paradigm. These are typically media specific single, single pollutant efforts. You know, and this effort really remains the stalwart of the agency. It is what the majority of our regulatory decisions are based upon. Many of you are probably familiar with the integrated risk information systems, the iris assessments. Those are the gold standard assessments which sets the hazard identification used in a risk analysis. I really want to draw your attention to kind of the way that we've been thinking now over the last five to 10 years. And that is really trying to understand the complex positive and negative interrelationships between humans and the environment. And that this simple frame really has now become the foundation of how we think about EPA's research and how we plan EPA's research. Through a systematic approach, we approach problems holistically, integrating human health and ecological sciences across scales from molecular to ecosystems to achieve the sustainable solutions and provide the rigorous scientific evidence to support decisions. And this framework we include the examination of multiple stressors and the integration of data, knowledge and perspectives of multiple stakeholders and scientific disciplines, including the natural social behavioral economics and decision sciences. I think what's unique about EPA is that when you think about scales. You know, our heart of our research is humans is at the organism level. And for the remainder of the talk I'll really focus on humans and that perspective from the organism perspective and think about scale from that. If you consider it over those course of the years we've made considerable investments, and that have made people making considerable investments and understanding the dose concentration effects on health outcomes. And it was really nice to hear the earlier talks, presenting especially from Annika, where she actually talked about the dose response and the health outcomes, because that is a critical component of what we do from the human health perspective down to the lower looking at everything from the organ to the molecular to the cellular levels. One of the useful tools and thinking about this has been the development and advancement of adverse outcome pathways. These model systems are really useful to identify the sequence of molecular and cellular events that produce a toxic effect when an organism is exposed to a substance. EPA has been rapidly developing advances in computational toxicology, bioinformatics, chemometrics, high throughput screening, combined with data from clinical trials, epidemiological studies and health records to expand the databases of chemical toxicity and patterns of health information. These advances significant have allowed for the development of indicators and metrics that have improved our monitoring as have the assessment protocols and application to provide a range of products to inform a variety of decisions. While decreasing scales are needed to understand how chemicals and pollutants cause health outcomes, increasing scales are required to understand exposure and sources from organisms to populations to communities to ecosystem. At the population level, we see intrinsic biological factors as the important of determinants and pollutant or multiple pollutant adverse health outcomes. This can include pre existing disease, life stages, reproductive status, age, sex and genetics. Over the last several decades, we have taken a greater approach and expanding our knowledge as to what impacts health outcomes. We've increasingly included the coupled influence of extrinsic social and structural factors on health outcome. By this we are acknowledging the differential susceptibility to exposure results in different health risks to communities expanding our studies to include poverty, racism, discrimination, social and income equality, access to health care and geography and occupational risk. Recently within ORD we produced a report on cumulative impacts and how we can use that to influence the science or how we can use that to inform the science that we're conducting. In that report we provided a definition for cumulative impacts and define them as the totality of exposures to combinations of chemicals and non chemical stressors, and their effects on health well being and the quality of life outcomes. These cumulative impacts include contemporary exposures to multiple stressors, as well as exposures throughout a person's lifetime. They are influenced by the distribution of stressors and encompasses both direct and indirect effect to people through impacts on resources in the environment. Cumulative impacts can be considered in the context of individuals geographically defined communities and defining definable population groups. Critical to this is the development of cumulative impact assessments, which here we define as the process evaluating both quantitative and qualitative data representing cumulative impacts to inform a decision. Cumulative impact assessments requires a systematic approach to characterize the combined effects from exposure to both chemical and non chemical stressors. Over time across the affected population group or community, it elevates how stressors from the built natural and social environments affect groups of people in both positive and negative ways. The elements of the cumulative impact assessment include community role in community involvement throughout the assessment, such as identifying problems, potential interventions, decision points to improve community health and well being. Our efforts are really kind of at this late at this stage are really beginning to kind of take new account the chemical and non chemical stressors it's thinking holistically about the problems that we have to address. From a research perspective it is through this lens of cumulative impacts, which is what how we're beginning to integrate the impacts of global megatrends such as climate change, economic power shifts demographic changes rapid urbanization and technology. To connect that into our research planning and thinking of terms of exposures and how those change over time, especially when it comes to susceptible populations. Our research portfolio is robust over the next four years will produce somewhere in the neighborhood of 770 different research products of which almost 122 or will be tied directly to environmental justice and cumulative impact research efforts. Starting to lose my voice I'm sorry. And we also look at this from a very expanded flat or a very expensive portfolio of work it includes tools methods databases approaches chemical assessments that that there's way too many for me to sit here and talk about. We can talk about the, the databases such as environment list. Our climate scenarios ecosystem goods and services are work on social sciences and community engagement. All this work is being collected to really enhance how we look at our science and how our science informs decision making through a cumulative impacts approach we're looking at. For example, I'll provide you with a couple examples. So one is looking through the risk and vulnerabilities of our contaminated superfund sites and where they're located and how they'll be responsive or how they may be impacted from increased climate change. And how we can couple those into our work on exposure sciences on talks out toxicology and to be able to understand the risk that those communities that will be experiencing in response to climate change. I think one of the clearest examples of how we incorporate scale in across the system is our examples of harmful algal blooms. The portfolio of work associated with harmful algal blooms focuses on not only the toxicology of the different toxins and developing methods to us to assess them rapidly and quickly. But then also looking at the treatment technologies that can be used to, you know, clean a water supply. Once an event is going on, but some of the most relevant work as it comes to continental biology is the use of satellite data to monitor in near real time, the presence of cyanobacterial blooms in 2000 large lakes across the country. This information is available to people on their phones. They can look at it. People can it's available to the public. They can look to see whether or not these 2000 large one of these 2000 large lakes is about to experience a harmful or a cyanobacteria bloom. And then managers on the ground can direct their resources to those sites to determine whether or not they need to be doing a health advisor because the bloom is indeed toxic and is approaching a beach. One of the other benefits of this is that's providing us the actual first real term. National coverage of whether or not harmful algal blooms are increasing or decreasing. We're able to use this information and reported on the report on EPA report on the environment to show the status and trends of harmful algal blooms in the United States. And I'm excited to actually say that more recently within the last month, our research teams on the cyanobacter have been able to develop an algorithm that allows them to predict with 80% confidence whether or not an harmful algal bloom will occur one week in advance of these 2000 lakes. Small little step but it's the first time that we have a national coverage. We actually have a way to predict and forecast whether or not a harmful algal bloom will occur. More excitingly is that with the launch of a geospatial satellite coming up, we'll be able to take that application and provide it out to the more than 300,000 freshwater lakes across the country, and to provide that same type of capability. So that is one way in which we go from the human health impact of being exposed to potential harmful algal bloom all the way up to how we can manage and provide a global scale analysis around that. I think I'm bumping up on time so I'll stop there although we do have another really exciting one with the launch of the trophosphere emissions monitoring pollution satellite that just went up last week. Great Scott, you are right on time. Thank you so much. So all the panelists have been superb in managing their time. And Scott, we actually, our last panelist had to cancel so we have a few extra minutes if you want to go ahead and talk about that launch I'd welcome that. Yeah, so our assistant administrator Chris Frey was actually able to attend NASA's launch of the trophosphere emissions monitoring and pollution satellite that went up into space, not last week, but the week before. And this is a geostationary satellite and to all the NASA folks online if I mess this up that's because I'm an aquatic ecologist. The satellite will once it's once it's up will be able to conduct hourly scans at high resolution measuring pollutants that include ozone nitrogen dioxide and formaldehyde with pixels of a few kilometers on a side. This information will allow researchers and others to look at on a global or on the national scale what is the pattern of these these air pollutants across the country. And it will also allow you to kind of go in on the community level to focus in on what is the potential exposure that one may anticipate or can you, you know, forecast when a community is going to be exposed to one of these potential chemicals. And then you can actually go ahead and advise on health advisory. When you couple this work with the our efforts to kind of work with communities on the ground to take the knowledge that we have in terms of our exposure and what the toxic toxicological values are. It is a really powerful tool that again kind of connects you from the source to exposure to actually being able to make a difference and protect people before they become exposed to it. And I will just add like one, one in this effort to kind of expand our RDS research effort, we have made a significant investment in social scientists over the last year and a half. We now have somewhere in the neighborhood of 40 social scientists that will be coming on board our organization to help us understand both the intrinsic and extrinsic factors that a community can be based on. And I will say, I'll need to jump off in about five minutes because I need to go convince 315 long term ecological research graduate students to come work in the government. Worthy work. Thank you. All right. So, let's see, as I mentioned, our last panelists had to cancel and so we can go ahead and jump into some questions and I know that we did have some questions come in already through the slido. But I can also open it up for our committee members here. Jack. Yes. Thank you so much. Stephanie or the great speakers and really enjoy your talks and also really appreciate that the great support you provided to the scientific community working across different scales and on different topics. Yesterday, there was a speaker commenting about the not sufficient long enough support for a lot of research. I know many of your agencies have been supporting long term research. And I'm wondering what kind of experience you have in supporting those long term research or whether you have new plans to support future long term research. Thank you so much. This will be for all the speakers. Anybody want to take that on. I'll start. So I think in our portfolio we do have a range of different long term efforts. We do have at the shorter range we do have funding opportunities that go out to the academic world across a variety of different disciplines those are generally on a three but sometimes a five year basis. We do have longer term programs at the DOE labs and these are the science focus area projects that are usually team oriented. They're also on a three year three to five year basis primarily on a three year basis reviewed on progress but but they are they are meant to be somewhat longer term they do come and go. But they are longer term than your standard academic grant. And there's also a lot of there's several major experimental programs in the DOE portfolio primarily in our sister division. Long term ecological ecological experiments of the spruce project up in northern Minnesota would be one example that's been running for quite a while and is an iteration of the old face program experiments that many may be familiar with. We do have occasional opportunities for longer term experiments and any and the opportunity for large more long term experiments at the DOE labs. I'll just leave that there. Great. Thank you. Thanks. Please. Thank you very much for all the talks. This also is a question for for kind of like two parts actually for everyone. So in in Simon's talk he talked about that sort of the integration of data and what we need to, you know, questions about what to know in terms of understanding how global ecosystems work. And, and so I was interested in the committees, or the panelists thoughts on the integral. So it was really exciting hearing about everyone's perspective and the databases that are being developed for each particular agency. But the, the perspectives were different and it seems like we need an integration of the both perspectives, even across agencies to actually attack this problem, for example, pollution affecting global aspects. So I just like to hear your thoughts about integration of, of data across agencies and also the computational tools across agencies. I want to tackle that one. I can, I can try. So, I do think a lot of our efforts but you know we do a lot of collaborations and a lot of work with our federal partners and other agencies and so we do a lot of work with any IH and NIH and Noah and NASA. And so a lot of the original platforms and development. I think there's because we're doing those in collaboration I think we're pretty. Pretty good there in terms of more recently in terms of having the same information or at least an understanding. We have those discussions early on. We have a lot of discussions about you know where does the data sit well if it's especially with satellite data for example where does it sit who has it. I think our biggest challenges is when we actually are looking at other data sets that essentially aren't within art within our, our family. And a lot of those is access to health records. As we begin to go down there that path of looking and getting information, you know, not, not every county or even every state collects health data at a hospital the same way. And so being able to kind of gather that information. We can access it publicly is according to all meeting all the guidelines. I mean that's a that's a significant challenge. And so it's really I think looking at looking at the broader spectrum of data integration. Great. Thank you. What do you think were you raising your hand to. Yeah, I was just going to respond to Louise's question I think you know the US global change research program has been up for a couple of decades now it does a lot of climate research work across agencies. For example, the carbon area there's a fairly robust cross Asia collaboration. I think we could do a better job again and you know, integrating our systems for managing and holding data. And also on some modeling others. There's some good. In the world there's some cross modeling effort that's going on. So it's happening it's not, I would say it's not it's it's biologies a bit behind carbon. In this regard, and if we want to make progress we need to step it up. Monica, were you also going to speak to this. Yeah, I was, I was also going to say this conversation is happening at NIH and even in our field of environmental health sciences. I have colleagues who are spearheading kind of an environmental health language collaborative so you know pulling together academic researchers and NIH folk and other stakeholders into developing a harmonized language and data and metadata standards as we continue to increase the number of data streams that we're trying to work with. And I also wanted to highlight the challenge of training as we're expecting the new generation of researchers to be increasingly interdisciplinary. So I think it's a consideration that we have to have different disciplines are going to have different ways of doing things but as they reach out and incorporate other disciplines into their work it just, we need to have that integration strategy in place. Great. Thank you. And Catherine, did you. Yeah, I just wanted to second what Annika just said about the training. That's also something that we have been thinking a lot about at NSF. And it's one other piece to add on the data front is it's not just about data that's available across federal agencies but also in the industry, like, you know when some of the data that we needed to kind of get access to in the context of research, a lot of these data sets are pretty biased because they're kind of self selected convenience data and not necessarily purposefully or purpose of sampling. And so there is kind of a level where there needs to be a little bit of a reset in terms of really kind of high precision, perhaps spatial technologies that collect data independent of particular individual kind of research. Streams. Yeah, that's all. Thanks. And Scott. Yeah, just to, and I think maybe to close this out. I know it was discussed yesterday, but within EPA, one of our biggest struggles is figuring out how to incorporate citizen science, or what we now call participatory science into our decision on a regulatory side, it's a pretty high bar for the information that has to go into make a regulatory determination or decision. But it doesn't mean that participatory science and our work with communities isn't value and needed. And so it's a, it's an ongoing effort to figure out how to use this type of information and how to use personal sensor information and phone data. And so I think as these new data streams come online, and they're coming from a series of different sources. The struggle is essentially when and where we can use them in different, in different decision context. Thank you. Shahid. Yeah, thanks. I wanted to, to perhaps dress as the whole thing it's really fascinating for me to hear from the different speakers here on the panel. And what got me sort of curious is that, you know, we were once I was at the University of Minnesota a while back, where Jeanine is now and we were funded by DLE to do a free air carbon dioxide enrichment experiment and the unit there was the species. You know how many species one, two, four, eight, 16 things like that. I guess it was nine or 16. I was thinking that when it comes to the socio ecological work, I think Jack had published a paper some time ago saying that you know the household is the right unit, not the, not the individual, not the, not the county right. And then, you know, and so this is motivated by thinking about size presentation, which was talking about linking the microscopic to the macroscopic but in some case the microscopic was the bird, not the genome of the bird, not, you know, some particular focus of it. If you want to understand the macro pattern of the flocks, which were amazing. And you really needed to understand the level of the bird. But I saw a lot of heavy focus I was surprised actually at how much of DOE's resources are going towards, you know, genomics in I'll just add a little more example right now in ecology. One of the biggest, you know, sort of paradigm shifts has been to work on what we call the trade because we realize the traits of the organisms can link up to the functions of the ecosystems. But a trait might be specific leaf area, or rate of photosynthesis, or relative growth rate, and this is going to be a massively polygenic trait which the genome would not help you at all in terms of trying to link it all the way up. On the other hand, I can see when you're trying to look at say toxic algal blooms that understanding the genomics of the cyanobacteria and linking that with the lake is the geophysical unit actually makes sense. So to what extent, you know, is there, you know, sort of an interest in putting out RFPs or calls for research that actually begins with the right unit to lead to the to the right outcome. Or do you just say, Well, we're looking for research that's actually going to work on, you know, this massive genomic data or these really high resolution things. So are we going to say we're interested in this phenomenon, the right unit is the species, the organism, the trait. Sorry, I don't have a question. I know. And so, yeah, Todd. Yeah, yeah. So, Bravo. That's that's that that is the mark. And we run into this. It's not interagency. You know, it's not intergovernmental activities. We run into this right within our own office. We have the biological system science division the earthen environmental system sciences, those are operating at two vastly different scales. And we run into this all the time how do we bridge those scales. What kind of activity can we take on jointly that would help resolve the kinds of questions you were just asking. What what is the right, the right item to look at in explaining environments and I think we've struggled with that for years. I don't think we have an answer yet. But I mean that you hit them. You hit it right on the mark. We've been struggling with that for years. Something about it. I don't get a follow up question. So if I mean there, there is this big interest in traits and the proteome is more closely linked to traits and is there any interest in in DOE or mechanisms and DOA DOE to to shift the focus more towards multi omics proteomics omics sorts of research. Oh, yeah, I'd say we were kind of already there. I think we're doing that in maybe not at scale right now but we're certainly certainly looking at that in some of the programs that we fund. You know, it was just it was interesting I was just you reminded me of a talk we just had our PI meeting last week and so we're all busy talking about some of the new research coming out and I remember one of our one of the highlights from our keynote address keynote speaker was that when we actually go in and looking at environmental samples and we work in soil, for the most part, that certainly the metagenomics are not capturing the active community we're capturing a lot of dead biomass there and so we're, we need some resolution there to figure out what is actively active. The transcriptomics can help the proteomics can help. But we're just now getting to the point where we can actually do that more broader scale and soil that may help understand a little bit more of the active community in these systems. But it still doesn't make the link to the traits that we might want to look at at a larger scale. Thank you. Jeanine. Yeah, thanks. So I want to build on this idea of organisms as fundamental units and biological processes and go to Woody's comments about this international recognition that's come on the heels of climate change in terms of goals and by targets for global biodiversity framework and geo bonds efforts to have monitoring systems and coming up with ways to actually monitor biological patterns globally. And just pose the question. When we're considering continental scale biological research needs in this in this report. What are the bottlenecks that you see in integrating large scale pattern data remote sensing data with biological processes where organisms might justifiably be the the fundamental impacts of response interaction and our agencies generally interested in in working either towards the monitoring efforts or the goals and targets themselves of the global biodiversity framework. So those are two, two questions but they're related. Thanks, Jeanine. And were you specifically tossing that to Woody or open. So I'm curious, Woody about the bottlenecks for integrating large scale patterns with biological processes where organisms are units of a process, but I'm also interested in the everyone's view on like the role of agencies in working towards international goals and targets. Yeah, hi, Jeanine. Thanks. I mean NASA's been fortunate a little bit on the global side and that so much of our data is global data. And so we sort of had a remit to work globally for since we got started and that helps us think about things like climate and biodiversity loss in the global Other agencies may not have that that history or mandate even. So, but I do think yeah I mean there's clearly an interest in linking up with our partners overseas we do it all the time other agencies certainly do it as well. That's becoming increasingly important, not only because we're dealing with local synonyms because the expertise is truly global and to get the best of something authentic overseas. In terms of what's limiting again I'm going to just go back to what I was saying earlier and that is I do think our model. So modeling infrastructure and our basic understanding as it gets back to scale is still quite limiting. And so that limits our ability to assemble the models to get to the right targets. People were talking about earlier, your target depends on what you're trying to figure out and the target will change depending on what what your questions are but we still need to understand how things connect to get to that target. So there's a modeling piece there, which I view as sort of a more of a research challenge and then there's the data piece that which is more of a technical challenge. But these challenges, these technical and research challenges are intertwined and you can't you can't do the modeling without better you know without better data systems you can't design better data systems without a sense of why you're designing it for what. And so those two are really closely related. And that's why I think, I mean, as I said at NASA we're still getting out of sort of the mission mindset that made us very much not only in terms of our data systems but even the science teams using the data very mission oriented. And I think I know other agencies may have different missions but they generally work along discipline lines and getting beyond those discipline lines is always challenging because you're trained people do certain things and they do it and they keep doing they do it well. They just keep doing it. So I love the fact that they're bringing in all these. So she can obviously comments that EPA and elsewhere I think that's that's one way to sort of broaden the pie and get better at but to me from a NASA centric. Look, I'd say, you know, our models have to get better and the data systems have to get better but they have to do that in tandem. Separate them and expect one to make a large fans without the other. And then we just have to think across cross systems but you think across systems for us that means across missions but for other folks it may be across systems or be they social or physical or something. I hope that makes sense. Yeah, thank you. Yeah, I do keep thinking about the biology itself like how do we do better at connecting the biology to the patterns we can get from space. That that's all about scale to me all about scale. Because the organisms you talk about organisms are generally not filling the pixel by any means. Sometimes they're not even visible in the pixel. And so when I started these programs it was all I had to convince people that you know we should even be in the game and was able to do so with help folks on this on this panel today in terms of making the case that you can you can indirectly you can directly sense biodiversity or elements of biodiversity you can indirectly through model. Great, thank you. Scott, you have a question. I do. Thanks everybody for your presentations today it's been really interesting and informative. My question is somewhat related to Jack's initial question but I'm more in a sort of retrospective manner in terms of what announcements or programs have you done sort of across agencies maybe calls for proposals and I wonder about what lessons learned you might have from those for so for example Woody I know you in the past have had joint calls for proposals with NSF I forget which program maybe bio complexity or something like that. And I yeah so I'm mostly curious about how those sort of interagency calls have fared and if there are any lessons learned from this. I'm glad that Katarina put her hand up so I didn't have to just call on her because I know that she knows a lot about these types of initiatives. Yeah, well so I'm at NSF we've historically and I think increasingly lately. We try to really work as much as possible in the inner agency space, especially if we are kind of rallying around some of the grand challenge problems like, of course pandemic research ecology of infectious diseases, or biodiversity related research and climate Some of the long standing programs that we have had and I talked a little bit about that is of course the ecology and evolution of infectious disease program which is running now for 20 years, which has had long term participation from NIH and from USDA, and also has long term participation from international agencies such as the UK with UKRI and the NSFC National Natural Science Foundation of China and NRF in South Africa. We also have had dimensions of biodiversity program, which worked, you know with international partners. We have several other programs that are being stood up or have been stood up right now that mostly work across and NIH USDA DOE. And so the lessons learned is that I find that it's always takes a little bit of time to get these programs together, but often there is we find kind of common ground of our missions. And often it's a matter of kind of hashing out what are the connective pieces where each of the agency can kind of work in that particular mission space and connect. And what I find in general is that the communities that are supported through these inner agency missions are, of course, often very vibrant there's often very interesting research that comes out of those particular efforts. And a lot of this filters also down in what we call our core programs where you know we just have novel ideas bubbling up from these interactions. And I mean my colleagues from other agencies can speak to that it's it's not I mean there is always a level of bureaucracy that has to be kind of worked through. So it's not always a nice one on one plug and play kind of situation. But I think, in general, my experience has been that we've been pretty good to kind of make those connections and make them last as long as we can despite all the budget are craziness if you always have to deal with. Thanks Katarina. And we're coming up on the end where Jack is going to sort of wrap things up. But I wonder what he did you have something kind of quick to add. I always got something to add. Thanks Stephanie. Yeah, no, we've had some great success working with NSF Dimensions by Diversity. I mean, Janine and Scott and others have gotten a benefit. It's been great, great work. Katarina is exactly right. The bureaucracy can be challenging. It works best if you don't exchange money you just keep the money on your side of the interface. It also works best if there's some sort of talking about scale if there's actually scale in terms of the size of the programs involved and what they're able to bring to it that that also helps. For this activity continental scale one idea one thing we could do which getting back to its its beginning neon was initially not just about sites and airborne transects but there was going to be a satellite layer on top of it. To sort of connect the multiple neon sites and give you a true, you know, seamless data set, or maybe data sets plural across across the country with the satellite data I think we should get back to that and I probably bear a lot of responsibility for it's not getting there because I didn't pursue it at the time as hard as I should have but there's an example where if you really want to do this this cross scale integration of information and data. Getting data sets that are truly national wall to wall to bring together with the site data and the airborne platform data. So complimentary so throw that out there. Thank you so much everybody thanks I do remember that. All right, thanks so much you're all incredibly busy people and you're doing really important work, and we appreciate you taking the time to talk with us today. So I'll go ahead and hand it back over to Jack to wrap us up. Yeah, thank you so much. Stephanie and all the excellent speakers for the great presentation and stimulating discussion. I summarize some of the takeaway message in that I had in three words, starting with later see their complexity cooperation and capacity building complexity as Simon mentioned that in his keynote presentation. The core of sustainability is to try and understand the complexity because the whole world is so complex. And this issue has been touched upon or spoke about by all the speakers, one way or another. For example, Katharina mentioned that the prediction of the spatial and temporal dynamics is extremely complex. And Scott also mentioned this complex human environment interactions in response to multiple stressors and need a lot of insight from multiple disciplines. And in terms of collaboration, right to address those complexity problems, we need a lot of collaboration Simon emphasize that the need for and the power of collaboration to achieve global sustainability. And Katharina mentioned, you know, give examples about collaboration within agencies for integrated sciences, and they actually she mentioned that we integrated science at much larger scales. And when I mentioned collaboration and between agencies, she gave an excellent example about this collaboration between NIH and NSF centers for oceans and human health. And also, would you mentioned, bring different sources of data from different sensors and the field work together, and through platforms and the cloud collaborative cloud environment for data processing analysis, software development. And Scott mentioned, you know, integrated systems approaches. And in terms of capacity, there are many resources, data tools, methods and workforce. For example, part mentioned the user facilities and the computational facilities. And really mention the multi multi mission algorithms and analysis platform. And Katharina and Annika mentioned the importance of training of diverse workforce, and for different disciplinary integration. And which also require pay more attention to justice and equity issues. So, this and many other insight that I could not have time to talk about will really help us to address big and challenging questions in the future. And the many other wonderful ideas. I just don't have time to mention here. But the committee has included myself has learned so much today and yesterday, but would like to learn more. So, we are planning to have the second public information gathering session on June 15. So, everybody is welcome to join that session to a more detailed information will be posted on the website of the national economies later. And also, I want to thank the excellent keynote speakers yesterday and today and also the other speakers yesterday and today for their really useful insights. And really helpful information and very valuable perspectives. And they are fantastic job that Luis and Stephanie did in modeling the moderating the sessions yesterday and today is also greatly appreciated. I'm mostly grateful to the wonderful committee members and the staff team members of the national academies, including the staff study director cliff and Tricia has been really leading the way in organizing this webinar and cat and many other staff member also have been enormously hopeful in many ways. So, also, I'd like to thank the engaging audience for the active participation, including questions and for and their feedback and the input to the committee will be really helpful. Again, the input and feedback can be posted on the website of the national academies or email cliff. So, this is really remarkable today. So I want to thank you so much, everyone. And I will look forward to see you on June 15 during our second webinar. So enjoy the rest of the day. Thank you so much.