Mapping Soils under Water

Soil survey and mapping is one of the most fundamental and best-known applications of pedology. The preparation of soil maps began in the 19th century (Yaalon, 1997), but systematic county-based soil surveys began in the 20th century in the United States (Simonson, 1987, p. 3). The production of soil maps based on systematic soil surveys has been one of the primary driving forces in pedologic research in both academic and governmental settings in the United States and worldwide through much of the 20th century (Simonson, 1987, 1997; Yaalon and Berkowicz, 1997). For example, soil survey and mapping has been a primary function of the USDA since 1899 (Simonson, 1987, p. 3; Soil Survey Division Staff, 1993, p. 11). Soil maps have been prepared for a variety of uses at scales ranging from a few hectares to those of continental and global magnitude. Published soil surveys contain a wealth of data on landscapes as well as soils, but are generally an underused (and likely misunderstood) resource in geoarchaeology, probably because of their agricultural and land-use orientation. This chapter presents a discussion of what soil surveys are (and are not) and potential as well as realized applications in archaeology. Much of the discussion focuses on the county soil surveys published by the USDA because they are so widely available, although applications of other kinds and scales of soil maps that have been applied in archaeology or that have archaeological applications also are discussed. Many countries in the world have national soil surveys whose primary mission is the mapping and inventorying of the nation’s soil resource. In the United States, soil survey is a cooperative venture of federal agencies, state agencies (including the Agricultural Experiment Stations), and local agencies, coordinated by the National Cooperative Soil Survey (Soil Survey Division Staff, 1993, p. 11). The principal federal agency involved in soil survey is the National Resource Conservation Service (NRCS; formerly the Soil Conservation Service, SCS) of the USDA. The mapping of soils by the NRCS/USDA is probably the agency’s best-known activity. Its many published county soil surveys are its most widely known and widely used product.

Annals of the New York Academy of SciencesVolume 691, Issue 1 p. 267-269 Carotenoids Slow the Growth of Small Cell Lung Cancer Cellsa L. J. GALLIGAN, L. J. GALLIGAN Food Science and Nutrition Research Center, University of Rhode Island, 530 Liberty Lane, West Kingston, Rhode Island 02892-1802 and Rhode Island Hospital/Brown University, Providence, Rhode Island 02903Search for more papers by this authorC. L. JACKSON, C. L. JACKSON Food Science and Nutrition Research Center, University of Rhode Island, 530 Liberty Lane, West Kingston, Rhode Island 02892-1802 and Rhode Island Hospital/Brown University, Providence, Rhode Island 02903Search for more papers by this authorL. E. GERBER, L. E. GERBER Food Science and Nutrition Research Center, University of Rhode Island, 530 Liberty Lane, West Kingston, Rhode Island 02892-1802 and Rhode Island Hospital/Brown University, Providence, Rhode Island 02903Search for more papers by this author L. J. GALLIGAN, L. J. GALLIGAN Food Science and Nutrition Research Center, University of Rhode Island, 530 Liberty Lane, West Kingston, Rhode Island 02892-1802 and Rhode Island Hospital/Brown University, Providence, Rhode Island 02903Search for more papers by this authorC. L. JACKSON, C. L. JACKSON Food Science and Nutrition Research Center, University of Rhode Island, 530 Liberty Lane, West Kingston, Rhode Island 02892-1802 and Rhode Island Hospital/Brown University, Providence, Rhode Island 02903Search for more papers by this authorL. E. GERBER, L. E. GERBER Food Science and Nutrition Research Center, University of Rhode Island, 530 Liberty Lane, West Kingston, Rhode Island 02892-1802 and Rhode Island Hospital/Brown University, Providence, Rhode Island 02903Search for more papers by this author First published: December 1993 https://doi.org/10.1111/j.1749-6632.1993.tb26191.xCitations: 4 a This work was supported in part by the Rhode Island Agricultural Experimental Station and the University of Rhode Island Foundation. This paper is Rhode Island Agricultural Experiment Station Publication No. 2901. AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume691, Issue1Carotenoids in Human HealthDecember 1993Pages 267-269 RelatedInformation

Science-based management of shallow-water habitats is limited by information on the spatial distribution of properties of sediments. This limitation in part stems from the lack of an adequate model or system to classify and delineate subaqueous soil types (sediments). Present classification systems are inadequate because the existing paradigm does not actually consider them as “soils” but merely as “sediments”. Field observations suggest that these sediments could be better understood as “soils”, and the present paradigm could be modified to incorporate a new one—a pedological paradigm. We propose the application of a pedological paradigm for subqueous soils of subtidal habitats to develop ecological interpretations of subaqueous soil types and apply an inventory of subaqueous soil resources for management of estuarine shallow-water habitats. *** DIRECT SUPPORT *** A01BY074 00009

Rapid changes in land use in many areas of the USA, and evolving concepts of soils and soil mapping have resulted in the need to update information gathered as part of the National Cooperative Soil Survey Program. In Florida, because of optimum soil conditions, large amounts of soils information can be gathered at a rapid rate by using ground‐penetrating radar (GPR). The information is being used to update soil surveys. Soil maps of the older soil survey report were evaluated first in order to determine if the map unit delineations consistently separate mappable landform and vegetative features. Using GPR, transects were made within randomly selected map unit delineations. Soils were identified and classified using conventional methods and their respective proportion and distribution along the transects were determined using the GPR imagery. These data were statistically analyzed to estimate the variability and composition of closely similar soils within each map unit and to justify correlation decisions. These data are presented in descriptive as well as tabular form in the published soil surveys. When compared to costs for traditional methods, the costs for updating soil survey information with GPR were dramatically reduced.

Use of soil information to determine application of ground penetrating radar

To remain relevant in a changing world, soil survey and soil science need to look beyond the traditional to urban applications. Urban and suburban areas generally have the highest population densities and land values and arguably the greatest need for the ecosystem services that soil can provide. The urban environment poses a distinctive set of challenges for soil scientists. The description, classification, and mapping of soils in human-altered and human-transported materials is the charge of the field soil scientist, extending above and beyond the urban setting. Environmental professionals, planners, educators, and students in urban areas are often unfamiliar with soil survey and soil science in general. This paper discusses a successful approach to establishing a soil survey or soil science program in the urban community. For over 20 years, the United States Department of Agriculture Natural Resources Conservation Service (USDA-NRCS) and the New York City Soil and Water Conservation District (NYCSWCD) have conducted a soil survey program in New York City, producing multiple soil surveys at different scales, culminating in a 1:12000 scale survey posted on the Web Soil Survey site in 2014. The multifaceted program has also included onsite investigations, research projects, and an education and outreach component including lectures, training sessions, and workshops, as well as volunteer and internship opportunities. New and innovative approaches in soil survey methods, product design and delivery, and outreach have been used, as appropriate, to best fit the needs of the urban environment. The NYC Soil Survey program has built a succession of partnerships with government agencies, colleges, universities, and community and commercial groups, resulting in a variety of products and services to meet local soil science needs. Over time, the program has successfully been able to raise awareness of soil science in the urban environment, establish a USDA-NRCS presence in the City, and provide useful soil information to an underserved segment of the population. Making the local connection, listening to local needs, offering a multifaceted and wide array of soil science-related services, exploring innovative approaches, and creating partnerships have shown to be successful components of establishing a soil survey program in the urban environment.

This study was conducted to examine relationships among specific physical self-perceptions, a more general physical self-worth, and global self-esteem in an adult population between the ages of 30 and 65. Adults from several intact groups (N=260) were given the Physical Self-Perception Profile (PSPP) (Fox and Corbin, 1989), Rosenberg's Self-Esteem Inventory (SEI) (Rosenberg, 1965), and several exercise history questions (Fernhall and Ausmus, 1987). The subjects were selected from members of the Saint Nicholas Greek Orthodox Church community in Lexington, Massachusetts; members of the YMCA in Melrose, Massachusetts; employees of Coldwell Banker Realtors, North Kingstown, Rhode Island; members of the Adult Fitness Program at the University of Rhode Island, Kingston, Rhode Island; and members of the Senior Swim Class, at the University of Rhode Island, Kingston, Rhode Island. Scale structure, relationships, and criterion validity were determined for the specific physical self-perceptions, physical self-worth, and global self-esteem. The coefficients between physical self-worth and the four self-perceptions (r's between .785 and .548 for females; r's between .798 and .623 for males) were significantly greater (p<.05) than the coefficients between the specific self-perceptions and global self-esteem (r's of between .564 and .247 for females: r's of between .544 and .316 for males). The factor analysis exhibited over lapping between physical self-worth and attractive body, but the four specific self-perceptions were shown to be independent. The PSPP scales were found to have good criterion validity. The physical condition subscale had the best convergent validity with physical activity of all the subscales. The Physical Self-Perception Profile (PSPP) was able to significantly{p<.001) discriminate between exercisers and non-exercisers. Using discriminant function analysis a total of 84.56 % of all female subjects were properly classified, while a total of 78.38% of all male subjects were properly. It was also determined that condition{p<.001) and strength(p<.02) were the only subscales which significantly distinguished between subjects who participated in an organized fitness program and those who did not participate. The four specific physical self-perception scales of the PSPP were found to be valid, and independent. However, the physical self-worth scale was found to be interdependent with the attractive body scale. This questions the ability of the physical self-worth scale to act as a mediating variable, and has also led to the recommendation that the scale not be utilized in conjunction with the specific self-perception scales until it is shown to be truly independent.

Land Grant Education in Rhode Island began with the awarding of 1862 Morrill Act funds to Brown University, making it Rhode Island's first Land Grant College. Continuing controversy over the next two decades mostly through Rhode Island's Grange and other farm organizations led to the formation of the Rhode Island College of Agriculture and Mechanic Arts (RICAM now the University of Rhode Island or URI). From the establishment of the Rhode Island Agricultural Experiment Station (RIAES) in 1888, station scientists engaged in a wide variety of Extension activities with local farmers and fishermen. The second president of RICAM now the University of Massachusetts). While at MAC he established an Extension Department there which further influenced the creation of the federal Smith-Lever Act of 1914 that established a Cooperative Extension program at all Land Grant Colleges nationwide. Later in 1966, administrators and faculty at URI made contributions to the expansion of the Land Grant philosophy toward the seacoast through the National Sea Grant College and Program Act of 1966. A Sea Grant College Act first proposed in 1963 by Athelstan F. Spilhaus of the University of Minnesota. It was later championed by John D. Knauss of the URI who worked with Sen. Claiborne Pell of Rhode Island in promoting the Sea Grant College and Program Act in 1965. First hearings for the Sea Grant bill were on 2 May 1966 at the URI campus in Kingston. The Smith-Lever Act Cooperative Extension programming philosophy was explicitly used by Pell as the model for the Sea Grant Marine Advisory Service, which is now successfully serving coastal communities nationwide.

Legacy soil maps as a covariate in digital soil mapping: A case study from Northern Iran

1958 The image above was taken in the spring of 1958 by Dr. Dick Arnold during the progressive field review of Fulton–Montgomery Counties Soil Survey in New York. From left to right: in red cap, Al Southard, soil scientist from Cornell University; Don Flora, area soil specialist out of Syracuse, NY; standing, Marlin Cline, New York soil correlator; in plaid shirt, Ray Marshall, SCS-New York, state soil scientist; and, on extreme right, is Alan Tallerico, SCS party member. Photo was taken by Dick Arnold, who was the project leader at the time, with Al Southard, party member, and both were university employees. Note the red cap on Al Southard. Both Al Southard and Dick Arnold were university mappers. Both had red caps or Ivy League berets they bought at the Cornell bookstore. However, Al Southard's red cap succumbed to harsh field conditions while finishing up the Fulton-Montgomery survey, while Dick's is preserved at the National Soil Survey Center, Lincoln, NE. Soil Survey Progress Field Review of Fulton-Montgomery Counties, New York. 1959 In the image above, taken in May 1959, Al Southard, on the left, was now the project leader for Fulton–Montgomery Counties, NY. Al had just accepted the project leader position, replacing Dick Arnold, the previous project leader, who had returned for graduate school at Cornell University. Eventually, around 1980, Dr. Arnold became the soil survey director in Washington, DC. In the center is Dr. George Nelson Coffey, who had been head of soil classification for the Bureau of Soils from 1905 to 1908 and was a contemporary with Curtis Marbut. Dr. Coffey was 84 years old and retired at the time this photo was taken. He planned a day in the field since he was close by, visiting relatives in Gloversville, NY. On the right is Leo Handler, a work unit conservationist, who lived and worked nearby. Dr. George N. Coffey, former employee of the Bureau of Soils, visits the Fulton–Montgomery Counties Soil Survey Crew 1964 Above is an image from the August 1964 final field review taken by Dr. Al Southard in Powder River County in southeastern Montana. At this time, Dr. Southard was Assistant Professor of Soil Science at Montana State University and the National Cooperative Soil Survey cooperator for Montana. Pictured from left to right are Dave Cawfield, state soil scientist of Montana in white hat; Ron Mosher, assistant state soil scientist of Montana, sitting and in plaid shirt; Clint Mogen, SCS soil correlator from the Bozeman State office, kneeling; Roy Simonson, national correlator out of Beltsville, holding his tie and who was known to be always well dressed for field reviews; John Parker, Powder River County soil survey project leader, leaning on the car; and Andy Aandahl, regional correlator from the NSSC, holding the bag. Soil Survey Progress Field Review in Powder River County, Montana Submissions courtesy Susan B. Southard, USDA-NRCS soil scientist, Davis, CA and Dr. Alvin Reid Southard, Professor Emeritus of Soil Science, Utah State University, Logan, UT.

Automated soil inference under fuzzy logic

Soil Survey HorizonsVolume 48, Issue 4 p. 90-92 Article Moorings: An Interpretation from the Coastal Zone Soil Survey of Little Narragansett Bay, Connecticut and Rhode Island Deborah A. Surabian, Corresponding Author Deborah A. Surabian Soil Scientist debbie.surabian@ct.usda.gov NRCS Connecticut State Office, Tolland, CTSearch for more papers by this author Deborah A. Surabian, Corresponding Author Deborah A. Surabian Soil Scientist debbie.surabian@ct.usda.gov NRCS Connecticut State Office, Tolland, CTSearch for more papers by this author First published: 04 August 2015 https://doi.org/10.2136/sh2007.4.0090Citations: 3Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article.Citing Literature Volume48, Issue4Winter 2007Pages 90-92 RelatedInformation

Most estimates of regional and global soil carbon stocks are based on extrapolations of mean soil C contents for broad categories of soil or vegetation types. Uncertainties exist in both the estimates of mean soil C contents and the area over which each mean should be extrapolated. Geographic information systems now permit spatially referenced estimates of soil C at finer scales of resolution than were previously practical. We compared estimates of total soil C stocks of the state of Maine using three methods: (1) multiplying the area of the state by published means of soil C for temperate forests and for Spodosols; (2) calculating areas of inclusions of soil taxa in the 1:5,000,000 FAO/UNESCO Soils Map of the World and multiplying those areas by selected mean carbon contents; and (3) calculating soil C for each soil series and map unit in the 1:250,000 State Soil Geographic Data Base (STATSGO) and summing these estimates for the entire state. The STATSGO estimate of total soil C was between 23% and 49% higher than the common coarse scale extrapolations, primarily because STATSGO included data on Histosols, which cover less than 5% of the area of the state, but which constitute over one-third of the soil C. Spodosols cover about 65% of the state, but contribute less than 39% of the soil C. Estimates of total soil C in Maine based on the FAO map agreed within 8% of the STATSGO estimate for one possible matching of FAO soil taxa with data on soil C, but another plausible matching overestimated soil C stocks. We also compared estimates from the 1:250,000 STATSGO database and from the 1:20,000 Soil Survey Geographic Data Base (SSURGO) for a 7.5 minute quadrangle within the state. SSURGO indicated 13% less total soil C than did STATSGO, largely because the attribute data on depths of soil horizons in SSURGO are more specific for this locality. Despite localized differences, the STATSGO database offers promise of scaling up county soil survey data to regional scales because it includes attribute data and estimates of areal coverage of C-rich inclusions within map units. The spatially referenced data also permit examination of covariation of soil C stocks with soil properties thought to affect stabilization of soil C. Clay content was a poor predictor of soil C in Maine, but drainage class covaried significantly with soil C across the state.

Two soil mapping methodologies at different scales applied in the same area were compared in order to investigate the potential of their combined use to achieve an integrated and more accurate soil description for sustainable land use management. The two methodologies represent the main types of soil mapping systems used and still applied in soil surveys in Greece. Diomedes Botanical Garden (DBG) (Athens, Greece) was used as a study area because past cartographic data of soil survey were available. The older soil survey data were obtained via the conventional methodology extensively used over time since the beginnings of soil mapping in Greece (1977). The second mapping methodology constitutes the current soil mapping system in Greece recently used for compilation of the national soil map. The obtained cartographic and soil data resulting from the application of the two methodologies were analyzed and compared using appropriate geospatial techniques. Even though the two mapping methodologies have been performed at different mapping scales, using partially different mapping symbols and different soil classification systems, the description of the soils based on the cartographic symbols of the two methodologies presented an agreement of 63.7% while the soil classification by the two taxonomic systems namely Soil Taxonomy and World Reference Base for Soil Resources had an average coincidence of 69.5%.

Ranch-Level Economics of Lesser Prairie Chicken Conservation Practice Implementation