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Exploring a Dynamic Soil Information System: Proceedings of a Workshop (2021)

Chapter: 5 Current Soil Information Systems

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Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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5

Current Soil Information Systems

The second panel discussion focused on the question “What soil information systems do we now have?” Moderated by organizing committee member Charles Rice of Kansas State University, the panel consisted of Mark Farrell from Australia’s Commonwealth Scientific and Industrial Research Organisation, Drew Kinney and Skye Wills, both from the Natural Resources Conservation Service (NRCS) at the U.S. Department of Agriculture (USDA), Luca Montanarella from the European Commission Joint Research Centre, Rik van den Bosch from the International Soil Reference and Information Centre (ISRIC), and Samantha Weintraub from the National Ecological Observatory Network (NEON). Each panelist offered a short statement and then the panel discussed the issue, taking questions from the moderator, each other, and audience members.

PRESENTATIONS

Mark Farrell
Commonwealth Scientific and Industrial Research Organisation

Speaking from Australia in a presentation that was prerecorded because of the time difference, Farrell said that the aim of Australia’s soil information systems, such as the Soil and Landscape Grid of Australia (SLGA), is to develop data products that are accessible to many types of users. In doing so, he said, the data should be harmonized and the system established in such a way that it can be continually added to and upgraded over time. Several soil-related projects have collected data over time, including the Australian Soil Resource Information System, individual state-level efforts, and projects carried out by researchers at universities and research agencies.

Substantial progress has been made in terms of making such data available through the SLGA web portal, which can be accessed through a web browser, Google Earth, or a data pull for use in global information systems or other spatial analysis workflows. This flexibility makes it possible for users ranging from individuals with casual interest up to

Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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major research institutions and land management projects to take advantage of the collected information.

The user base for these data and associated applications is diverse, widespread, and growing, Farrell said. Currently the main users are researchers and policy professionals from state and federal government departments who are either interested in furthering their understanding of agricultural or environmental issues or working on land use policy. However, the number of other types of users is growing. These users are likely to take advantage of more user-friendly interfaces; for example, agronomic consultants and even landholders can learn more about the soils that they manage. There is also increasing interest in using the data to value natural capital, he said, because the quality and health of soils can feature heavily in such valuations.

One limitation of the SLGA is that, at present, most of its spatial data are from a single point in time, Farrell said, and because soil sampling dates may differ by decades, data harmonization is a major challenge. Data are currently available at a 90-by-90-meter pixel resolution, but the goal is to reduce that to no more than 30 by 30 meters. Most of the available data are of the more traditional types, such as pH, soil depth, and landscape attributes. However, other types of information are also available, such as data on mineralogy and plant water-holding capacity.

Farrell concluded with a look to the future of Australia’s soil information systems. Currently, he said, there is a demand for time-series data that can be used to develop a better understanding of the trends of the state of Australia’s soils. Furthermore, the demand for information on soil biological variables, both on function and community structure, is growing. “By this, I mean a database of microbial sequences that is spatially resolved,” he said, “but also things like nutrient cycling and carbon turnover rates.” The value of such soil data can be enhanced by integrating them with food and produce traceability systems while capturing other variables, such as isotopic data. This effort is proving particularly important, he said, in helping the country improve its ability to trace food and thus protect its high-value export markets.

Drew Kinney
U.S. Department of Agriculture’s Natural Resources Conservation Service

USDA’s NRCS has several soil-related datasets, Kinney said, made possible by the National Cooperative Soil Survey effort. Several databases in the National Soil Information System (NASIS) provide traditional vector-based model data. The best known of these is the Soil Survey Geographic Database, or SSURGO, which is a county-based soil survey that traces back to 1935. The data are structured so that analyses can be performed at any scale, from a continental scale to the field level. Most of the data were captured at a scale of 1 to 24,000.

USDA has known for years that its vector-based dataset has certain limitations, Kinney said. For example, it does not lend itself well to modeling. In response, the department has been working to create its data more into a raster dataset, which is more conducive to modeling, and now produces several datasets in the raster format. One is gSSURGO, which has the same data as the SSURGO product but in a raster-based format.

Within the past 2 years, USDA has been offering the Gridded National Soil Survey Geographic Database (gNATSGO), which Kinney described as the department’s best available soils product. gNATSGO combines data from SSURGO and from STATSGO, which contains general soils maps, for cases when SSURGO has no data for a particular region. gNATSGO is proving to be quite popular, he said. Also within the past few years, USDA

Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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has been conducting raster soil surveys using remote sensing and digital elevation models, wetness indices, and satellite imagery and then using all of those data in an inference engine to create soil surveys, which are placed in the gNATSGO dataset. All of the raster datasets are available through USDA’s Geodata Gateway site.

USDA also provides point information collected during its soil survey work, with the laboratory data on soil collected in the field available through the Soil Characterization Database, which can be accessed on the USDA website. That database contains lab data on nearly 66,000 pedons—individual volumes of soil, usually 1 meter square on the surface and extending down to bedrock, so that all soil layers are captured. “We are also working on a pedon database,” Kinney added. “All the pedons that we’ve described in the field that we have, including those that we have not sampled, exist in our database, and we’re looking to deliver that information here in the near future.” USDA has about 456,000 full pedon descriptions that will be added to the database once they are cleaned and privacy issues addressed.

Kinney showed a complex representation of the NASIS database schema. Its National Soils Information System is not only what SSURGO products are exported from, which are available to the public, but is also internal to NRCS. It is a very robust and complex database, encompassing almost every aspect of day-to-day operations, including the planning that NRCS does within the NASIS database schema all the way to the data delivery mechanisms. The two predominant delivery mechanisms are the Web Soil Survey and a web service called Soil Data Access, where users can input queries to the Soil SSURGO database itself.

USDA’s available soil information, Kinney said, can be accessed at https://www.nrcs.usda.gov/wps/portal/nrcs/main/soils/survey/tools. The webpage has nine buttons that direct visitors to various datasets and applications, including some of the tools that USDA has developed to work with the data, such as raster datasets. Those tools are available for download as well.

Skye Wills
U.S. Department of Agriculture’s Natural Resources Conservation Service

Following Kinney’s presentation, Wills, who is also from NRCS, provided more details on the soil information products that the service provides. Noting that Kinney had provided an overview of finished data products as well as the complexity of the information that goes into NASIS, Wills said that she would provide an intermediate-level description of the details that are important to researchers.

She began by showing a figure that illustrates the key steps in collecting soil survey data for research (see Figure 5-1). Once samples are collected, they are placed into NASIS. From there, some samples are sent to the Kellogg Soil Survey Lab (KSSL) for a number of analyses, although based on the way in which KSSL analyzes and stores the data, neither the public nor even soil scientists need to interact with it, Wills said. After analysis and storage, the next step is to aggregate the various databases, at which point certain procedures, such as R scripts and NASIS queries, are conducted. This behind-the-scenes work, which most people never see, produces components and data map units that go into NRCS’s published map. “And then we can take those published maps and then we can do scripts and queries and all that stuff on them again,” she said. Wills then showed a complex representation of the KSSL samples to highlight “the nested hierarchy of complicated systems that leads to us having and providing soil data.”

In performing the work that leads to the soil databases, NRCS staff follow a series of guidance documents that cover topics such as soil sampling, lab procedures, and the storage and display of data. “We need guidance documents that take us all the way from the very

Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
×
Image
FIGURE 5-1 Key steps in the Natural Resources Conservation Service’s process for collecting soil survey data for research.
NOTE: KSSL = Kellogg Soil Survey Laboratory; NASIS = National Soil Information System; NCSS = National Cooperative Soil Survey.
SOURCE: Wills, slide 1.

basic stuff and relatively simple to the very precise: how do you actually put information into the system?” she said.

Wills then highlighted a very important but often overlooked element of the system: the people behind the information (see Figure 5-2). This group includes soil scientists who gather data, lab analysts who make measurements, and regional staff who conduct reviews at various points in the process. It is the interaction among the individual people and the quality assurance/quality control process that ensures the value of the agency’s products. Very few small data collections can complete all of the functions necessary for providing, maintaining, and making available so much high-quality information, she said.

Because the workshop title includes the word “dynamic,” Wills offered two ways in which the NASIS databases are dynamic. First, the system records when a site is visited, so if a site is visited on multiple occasions, there is a record of that and thus, how it changed over time. Second, even when multiple measurements are not recorded at a site over time, she said, there is an effort to infer what is happening over time from other data, such as land use and management information.

Referring to the development of the Rapid Carbon Assessment offered by NRCS, Wills explained that “we had to take our standardized guidance and our standardized databases and lay a new level on top of it.” All of the data have been collected and entered into the SSURGO products, but individual point measurements live in a giant Excel file on Wills’s desktop computer. This situation is not ideal, she acknowledged, but must suffice for now, in part because of the sensitivity of locations and in part because of the one-time nature of this project. The data can be shared, but that part of the process is not automated.

Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
×
Image
FIGURE 5-2 People in key steps in the Natural Resources Conservation Service’s process for gathering, analyzing, and reviewing soil survey data.
NOTE: IT = information technology; MLRA = Major Land Resource Area; NCSS = National Cooperative Soil Survey; NSSC = National Soil Survey Center.
SOURCE: Wills, slide 4.

In closing, Wills said that she and her colleagues are working on the next step in the project, which they are calling the Dynamic Soil Properties Hub. The idea is to link data from multiple USDA sources and apply models and interpretations to all of those data. This step will make it possible to bring in new types of information, such as remote sensing data and geographic datasets, and also to embed metadata, such as the details on the versions of the data, models, and standards. It is an ambitious project, she said, but a prototype is expected to be finished within a few months.

Luca Montanarella
European Commission Joint Research Centre

Beginning in the early 1990s, Montanarella said, the European Commission, which is the executive body of the European Union, began to compile the soil data systems of the EU’s various member states into a single system with a harmonized database. The process was long and quite tedious, he said, particularly because the various databases being aggregated had been collected at very different times, under very different conditions, and using very different methodologies and standards. Now, with the successful integration, he said, countries who are candidates to join the European Union have usually joined the European Soil Information System even before they enter the European Union.

To make the data accessible and understandable to the general public, the European Union prepared a series of documents, particularly soil atlases. The Soil Atlas of Europe was

Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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the first of many documents, and the European Union has also published soil atlases of other continents, including Africa, Latin America, and, now under preparation, Asia.

Montanarella said that the work to develop common soil information systems is not purely scientific, but rather is at the interface between science and policy making. “We are not a research organization,” he said. “We are a science policy interface within the European Commission” with a mission to supply scientific evidence to support EU policy making related to soils.

In particular, having completed the first scientific understanding of soils across the European Union, the center helped to develop a common legal framework for soils in the European Union, the Soil Thematic Strategy of 2006. This crucial framework justifies further investment in more sophisticated data collection exercises and more detailed information systems going forward. It sets forth a plan for managing, in a sustainable way, soil resources in the European Union. That plan is rooted in a vision of soils having many different functions—not only producing biomass in agriculture and forestry, but also storing, filtering, and transforming nutrients, substances, and water; protecting biodiversity; providing a physical and cultural environment for humans and human activities; providing raw materials; acting as a carbon pool; and serving as an archive of geological and archeological heritage.

This multifunctional view of soils, with seven different functions identified by the European Union, is crucial to the EU’s approach to soils, Montanarella said. It goes beyond property rights and enables legislation regarding the functions. “One crucial element of our legislation is that we don’t want to protect soils, we want to protect soil functions that are relevant to all EU citizens,” he said. The desire to document progress in protecting those seven functions is a significant part of the reason that the European Union wishes to gather and analyze information about soils.

An EU-wide soil monitoring system called the Land Use and Coverage Area frame Survey (LUCAS) is intended to detect changes in soil properties, which requires that regular monitoring with the same measurements is carried out in the same locations again and again over time. To do this, LUCAS takes measurements at about 25,000 points across the European Union that are highly georeferenced so that their locations and types of land use are well documented. LUCAS regularly surveys the points and follows a systematic approach to collecting the data and samples, which are kept in long-term storage after they are analyzed. One important step, Montanarella said, was the decision to abandon the usual approach of dividing analytic work across several laboratories in different EU member states and instead select a single laboratory to do all of the analytical work. Experience had shown that this approach is the only way to ensure consistency in the analyses, he said.

LUCAS’s fourth sampling survey is now under way; three earlier ones were completed in 2009, 2015, and 2018. There are plans to expand the system in the near future, Montanarella said, probably to 250,000 sites, or 10 times the current number. The list of parameters measured is evolving over time, he said, as different policy priorities emerge. The point measurements are input into models to create various sorts of maps, such as of carbon or phosphorus content, and results are regularly reported.

Finally, Montanarella mentioned the EU Soil Observatory, a new initiative of the European Commission that was launched in December 2020 in support of the European Green Deal, a new EU policy framework. Soils play a central role in the European Green Deal, which is focused on, among other things, climate change and diversity in the farm-to-fork strategy. Thus, the EU Soil Observatory will provide a much more structured and strengthened monitoring of soils than is possible with the current European Soil Information System, with the resulting data and information freely available through the European Soil Data Center.

Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
×

Rik van den Bosch
International Soil Reference and Information Centre

ISRIC is a small institute in the Netherlands, van den Bosch said, and its vision is to create a world in which “reliable and relevant soil information is freely available and properly used to address environmental and societal challenges.”

ISRIC has four workstreams. The first relates to standards setting. In partnership with the Food and Agriculture Organization (FAO) of the United Nations (UN), ISRIC works to set standards for measuring soil, analyzing soils, databases, interoperability, and providing data. The second is global data provisioning. The third is capacity building, which is geared toward national soil information institutes around the world, but predominantly in Africa. The fourth is applications of soil information.

One ISRIC product is the World Soil Information System (WoSIS), which is a point data repository. ISRIC serves as a custodian of soil information, working with researchers and others who have datasets but not the infrastructure to maintain those datasets and distribute their data. “They can send it to us, and we put it in our repository,” van den Bosch said. “We serve it so everybody can find it. It doesn’t get lost.” ISRIC has more than 450,000 profiles registered “as is” in its data repository from a wide range of data providers. Available data are cleansed and standardized using consistent procedures and then placed in the WoSIS database. At present, the repository contains about 200,000 standardized profiles that are publicly available with a Creative Commons CC-BY license. It also contains another 24,000 profiles that cannot be shared, but that can be used in ISRIC’s own applications.

Using the data from the point dataset, ISRIC produces a soil property map on a 250-by-250-meter global grid. The properties are predicted for each square on the grid with state-of-the-art modeling methods that provide both physical and chemical parameters up to a depth of 2 meters along with quantified uncertainties. When additional datasets become available with substantial amounts of new data, ISRIC runs through the modeling anew and updates its predictions. The point datasets and the grid products are available at www.soilgrids.org, and they have also been uploaded to Google Earth Engine.

At present, van den Bosch said, the point datasets and the grid products provide only basic soil parameters, but ISRIC is working to add more soil quality indicators in a quantitative way.

Most of the users of these products are global modelers from academia, he said, but UN organizations also use them. However, he added, these global products are not well suited for producing real impact on the ground. To help in that area, ISRIC is working with national soil information institutes to produce soil information systems for their own territories that use their own datasets and take advantage of their own knowledge of their area’s soils and their own clients and users.

In closing, van den Bosch said that FAO is working with the Global Soil Partnership to create the Global Soil Information System (GLOSIS), which will provide a standardized package to national institutions that enables them to build up their own national soil information systems relatively quickly using the GLOSIS methodology. Ultimately, he said, the goal is to connect those national nodes with each other through common standards and a global discovery hub so that users can explore the nodes of the different countries and get information from the entire system. The major benefit of this program, he said, is that it “can really help national institutions to get going quickly, especially those in the South, with setting up their own national soil information systems.”

Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
×

Samantha Weintraub
National Ecological Observatory Network

NEON is a continental-scale, U.S.-based observatory, Weintraub said. Of its 81 field sites, 47 are terrestrial, where soil, plants, and other things that grow on land are monitored (see Figure 5-3). It offers a total of 181 data products, including 15 soil data products, that are aimed at illuminating how the nation’s ecosystems are changing. Those products are very diverse, ranging from micrometeorology to disease ecology and biodiversity monitoring. “So soils is a small but important piece of the broader suite of things that are going on at the National Ecological Observatory Network,” she said.

NEON’s soil monitoring and measurements vary both temporally, from one-time measurements to minute-by-minute monitoring, and spatially, from point measurements to information over a scale of hectares to multiple square kilometers (see Figure 5-4). There is also a depth component, with some measurements focused on the surface while others go down to 1- or 2-meter depths.

The measurements use several of the NRCS standard methods, including both field and lab procedures for doing soil taxonomy, pathology, and geochemistry. “We sample for biogeochemical processes,” Weintraub said. “We measure soil carbon, soil and organic nitrogen, soil microbes, both through PLFA [phospholipid fatty acids] and genomic efforts.”

NEON has standardized procedures for data ingestion, creation, and sharing. The data are subject to initial quality control when first entered into the system, she said, followed by a great deal of processing, including quality assurance and algorithm calibration. “Some of the sensor data products actually need quite a bit of calculation and higher-level data algorithms to go from voltage from a sensor to unit of soil moisture, say, or temperature.”

Image
FIGURE 5-3 NEON field sites map.
SOURCE: Weintraub, slide 2.
Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
×
Image
FIGURE 5-4 NEON soil data products and archives.
SOURCE: Weintraub, slide 3.

Once processed, the data are published in the data repository where they are freely available through the NEON data portal. That portal also provides other resources, such as information on the protocols and algorithms used on the data and user guide documents that explain how the data are collected, curated, and published.

The “bread and butter” users of NEON are academic researchers, their students, post-docs, and, in general, people seeking to answer fundamental questions in ecology, soil science, biogeochemistry, and so on. However, many other groups use its resources, Weintraub said, for example, local land managers. NEON does not own the land where its sites are located; many sites are owned and managed by the U.S. Forest Service, and several sites are managed by The Nature Conservancy. “We know those land management partners are interested in trying to see how they can use our data to inform land management at the sites,” she said. Data from NEON are also used by other data repositories, such as IsoBank (a centralized database of stable isotope data) and Soils Data Harmonization (known by the acronym SoDaH), and some industry start-ups are exploring whether they can use NEON data and perhaps partner with NEON. Modelers are excited about using NEON’s standardized datasets, and some educators have taken advantage of the tutorials, lesson plans, and modules that NEON provides for teaching students how to use big, open ecological data, including soil data. Finally, NEON also has partnerships with several national labs.

DISCUSSION

To open the discussion, Rice asked Montanarella a question from Slack about the varying quality of testing among laboratories. It is a big problem, Montanarella said, at least in Europe. For example, for many years a forest soil monitoring system involved extensive

Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
×

inter-laboratory calibrations and various national laboratories performing analytical work. “It turned out,” he said, “that suddenly pH between Germany and France was changing across borders, or things like that, simply because measurements were done differently.” So, ensuring comparability of data when multiple laboratories are involved, particularly from different countries, is a major challenge. For this reason, the Joint Research Centre centralizes its sampling strategy and uses teams that are completely trained and managed by the center rather than teams from different countries. “Otherwise,” he said, “we would end up every time with a patchwork of different parameters, giving different responses according to national boundaries.”

Tomislav Hengl commented that LUCAS seems very advanced as a monitoring project and asked about its annual costs. Montanarella responded that every survey costs about €8 million ($9.4 million). Hengl opined that the cost is low, given that the entire continent is covered, and asked whether the cost will drop in the future because most of the data are based on soil spectroscopy. Montanarella answered that even while low, it remains difficult to convince the European parliament to fund that cost. “We really have to have good arguments that taxpayer money of European citizens should be used for soil monitoring.” With regard to reducing the cost, in the beginning the hope was that the cost would go down over time by getting rid of wet chemistry for many of the parameters and working instead with spectral reflectance data from the soil samples. However, he said, no evidence has emerged that moving away from wet chemistry for all parameters is a workable solution. Furthermore, he said, the largest portion of the cost is for sampling, not for analysis. Supporting a team of roughly 5,000 surveyors is quite costly.

Responding to Hengl’s comment regarding the value of having soil information down to 2 meters instead of the 20 or 30 centimeters used, Montanarella said that the depth was a compromise “due to the fact that we must decide if we want to have more points or if we want to have more in-depth sampling per point.” For the moment, he said, the shallower depth is the balance that they have settled on.

Next, Rice asked whether the end users of the systems described by the presenters are likely to change with time. For example, NEON data are aimed mostly at scientific researchers, while the EU data are aimed at policy makers. What are the opportunities and challenges in expanding beyond those user groups? Weintraub said that NEON’s data, designed for use by researchers, would need some sort of modeling or interpretation to become useful for policy makers and decision makers. Hopefully, she said, NEON’s database can be made accessible to increase its value for land managers and decision makers.

Following Weintraub, van den Bosch said that ISRIC is specifically focused on global users and is packaging the database’s information toward their needs. ISRIC would prefer to not modify the data to enhance usability by others, such as land managers, and instead work with national institutions to create the proper products for their stakeholders.

Wills said that NRCS takes a two-pronged approach. It wants more specific information, both spatially and temporally, which is really helpful for precision agriculture, land management decisions, and similar uses. However, NRCS is also interested in providing new types of information that do not exist in older information systems, such as soil quality indicators. USDA is working to understand how to incorporate the new information into a system. “So, we will need to make individual measurements,” she said, “but we’ll also need to figure out rules for aggregating measurements because just giving people a lot of raw data isn’t really our business.” NRCS is actively discussing ways to maintain its current user base and the current products that people rely on while expanding into these new areas. Kinney added that NRCS will probably deliver more data products via the Cloud in the future because of the size limitations of USDA’s current systems.

Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
×

In response to a question about the difference between LTER and NEON, Weintraub said that LTER is very question-driven. “Each LTER site has this theme, and they have specific questions and hypotheses that they are testing using their own methods and setting up the management of their LTER how they want to.” In direct contrast, NEON was designed to provide continental-scale datasets containing observations of ecological and environmental properties collected using standardized methods and sensors and analyzed using standardized lab techniques. The two are complementary, she said. Each has an important role to play in ecological data systems, albeit following very different approaches. Margaret O’Brien from the University of California, Santa Barbara, added via Slack that NEON is a top-down observatory designed to be a platform, whereas LTER is bottom up and has, as Weintraub said, specific research questions at each site. Furthermore, NEON is primarily terrestrial and located in the United States (including Alaska and Hawaii), whereas LTER is terrestrial, wetland, and marine, with some sites outside of the continental United States. Both are funded by NSF.

Alfred Hartemink observed that many databases have been developed with particular users in mind, for example, for those in agriculture. He asked the panelists how other communities of users could be served. “How do we serve the urban community who wants to have information on contaminants or hydrocarbons or PFAS [Per- and polyfluoroalkyl substances] or anything that really may be affecting many more people than what we currently serve with the current databases?” Weintraub responded that unfortunately, urban sites were de-scoped from NEON when it was operationalized. Rice added that a few LTER sites are urban. Kinney said that NRCS has considered this issue, but because of the diversity of audiences it serves, it cannot practically cater to any one specific community. Wills added that NRCS offers several different versions of its data, because it constantly works to incorporate new areas, such as urban gardening, to meet everyone’s needs.

Fenny van Egmond from ISRIC asked via Slack whether any U.S. experts were exploring the possibility of combining monitoring systems. In Europe, consideration is being paid to combining monitoring systems at different scales, such as the national efforts with LUCAS. David Lindbo from NRCS responded that what can be done is being done in this regard.

Via Slack, participants discussed the challenges faced by new entrants into the information space who want to use the data products but are unfamiliar with the systems. Kathe Todd-Brown responded that these challenges can be overcome by locating the data, understanding the methods associated with them, and then determining their interoperability for different use cases. These aspects of data are difficult to tackle when seeking an entry point into soil data. To address this difficulty, projects are striving to improve the searchability of archives (e.g., DataONE). Todd-Brown commented that the community appears to be pivoting toward data integration and harmonization, as well as the tools needed to achieve those outcomes. Finding a human point to field questions can be tricky. Larger organizations such ISRIC, LUCAS, and NRCS often have outreach arms, but smaller research groups such as ISRaD and ISCN cannot offer that kind of support.

Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Page 43
Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Page 44
Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Page 45
Suggested Citation:"5 Current Soil Information Systems." National Academies of Sciences, Engineering, and Medicine. 2021. Exploring a Dynamic Soil Information System: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26170.
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Page 46
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As a living substrate, soil is critical to the function of Earth's geophysical and chemical properties. Soil also plays a major role in several human activities, including farming, forestry, and environmental remediation. Optimizing those activities requires a clear understanding of different soils, their function, their composition and structure, and how they change over time and from place to place. Although the importance of soil to Earth's biogeochemical cycles and to human activities is recognized, the current systems in place for monitoring soil properties - including physical, chemical, and, biological characteristics - along with measures of soil loss through erosion, do not provide an accurate picture of changes in the soil resource over time. Such an understanding can only be developed by collecting comprehensive data about soils and the various factors that influence them in a way that can be updated regularly and made available to researchers and others who wish to understand soils and make decisions based on those data.

The National Academies of Sciences, Engineering, and Medicine convened key stakeholders in a workshop on March 2-4, 2021, to discuss the development of a dynamic soil information system. Workshop discussions explored possiblities to dynamically and accurately monitor soil resources nationally with the mutually supporting goals of (1) achieving a better understanding of causal influences on observed changes in soil and interactions of soil cycling of nutrients and gases with earth processes, and (2) providing accessible, useful, and actionable information to land managers and others. This publication summarizes the presentation and discussion of the workshop.

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