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This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.

Soils harbor enormously diverse bacterial populations, and soil bacterial communities can vary greatly in composition across space. However, our understanding of the specific changes in soil bacterial community structure that occur across larger spatial scales is limited because most previous work has focused on either surveying a relatively small number of soils in detail or analyzing a larger number of soils with techniques that provide little detail about the phylogenetic structure of the bacterial communities. Here we used a bar-coded pyrosequencing technique to characterize bacterial communities in 88 soils from across North and South America, obtaining an average of 1,501 sequences per soil. We found that overall bacterial community composition, as measured by pairwise UniFrac distances, was significantly correlated with differences in soil pH (r = 0.79), largely driven by changes in the relative abundances of Acidobacteria, Actinobacteria, and Bacteroidetes across the range of soil pHs. In addition, soil pH explains a significant portion of the variability associated with observed changes in the phylogenetic structure within each dominant lineage. The overall phylogenetic diversity of the bacterial communities was also correlated with soil pH (R(2) = 0.50), with peak diversity in soils with near-neutral pHs. Together, these results suggest that the structure of soil bacterial communities is predictable, to some degree, across larger spatial scales, and the effect of soil pH on bacterial community composition is evident at even relatively coarse levels of taxonomic resolution.

Soil pH is a measure of the activity of ionized H (H+) in the soil solution. Although other criteria are sometimes used as indices of lime needs of acid soils, the lime requirement (LR) is generally a measure of the base (lime) required to neutralize that fraction of the total acidity that must be neutralized to attain a desired soil pH that is favorable for crop growth. Hence the activity of H ion in the soil solutions is the intensity factor (index), whereas exchange acidity and LR are the capacity factors of soil acidity. Before the development of laboratory soil tests for determining the LR of individual soils, the amount of lime for a given soil condition and crop, or cropping sequence, was based on field experiments. Laboratory methods to determine LRs have involved soil-lime incubations, soil-base titrations, and soil-buffer equilibrations.

Although researchers have begun cataloging the incredible diversity of bacteria found in soil, we are largely unable to interpret this information in an ecological context, including which groups of bacteria are most abundant in different soils and why. With this study, we examined how the abundances of major soil bacterial phyla correspond to the biotic and abiotic characteristics of the soil environment to determine if they can be divided into ecologically meaningful categories. To do this, we collected 71 unique soil samples from a wide range of ecosystems across North America and looked for relationships between soil properties and the relative abundances of six dominant bacterial phyla (Acidobacteria, Bacteroidetes, Firmicutes, Actinobacteria, alpha-Proteobacteria, and the beta-Proteobacteria). Of the soil properties measured, net carbon (C) mineralization rate (an index of C availability) was the best predictor of phylum-level abundances. There was a negative correlation between Acidobacteria abundance and C mineralization rates (r2 = 0.26, P < 0.001), while the abundances of beta-Proteobacteria and Bacteroidetes were positively correlated with C mineralization rates (r2 = 0.35, P < 0.001 and r2 = 0.34, P < 0.001, respectively). These patterns were explored further using both experimental and meta-analytical approaches. We amended soil cores from a specific site with varying levels of sucrose over a 12-month period to maintain a gradient of elevated C availabilities. This experiment confirmed our survey results: there was a negative relationship between C amendment level and the abundance of Acidobacteria (r2 = 0.42, P < 0.01) and a positive relationship for both Bacteroidetes and beta-Proteobacteria (r2 = 0.38 and 0.70, respectively; P < 0.01 for each). Further support for a relationship between the relative abundances of these bacterial phyla and C availability was garnered from an analysis of published bacterial clone libraries from bulk and rhizosphere soils. Together our survey, experimental, and meta-analytical results suggest that certain bacterial phyla can be differentiated into copiotrophic and oligotrophic categories that correspond to the r- and K-selected categories used to describe the ecological attributes of plants and animals. By applying the copiotroph-oligotroph concept to soil microorganisms we can make specific predictions about the ecological attributes of various bacterial taxa and better understand the structure and function of soil bacterial communities.

In 1998, the International Union of Sciences (IUSS) officially adopted the world reference base for soil resources (WRB) as the Union's system for soil correlation. The structure, concepts, and definitions of the WRB are strongly influenced by the FAO-UNESCO legend of the soil map of the world (1-2). At the time of itsinception, the WRB proposed 30 Soil Reference Groups accommodating more than 200 (second level) soil units. WRB (3-5) was endorsed by the IUSS in 1998 and provides an opportunity to create and refine a common and global language for soil classification. WRB aims to serve as a framework through which ongoing soil classification throughout the world can be harmonized. The ultimate objective is to reach international agreement on the major soil groups to be recognized at a global scale as well as on the criteria and methodology to be applied for defining and separating them. Such an agreement is needed to facilitate the exchange of information and experience, to provide a common scientific language, to strengthen the applications of soil science, and to enhance the communication with other disciplines and make the major soil names into household names

As the largest pool of terrestrial organic carbon, soils interact strongly with atmospheric composition, climate, and land cover change. Our capacity to predict and ameliorate the consequences of global change depends in part on a better understanding of the distributions and controls of soil organic carbon (SOC) and how vegetation change may affect SOC distributions with depth. The goals of this paper are (1) to examine the association of SOC content with climate and soil texture at different soil depths; (2) to test the hypothesis that vegetation type, through patterns of allocation, is a dominant control on the vertical distribution of SOC; and (3) to estimate global SOC storage to 3 m, including an analysis of the potential effects of vegetation change on soil carbon storage. We based our analysis on >2700 soil profiles in three global databases supplemented with data for climate, vegetation, and land use. The analysis focused on mineral soil layers. Plant functional types significantly affected the vertical distribution of SOC. The percentage of SOC in the top 20 cm (relative to the first meter) averaged 33%, 42%, and 50% for shrublands, grasslands, and forests, respectively. In shrublands, the amount of SOC in the second and third meters was 77% of that in the first meter; in forests and grasslands, the totals were 56% and 43%, respectively. Globally, the relative distribution of SOC with depth had a slightly stronger association with vegetation than with climate, but the opposite was true for the absolute amount of SOC. Total SOC content increased with precipitation and clay content and decreased with temperature. The importance of these controls switched with depth, climate dominating in shallow layers and clay content dominating in deeper layers, possibly due to increasing percentages of slowly cycling SOC fractions at depth. To control for the effects of climate on vegetation, we grouped soils within climatic ranges and compared distributions for vegetation types within each range. The percentage of SOC in the top 20 cm relative to the first meter varied from 29% in cold arid shrublands to 57% in cold humid forests and, for a given climate, was always deepest in shrublands, intermediate in grasslands, and shallowest in forests (P < 0.05 in all cases). The effect of vegetation type was more important than the direct effect of precipitation in this analysis. These data suggest that shoot/root allocations combined with vertical root distributions, affect the distribution of SOC with depth. Global SOC storage in the top 3 m of soil was 2344 Pg C, or 56% more than the 1502 Pg estimated for the first meter (which is similar to the total SOC estimates of 1500–1600 Pg made by other researchers). Global totals for the second and third meters were 491 and 351 Pg C, and the biomes with the most SOC at 1–3 m depth were tropical evergreen forests (158 Pg C) and tropical grasslands/savannas (146 Pg C). Our work suggests that plant functional types, through differences in allocation, help to control SOC distributions with depth in the soil. Our analysis also highlights the potential importance of vegetation change and SOC pools for carbon sequestration strategies.

Soil Microbiology and Biochemistry in Perspective. Soil as a Habitat for Organisms and Their Reactions. Methods for Studying Soil Organisms. Components of the Soil Biota. Occurrence and Distribution of Soil Organisms. Carbon Cycling and Soil Organic Matter. Dynamics of Residue Decomposition and Soil Organic Matter Turnover. Ammonification and Nitrification. The Fate of Nitrates. Closing the Nitrogen Cycle: Return of Nitrogen to the Soil. Mycorrhizal Relationships. The Commercialization of Organisms. Phosphorus Transformations. Sulfur Transformations in Soil. Microbial Transformations of Metal. Chapter References and Suggested Reading. Subject Index.

Abstract The second edition of The Chemistry of Soils, published in 2008, has been used as a main text in soil-science courses across the world, and the book is widely cited as a reference for researchers in geoscience, agriculture, and ecology. The book introduces soil into its context within geoscience and chemistry, addresses the effects of global climate change on soil, and provides insight into the chemical behavior of pollutants in soils. Since 2008, the field of soil science has developed in three key ways that Sposito addresses in this third edition. For one, research related to the Critical Zone (the material extending downward from vegetation canopy to groundwater) has undergone widespread reorganization as it becomes better understood as a key resource to human life. Secondly, scientists have greatly increased their understanding of how organic matter in soil functions in chemical reactions. Finally, the study of microorganisms as they relate to soil science has significantly expanded. The new edition is still be comprised of twelve chapters, introducing students to the principal components of soil, discussing a wide range of chemical reactions, and surveying important human applications. The chapters also contain completely revised annotated reading lists and problem sets.

Abstract A DTPA soil test was developed to identify near‐neutral and calcareous soils with insufficient available Zn, Fe, Mn, or Cu for maximum yields of crops. The extractant consists of 0.005 M DTPA (diethylenetriaminepentaacetic acid), 0.1 M triethanolamine, and 0.01 M CaCl 2 , with a pH of 7.3. The soil test consists of shaking 10 g of air‐dry soil with 20 ml of extractant for 2 hours. The leachate is filtered, and Zn, Fe, Mn, and Cu are measured in the filtrate by atomic absorption spectrophotometry. The soil test successfully separated 77 Colorado soils on the basis of crop response to Zn, Fe, and Mn fertilizers. Critical nutrient levels must be determined separately for each crop using standardized procedures for soil preparation, grinding, and extraction. The critical levels for corn using the procedures reported herein were: 0.8 ppm for Zn, 4.5 ppm for Fe, and tentatively 1.0 ppm for Mn, and 0.2 ppm for Cu. Development of the soil test was based, in part, on theoretical considerations. The extractant is buffered at pH 7.30 and contains CaCl 2 so that equilibrium with CaCO 3 is established at a CO 2 level about 10 times that of the atmosphere. Thus, the extractant precludes dissolution of CaCO 3 and the release of occluded nutrients which are normally not available to plants. DTPA was selected as the chelating agent because it can effectively extract all four micronutrient metals. Factors such as pH, concentration of chelating agent, time of shaking, and temperature of extraction affect the amount of micronutrients extracted and were adjusted for maximum overall effectiveness.

The carbon sink capacity of the world's agricultural and degraded soils is 50 to 66% of the historic carbon loss of 42 to 78 gigatons of carbon. The rate of soil organic carbon sequestration with adoption of recommended technologies depends on soil texture and structure, rainfall, temperature, farming system, and soil management. Strategies to increase the soil carbon pool include soil restoration and woodland regeneration, no-till farming, cover crops, nutrient management, manuring and sludge application, improved grazing, water conservation and harvesting, efficient irrigation, agroforestry practices, and growing energy crops on spare lands. An increase of 1 ton of soil carbon pool of degraded cropland soils may increase crop yield by 20 to 40 kilograms per hectare (kg/ha) for wheat, 10 to 20 kg/ha for maize, and 0.5 to 1 kg/ha for cowpeas. As well as enhancing food security, carbon sequestration has the potential to offset fossil fuel emissions by 0.4 to 1.2 gigatons of carbon per year, or 5 to 15% of the global fossil-fuel emissions.

For centuries, biologists have studied patterns of plant and animal diversity at continental scales. Until recently, similar studies were impossible for microorganisms, arguably the most diverse and abundant group of organisms on Earth. Here, we present a continental-scale description of soil bacterial communities and the environmental factors influencing their biodiversity. We collected 98 soil samples from across North and South America and used a ribosomal DNA-fingerprinting method to compare bacterial community composition and diversity quantitatively across sites. Bacterial diversity was unrelated to site temperature, latitude, and other variables that typically predict plant and animal diversity, and community composition was largely independent of geographic distance. The diversity and richness of soil bacterial communities differed by ecosystem type, and these differences could largely be explained by soil pH (r(2) = 0.70 and r(2) = 0.58, respectively; P < 0.0001 in both cases). Bacterial diversity was highest in neutral soils and lower in acidic soils, with soils from the Peruvian Amazon the most acidic and least diverse in our study. Our results suggest that microbial biogeography is controlled primarily by edaphic variables and differs fundamentally from the biogeography of "macro" organisms.

Soil pH is probably the single most informative measurement that can be made to determine soil characteristics. Soil pH values in the neighborhood of two to three indicate the presence of free mineral acid, usually H2SO4. The ratio of water to soil in the suspension has the effect of increasing pH as the ratio increases. In soils with higher pH values, hydrolysis of basic cations tends to maintain a stable pH with dilution. A major factor influencing pH of soils is the salt content of the soil solution. Colorimetric methods for pH determination are based on weak acids or weak bases, the colors of which change with undissociated or dissociated forms. Glass used in the H+ -sensitive electrode is characterized by low electrical resistance, low melting point, and high Na content. In addition, the glass must have the tendency to hydrate easily if it is to be predictably related to the activity of H+.

The dependence of the dielectric constant, at frequencies between 1 MHz and 1 GHz, on the volumetric water content is determined empirically in the laboratory. The effect of varying the texture, bulk density, temperature, and soluble salt content on this relationship was also determined. Time‐domain reflectometry (TDR) was used to measure the dielectric constant of a wide range of granular specimens placed in a coaxial transmission line. The water or salt solution was cycled continuously to or from the specimen, with minimal disturbance, through porous disks placed along the sides of the coaxial tube. Four mineral soils with a range of texture from sandy loam to clay were tested. An empirical relationship between the apparent dielectric constant K a and the volumetric water content θ v , which is independent of soil type, soil density, soil temperature, and soluble salt content, can be used to determine θ v , from air dry to water saturated, with an error of estimate of 0.013. Precision of θ v to within ±0.01 from K a can be obtained with a calibration for the particular granular material of interest. An organic soil, vermiculite, and two sizes of glass beads were also tested successfully. The empirical relationship determined here agrees very well with other experimenters' results, which use a wide range of electrical techniques over the frequency range of 20 MHz and 1 GHz and widely varying soil types. The results of applying the TDR technique on parallel transmission lines in the field to measure θ v versus depth are encouraging.

Renard, K.G., G.R. Foster, G.A. Weesies, D.K. McCool, and D.C. Yoder, coordinators. Predicting Soil Erosion by Water: A Guide to Conservation Planning With the Revised Universal Soil Loss Equation (RUSLE). U.S. Department of Agriculture, Agriculture Handbook No. 703, 404 pp. The Revised Universal Soil Loss Equation (RUSLE) is an erosion model predicting longtime average annual soil loss (A) resulting from raindrop splash and runoff from specific field slopes in specified cropping and management systems and from rangeland. Widespread use has substantiated the RUSLE’s usefulness and validity. RUSLE retains the six factors of Agriculture Handbook No. 537 to calculate A from a hillslope. Technology for evaluating these factor values has been changed and new data added. The technology has been computerized to assist calculation. Thus soil-loss evaluations can be made for conditions not included in the previous handbook using fundamental information available in three data bases: CITY, which includes monthly precipitation and temperature, front-free period, annual rainfall erosivity (R) and twice monthly distributions of storm erosivity (E); CROP, including below-ground biomass, canopy cover, and canopy height at 15-day intervals as well as information on crop characteristics; and OPERATION, reflecting soil and cover disturbances that are associated with typical farming operations.

This introduction to modern soil chemistry describes chemical processes in soils in terms of established principles of inorganic, organic, and physical chemistry. The text provides an understanding of the structure of the solid mineral and organic materials from which soils are formed, and explains such important processes as cation exchange, chemisorption and physical absorption of organic and inorganic ions and molecules, soil acidification and weathering, oxidation-reduction reactions, and development of soil alkalinity and swelling properties. Environmental rather than agricultural topics are emphasized, with individual chapters on such pollutants as heavy metals, trace elements, and inorganic chemicals.

Abstract A new and relatively simple equation for the soil‐water content‐pressure head curve, θ( h ), is described in this paper. The particular form of the equation enables one to derive closed‐form analytical expressions for the relative hydraulic conductivity, K r , when substituted in the predictive conductivity models of N.T. Burdine or Y. Mualem. The resulting expressions for K r ( h ) contain three independent parameters which may be obtained by fitting the proposed soil‐water retention model to experimental data. Results obtained with the closed‐form analytical expressions based on the Mualem theory are compared with observed hydraulic conductivity data for five soils with a wide range of hydraulic properties. The unsaturated hydraulic conductivity is predicted well in four out of five cases. It is found that a reasonable description of the soil‐water retention curve at low water contents is important for an accurated prediction of the unsaturated hydraulic conductivity.

Soils collected across a long-term liming experiment (pH 4.0-8.3), in which variation in factors other than pH have been minimized, were used to investigate the direct influence of pH on the abundance and composition of the two major soil microbial taxa, fungi and bacteria. We hypothesized that bacterial communities would be more strongly influenced by pH than fungal communities. To determine the relative abundance of bacteria and fungi, we used quantitative PCR (qPCR), and to analyze the composition and diversity of the bacterial and fungal communities, we used a bar-coded pyrosequencing technique. Both the relative abundance and diversity of bacteria were positively related to pH, the latter nearly doubling between pH 4 and 8. In contrast, the relative abundance of fungi was unaffected by pH and fungal diversity was only weakly related with pH. The composition of the bacterial communities was closely defined by soil pH; there was as much variability in bacterial community composition across the 180-m distance of this liming experiment as across soils collected from a wide range of biomes in North and South America, emphasizing the dominance of pH in structuring bacterial communities. The apparent direct influence of pH on bacterial community composition is probably due to the narrow pH ranges for optimal growth of bacteria. Fungal community composition was less strongly affected by pH, which is consistent with pure culture studies, demonstrating that fungi generally exhibit wider pH ranges for optimal growth.

Still the Gold Standard Resource on Trace Elements and Metals in SoilsThis highly anticipated fourth edition of the bestselling Trace Elements in Soils and Plants reflects the explosion of research during the past decade regarding the presence and actions of trace elements in the soil-plant environment. The book provides information on the biogeoch

Thoroughly updated and revised, this second edition of the bestselling Soil Sampling and Methods of Analysis presents several new chapters in the areas of biological and physical analysis and soil sampling. Reflecting the burgeoning interest in soil ecology, new contributions describe the growing number and assortment of new microbiological