Master of Science / Department of Agronomy / Michel D. Ransom / Soil Taxonomy is the official soil classification system used in the United States and many other countries. Any soil in the world can be classified from the order to the family level using a set of classification keys that are currently in an eleventh edition. The classification system is quite complex and can be too complicated for beginning soil science students to understand and use. Thus, a national advisory working group of the National Cooperative Soil Survey developed an abbreviated guide called the Simplified Guide to Soil Taxonomy. The goal of the simplified guide is to help reduce the complexity of soil taxonomy and aid in the classification of soils from the order to the great group level. The purpose of this study was to evaluate the effectiveness of the simplified guided when used by students in soil science courses to classify soils as compared to traditional methods using the more detailed keys. Classes at Kansas State University were used in the study and included the laboratory sections of AGRON 305 (Soils) and AGRON 515 (Soil Genesis and Classification). Student learning was evaluated using pre and post-test scores, assignments, and evaluation surveys. Results from the fall and spring semesters of AGRON 305 vary based on pre and post test scores and the assignment. Written evaluations indicated that both methods were easy to understand, especially as the lab progressed, but students responded more favorably to the abbreviated descriptions of taxa, pictures, and hyperlinks associated with the simplified guide. The Simplified Guide to Soil Taxonomy can be used in introductory soils courses. However, it is more suited for mid to upper level soil science courses, such as AGRON 515, where students responded favorably to the shorter and more comprehensible descriptions of taxa at the order, suborder, and great group level.

The aim of Part One was to discover and investigate the physical and chemical properties of coal minesoils occurring within the Big South Fork National River and Recreation Area (BSF) in order to better understand the nature of these anthropogenic soils. In particular, this information was to identify which, if any, un-reclaimed or recently reclaimed minesoils were actively producing acid mine drainage (AMD) and what properties were inhibiting revegetation. Historical knowledge and maps were used to locate more than 30 un-reclaimed and reclaimed minesoil sites, which were mapped with GPS. Soil profiles were exposed on 18 sites and grab samples taken on another 12. The morphological properties of each full profile were described according to the National Soil Survey Handbook and samples were taken from each horizon. Chemical properties analyzed for include: particle size, acid-base account, pH, exchangeable aluminum, manganese oxides, soil organic carbon, cation-exchange capacity, exchangeable bases, Mehlich I-extractable elements, and total elemental concentrations. Significant differences in the following properties (averaged) were discovered between the un-reclaimed and reclaimed minesoils: slope, percent rock fragments, dominant lithology, net neutralization potential, pH, extractable aluminum, base saturation, several Mehlich I-extractable nutrients and total elemental concentrations. Hierarchical clustering analysis revealed similar findings and also highlighted instances where reclaimed minesoils were statistically more similar to un-reclaimed minesoils than to other reclaimed minesoils. This indicated that reclamation efforts may not have been completely successful on these sites. In Part Two, minesoil profiles were classified according to Soil Taxonomy and according to proposed amendments by the International Committee for Anthropogenic Soils (ICOMANTH). The ICOMANTH amendments provided more informative classifications for coal minesoils in the BSF however, shortcomings were noted. Additional recommendations were made and the minesoils were again classified according to these recommendations. Compared to both the Soil Taxonomy and the ICOMANTH classifications, those according to the proposed additional amendments revealed more of the unique properties of the minesoils studied in this project. The results of this study can aid the National Park Service with future land management of the minesoils located within the BSF boundaries and other users of drastically disturbed minesoils.

Data about the spatial variation of soil attributes is required to address a great number of environmental issues, such as improving water quality, flood mitigation, and determining the effects of the terrestrial carbon cycle. The need for a continuum of soils data is problematic, as it is only possible to observe soil attributes at a limited number of locations, beyond which, prediction is required. There is, however, disparity between the way in which much of the existing information about soil is recorded and the format in which the data is required. There are two primary methods of representing the variation in soil properties, as a set of distinct classes or as a continuum. The former is how the variation in soils has been recorded historically by the soil survey, whereas the latter is how soils data is typically required. One solution to this issue is to use a soil-landscape modelling approach which relates the soil to the wider landscape (including topography, land-use, geology and climatic conditions) using a statistical model. In this study, the soil-landscape modelling approach has been applied to the prediction of soil bulk density (Db). The original contribution to knowledge of the study is demonstrating that producing a continuous surface of Db using a soil-landscape modelling approach is that a viable alternative to the ‘classification’ approach which is most frequently used. The benefit of this method is shown in relation to the prediction of soil carbon stocks, which can be predicted more accurately and with less uncertainty. The second part of this study concerns the inclusion of expert knowledge within the soil-landscape modelling approach. The statistical modelling approaches used to predict Db are data driven, hence it is difficult to interpret the processes which the model represents. In this study, expert knowledge is used to predict Db within a Bayesian network modelling framework, which structures knowledge in terms of probability. This approach creates models which can be more easily interpreted and consequently facilitate knowledge discovery, it also provides a method for expert knowledge to be used as a proxy for empirical data. The contribution to knowledge of this section of the study is twofold, firstly, that Bayesian networks can be used as tools for data-mining to predict a continuous soil attribute such as Db and that in lieu of data, expert knowledge can be used to accurately predict landscape-scale trends in the variation of Db using a Bayesian modelling approach.

La Albufera de Valencia, por su alto valor paisajístico y ambiental, es uno de los humedales más importantes de la península ibérica. Declarada Parque Natural en 1986 está incluida también en la lista de zonas húmedas de importancia internacional para las Aves (Convenio RAMSAR). El agua es el principal recurso del parque y su ciclo natural determina la vida de éste. En este sentido desde la expansión del cultivo del arroz a principios del pasado siglo, la evolución del humedal ha quedado condicionada al complejo sistema de regadío que controla las entradas y salidas de agua del lago. El manejo del arrozal supone el paso de aguas superficiales desde las parcelas superiores a las de inferior cota, hasta llegar a los denominados ¿tancats¿ (unidades hidrológicas características de la zona, formadas por parcelas de arroz a cota inferior a la lámina de agua del lago y situadas en el anillo circundante a éste). Los problemas a los que se ha enfrentado el Parque en las últimas décadas se refieren principalmente a la calidad del agua y sus implicaciones con la salinidad del suelo. Aunque el parque ha sido objeto de diversidad de estudios, ni se han definido sus suelos ni tampoco se ha realizado un estudio exhaustivo de la relación de las aguas freáticas y superficiales respecto a la salinidad. Es por ello que nace el presente trabajo de investigación que pretende caracterizar y evaluar la calidad de las aguas y los suelos del Parque desde el punto de vista espacial y temporal con respecto a la salinidad. Para ello se ha establecido un plan de trabajo en cuatro líneas de actuación que corresponden al control de las aguas superficiales y freáticas de 133 piezómetros instalados, el control de 54 acequias que aportan aguas a las parcelas de arroz, el control del nivel freático y de lámina libre en los piezómetros y, por último, el estudio de los suelos. Los diferentes análisis realizado son pH y Conductividad Eléctrica (CE), Na+ , K+ , Cl- , SO4 -2 , HCO3 - , CO3 -2 , Ca+2, Mg+2, Total de Sólidos Disueltos (TDS), Relación de Adsorción de Sodio (RAS) para aguas; y textura, materia orgánica, carbonatos, color, Conductividad Eléctrica del extracto de saturación CEe, pH del extracto, además del valor n, la humedad de saturación y los elementos gruesos, hierro, además de calcular del extracto de saturación los cationes y aniones principales en suelos. El estudio de la evolución durante 32 meses de la calidad de las aguas en los 133 piezómetros y las 54 acequias han permitido establecer que la zona norte del lago sufre salinización por la influencia de la capa freática elevada que está íntimamente relacionada con la distancia al lago y la cota además de con el ciclo del cultivo del arroz. La salinidad en las muestras de acequias y las de lámina libre presentan valores de CE aceptables para el uso en el arroz, habiéndose detectado una salinización de estas por el efecto de la capa freática fluctuante y la salinidad de los suelos. La clasificación taxonómica de los suelos se agrupan en tres subórdenes: Aquents, Fluvents y Salids. Con todos los resultados expuestos se ha caracterizado dos recursos importantísimos en el humedal cuyo conocimiento era parcial o nulo puesto que no existían datos de cotas piezométricas ni de calidad de agua ni variables edáficas a tanto detalle y con una densidad de muestreo tan alta. / Moreno Ramón, H. (2013). Evaluación espacio-temporal de las aguas y suelos de la zona colindante al lago de la Albufera de Valencia: Intento de recuperación [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/32827 / Alfresco

Climate types, biome types, and soil orders are commonly used among physical geographers in research and to describe natural environmental characteristics. However, little attempt has been made to quantify the percentage of global land surface that is covered by combinations of climate types, biomes, and soil orders. This research overlays a world map of 31 climate types produced based on the Köppen-Geiger criteria using gridded NCAR/NCEP reanalysis monthly mean surface air temperature and precipitation data from 1981 to 2010 with global maps of eight biomes adapted from World Wildlife Federation and 12 soil orders from United States Natural Resources Conservation Service. Areas covered by each of the 2976 combinations are then calculated. Results suggest that, as expected, a few climate/biome/soil combinations are most common, such as desert climate/desert biome/entisols, tundra climate/tundra biome/gelisols, and desert climate/desert biome/aridisols. The local nature of soil properties causes small enclaves of unexpected combinations of climate, biome, and soils, and the 10 most extensive climate/biome/soil combinations occupy only one-quarter of the global land surface. The strong correspondence between climate and biome types validates the Köppen-Geiger criteria for categorizing climates based on vegetation realms, even today, despite the general paucity of data available when the criteria were established.

The ancient inhabitants of the Maya Lowlands enjoyed a long and fruitful period of growth which climaxed at around AD 800. At that time, millions of people successfully subsisted in a challenging environment that today only supports a population a fraction of that size. These facts, and the subsequent "Maya Collapse", are the impetus of many recent studies that utilize environmental data, in addition to conventional archaeology, to investigate this Maya mystery. Pedological studies and stable carbon isotope analysis of soil organic matter, combined with Geographic Information Systems (GIS) are three tools that can be used to answer crucial questions as to how the Maya managed their soil resources. GIS maps that indicated areas of best agricultural potential based on slope and soil type were used as a guide to opportunistically sample soils in an area south of Piedras Negras Guatemala – an area that was densely vegetated and unexplored. Soils that represented the different soil resources of the area were sampled with a bucket auger at 15 cm intervals. The samples were then tested in a laboratory for physical and chemical characteristics and δ-13C values were determined for soil organic matter. Soil taxonomical descriptions indicated that overall the soil resources of the area were very good as almost all the soils were classified as Mollisols - the most fertile of all the soil orders. The suite of great groups found was Haprendolls, Argiudolls, Argiaquolls and Udorthents. The characteristics which distinguish these great groups were used to further investigate relative agricultural productivity from an ancient soil resources point of view. Haprendolls were better drained and probably made for good agricultural soils given soil depth and rainfall were adequate. The Argiudolls and especially the Argiaquolls were probably less favored because of very high clay contents that made them more difficult to work with and poor drainage. Stable carbon isotope analyses revealed strong evidence for maize agriculture in some environments of the study area. δ-13C values as high as -16.6‰ (76% C4—Carbon) were observed in areas of significant soil accumulation in well drained and moderately drained soils. Minimal evidence of maize agriculture was found in more marginal environments such as those with little soil accumulation or poorly drained areas. Also, the pattern of the graph of δ-13C values versus depth indicated that ancient agriculture occurred continuously in some areas, but in other areas as distinguishable events. Finally, when the strength of the C4 signal was represented graphically and overlaid with a modified GIS agricultural potential map, a visual representation of the extent and degree of ancient agriculture was achieved. Our findings suggest that upland agriculture was favored by the ancient Maya of Piedras Negras and that the region between Piedras Negras and Yaxchilan was an agriculturally important breadbasket. The methods and results of this study provide foundational information for the investigation of ancient Maya agriculture. In future studies, it may be possible to more systematically map ancient agricultural fields and estimate the carrying capacity of a region based on its soil resources.

Post-mining land use potentials are greatly influenced by mine soil properties. I analyzed and classified coal mine soils in SW VA and mineral sands mine soils in SE VA to aid development of appropriate post-mining land use interpretations. For coal mine soils, long-term pedogenesis was assessed in sandstone (SS) and/or siltstone (SiS) spoils with and without surface amendments. For mineral sands mined lands, I evaluated their spatial variability with respect to underlying relic mining influences and rowcrop productivity. Coal mine subsoils densified as root-limiting layers formed that were not observed initially and all soils had weak pedogenic development (^Bw; cambic horizons), particularly SS derived soils. Initial rock spoil type strongly influenced coal mine soils over time (i.e., SS had coarser textures and lower subsoil pH vs. SiS). However, most soil chemical properties (e.g., pH, EC, CEC) became similar in ^A horizons over time. Fe-oxides increased, and extractable-P decreased with weathering, raising concerns for long-term P-availability. Organic amendments applied to rock spoil surfaces sustained higher total-N (sawdust and biosolids) and extractable P (biosolids). Soil carbon sequestration rates did not differ among rock types or amendments (0.16 to 0.28 Mg ha yr-1). Further, mineral sands mine soils were limited by densic contacts and short-range variability of important properties (texture) appeared related to underlying relic mining features (pits and berms). Yields in reclaimed soils were more variable than in adjacent undisturbed farmland, but mean yields were only slightly reduced for soybean in 2020. Coloration and Fe-oxide spectral indices had weak to moderate negative correlations with yield. Berm positions supported better soybean growth (three out of five sites), while pit positions were redder/darker (one out of five sites). Current Soil Taxonomy conveys anthropogenic origins at the family (e.g., spolic) and subgroup (e.g., Anthroportic) levels. Existing taxa and proposed Artesols order criteria both acknowledge effective soil depth x compaction limitations (Anthrodensic subgroup), but Artesols more effectively recognizes pedogenesis (Inceptic subgroup) and acknowledges mine soils at the highest level. The biggest management limitation for both mine soil types is root-limiting compaction; thus, future efforts should focus on defining depth ranges and taxonomic interpretations for densic contacts. / Doctor of Philosophy / Surface mining results in drastic disturbances to the original soil, land, and water features. Actual impacts vary due to local site conditions and methods used for mineral extraction and reclamation. Advancing reclamation science requires an understanding of the resulting mine soil properties and how they vary spatially and develop over time. This research program involved two very different mining scenarios and resultant mine soil types in Virginia that were both evaluated in terms of soil properties, taxonomic placements, and land use interpretations. First, I assessed Appalachian coal mine soils in southwestern Virginia following 34 years of soil development in sandstone (SS) and/or siltstone (SiS) derived overburden with and without surface amendments. Over time, rocky mine spoils transformed into weakly developed soil profiles, commonly with four to five total distinct layers (horizons), along with apparent "self-compacted" layers at depth. SS soils were coarser textured with somewhat better subsoil structure, while SiS soils were finer textured and had higher subsoil pH. However, many chemical properties were similar in the soil surface. Organic amendments and topsoil return imparted only subtle differences over time. A secondary objective was to assess mineral sands mine soils, which originate from recombined Coastal Plain sediments. Due to the nature of their wet deposition during final reclamation, these mine soils exhibited high variability across local landforms. Soil profiles over former berm positions were composed mostly of sandier materials, while pit positions had more variable materials and features. Reclaimed rowcrop yields were moderately correlated with bare soil remotely sensed variables. Soils in pit positions were redder in color due to higher clay. While yields were variable, especially in drier years, berms appeared to support better soybean growth, but results were inconsistent across fields. For both mine soil types, root-limiting compaction is their biggest impediment to productive use. Forestry is the predominant post-mining land use on former coal mines, while rowcrop production is becoming more common on former minerals sands mines. Since these two different post-mining environments present unique challenges for correctly interpreting their post-disturbance land-uses, it is important to convey their special properties (e.g., densic contacts) and limitations in their classification.

Agricultural yields in Northwest Yucatán are constrained by climate, thin soils, and low fertility. Despite this, the ancient Maya city of Chunchucmil Yucatán, Mexico, boasted an immense, dense, and wealthy population during the Middle Classic period (ca A.D. 400-700). Soil physical and chemical properties were explored to determine how the ancient Maya of Chunchucmil fed themselves. Soil profiles were collected from various locations within ancient Chunchucmil's suspected sustaining area. The physical and chemical properties, carbon isotopes, black carbon, and coprostanols of soil profiles sampled were compared to ancient rural settlement and remotely sensed images, such as AIRSAR (airborne synthetic aperture radar). Our objectives were to geographically determine the areas of agricultural importance and determine whether evidence of ancient agricultural intensification could be observed in the surrounding soil resources of Chunchucmil. Indigenous Maya of the area identify three major soil classes, boxlu'um, saklu'um, and kancab. The ancient Maya likely preferred kancab because it provided some security with higher soil moisture, greater soil depth, and improved nutrient availability. The land use capability is severely limited in the swamp/estuary and tzekel. The lack of rural settlement within these zones suggests that they were not used for cultivation in ancient times; however, the wood resources likely provided Chunchucmil with vital raw materials. The carbon isotopic signature of ancient C4 crops was not detected suggesting that either maize was not extensively produced or that the mix of native C3 and C4 plants in the savanna hid the signature. There were no soil chemical or biomarker evidences of ancient agricultural intensification, suggesting that ancient agriculture was mainly based on shifting cultivation at Chunchucmil. Concentrations of black carbon, calcium, phosphorus, potassium (Olsen Method), magnesium, and organic carbon within urban and rural settlements were enhanced by incidental human activities. We determined that the land requirement would have been extensive to sustain the population of Chunchucmil during the Middle Classic based on traditional agricultural methods. The ancient Maya of Chunchucmil likely traded marine and estuary products from the Gulf coast and other high value trade items for agricultural products from the nearby Puuc Hills.