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USGS1994

Estimates of soil ingestion by wildlife

Many wildlife species ingest soil while feeding, but ingestion rates are known for only a few species. Knowing ingestion rates may be important for studies of environmental contaminants. Wildlife may ingest soil deliberately, or incidentally, when they ingest soil-laden forage or animals that contain soil. We fed white-footed mice ( Peromyscus leucopus ) diets containing 0-15% soil to relate the dietary soil content to the acid-insoluble ash content of scat collected from the mice. The relation was described by an equation that required estimates of the percent acid-insoluble ash content of the diet, digestibility of the diet, and mineral content of soil. We collected scat from 28 wildlife species by capturing animals, searching appropriate habitats for scat, or removing material from the intestines of animals collected for other purposes. We measured the acid-insoluble ash content of the scat and estimated the soil content of the diets by using the soil-ingestion equation. Soil ingestion estimates should be considered only approximate because they depend on estimated rather than measured digestibility values and because animals collected from local populations at one time of the year may not represent the species as a whole. Sandpipers ( Calidris spp.), which probe or peck for invertebrates in mud or shallow water, consumed sediments at a rate of 7-30% of their diets. Nine-banded armadillo ( Dasypus novemcinctus , soil = 17% of diet), American woodcock ( Scolopax minor , 10%), and raccoon ( Procyon lotor , 9%) had high rates of soil ingestion, presumably because they ate soil organisms. Bison ( Bison bison , 7%), black-tailed prairie dog ( Cynomys ludovicianus , 8%), and Canada geese ( Branta canadensis , 8%) consumed soil at the highest rates among the herbivores studied, and various browsers studied consumed little soil. Box turtle ( Terrapene carolina , 4%), opossum ( Didelphis virginiana , 5%), red fox ( Vulpes vulpes , 3%), and wild turkey ( Meleagris gallopavo , 9%) consumed soil at intermediate rates. Ingested soil may be the principal means of exposure to some environmental contaminants or the principal source of certain minerals. Soil-ingestion estimates may be required for risk assessments of wildlife inhabiting contaminated sites and for computing budgets of those nutrients associated mainly with soil.

Colorado, Kansas, Louisiana, Maine, Maryland, Minn↗

USGS2009

Analytical Results for Agricultural Soils Samples from a Monitoring Program Near Deer Trail, Colorado (USA)

Since late 1993, Metro Wastewater Reclamation District of Denver (Metro District, MWRD), a large wastewater treatment plant in Denver, Colorado, has applied Grade I, Class B biosolids to about 52,000 acres of nonirrigated farmland and rangeland near Deer Trail, Colorado, USA. In cooperation with the Metro District in 1993, the U.S. Geological Survey (USGS) began monitoring groundwater at part of this site. In 1999, the USGS began a more comprehensive monitoring study of the entire site to address stakeholder concerns about the potential chemical effects of biosolids applications to water, soil, and vegetation. This more comprehensive monitoring program has recently been extended through 2010. Monitoring components of the more comprehensive study include biosolids collected at the wastewater treatment plant, soil, crops, dust, alluvial and bedrock groundwater, and stream bed sediment. Soils for this study were defined as the plow zone of the dry land agricultural fields - the top twelve inches of the soil column. This report presents analytical results for the soil samples collected at the Metro District farm land near Deer Trail, Colorado, during three separate sampling events during 1999, 2000, and 2002. Soil samples taken in 1999 were to be a representation of the original baseline of the agricultural soils prior to any biosolids application. The soil samples taken in 2000 represent the soils after one application of biosolids to the middle field at each site and those taken in 2002 represent the soils after two applications. There have been no biosolids applied to any of the four control fields. The next soil sampling is scheduled for the spring of 2010. Priority parameters for biosolids identified by the stakeholders and also regulated by Colorado when used as an agricultural soil amendment include the total concentrations of nine trace elements (arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, and zinc), plutonium isotopes, and gross alpha and beta activity (Colorado Department of Public Health and Environment, Hazardous Materials and Waste Management Division, 1997; Colorado Department of Public Health and Environment,1998; U.S. Environmental Protection Agency, 1993). Since these were the identified priority parameters for the biosolids, the soils have the same set of priority parameters. Although the composite soils' priority analytes have been reported earlier to Metro District, the remaining elemental datasets for both the composite soils samples and selected fields' individual subsamples' data are presented here for the first time. More information about the other monitoring components is presented elsewhere in the literature (http://co.water.usgs.gov/projects/CO406/CO406.html). In general, the objective of each component of the study was to determine whether concentrations of priority parameters (1) were higher than regulatory limits, (2) were increasing with time, and(or) (3) were significantly higher in biosolids-applied areas than in a similar farmed area where biosolids were not applied. The method chosen for sampling the soils proved to be an efficient and reliable representation of the average composition of each field. This was shown by analyzing individual subsamples, averaging the resulting values, and then comparing the values to the composited samples' values. The soil chemistry shows distinct differences between the two sites, most likely due to the different underlying parent material. Biosolids data were used to compile an inorganic-chemical biosolids signature that can be contrasted with the geochemical signature of the agricultural soils for this site. The biosolids signature and an understanding of the geology and hydrology of the site can be used to separate biosolids effects from natural geochemical effects. Elements of particular interest for a biosolids signature after application in the soils include bismuth, copper, silver, mercury, and phosphorus. This signat

Open-File Report↗

USGS2008

Revisiting classic water erosion models in drylands: The strong impact of biological soil crusts

Soil erosion and subsequent degradation has been a contributor to societal collapse in the past and is one of the major expressions of desertification in arid regions. The revised universal soil loss equation (RUSLE) models soil lost to water erosion as a function of climate erosivity (the degree to which rainfall can result in erosion), topography, soil erodibility, and land use/management. The soil erodibility factor (K) is primarily based upon inherent soil properties (those which change slowly or not at all) such as soil texture and organic matter content, while the cover/management factor (C) is based on several parameters including biological soil crust (BSC) cover. We examined the effect of two more precise indicators of BSC development, chlorophyll a and exopolysaccharides (EPS), upon soil stability, which is closely inversely related to soil loss in an erosion event. To examine the relative influence of these elements of the C factor to the K factor, we conducted our investigation across eight strongly differing soils in the 0.8 million ha Grand Staircase-Escalante National Monument. We found that within every soil group, chlorophyll a was a moderate to excellent predictor of soil stability (R2 = 0.21-0.75), and consistently better than EPS. Using a simple structural equation model, we explained over half of the variance in soil stability and determined that the direct effect of chlorophyll a was 3?? more important than soil group in determining soil stability. Our results suggest that, holding the intensity of erosive forces constant, the acceleration or reduction of soil erosion in arid landscapes will primarily be an outcome of management practices. This is because the factor which is most influential to soil erosion, BSC development, is also among the most manageable, implying that water erosion in drylands has a solution. ?? 2008 Elsevier Ltd.

Soil Biology and Biochemistry↗

USGS2021

Improved wetland soil organic carbon stocks of the conterminous U.S. through data harmonization

Wetland soil stocks are important global repositories of carbon (C) but are difficult to quantify and model due to varying sampling protocols, and geomorphic/spatio-temporal discontinuity. Merging scales of soil-survey spatial extents with wetland-specific point-based data offers an explicit, empirical and updatable improvement for regional and continental scale soil C stock assessments. Agency-collected (U.S. Department of Agriculture, U.S. Environmental Protection Agency) and community-contributed soil datasets were compared for representativeness and bias, with the goal of producing a harmonized national map of wetland soil C stocks with error quantification for wetland areas of the conterminous United States (CONUS) identified by the USGS National Landcover Change Dataset (NLCD). This allowed application of an empirical predictive model of SOC density to be applied across the entire CONUS using relational %OC distribution alone. A broken-stick quantile-regression model identified %OC with its relatively high analytical confidence as a key predictor of SOC density in soil segments; soils less than 6%OC (hereafter, mineral wetland soils, 85% of the dataset) had a strong linear relationship of %OC to SOC density (RMSE = 0.0059, ~4% mean RMSE) and soils greater than 6%OC (organic wetland soils, 15% of the dataset) had virtually no predictive relationship of %OC to SOC density (RMSE = 0.0348 g C cm-3, ~56% mean RMSE). Disaggregation by vegetation type (woody v. emergent herbaceous), or region did not alter the breakpoint significantly (6% OC) nor improve model accuracies for inland and tidal wetlands. Similarly, SOC stocks in tidal wetlands were related to %OC, but without a mappable product for disaggregation to improve accuracy by soil class, region or depth. Our layered, harmonized CONUS wetland soil maps have now revised wetland SOC stock estimates downward by 24% (9.5 vs. 12.5Pg C) with the overestimation being entirely an issue of inland, organic wetland soils, (35% lower than SSURGO-derived SOC stocks). Further, SSURGO underestimated soil carbon stocks at depth, as modeled wetland SOC stocks for organic-rich soils showed significant preservation downcore in the NWCA dataset (<3% loss between 0-30 cm and 30-100 cm depths) in contrast to mineral-rich soils (37% downcore stock loss). Future CONUS wetland soil C assessments will benefit from focused attention on improved organic wetland soil measurements, land history, and spatial representativeness.

Frontiers in Soil Science↗

USGS2003

Investigation of the possible connection of rock and soil geochemistry to the occurrence of high rates of neurodegenerative diseases on Guam and a hypothesis for the cause of the diseases

High incidences of neurodegenerative diseases, mainly dementia, parkinsonism, and amyotrophic lateral sclerosis, occur on the island of Guam (Koerner, 1952; Kurland and Mulder, 1954). The occurrence and description of the diseases and a summary of the investigations can be found in Perl (1997). The diseases have been more prevalent along the southern coast, particularly the small villages of Umatac, Merizo, and Inarajan (Reed and Brody, 1975; Roman, 1996; and Perl, 1997) (fig. 1), and referred to as the southern villages in this report. Tertiary volcanic rocks underlie most of the southern part of the island, including these villages. The northern part of Guam, with lower incidences of the diseases, consists of carbonate rocks. Epidemiological studies beginning in the early 1950’s failed to show the cause to be genetic etiology (Plato and others, 1986; Zhang and others, 1990). In recent studies, the search for pathogenic mechanisms has shifted to environmental factors. Excesses or deficiencies of various elements from dietary sources including drinking water can have an effect on human health. These deficiencies or excesses can usually be attributed to the geochemical composition of the rocks and derived soils that underlie the area. An example is the high concentration of Se in soil associated with the occurrence of selenosis in adults (Mills, 1996). Yase (1972) suggested that the neurodegenerative diseases on Guam may be related to accumulation of trace elements such as manganese and aluminum, both of which may cause neurodegeneration. It has been suggested that a deficiency in calcium and magnesium in the soil and water along with readily available aluminum could be connected to the occurrence of the diseases (Gajdusek, 1982; Yanagihara and others, 1984; Garruto and others, 1989). Some of the studies investigated metal exposure, particularly aluminum and manganese, and deficiencies in calcium and magnesium (Garruto and others, 1984). Aluminum has been shown to have neurotoxic effects (MacDonald and Martin, 1988), and aluminum has been implicated in the pathogenesis of Alzheimer’s disease and similar dementia by Perl and others (1982). Studies of soils developed on volcanic rocks on Guam and other islands by McLachlan and others (1989) found that soils on Guam averaged 42-fold higher yield of elutable aluminum than soils developed on volcanic rocks on Jamaica or Palau. They did not detect unusually high dietary aluminum or low dietary calcium, but concluded that the soils and possibly the dusts of Guam might be a major source of aluminum entering the body of the inhabitants. This study was conducted to investigate the geochemistry of the soils and rocks of the volcanic southern part of the island of Guam, particularly in the vicinity of the three southern villages (Umatac, Merizo, and Inarajan) with high incidences of the diseases. In addition to total chemical analyses of the soils and rocks, various extractions of soils were carried out. Both excesses and deficiencies of various elements were looked for. Because soluble aluminum in the soil was shown by McLachlan and others (1989) to be unusually high, water-soluble extractions as well as sequential extractions of the soils were carried out. In addition, elements such as aluminum found in dust can traverse the nose-brain barrier in experimental animals (Sunderman, 2000) and respiratory epithelium is known to contain the highest concentration of aluminum in the human body (Tipton and others, 1957). The availability of elements, particularly aluminum from human inhalation of dust, derived from soil, was investigated. The available elements were determined by extractions of soils using a simulated lung-fluid extraction. In order to compare the results of the chemical data of rocks and soils from Guam to other rocks and soils elsewhere, samples of similar rocks and soils were collected in the western United States and similar analyses to those for the Guam samples carried out. The complete chemical analyses of the soils, rocks, and streambed sediments as well as descriptions of the methods used can be found in Miller and others (2002).

Open-File Report↗

USGS2001

Soil analyses for 1,3-dichloropropene (1,3-DCP), sodium n-methyldithiocarbamate (metam-sodium), and their degradation products near Fort Hall Idaho, September 1999 through March 2000

Between September 1999 and March 2000, soil samples from the Fort Hall, Idaho, area were analyzed for two soil fumigants, 1,3-dichloropropene (1,3-DCP) and sodium n-methyldithiocarbamate (metam-sodium), and their degradation products. Ground water is the only source of drinking water at Fort Hall, and the purpose of the investigation was to determine potential risk of ground-water contamination from persistence and movement of these pesticides in cropland soils. 1,3-DCP, metam-sodium, or their degradation products were detected in 42 of 104 soil samples. The samples were collected from 1-, 2-, and 3-foot depths in multiple backhoe trenches during four sampling events—before pesticide application in September; after application in October; before soil freeze in December; and after soil thaw in March. In most cases, concentrations of the pesticide compounds were at or near their laboratory minimum reporting limits. U.S. Environmental Protection Agency Method 5035 was used as the guideline for soil sample preparation and analyses, and either sodium bisulfate (NaHSO4), an acidic preservative, or pesticide-free water was added to samples prior to analyses. Addition of NaHSO4 to the samples resulted in a greater number of compound detections, but pesticide-free water was added to most samples to avoid the strong reactions of soil carbonate minerals with the NaHSO4. As a result, nondetection of compounds in samples containing pesticide-free water did not necessarily indicate that the compounds were absent. Detections of these compounds were inconsistent among trenches with similar soil characteristics and histories of soil fumigant use. Compounds were detected at different depths and different trench locations during each sampling event. Overall results of this study showed that the original compounds or their degradation products can persist in soil 6 months or more after their application and are present to at least 3 feet below land surface in some areas. A few of the soil analyses results were unexpected. Degradation products of metam-sodium were detected in samples from croplands with a history of 1,3-DCP applications only, and were not detected in samples from croplands with a history of metam-sodium applications. Although 1,2-dibromoethane (EDB) has not been used in the area for many years, EDB was detected in a few soil samples. The presence of EDB in soil could be caused by irrigation of croplands with EDBcontaminated ground water. Analyses of these soil samples resulted in many unanswered questions, and further studies are needed. One potential study to determine vertical extent of pesticide compound migration in sediments, for example, would include analysis of one or more columns of soil and sediments (land surface to ground water, about 35 to 50 feet below land surface) in areas with known soil contamination. Another study would expand the scope of soil contamination to include broader types of cropland conditions and compound analyses.

Idaho↗

USGS2017

Timescales of carbon turnover in soils with mixed crystalline mineralogies

Organic matter–mineral associations stabilize much of the carbon (C) stored globally in soils. Metastable short-range-order (SRO) minerals such as allophane and ferrihydrite provide one mechanism for long-term stabilization of organic matter in young soil. However, in soils with few SRO minerals and a predominance of crystalline aluminosilicate or Fe (and Al) oxyhydroxide, C turnover should be governed by chemisorption with those minerals. Here, we correlate mineral composition from soils containing small amounts of SRO minerals with mean turnover time (TT) of C estimated from radiocarbon ( 14 C) in bulk soil, free light fraction and mineral-associated organic matter. We varied the mineral amount and composition by sampling ancient soils formed on different lithologies in arid to subhumid climates in Kruger National Park (KNP), South Africa. Mineral contents in bulk soils were assessed using chemical extractions to quantify Fe oxyhydroxides and SRO minerals. Because of our interest in the role of silicate clay mineralogy, particularly smectite (2 : 1) and kaolinite (1 : 1), we separately quantified the mineralogy of the clay-sized fraction using X-ray diffraction (XRD) and measured 14 C on the same fraction. Density separation demonstrated that mineral associated C accounted for 40–70 % of bulk soil organic C in A and B1 horizons for granite, nephelinite and arid-zone gabbro soils, and > 80 % in other soils. Organic matter strongly associated with the isolated clay-sized fraction represented only 9–47 % of the bulk soil C. The mean TT of C strongly associated with the clay-sized fraction increased with the amount of smectite (2 : 1 clays); in samples with > 40 % smectite it averaged 1020 ± 460 years. The C not strongly associated with clay-sized minerals, including a combination of low-density C, the C associated with minerals of sizes between 2 µm and 2 cm (including Fe oxyhydroxides as coatings), and C removed from clay-sized material by 2 % hydrogen peroxide had TTs averaging 190 ± 190 years in surface horizons. Summed over the bulk soil profile, we found that smectite content correlated with the mean TT of bulk soil C across varied lithologies. The SRO mineral content in KNP soils was generally very low, except for the soils developed on gabbros under more humid climate that also had very high Fe and C contents with a surprisingly short, mean C TTs. In younger landscapes, SRO minerals are metastable and sequester C for long timescales. We hypothesize that in the KNP, SRO minerals represent a transient stage of mineral evolution and therefore lock up C for a shorter time. Overall, we found crystalline Fe-oxyhydroxides (determined as the difference between Fe in dithionate citrate and oxalate extractions) to be the strongest predictor for soil C content, while the mean TT of soil C was best predicted from the amount of smectite, which was also related to more easily measured bulk properties such as cation exchange capacity or pH. Combined with previous research on C turnover times in 2 : 1 vs. 1 : 1 clays, our results hold promise for predicting C inventory and persistence based on intrinsic timescales of specific carbon–mineral interactions.

SOIL↗

USGS2016

Ca, Sr and Ba stable isotopes reveal the fate of soil nutrients along a tropical climosequence

Nutrient biolifting is an important pedogenic process in which plant roots obtain inorganic nutrients such as phosphorus (P) and calcium (Ca) from minerals at depth and concentrate those nutrients at the surface. Here we use soil chemistry and stable isotopes of the alkaline earth elements Ca, strontium (Sr) and barium (Ba) to test the hypothesis that biolifting of P has been an important pedogenic process across a soil climosequence developed on volcanic deposits at Kohala Mountain, Hawaii. The geochemical linkage between these elements is revealed as generally positive site-specific relationships in soil mass gains and losses, particularly for P, Ba and Ca, using the ratio of immobile elements titanium and niobium (Ti/Nb) to link individual soil samples to a restricted compositional range of the chemically and isotopically diverse volcanic parent materials. At sites where P is enriched in surface soils relative to abundances in deeper soils, the isotope compositions of exchangeable Ca, Sr and Ba in the shallowest soil horizons (< 10 cm depth) are lighter than those of the volcanic parent materials and trend toward those of plants growing on fresh volcanic deposits. In contrast the isotope composition of exchangeable Ba in deeper soil horizons (> 10 cm depth) at those sites is consistently heavier than the volcanic parent materials. The isotope compositions of exchangeable Ca and Sr trend toward heavier compositions with depth more gradually, reflecting increasing leakiness from these soils in the order Ba < Sr < Ca and downward transfer of light biocycled Ca and Sr to deeper exchange sites. Given the long-term stability of ecosystem properties at the sites where P is enriched in surface soils, a simple box model demonstrates that persistence of isotopically light exchangeable Ca, Sr and Ba in the shallowest soil horizons requires that the uptake flux to plants from those near-surface layers is less than the recycling flux returned to the surface as litterfall. This observation implicates an uptake flux from an additional source which we attribute to biolifting. We view the heavy exchangeable Ba relative to soil parent values in deeper soils at sites where P is enriched in surface soils, and indeed at all but the wettest site across the climosequence, to represent the complement of an isotopically light Ba fraction removed from these soils by plant roots consistent with the biolifting hypothesis. We further suggest that decreasing heaviness of depth-integrated exchangeable Ba in deeper soils with increasing median annual precipitation across the climosequence reflects greater reliance on shallow nutrient sources as site water balance increases. While the Ca, Sr and Ba isotopes considered together were useful in confirming an important role for nutrient biolifting across the climosequence, the Ba isotopes provided the most robust tracer of biolifting and have the greatest potential to find application as an isotopic proxy for P dynamics in soils.

Hawaii↗

USGS2015

Machine learning for predicting soil classes in three semi-arid landscapes

Mapping the spatial distribution of soil taxonomic classes is important for informing soil use and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial distribution of soil taxonomic classes. Key components of DSM are the method and the set of environmental covariates used to predict soil classes. Machine learning is a general term for a broad set of statistical modeling techniques. Many different machine learning models have been applied in the literature and there are different approaches for selecting covariates for DSM. However, there is little guidance as to which, if any, machine learning model and covariate set might be optimal for predicting soil classes across different landscapes. Our objective was to compare multiple machine learning models and covariate sets for predicting soil taxonomic classes at three geographically distinct areas in the semi-arid western United States of America (southern New Mexico, southwestern Utah, and northeastern Wyoming). All three areas were the focus of digital soil mapping studies. Sampling sites at each study area were selected using conditioned Latin hypercube sampling (cLHS). We compared models that had been used in other DSM studies, including clustering algorithms, discriminant analysis, multinomial logistic regression, neural networks, tree based methods, and support vector machine classifiers. Tested machine learning models were divided into three groups based on model complexity: simple, moderate, and complex. We also compared environmental covariates derived from digital elevation models and Landsat imagery that were divided into three different sets: 1) covariates selected a priori by soil scientists familiar with each area and used as input into cLHS, 2) the covariates in set 1 plus 113 additional covariates, and 3) covariates selected using recursive feature elimination. Overall, complex models were consistently more accurate than simple or moderately complex models. Random forests (RF) using covariates selected via recursive feature elimination was consistently the most accurate, or was among the most accurate, classifiers between study areas and between covariate sets within each study area. We recommend that for soil taxonomic class prediction, complex models and covariates selected by recursive feature elimination be used. Overall classification accuracy in each study area was largely dependent upon the number of soil taxonomic classes and the frequency distribution of pedon observations between taxonomic classes. Individual subgroup class accuracy was generally dependent upon the number of soil pedon observations in each taxonomic class. The number of soil classes is related to the inherent variability of a given area. The imbalance of soil pedon observations between classes is likely related to cLHS. Imbalanced frequency distributions of soil pedon observations between classes must be addressed to improve model accuracy. Solutions include increasing the number of soil pedon observations in classes with few observations or decreasing the number of classes. Spatial predictions using the most accurate models generally agree with expected soil–landscape relationships. Spatial prediction uncertainty was lowest in areas of relatively low relief for each study area.

New Mexico, Utah, Wyoming↗

USGS2008

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

Journal of Hydrology↗

USGS2014

Desert shrub responses to experimental modification of precipitation seasonality and soil depth: relationship to the two-layer model and ecohydrological niche

1. Ecohydrological niches are important for understanding plant community responses to climate shifts, particularly in dry lands. According to the two-layer hypothesis, selective use of deep-soil water increases growth or persistence of woody species during warm and dry summer periods and thereby contributes to their coexistence with shallow-rooted herbs in dry ecosystems. The resource-pool hypothesis further suggests that shallow-soil water benefits growth of all plants while deep-soil water primarily enhances physiological maintenance and survival of woody species. Few studies have directly tested these by manipulating deep-soil water availability and observing the long-term outcomes. 2. We predicted that factors promoting infiltration and storage of water in deep soils, specifically greater winter precipitation and soil depth, would enhance Artemisia tridentata (big sagebrush) in cold, winter-wet/summer-dry desert. Sagebrush responses to 20 years of winter irrigation were compared to summer- or no irrigation, on plots having relatively deep or shallow soils (2 m vs. 1 m depths). 3. Winter irrigation increased sagebrush cover, and crown and canopy volumes, but not density (individuals/plot) compared to summer or no irrigation, on deep-soil plots. On shallow-soil plots, winter irrigation surprisingly decreased shrub cover and size, and summer irrigation had no effect. Furthermore, multiple regression suggested that the variations in growth were related (i) firstly to water in shallow soils (0-0.2 m) and secondly to deeper soils (> 1 m deep) and (ii) more by springtime than by midsummer soil water. Water-use efficiency increased considerably on shallow soils without irrigation and was lowest with winter irrigation. 4. Synthesis . Sagebrush was more responsive to the seasonal timing of precipitation than to total annual precipitation. Factors that enhanced deep-water storage (deeper soils plus more winter precipitation) led to increases in Artemisia tridentata that were consistent with the two-layer hypothesis, and the contribution of shallow water to growth on these plots was consistent with the resource-pool hypothesis. However, shallow-soil water also had negative effects on sagebrush, suggesting an ecohydrological trade-off not considered in these or related theories. The interaction between precipitation timing and soil depth indicates that increased winter precipitation could lead to a mosaic of increases and decreases in A. tridentata across landscapes having variable soil depth.

Idaho↗

USGS1995

Quaternary soils and dust deposition in southern Nevada and California

Eolian dust constitutes much of the pedogenic material in late Pleistocene and Holocene soils of many arid regions of the world. Comparison of the compositions and influx rates of modern dust with the eolian component of dated soils at 24 sites in southern Nevada and California yields information on (1) the composition and influx rate of dust in late Pleistocene and Holocene soils, (2) paleoclimate and its effects on the genesis of aridic soils, especially with regard to dustfall events, (3) the timing and relative contribution of dust from playa sources versus alluvial sources, and (4) the effects of accumulation of dust in soil horizons. The <2 mm fractions of A and B horizons of soils formed on gravelly alluvial-fan deposits in the study area are similar to modern dust in grain size, content of CaCO 3 and salt, major oxides, and clay mineralogy; thus, they are interpreted to consist largely of dust. The major-oxide compositions of the shallow soil horizons are nearly identical to that of the modern dust, but the compositions of progressively deeper horizons approach that of the parent material. The clay mineralogy of modern dust at a given site is similar to that of the Av horizons of nearby Holocene soils but is commonly different from the mineralogies of deeper soil horizons and of the Av horizons of nearby Pleistocene soils. These results are interpreted to indicate that dust both accumulates and is transformed in Av horizons with time. Changes in soil-accumulation rates provide insights into the interplay of paleoclimate, dust supply, and soil-forming processes. Modern dust-deposition rates are more than large enough to account for middle and late Holocene soil-accumulation rates at nearly all sites. However, the early Holocene soil-accumulation rates in areas near late Pleistocene pluvial lakes are much higher than modern rates and clearly indicate a dust-deflation and -deposition event that caused rapid formation of fine-grained shallow soil horizons on uppermost Pleistocene and lower Holocene deposits. We interpret late Pleistocene soil-accumulation rates to indicate that dust-deposition rates were low during this period but that increased effective moisture during the late Wisconsinan favored translocation of clay and CaCO 3 from near the surface to deeper in the soil profile. Pre–late Pleistocene rates are very low in most areas, mainly due to a pedogenic threshold that was crossed when accumulations of silt, clay, and CaCO 3 began to inhibit the downward transport of eolian material, but in part due to erosion.

Geological Society of America Bulletin↗

USGS2019

Baseline environmental monitoring of groundwater, surface water, and soil at the Ammonium Perchlorate Rocket Motor Destruction Facility at the Letterkenny Army Depot, Chambersburg, Pennsylvania, 2016

Letterkenny Army Depot in Chambersburg, Pennsylvania, built an Ammonium Perchlorate Rocket Motor Destruction (ARMD) facility in 2016. The ARMD Facility was designed to centralize rocket motor destruction and contain or capture all waste during the destruction process. Ideally, there would be no contaminant transport to air, soil, or water from the facility, but the Code of Federal Regulations requires that any hazardous waste disposal facility have an environmental monitoring program in place. In a study by the U.S. Geological Survey, in cooperation with the Letterkenny Army Depot, baseline characterization of constituents in groundwater, surface water, and soil was conducted from September to December 2016 to document site conditions prior to the beginning of operations at the facility in January 2017. Groundwater wells, surface water, and soils were sampled monthly during the baseline characterization period. No sediment transport from the site occurred on days when samples were collected from surface-water sites, so no sediment was collected from the retention basin at the facility during the baseline period. Data collected during the baseline period can be compared to data collected in future years to determine whether there is any contaminant transport from the ARMD Facility to the surrounding environment. During the baseline characterization period, monthly samples were collected from 4 groundwater wells and 9 soil sites near the ARMD Facility. The only surface-water site sampled monthly during the baseline period was upgradient from the facility. There was no streamflow at surface-water sites downgradient from the facility on days when surface-water samples were collected during the baseline characterization period. Groundwater results for the four wells sampled near the ARMD Facility during the baseline period did not show any major water-quality issues. Mean specific conductance (SC) and pH in groundwater ranged from 220 to 771 microsiemens per centimeter at 25 degrees Celsius (μS/cm) and 6.45 to 6.98, respectively. No constituents in groundwater samples exceeded any U.S. Environmental Protection Agency (EPA) Maximum Contaminant Level (MCL). Dissolved iron (Fe) was the only groundwater constituent that exceeded a Secondary Maximum Contaminant Level (SMCL) established by the EPA. The SMCL for Fe is 300 micrograms per liter (μg/L); samples from three wells had mean dissolved Fe concentrations ranging from 1,100 to 2,600 μg/L. The only volatile organic compounds (VOCs) detected in groundwater samples were bromomethane, acetone, and chloromethane. All VOC detections in groundwater samples were less than the Reporting Detection Levels (RDLs). These three compounds also were detected in blank samples submitted for groundwater samples. Perchlorate was not detected in any groundwater sample collected during the baseline period. Surface-water data collected during the baseline period were strictly representative of a stream reach upgradient from the ARMD Facility. Stream discharge ranged from 0.03 to 0.08 cubic feet per second during sample collection. The mean SC and pH were 310 μS/cm and 7.6, respectively. No EPA established MCLs or SMCLs were exceeded for any constituents in samples collected from this upgradient stream. Some VOCs were detected in surface water at less than the RDLs. The VOCs detected in surface water were generally the same VOCs as those detected at less than the RDLs for groundwater. Perchlorate was detected in each sample collected from the stream; the mean concentration was 0.07 μg/L. All perchlorate results were less than the RDL of 0.2 μg/L. Soil samples collected during the baseline period did not have any constituent concentrations that exceeded any medium-specific concentrations (MSC) or soil screening levels (SSL) established by either the Commonwealth of Pennsylvania or the EPA. The Commonwealth of Pennsylvania calculates MSCs based on either a function of acceptable concentrations in groundwater or based on health concerns if the soil is directly contacted. The EPA derives acceptable concentrations of constituents (SSLs) in soil based on standardized equations combining exposure information assumptions with EPA toxicity data. The EPA calculates SSLs for residential and industrial sites. Soil sites at the ARMD Facility were considered “industrial” for comparative purposes. There was at least one order of magnitude difference between any inorganic constituent concentration detected in soil and the MSC and (or) SSL for that constituent. Four VOCs were detected in soil samples collected during the baseline period. None of the VOCs detected in the soils were within three orders of magnitude of any established MSCs or SSLs. The VOCs detected in soil were dichloromethane (also known as methylene chloride), methyl tert-butyl ether (MTBE), tetrachloroethene, and acetone (only detected once). Dichloromethane was the only VOC detected at greater than the RDLs; concentrations in all soil samples were greater than the RDLs. Dichloromethane concentrations ranged from 1.9 to 50.1 micrograms per kilogram (μg/kg). MTBE was detected in 50 percent of samples collected but all results were less than the RDLs of 1.7 to 2.6 μg/kg. Tetrachloroethene was detected in 20 percent of soil samples collected, with a maximum estimated value of 1.5 μg/kg. Inorganic constituents with the highest concentrations in soil were Fe and aluminum (Al); mean Fe and Al concentrations ranged from 28,700 to 52,400 and 10,300 to 19,800 milligrams per kilogram (mg/kg), respectively. Data collected during the baseline period in 2016 can be compared to future data to determine whether concentrations in water and soils surrounding the facility have shown any changes that could be caused by the facility operation.

Pennsylvania↗

USGS1988

Estimating soil matric potential in Owens Valley, California

Much of the floor of the Owens Valley, California, is covered with alkaline scrub and alkaline meadow plant communities, whose existence is dependent partly on precipitation and partly on water infiltrated into the rooting zone from the shallow water table. The extent to which these plant communities are capable of adapting to and surviving fluctuations in the water table depends on physiological adaptations of the plants and on the water content, matric potential characteristics of the soils. Two methods were used to estimate soil matric potential in test sites in Owens Valley. The first was the filter-paper method, which uses water content of filter papers equilibrated to water content of soil samples taken with a hand auger. The other method of estimating soil matric potential was a modeling approach based on data from this and previous investigations. These data indicate that the base 10 logarithm of soil matric potential is a linear function of gravimetric soil water content for a particular soil. Estimates of soil water characteristic curves were made at two sites by averaging the gravimetric soil water content and soil matric potential values from multiple samples at 0.1 m depths derived by using the hand auger and filter paper method and entering these values in the soil water model. The characteristic curves then were used to estimate soil matric potential from estimates of volumetric soil water content derived from neutron-probe readings. Evaluation of the modeling technique at two study sites indicated that estimates of soil matric potential within 0.5 pF units of the soil matric potential value derived by using the filter paper method could be obtained 90 to 95% of the time in soils where water content was less than field capacity. The greatest errors occurred at depths where there was a distinct transition between soils of different textures. (Lantz-PTT)

California↗

USGS1981

Evaluation of Landsat Multispectral Scanner data for mapping vegetated soil landscapes

Landsat multispectral scanner data for Brazos County, Texas, were evaluated in terms of effectiveness for classifying soils on vegetated landscapes at three times during the year: a time of normally adequate soil water, a time of expected soil water deficit, and a time when soil water is normally being replenished. Six test sites were used to evaluate LARSYS supervised and unsupervised classification of vegetated soil landscapes. Open grassland soils were best separated in the fall during a period when soil moisture was being replenished after the summer period of soil water deficit. Woodland soils were separated by Landsat data in late spring when adequate moisture was available. However, a high degree of accuracy was not achieved using Landsat for separating soil map units. Accurate separation of soil mapping units on vegetated landscapes was not possible during late summer when soil water was deficient. Selected soil properties important to plant growth were separable on the test sites using June and October Landsat data. Particle size and soil moisture regime were separated at both dates. Soils with argillic horizons were separated from soils without argillic horizons.

Texas↗

USGS2016

Riparian soil development linked to forest succession above and below dams along the Elwha River, Washington, USA

Riparian forest soils can be highly dynamic, due to frequent fluvial disturbance, erosion, and sediment deposition, but effects of dams on riparian soils are poorly understood. We examined soils along toposequences within three river segments located upstream, between, and downstream of two dams on the Elwha River to evaluate relationships between riparian soil development and forest age, succession, and channel proximity, explore dam effects on riparian soils, and provide a baseline for the largest dam removal in history. We found that older, later-successional forests and geomorphic surfaces contained soils with finer texture and greater depth to cobble, supporting greater forest floor mass, mineral soil nutrient levels, and cation exchange. Forest stand age was a better predictor than channel proximity for many soil characteristics, though elevation and distance from the channel were often also important, highlighting how complex interactions between fluvial disturbance, sediment deposition, and biotic retention regulate soil development in this ecosystem. Soils between the dams, and to a lesser extent below the lower dam, had finer textures and higher mineral soil carbon, nitrogen, and cation exchange than above the dams. These results suggested that decreased fluvial disturbance below the dams, due to reduced sediment supply and channel stabilization, accelerated soil development. In addition, reduced sediment supply below the dams may have decreased soil phosphorus. Soil δ15N suggested that salmon exclusion by the dams had no discernable effect on nitrogen inputs to upstream soils. Recent dam removal may alter riparian soils further, with ongoing implications for riparian ecosystems.

Washington↗

USGS2015

Soil organic matter regulates molybdenum storage and mobility in forests

The trace element molybdenum (Mo) is essential to a suite of nitrogen (N) cycling processes in ecosystems, but there is limited information on its distribution within soils and relationship to plant and bedrock pools. We examined soil, bedrock, and plant Mo variation across 24 forests spanning wide soil pH gradients on both basaltic and sedimentary lithologies in the Oregon Coast Range. We found that the oxidizable organic fraction of surface mineral soil accounted for an average of 33 %of bulk soil Mo across all sites, followed by 1.4 % associated with reducible Fe, Al, and Mn-oxides, and 1.4 % in exchangeable ion form. Exchangeable Mo was greatest at low pH, and its positive correlation with soil carbon (C) suggests organic matter as the source of readily exchangeable Mo. Molybdenum accumulation integrated over soil profiles to 1 m depth ( τMo Nb ) increased with soil C, indicating that soil organic matter regulates long-term Mo retention and loss from soil. Foliar Mo concentrations displayed no relationship with bulk soil Mo, and were not correlated with organic horizon Mo or soil extractable Mo, suggesting active plant regulation of Mo uptake and/or poor fidelity of extractable pools to bioavailability. We estimate from precipitation sampling that atmospheric deposition supplies, on average, over 10 times more Mo annually than does litterfall to soil. In contrast, bedrock lithology had negligible effects on foliar and soil Mo concentrations and on Mo distribution among soil fractions. We conclude that atmospheric inputs may be a significant source of Mo to forest ecosystems, and that strong Mo retention by soil organic matter limits ecosystem Mo loss via dissolution and leaching pathways.

Oregon↗

USGS2000

Mineralogic and compositional properties of Martian soil and dust: results from Mars Pathfinder

Mars Pathfinder obtained multispectral, elemental, magnetic, and physical measurements of soil and dust at the Sagan Memorial Station during the course of its 83 sol mission. We describe initial results from these measurements, concentrating on multispectral and elemental data, and use these data, along with previous Viking, SNC meteorite, and telescopic results, to help constrain the origin and evolution of Martian soil and dust. We find that soils and dust can be divided into at least eight distinct spectral units, based on parameterization of Imager for Mars Pathfinder (IMP) 400 to 1000 nm multispectral images. The most distinctive spectral parameters for soils and dust are the reflectivity in the red, the red/blue reflectivity ratio, the near-IR spectral slope, and the strength of the 800 to 1000 nm absorption feature. Most of the Pathfinder spectra are consistent with the presence of poorly crystalline or nanophase ferric oxide(s), sometimes mixed with small but varying degrees of well-crystalline ferric and ferrous phases. Darker soil units appear to be coarser-grained, compacted, and/or mixed with a larger amount of dark ferrous materials relative to bright soils. Nanophase goethite, akaganeite, schwertmannite, and maghemite are leading candidates for the origin of the absorption centered near 900 nm in IMP spectra. The ferrous component in the soil cannot be well-constrained based on IMP data. Alpha proton X-ray spectrometer (APXS) measurements of six soil units show little variability within the landing site and show remarkable overall similarity to the average Viking-derived soil elemental composition. Differences exist between Viking and Pathfinder soils, however, including significantly higher S and Cl abundances and lower Si abundances in Viking soils and the lack of a correlation between Ti and Fe in Pathfinder soils. No significant linear correlations were observed between IMP spectral properties and APXS elemental chemistry. Attempts at constraining the mineralogy of soils and dust using normative calculations involving mixtures of smectites and silicate and oxide minerals did not yield physically acceptable solutions. We attempted to use the Pathfinder results to constrain a number of putative soil and dust formation scenarios, including palagonitization and acid-fog weathering. While the Pathfinder soils cannot be chemically linked to the Pathfinder rocks by palagonitization, this study and McSween et al. [1999] suggest that palagonitic alteration of a Martian basaltic rock, plus mixture with a minor component of locally derived andesitic rock fragments, could be consistent with the observed soil APXS and IMP properties.

Journal of Geophysical Research E: Planets↗