Spatial Variation of Soil Type and Soil Moisture in the Regional Atmospheric Modeling System

Energy Technology Data Exchange (ETDEWEB)

Buckley, R.

2001-06-27

Soil characteristics (texture and moisture) are typically assumed to be initially constant when performing simulations with the Regional Atmospheric Modeling System (RAMS). Soil texture is spatially homogeneous and time-independent, while soil moisture is often spatially homogeneous initially, but time-dependent. This report discusses the conversion of a global data set of Food and Agriculture Organization (FAO) soil types to RAMS soil texture and the subsequent modifications required in RAMS to ingest this information. Spatial variations in initial soil moisture obtained from the National Center for Environmental Predictions (NCEP) large-scale models are also introduced. Comparisons involving simulations over the southeastern United States for two different time periods, one during warmer, more humid summer conditions, and one during cooler, dryer winter conditions, reveals differences in surface conditions related to increases or decreases in near-surface atmospheric moisture con tent as a result of different soil properties. Three separate simulation types were considered. The base case assumed spatially homogeneous soil texture and initial soil moisture. The second case assumed variable soil texture and constant initial soil moisture, while the third case allowed for both variable soil texture and initial soil moisture. The simulation domain was further divided into four geographically distinct regions. It is concluded there is a more dramatic impact on thermodynamic variables (surface temperature and dewpoint) than on surface winds, and a more pronounced variability in results during the summer period. While no obvious trends in surface winds or dewpoint temperature were found relative to observations covering all regions and times, improvement in surface temperatures in most regions and time periods was generally seen with the incorporation of variable soil texture and initial soil moisture.

Spatial Variation of Arsenic in Soil, Irrigation Water, and Plant Parts: A Microlevel Study

OpenAIRE

Kabir, M. S.; Salam, M. A.; Paul, D. N. R.; Hossain, M. I.; Rahman, N. M. F.; Aziz, Abdullah; Latif, M. A.

2016-01-01

Arsenic pollution became a great problem in the recent past in different countries including Bangladesh. The microlevel studies were conducted to see the spatial variation of arsenic in soils and plant parts contaminated through ground water irrigation. The study was performed in shallow tube well command areas in Sadar Upazila (subdistrict), Faridpur, Bangladesh, where both soil and irrigation water arsenic are high. Semivariogram models were computed to determine the spatial dependency of s...

Spatial variability of soil erosion and soil quality on hillslopes in the Chinese loess plateau

International Nuclear Information System (INIS)

Li, Y.; Lindstrom, M.J.; Zhang, J.; Yang, J.

2000-01-01

Soil erosion rates and soil quality indicators were measured along two hillslope transects in the Loess Plateau near Yan'an, China. The objectives were to: (a) quantify spatial patterns and controlling processes of soil redistribution due to water and tillage erosion, and (b) correlate soil quality parameters with soil redistribution along the hillslope transects for different land use management systems. Water erosion data were derived from 137 Cs measurements and tillage erosion from the simulation of a Mass Balance Model along the hillslope transects. Soil quality measurements, i.e. soil organic matter, bulk density and available nutrients were made at the same sampling locations as the 137 Cs measurements. Results were compared at the individual site locations and along the hillslope transect through statistical and applied time series analysis. The results showed that soil loss due to water erosion and soil deposition from tillage are the dominant soil redistribution processes in range of 23-40 m, and soil deposition by water erosion and soil loss by tillage are dominant processes occurring in range of more than 80 m within the cultivated landscape. However, land use change associated with vegetation cover can significantly change both the magnitudes and scale of these spatial patterns within the hillslope landscapes. There is a strong interaction between the spatial patterns of soil erosion processes and soil quality. It was concluded that soil loss by water erosion and deposition by tillage are the main cause for the occurrence of significant scale dependency of spatial variability of soil quality along hillslope transects. (author)

Contamination and Spatial Variation of Heavy Metals in the Soil-Rice System in Nanxun County, Southeastern China

Science.gov (United States)

Zhao, Keli; Fu, Weijun; Ye, Zhengqian; Zhang, Chaosheng

2015-01-01

There is an increasing concern about heavy metal contamination in farmland in China and worldwide. In order to reveal the spatial features of heavy metals in the soil-rice system, soil and rice samples were collected from Nanxun, Southeastern China. Compared with the guideline values, elevated concentrations of heavy metals in soils were observed, while heavy metals in rice still remained at a safe level. Heavy metals in soils and rice had moderate to strong spatial dependence (nugget/sill ratios: 13.2% to 49.9%). The spatial distribution of copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) in soils illustrated that their high concentrations were located in the southeast part. The high concentrations of cadmium (Cd) in soils were observed in the northeast part. The accumulation of all the studied metals is related to the long-term application of agrochemicals and industrial activities. Heavy metals in rice showed different spatial distribution patterns. Cross-correlograms were produced to quantitatively determine the spatial correlation between soil properties and heavy metals composition in rice. The pH and soil organic matter had significant spatial correlations with the concentration of heavy metals in rice. Most of the selected variables had clear spatial correlation ranges for heavy metals in rice, which could be further applied to divide agricultural management zones. PMID:25635917

Contamination and Spatial Variation of Heavy Metals in the Soil-Rice System in Nanxun County, Southeastern China

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Keli Zhao

2015-01-01

Full Text Available There is an increasing concern about heavy metal contamination in farmland in China and worldwide. In order to reveal the spatial features of heavy metals in the soil-rice system, soil and rice samples were collected from Nanxun, Southeastern China. Compared with the guideline values, elevated concentrations of heavy metals in soils were observed, while heavy metals in rice still remained at a safe level. Heavy metals in soils and rice had moderate to strong spatial dependence (nugget/sill ratios: 13.2% to 49.9%. The spatial distribution of copper (Cu, nickel (Ni, lead (Pb and zinc (Zn in soils illustrated that their high concentrations were located in the southeast part. The high concentrations of cadmium (Cd in soils were observed in the northeast part. The accumulation of all the studied metals is related to the long-term application of agrochemicals and industrial activities. Heavy metals in rice showed different spatial distribution patterns. Cross-correlograms were produced to quantitatively determine the spatial correlation between soil properties and heavy metals composition in rice. The pH and soil organic matter had significant spatial correlations with the concentration of heavy metals in rice. Most of the selected variables had clear spatial correlation ranges for heavy metals in rice, which could be further applied to divide agricultural management zones.

Contamination and spatial variation of heavy metals in the soil-rice system in Nanxun County, Southeastern China.

Science.gov (United States)

Zhao, Keli; Fu, Weijun; Ye, Zhengqian; Zhang, Chaosheng

2015-01-28

There is an increasing concern about heavy metal contamination in farmland in China and worldwide. In order to reveal the spatial features of heavy metals in the soil-rice system, soil and rice samples were collected from Nanxun, Southeastern China. Compared with the guideline values, elevated concentrations of heavy metals in soils were observed, while heavy metals in rice still remained at a safe level. Heavy metals in soils and rice had moderate to strong spatial dependence (nugget/sill ratios: 13.2% to 49.9%). The spatial distribution of copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) in soils illustrated that their high concentrations were located in the southeast part. The high concentrations of cadmium (Cd) in soils were observed in the northeast part. The accumulation of all the studied metals is related to the long-term application of agrochemicals and industrial activities. Heavy metals in rice showed different spatial distribution patterns. Cross-correlograms were produced to quantitatively determine the spatial correlation between soil properties and heavy metals composition in rice. The pH and soil organic matter had significant spatial correlations with the concentration of heavy metals in rice. Most of the selected variables had clear spatial correlation ranges for heavy metals in rice, which could be further applied to divide agricultural management zones.

Spatial Structure of Soil Macrofauna Diversity and Tree Canopy in Riparian Forest of Maroon River

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Ehsan Sayad

2017-02-01

with a mean temperature of 24.5oc. Plant cover, mainly comprises Populus euphratica Olivie and Tamarix arceuthoides Bge and Lycium shawii Roemer & Schultes. Soil macrofauna were sampled using 175 sampling point along parallel transects (perpendicular to the river. The distance between transects was 100m. We considered distance between samples as 50 m. tree canopy were measured in 5* 5 plots. soil macrofauna were extracted from 50 cm×50 cm×10 cm soil monolith by hand-sorting procedure. All soil macrofauna were identified to family level. Evenness (Sheldon index, richness (Menhinich index and diversity (Shannon H’ index by using PAST version 1.39, were determined in each sample. Classical statistical parameters, i.e. mean, standard deviation, coefficient of variation, minimum and maximum, were calculated using SPSS17 software. For analysis of the relationship between Soil macrofauna diversity indices and tree canopy (Total canopy, Populous canopy, Tamarix canopy and Serim canopy we calculated the correlation among soil properties and macrofauna using the Pearson correlation coefficient. Next, to determining the spatial structure, we calculated the semivariances. Semivariance quantifies the spatial dependence of spatially ordered variable values. In order to gather information about the spatial connection between any two variables, and to compare the similarity of their spatial structure patterns, cross-variograms were constructed. Cross-variograms are plots of cross-semivariance against the lag distance. Results and Discussion: Soil macrofauna communities were dominated by earthworm, diplopods, coleoptera, gastropoda, araneae, and insect larvae. Correlation analysis of soil macrofauna and tree canopy indicated weak relationships between them. Weak, but significant relationships were found between macrofauna diversity, evenness, richness and total canopy, Populous canopy and Tamarix canopy (positive. Macrofauna indices and tree canopy(excepted Tamarix canopy were

Spatial variability of atrazine dissipation in an allophanic soil.

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Müller, Karin; Smith, Roger E; James, Trevor K; Holland, Patrick T; Rahman, Anis

2003-08-01

The small-scale variability (0.5 m) of atrazine (6-chloro-N2-ethyl-N4-isopropyl-1,3,5-triazine-2,4-diamine) concentrations and soil water contents in a volcanic silt loam soil (Haplic Andosol, FAO system) was studied in an area of 0.1 ha. Descriptive and spatial statistics were used to analyse the data. On average we recovered 102% of the applied atrazine 2 h after the herbicide application (CV = 35%). An increase in the CV of the concentrations with depth could be ascribed to a combination of extrinsic and intrinsic factors. Both variables, atrazine concentrations and soil water content, showed a high horizontal variability. The semivariograms of the atrazine concentrations exhibited the pure nugget effect, no pattern could be determined along the 15.5-m long transects on any of the seven sampling days over a 55-day period. Soil water content had a weak spatial autocorrelation with a range of 6-10 m. The dissipation of atrazine analysed using a high vertical sampling resolution of 0.02 m to 0.2 m showed that 70% of the applied atrazine persisted in the upper 0.02-m layer of the soil for 12 days. After 55 days and 410 mm of rainfall the centre of the pesticide mass was still at a soil depth of 0.021 m. The special characteristics of the soil (high organic carbon content, allophanic clay) had a strong influence on atrazine sorption and mobility. The mass recovery after 55 days was low. The laboratory degradation rate for atrazine, determined in a complementary incubation study and corrected for the actual field temperature using the Arrhenius equation, only accounted for about 35% of the losses that occurred in the field. Results suggest field degradation rates to be more changeable in time and much faster than under controlled conditions. Preferential flow is discussed as a component of the field transport process.

SPATIAL MODELLING FOR DESCRIBING SPATIAL VARIABILITY OF SOIL PHYSICAL PROPERTIES IN EASTERN CROATIA

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Igor Bogunović

2016-06-01

Full Text Available The objectives of this study were to characterize the field-scale spatial variability and test several interpolation methods to identify the best spatial predictor of penetration resistance (PR, bulk density (BD and gravimetric water content (GWC in the silty loam soil in Eastern Croatia. The measurements were made on a 25 x 25-m grid which created 40 individual grid cells. Soil properties were measured at the center of the grid cell deep 0-10 cm and 10-20 cm. Results demonstrated that PR and GWC displayed strong spatial dependence at 0-10 cm BD, while there was moderate and weak spatial dependence of PR, BD and GWC at depth of 10-20 cm. Semi-variogram analysis suggests that future sampling intervals for investigated parameters can be increased to 35 m in order to reduce research costs. Additionally, interpolation models recorded similar root mean square values with high predictive accuracy. Results suggest that investigated properties do not have uniform interpolation method implying the need for spatial modelling in the evaluation of these soil properties in Eastern Croatia.

Spatial variability of soil CO2 emission in different topographic positions

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Liziane de Figueiredo Brito

2010-01-01

Full Text Available The spatial variability of soil CO2 emission is controlled by several properties related to the production and transport of CO2 inside the soil. Considering that soil properties are also influenced by topography, the objective of this work was to investigate the spatial variability of soil CO2 emission in three different topographic positions in an area cultivated with sugarcane, just after mechanical harvest. One location was selected on a concave-shaped form and two others on linear-shaped form (in back-slope and foot-slope. Three grids were installed, one in each location, containing 69 points and measuring 90 x 90 m each. The spatial variability of soil CO2 emission was characterized by means of semivariance. Spatial variability models derived from soil CO2 emission were exponential in the concave location while spherical models fitted better in the linear shaped areas. The degree of spatial dependence was moderate in all cases and the range of spatial dependence for the CO2 emission in the concave area was 44.5 m, higher than the mean value obtained for the linear shaped areas (20.65 m. The spatial distribution maps of soil CO2 emission indicate a higher discontinuity of emission in the linear form when compared to the concave form.

Spatial Variability of Soil Morphorlogical and Physico- Chemical ...

African Journals Online (AJOL)

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The available moisture of soil was very low thus water holding capacity (WHC) and wilting point (WP) of the soil was ... with spatial distribution of soil properties and its effect on ... Pore size and root .... nutrient and have better stability. Thus.

Field Scale Studies on the Spatial Variability of Soil Quality Indicators in Washington State, USA

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Jeffrey L. Smith

2011-01-01

Full Text Available Arable lands are needed for sustainable agricultural systems to support an ever-growing human population. Soil quality needs to be defined to assure that new land brought into crop production is sustainable. To evaluate soil quality, a number of soil attributes will need to be measured, evaluated, and integrated into a soil-quality index using the multivariable indicator kriging (MVIK procedure. This study was conducted to determine the spatial variability and correlation of indicator parameters on a field scale with respect to soil quality and suitability for use with MVIK. The variability of the biological parameters decreased in the order of respiration > enzyme assays and qCO2 > microbial biomass C. The distribution frequency of all parameters except respiration were normal although the spatial distribution across the landscape was highly variable. The biological parameters showed little correlation with each other when all data points were considered; however, when grouped in smaller sections, the correlations were more consistent with observed patterns across the field. To accurately assess soil quality, and arable land use, consideration of spatial and temporal variability, soil conditions, and other controlling factors must be taken into account.

Controls of Soil Spatial Variability in a Dry Tropical Forest.

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Sandeep Pulla

Full Text Available We examined the roles of lithology, topography, vegetation and fire in generating local-scale (<1 km2 soil spatial variability in a seasonally dry tropical forest (SDTF in southern India. For this, we mapped soil (available nutrients, Al, total C, pH, moisture and texture in the top 10 cm, rock outcrops, topography, all native woody plants ≥1 cm diameter at breast height (DBH, and spatial variation in fire frequency (times burnt during the 17 years preceding soil sampling in a permanent 50-ha plot. Unlike classic catenas, lower elevation soils had lesser moisture, plant-available Ca, Cu, Mn, Mg, Zn, B, clay and total C. The distribution of plant-available Ca, Cu, Mn and Mg appeared to largely be determined by the whole-rock chemical composition differences between amphibolites and hornblende-biotite gneisses. Amphibolites were associated with summit positions, while gneisses dominated lower elevations, an observation that concurs with other studies in the region which suggest that hillslope-scale topography has been shaped by differential weathering of lithologies. Neither NO3(--N nor NH4(+-N was explained by the basal area of trees belonging to Fabaceae, a family associated with N-fixing species, and no long-term effects of fire on soil parameters were detected. Local-scale lithological variation is an important first-order control over soil variability at the hillslope scale in this SDTF, by both direct influence on nutrient stocks and indirect influence via control of local relief.

Mapping spatial variability of soil salinity in a coastal paddy field based on electromagnetic sensors.

Science.gov (United States)

Guo, Yan; Huang, Jingyi; Shi, Zhou; Li, Hongyi

2015-01-01

In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9) allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v) as well as other EMI instruments (e.g. DUALEM-421) can be incorporated to conduct Quasi-3D inversions for deeper soil profiles.

Mapping spatial variability of soil salinity in a coastal paddy field based on electromagnetic sensors.

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Yan Guo

Full Text Available In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9 allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v as well as other EMI instruments (e.g. DUALEM-421 can be incorporated to conduct Quasi-3D inversions for deeper soil profiles.

Mapping Spatial Variability of Soil Salinity in a Coastal Paddy Field Based on Electromagnetic Sensors

Science.gov (United States)

Guo, Yan; Huang, Jingyi; Shi, Zhou; Li, Hongyi

2015-01-01

In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9) allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v) as well as other EMI instruments (e.g. DUALEM-421) can be incorporated to conduct Quasi-3D inversions for deeper soil profiles. PMID:26020969

Spatial heterogeneity of physicochemical properties explains differences in microbial composition in arid soils from Cuatro Cienegas, Mexico

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Silvia Pajares

2016-09-01

Full Text Available Arid ecosystems are characterized by high spatial heterogeneity, and the variation among vegetation patches is a clear example. Soil biotic and abiotic factors associated with these patches have also been well documented as highly heterogeneous in space. Given the low vegetation cover and little precipitation in arid ecosystems, soil microorganisms are the main drivers of nutrient cycling. Nonetheless, little is known about the spatial distribution of microorganisms and the relationship that their diversity holds with nutrients and other physicochemical gradients in arid soils. In this study, we evaluated the spatial variability of soil microbial diversity and chemical parameters (nutrients and ion content at local scale (meters occurring in a gypsum-based desert soil, to gain knowledge on what soil abiotic factors control the distribution of microbes in arid ecosystems. We analyzed 32 soil samples within a 64 m2 plot and: (a characterized microbial diversity using T-RFLPs of the bacterial 16S rRNA gene, (b determined soil chemical parameters, and (c identified relationships between microbial diversity and chemical properties. Overall, we found a strong correlation between microbial composition heterogeneity and spatial variation of cations (Ca2, K+ and anions (HCO ${}_{3}^{-}$ 3 − , Cl−, SO ${}_{4}^{2-}$ 4 2 − content in this small plot. Our results could be attributable to spatial differences of soil saline content, favoring the patchy emergence of salt and soil microbial communities.

Spatial distribution of the chemical properties of the soil and of soybean yield in the field

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Alexandre Gazolla-Neto

2016-06-01

Full Text Available ABSTRACT The aim of this study was to evaluate the spatial dependence between chemical properties of the soil and yield components in the soybean using precision farming techniques. Samples of the soil and plants were taken from georeferenced points to determine the chemical properties of the soil and the yield components. The results were submitted to Pearson correlation analysis, descriptive statistics and geostatistics. The coefficient of variation showed a wide range of distribution for the chemical attributes of the soil, with the highest indices being found for the levels of available phosphorus (102% and potassium (72.65%. Soil pH and organic matter showed a coefficient of variation of 5.96 and 15.93% respectively. Semivariogram analysis of the yield components (productivity, 1,000-seed weight and number of seeds and the chemical properties of the soil (organic matter, pH, phosphorus, potassium, calcium, magnesium, boron, manganese and zinc fitted the spherical model with moderate spatial dependence, with values ranging from 200 to 700 m. Spatial distribution by means of map interpolation was efficient in evaluating spatial variability, allowing the identification and quantification of regions of low and high productivity in the production area, together with the distribution of soil attributes and their respective levels of availability to the soybean plants.

Acoustic Determination of Near-Surface Soil Properties

Science.gov (United States)

2008-12-01

requiring geostatistical analysis, while nearby others are spatially independent. In studies involving many different soil properties and chemistry ...Am 116(6), p. 3354-3369. Kravchenko, N., C.W. Boast, D.G. Bullock, 1991. Fractal analysis of soil spatial variability. Agronomy Journal 91

Spatial variability of soil pH based on GIS combined with geostatistics in Panzhihua tobacco area

International Nuclear Information System (INIS)

Du Wei; Wang Changquan; Li Bing; Li Qiquan; Du Qian; Hu Jianxin; Liu Chaoke

2012-01-01

GIS and geostatistics were utilized to study the spatial variability of soil pH in Panzhihua tobacco area. Results showed that pH values in this area ranged from 4.5 to 8.3, especially 5.5 to 6.5, and in few areas were lower than 5.0 or higher than 7.0 which can meet the need of high-quality tobacco production. The best fitting model of variogram was exponential model with the nugget/sill of soil pH in 13.61% indicating strong spatial correlation. The change process was 5.40 km and the coefficient of determination was 0.491. The spatial variability of soil pH was mainly caused by structural factors such as cane, topography and soil type. The soil pH in Panzhihua tobacco area also showed a increasing trend of northwest to southeast trend. The pH of some areas in Caochang, Gonghe and Yumen were lower, and in Dalongtan were slightly higher. (authors)

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

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Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

Science.gov (United States)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial

The use of spatial empirical models to estimate soil erosion in arid ecosystems.

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Abdullah, Meshal; Feagin, Rusty; Musawi, Layla

2017-02-01

The central objective of this project was to utilize geographical information systems and remote sensing to compare soil erosion models, including Modified Pacific South-west Inter Agency Committee (MPSIAC), Erosion Potential Method (EPM), and Revised Universal Soil Loss Equation (RUSLE), and to determine their applicability for arid regions such as Kuwait. The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the de-militarized zone (DMZ) adjacent to Iraq and has been fenced off to restrict public access since 1994. Results showed that the MPSIAC and EPM models were similar in spatial distribution of erosion, though the MPSIAC had a more realistic spatial distribution of erosion and presented finer level details. The RUSLE presented unrealistic results. We then predicted the amount of soil loss between coastal and desert areas and fenced and unfenced sites for each model. In the MPSIAC and EPM models, soil loss was different between fenced and unfenced sites at the desert areas, which was higher at the unfenced due to the low vegetation cover. The overall results implied that vegetation cover played an important role in reducing soil erosion and that fencing is much more important in the desert ecosystems to protect against human activities such as overgrazing. We conclude that the MPSIAC model is best for predicting soil erosion for arid regions such as Kuwait. We also recommend the integration of field-based experiments with lab-based spatial analysis and modeling in future research.

The contribution of hydroxylamine content to spatial variability of N2O formation in soil of a Norway spruce forest

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Liu, Shurong; Herbst, Michael; Bol, Roland; Gottselig, Nina; Pütz, Thomas; Weymann, Daniel; Wiekenkamp, Inge; Vereecken, Harry; Brüggemann, Nicolas

2016-04-01

Hydroxylamine (NH2OH), a reactive intermediate of several microbial nitrogen turnover processes, is a potential precursor of nitrous oxide (N2O) formation in the soil. However, the contribution of soil NH2OH to soil N2O emission rates in natural ecosystems is unclear. Here, we determined the spatial variability of NH2OH content and potential N2O emission rates of organic (Oh) and mineral (Ah) soil layers of a Norway spruce forest, using a recently developed analytical method for the determination of soil NH2OH content, combined with a geostatistical Kriging approach. Potential soil N2O emission rates were determined by laboratory incubations under oxic conditions, followed by gas chromatographic analysis and complemented by ancillary measurements of soil characteristics. Stepwise multiple regressions demonstrated that the potential N2O emission rates, NH2OH and nitrate (NO3-) content were spatially highly correlated, with hotspots for all three parameters observed in the headwater of a small creek flowing through the sampling area. In contrast, soil ammonium (NH4+) was only weakly correlated with potential N2O emission rates, and was excluded from the multiple regression models. While soil NH2OH content explained the potential soil N2O emission rates best for both layers, also NO3- and Mn content turned out to be significant parameters explaining N2O formation in both soil layers. The Kriging approach was improved markedly by the addition of the co-variable information of soil NH2OH and NO3- content. The results indicate that determination of soil NH2OH content could provide crucial information for the prediction of the spatial variability of soil N2O emissions.

Temporal and spatial variations of soil carbon dioxide, methane, and nitrous oxide fluxes in a Southeast Asian tropical rainforest

Science.gov (United States)

Itoh, M.; Kosugi, Y.; Takanashi, S.; Hayashi, Y.; Kanemitsu, S.; Osaka, K.; Tani, M.; Nik, A. R.

2010-09-01

To clarify the factors controlling temporal and spatial variations of soil carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes, we investigated these gas fluxes and environmental factors in a tropical rainforest in Peninsular Malaysia. Temporal variation of CO2 flux in a 2-ha plot was positively related to soil water condition and rainfall history. Spatially, CO2 flux was negatively related to soil water condition. When CO2 flux hotspots were included, no other environmental factors such as soil C or N concentrations showed any significant correlation. Although the larger area sampled in the present study complicates explanations of spatial variation of CO2 flux, our results support a previously reported bipolar relationship between the temporal and spatial patterns of CO2 flux and soil water condition observed at the study site in a smaller study plot. Flux of CH4 was usually negative with little variation, resulting in the soil at our study site functioning as a CH4 sink. Both temporal and spatial variations of CH4 flux were positively related to the soil water condition. Soil N concentration was also related to the spatial distribution of CH4 flux. Some hotspots were observed, probably due to CH4 production by termites, and these hotspots obscured the relationship between both temporal and spatial variations of CH4 flux and environmental factors. Temporal variation of N2O flux and soil N2O concentration was large and significantly related to the soil water condition, or in a strict sense, to rainfall history. Thus, the rainfall pattern controlled wet season N2O production in soil and its soil surface flux. Spatially, large N2O emissions were detected in wet periods at wetter and anaerobic locations, and were thus determined by soil physical properties. Our results showed that, even in Southeast Asian rainforests where distinct dry and wet seasons do not exist, variation in the soil water condition related to rainfall history controlled the

Spatial variability of soil potassium in sugarcane areas subjected to the application of vinasse

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LAÉRCIO A. DE CARVALHO

2014-12-01

Full Text Available When deposited on land the vinasse can promote improvement in fertility, however, often fertilizer application occurs in areas considered homogeneous, without taking into account the variability of the soil. The objective of this study was to evaluate the effect of vinasse application on potassium content in two classes of soils cultivated with sugarcane, and characterize the spatial variability of soil using geostatistical techniques. In the 2010 and 2011 crop year, soil samples were collected from an experimental grid at 0-0.2 and 0.2-0.4 m depth in three soils cultivated with sugarcane, totaling 90 samplings in each grid, for the determination of pH, calcium (Ca, magnesium (Mg, potassium (K, phosphorus (P, aluminum (Al and potential acidity (H + Al. The data have been submitted to analysis of descriptive statistics and the K attribute was subjected to geostatistical analysis. The coefficient of variation indicated medium and high variability of K for the three soils. The results showed that the spatial dependence of K increased in depth to FRce and decreased to PHlv, indicating that the attribute could have followed the pattern of distribution of clay in depth. The investigation of the spatial variability of K on the surface and subsurface soils provided the definition of management zones with different levels of fertility, which can be organized into sub-areas for a more efficient management of the resources and the environment.

Vegetation-induced spatial variability of soil redox properties in wetlands

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Szalai, Zoltán; Jakab, Gergely; Kiss, Klaudia; Ringer, Marianna; Balázs, Réka; Zacháry, Dóra; Horváth Szabó, Kata; Perényi, Katalin

2016-04-01

Vegetation induced land patches may result spatial pattern of on soil Eh and pH. These spatial pattern are mainly emerged by differences of aeration and exudation of assimilates. Present paper focuses on vertical extent and temporal dynamics of these patterns in wetlands. Two study sites were selected: 1. a plain wetland on calcareous sandy parent material (Ceglédbercel, Danube-Tisza Interfluve, Hungary); 2. headwater wetland with calcareous loamy parent material (Bátaapáti, Hungary). Two vegetation patches were studied in site 1: sedgy (dominated by Carex riparia) and reedy (dominated by Phragmites australis). Three patches were studied in site2: sedgy1 (dominated by C vulpina), sedgy 2 (C. riparia); nettle-horsetail (Urtica dioica and Equisetum arvense). Boundaries between patches were studied separately. Soil redox, pH and temperature studied by automated remote controlled instruments. Three digital sensors (Ponsell) were installed in each locations: 20cm and 40cm sensors represent the solum and 100 cm sensor monitors the subsoil). Groundwater wells were installed near to triplets for soil water sampling. Soil Eh, pH and temperature values were recorded in each 10 minutes. Soil water sampling for iron and DOC were carried out during saturated periods. Spatial pattern of soil Eh is clearly caused by vegetation. We measured significant differences between Eh values of the studied patches in the solum. We did not find this kinds horizontal differences in the subsoil. Boundaries of the patches usually had more reductive soil environment than the core areas. We have found temporal dynamics of the spatial redox pattern. Differences were not so well expressed during wintertime. These spatial patterns had influence on the DOC and iron content of porewater, as well. Highest temporal dynamics of soil redox properties and porewater iron could be found in the boundaries. These observations refer to importance patchiness of vegetation on soil chemical properties in

Spatial variability of soil carbon stock in the Urucu river basin, Central Amazon-Brazil.

Science.gov (United States)

Ceddia, Marcos Bacis; Villela, André Luis Oliveira; Pinheiro, Érika Flávia Machado; Wendroth, Ole

2015-09-01

The Amazon Forest plays a major role in C sequestration and release. However, few regional estimates of soil organic carbon (SOC) stock in this ecoregion exist. One of the barriers to improve SOC estimates is the lack of recent soil data at high spatial resolution, which hampers the application of new methods for mapping SOC stock. The aims of this work were: (i) to quantify SOC stock under undisturbed vegetation for the 0-30 and the 0-100 cm under Amazon Forest; (ii) to correlate the SOC stock with soil mapping units and relief attributes and (iii) to evaluate three geostatistical techniques to generate maps of SOC stock (ordinary, isotopic and heterotopic cokriging). The study site is located in the Central region of Amazon State, Brazil. The soil survey covered the study site that has an area of 80 km(2) and resulted in a 1:10,000 soil map. It consisted of 315 field observations (96 complete soil profiles and 219 boreholes). SOC stock was calculated by summing C stocks by horizon, determined as a product of BD, SOC and the horizon thickness. For each one of the 315 soil observations, relief attributes were derived from a topographic map to understand SOC dynamics. The SOC stocks across 30 and 100 cm soil depth were 3.28 and 7.32 kg C m(-2), respectively, which is, 34 and 16%, lower than other studies. The SOC stock is higher in soils developed in relief forms exhibiting well-drained soils, which are covered by Upland Dense Tropical Rainforest. Only SOC stock in the upper 100 cm exhibited spatial dependence allowing the generation of spatial variability maps based on spatial (co)-regionalization. The CTI was inversely correlated with SOC stock and was the only auxiliary variable feasible to be used in cokriging interpolation. The heterotopic cokriging presented the best performance for mapping SOC stock. Copyright © 2015 Elsevier B.V. All rights reserved.

Intelligent estimation of spatially distributed soil physical properties

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Iwashita, F.; Friedel, M.J.; Ribeiro, G.F.; Fraser, Stephen J.

2012-01-01

Spatial analysis of soil samples is often times not possible when measurements are limited in number or clustered. To obviate potential problems, we propose a new approach based on the self-organizing map (SOM) technique. This approach exploits underlying nonlinear relation of the steady-state geomorphic concave-convex nature of hillslopes (from hilltop to bottom of the valley) to spatially limited soil textural data. The topographic features are extracted from Shuttle Radar Topographic Mission elevation data; whereas soil textural (clay, silt, and sand) and hydraulic data were collected in 29 spatially random locations (50 to 75. cm depth). In contrast to traditional principal component analysis, the SOM identifies relations among relief features, such as, slope, horizontal curvature and vertical curvature. Stochastic cross-validation indicates that the SOM is unbiased and provides a way to measure the magnitude of prediction uncertainty for all variables. The SOM cross-component plots of the soil texture reveals higher clay proportions at concave areas with convergent hydrological flux and lower proportions for convex areas with divergent flux. The sand ratio has an opposite pattern with higher values near the ridge and lower values near the valley. Silt has a trend similar to sand, although less pronounced. The relation between soil texture and concave-convex hillslope features reveals that subsurface weathering and transport is an important process that changed from loss-to-gain at the rectilinear hillslope point. These results illustrate that the SOM can be used to capture and predict nonlinear hillslope relations among relief, soil texture, and hydraulic conductivity data. ?? 2011 Elsevier B.V.

Identifying change in spatial accumulation of soil salinity in an inland river watershed, China.

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Wang, Yugang; Deng, Caiyun; Liu, Yan; Niu, Ziru; Li, Yan

2018-04-15

Soil salinity accumulation is strong in arid areas and it has become a serious environmental problem. Knowledge of the process and spatial changes of accumulated salinity in soil can provide an insight into the spatial patterns of soil salinity accumulation. This is especially useful for estimating the spatial transport of soil salinity at the watershed scale. This study aimed to identify spatial patterns of salt accumulation in the top 20cm soils in a typical inland watershed, the Sangong River watershed in arid northwest China, using geostatistics, spatial analysis technology and the Lorenz curve. The results showed that: (1) soil salt content had great spatial variability (coefficient variation >1.0) in both in 1982 and 2015, and about 56% of the studied area experienced transition the degree of soil salt content from one class to another during 1982-2015. (2) Lorenz curves describing the proportions of soil salinity accumulation (SSA) identified that the boundary between soil salinity migration and accumulation regions was 24.3m lower in 2015 than in 1982, suggesting a spatio-temporal inequality in loading of the soil salinity transport region, indicating significant migration of soil salinity from the upstream to the downstream watershed. (3) Regardless of migration or accumulation region, the mean value of SSA per unit area was 0.17kg/m 2 higher in 2015 than 1982 (pwatershed during the studied period in the arid northwest of China. This study demonstrates the spatial patterns of soil salinity accumulation, which is particularly useful for estimating the spatial transport of soil salinity at the watershed scale. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial prediction of near surface soil water retention functions using hydrogeophysics

Science.gov (United States)

Gibson, J. P.; Franz, T. E.

2017-12-01

The hydrological community often turns to widely available spatial datasets such as SSURGO to characterize the spatial variability of soil across a landscape of interest. This has served as a reasonable first approximation when lacking localized soil data. However, previous work has shown that information loss within land surface models primarily stems from parameterization. Localized soil sampling is both expensive and time intense, and thus a need exists in connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with larger spatial datasets. In this work, we utilize 2 geophysical techniques; cosmic ray neutron probe and electromagnetic induction, to identify temporally stable soil moisture patterns. This is achieved by measuring numerous times over a range of wet to dry field conditions in order to apply an empirical orthogonal function. We then present measured water retention functions of shallow cores extracted within each temporally stable zone. Lastly, we use soil moisture patterns as a covariate to predict soil hydraulic properties in areas without measurement and validate using a leave-one-out cross validation analysis. Using these approaches to better constrain soil hydraulic property variability, we speculate that further research can better estimate hydrologic fluxes in areas of interest.

A Risk Assessment Example for Soil Invertebrates Using Spatially Explicit Agent-Based Models

DEFF Research Database (Denmark)

Reed, Melissa; Alvarez, Tania; Chelinho, Sonia

2016-01-01

Current risk assessment methods for measuring the toxicity of plant protection products (PPPs) on soil invertebrates use standardized laboratory conditions to determine acute effects on mortality and sublethal effects on reproduction. If an unacceptable risk is identified at the lower tier...... population models for ubiquitous soil invertebrates (collembolans and earthworms) as refinement options in current risk assessment. Both are spatially explicit agent-based models (ABMs), incorporating individual and landscape variability. The models were used to provide refined risk assessments for different...... application scenarios of a hypothetical pesticide applied to potato crops (full-field spray onto the soil surface [termed “overall”], in-furrow, and soil-incorporated pesticide applications). In the refined risk assessment, the population models suggest that soil invertebrate populations would likely recover...

SPATIAL CORRELATION BETWEEN PHYSICAL PROPERTIES OF SOIL AND WEEDS IN TWO MANAGEMENT SYSTEMS

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Valter Roberto Schaffrath

2015-02-01

Full Text Available The spatial correlation between soil properties and weeds is relevant in agronomic and environmental terms. The analysis of this correlation is crucial for the interpretation of its meaning, for influencing factors such as dispersal mechanisms, seed production and survival, and the range of influence of soil management techniques. This study aimed to evaluate the spatial correlation between the physical properties of soil and weeds in no-tillage (NT and conventional tillage (CT systems. The following physical properties of soil and weeds were analyzed: soil bulk density, macroporosity, microporosity, total porosity, aeration capacity of soil matrix, soil water content at field capacity, weed shoot biomass, weed density, Commelina benghalensis density, and Bidens pilosa density. Generally, the ranges of the spatial correlations were higher in NT than in CT. The cross-variograms showed that many variables have a structure of combined spatial variation and can therefore be mapped from one another by co-kriging. This combined variation also allows inferences about the physical and biological meanings of the study variables. Results also showed that soil management systems influence the spatial dependence structure significantly.

Seedling establishment and physiological responses to temporal and spatial soil moisture changes

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Jeremy Pinto; John D. Marshall; Kas Dumroese; Anthony S. Davis; Douglas R. Cobos

2016-01-01

In many forests of the world, the summer season (temporal element) brings drought conditions causing low soil moisture in the upper soil profile (spatial element) - a potentially large barrier to seedling establishment. We evaluated the relationship between initial seedling root depth, temporal and spatial changes in soil moisture during drought after...

Spatial variability of detrended soil plow layer penetrometer resistance transect in a sugarcane field

Science.gov (United States)

Pérez, Luis D.; Cumbrera, Ramiro; Mato, Juan; Millán, Humberto; Tarquis, Ana M.

2015-04-01

Spatial variability of soil properties is relevant for identifying those zones with physical degradation. In this sense, one has to face the problem of identifying the origin and distribution of spatial variability patterns (Brouder et al., 2001; Millán et al., 2012). The objective of the present work was to quantify the spatial structure of soil penetrometer resistance (PR) collected from a transect data consisted of 221 points equidistant. In each sampling, readings were obtained from 0 cm till 70 cm of depth, with an interval of 5 cm (Pérez, 2012). The study was conducted on a Vertisol (Typic Hapludert) dedicated to sugarcane (Saccharum officinarum L.) production during the last sixty years (Pérez et al., 2010). Recently, scaling approach has been applied on the determination of the scaling data properties (Tarquis et al., 2008; Millán et al., 2012; Pérez, 2012). We focus in the Hurst analysis to characterize the data variability for each depth. Previously a detrended analysis was conducted in order to better study de intrinsic variability of the series. The Hurst exponent (H) for each depth was estimated showing a characteristic pattern and differentiating PR evolution in depth. References Brouder, S., Hofmann, B., Reetz, H.F., 2001. Evaluating spatial variability of soil parameters for input management. Better Crops 85, 8-11. Millán, H; AM Tarquís, Luís D. Pérez, Juan Mato, Mario González-Posada, 2012. Spatial variability patterns of some Vertisol properties at a field scale using standardized data. Soil and Tillage Research, 120, 76-84. Pérez, Luís D. 2012. Influencia de la maquinaria agrícola sobre la variabilidad espacial de la compactación del suelo. Aplicación de la metodología geoestadística-fractal. PhD thesis, UPM (In Spanish). Pérez, Luís D., Humberto Millán, Mario González-Posada 2010. Spatial complexity of soil plow layer penetrometer resistance as influenced by sugarcane harvesting: A prefractal approach. Soil and Tillage

ASSESSMENT SPATIAL VARIABILITY OF SOIL ERODIBILITY BY USING OF GEOSTATISTIC AND GIS (Case study MEHR watershed of SABZEVAR

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Ayoubi, S.A

2005-05-01

Full Text Available Soil erodibility is one of the key factors on some sediment and soil erosion models such as USLE, MUSLE, RUSLE, AUSLE (USLE modified in LS factor and MMF and represents like K factor and is function of particle distribution, organic mater, soil structure and ermeability. Traditional methods do not take spatial variability and estimate precision of variables in to consideration and amount of them are constant across the whole of soil series .This study was performed to assess spatial variability of soil erodibility and its relevant variables at MEHR watershed from Khorasan province, in northern Iran. Interested network was designed by 110 samples like nested- systematic with distance about 50, 100, 250 and 500 meter across the study area by preparing point map at GIS. Sampling points were identified in field by an Global Positioning system. Soil sampling was done at depth of 0-5cm of ground surface and permeability was studied at depth of 5-30 cm. Some soil properties such as particle distribution and organic mater were measured at laboratory. Particle size distribution was determined by Hydrometer method and Organic matter was measured by wet oxidation approach. Then spatial analysis was done. Variography analysis on soil attributes according to soil erodibility, showed that Gaussian, exponential and spherical models were the most models to predict spatial variability of soil parameters. The range of spatial dependencies was changed from 320 to 3200 m. Soil attribute maps prepared by kriging technique using models parameters. Then soil attributes were composed by Wischmeier (1978 formula in Illwis media to calculate K factor. Amount of soil erodibility changed from 0.13 to 0.91 that it's maximum and minimum was identified in east and southwest of studiedarea. Soil spatial variability pattern, is similar to silt pattern due to high effect of silt on soil rodibility, Also that is partially confirmed with geology map, indicated which soil

Spatial correlation between weed species densities and soil properties

DEFF Research Database (Denmark)

Walter, Mette; Christensen, Svend; Simmelsgaard, Svend Erik

2002-01-01

The spatial cross-correlation between weed species densities and six soil properties within fields was analysed using cross-semivariograms. The survey was carried out in three successive years in two fields. The most consistent relationship between weed species density (numbers m−2) and soil...... properties was negative cross-correlation between the density of Viola arvensis Murray and clay content. This correlation was found in both fields; however, the range of spatial dependence varied between fields. In one of the fields, the density of Lamium purpureum L. was positively cross......-correlated with the phosphorus content in the soil in all years. The density of Veronica spp. and Poa annua L. was negatively cross-correlated with pH in all three years. Other spatial cross-correlations that were found in this study were inconsistent over time or field site. The densities of some of the weed species were...

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

Energy Technology Data Exchange (ETDEWEB)

Price, Oliver R., E-mail: oliver.price@unilever.co [Warwick-HRI, University of Warwick, Wellesbourne, Warwick, CV32 6EF (United Kingdom); University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom); Oliver, Margaret A. [University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom); Walker, Allan [Warwick-HRI, University of Warwick, Wellesbourne, Warwick, CV32 6EF (United Kingdom); Wood, Martin [University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom)

2009-05-15

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field. - Estimating the spatial scale of herbicide and soil interactions by nested sampling.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

International Nuclear Information System (INIS)

Price, Oliver R.; Oliver, Margaret A.; Walker, Allan; Wood, Martin

2009-01-01

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field. - Estimating the spatial scale of herbicide and soil interactions by nested sampling.

Soil nitrate reducing processes - drivers, mechanisms for spatial variation, and significance for nitrous oxide production.

Science.gov (United States)

Giles, Madeline; Morley, Nicholas; Baggs, Elizabeth M; Daniell, Tim J

2012-01-01

The microbial processes of denitrification and dissimilatory nitrate reduction to ammonium (DNRA) are two important nitrate reducing mechanisms in soil, which are responsible for the loss of nitrate ([Formula: see text]) and production of the potent greenhouse gas, nitrous oxide (N(2)O). A number of factors are known to control these processes, including O(2) concentrations and moisture content, N, C, pH, and the size and community structure of nitrate reducing organisms responsible for the processes. There is an increasing understanding associated with many of these controls on flux through the nitrogen cycle in soil systems. However, there remains uncertainty about how the nitrate reducing communities are linked to environmental variables and the flux of products from these processes. The high spatial variability of environmental controls and microbial communities across small sub centimeter areas of soil may prove to be critical in determining why an understanding of the links between biotic and abiotic controls has proved elusive. This spatial effect is often overlooked as a driver of nitrate reducing processes. An increased knowledge of the effects of spatial heterogeneity in soil on nitrate reduction processes will be fundamental in understanding the drivers, location, and potential for N(2)O production from soils.

Spatial variability of soil carbon stock in the Urucu river basin, Central Amazon-Brazil

International Nuclear Information System (INIS)

Ceddia, Marcos Bacis; Villela, André Luis Oliveira; Pinheiro, Érika Flávia Machado; Wendroth, Ole

2015-01-01

The Amazon Forest plays a major role in C sequestration and release. However, few regional estimates of soil organic carbon (SOC) stock in this ecoregion exist. One of the barriers to improve SOC estimates is the lack of recent soil data at high spatial resolution, which hampers the application of new methods for mapping SOC stock. The aims of this work were: (i) to quantify SOC stock under undisturbed vegetation for the 0–30 and the 0–100 cm under Amazon Forest; (ii) to correlate the SOC stock with soil mapping units and relief attributes and (iii) to evaluate three geostatistical techniques to generate maps of SOC stock (ordinary, isotopic and heterotopic cokriging). The study site is located in the Central region of Amazon State, Brazil. The soil survey covered the study site that has an area of 80 km 2 and resulted in a 1:10,000 soil map. It consisted of 315 field observations (96 complete soil profiles and 219 boreholes). SOC stock was calculated by summing C stocks by horizon, determined as a product of BD, SOC and the horizon thickness. For each one of the 315 soil observations, relief attributes were derived from a topographic map to understand SOC dynamics. The SOC stocks across 30 and 100 cm soil depth were 3.28 and 7.32 kg C m −2 , respectively, which is, 34 and 16%, lower than other studies. The SOC stock is higher in soils developed in relief forms exhibiting well-drained soils, which are covered by Upland Dense Tropical Rainforest. Only SOC stock in the upper 100 cm exhibited spatial dependence allowing the generation of spatial variability maps based on spatial (co)-regionalization. The CTI was inversely correlated with SOC stock and was the only auxiliary variable feasible to be used in cokriging interpolation. The heterotopic cokriging presented the best performance for mapping SOC stock. - Highlights: • The SOC stocks across 30 and 100 cm depth were 3.28 and 7.32 kg C m −2 , respectively. • SOC stocks were 34 and 16%, respectively

Toward Soil Spatial Information Systems (SSIS) for global modeling and ecosystem management

Science.gov (United States)

Baumgardner, Marion F.

1995-01-01

The general objective is to conduct research to contribute toward the realization of a world soils and terrain (SOTER) database, which can stand alone or be incorporated into a more complete and comprehensive natural resources digital information system. The following specific objectives are focussed on: (1) to conduct research related to (a) translation and correlation of different soil classification systems to the SOTER database legend and (b) the inferfacing of disparate data sets in support of the SOTER Project; (2) to examine the potential use of AVHRR (Advanced Very High Resolution Radiometer) data for delineating meaningful soils and terrain boundaries for small scale soil survey (range of scale: 1:250,000 to 1:1,000,000) and terrestrial ecosystem assessment and monitoring; and (3) to determine the potential use of high dimensional spectral data (220 reflectance bands with 10 m spatial resolution) for delineating meaningful soils boundaries and conditions for the purpose of detailed soil survey and land management.

County-Scale Spatial Distribution of Soil Enzyme Activities and Enzyme Activity Indices in Agricultural Land: Implications for Soil Quality Assessment

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Xiangping Tan

2014-01-01

Full Text Available Here the spatial distribution of soil enzymatic properties in agricultural land was evaluated on a county-wide (567 km2 scale in Changwu, Shaanxi Province, China. The spatial variations in activities of five hydrolytic enzymes were examined using geostatistical methods. The relationships between soil enzyme activities and other soil properties were evaluated using both an integrated total enzyme activity index (TEI and the geometric mean of enzyme activities (GME. At the county scale, soil invertase, phosphatase, and catalase activities were moderately spatially correlated, whereas urease and dehydrogenase activities were weakly spatially correlated. Correlation analysis showed that both TEI and GME were better correlated with selected soil physicochemical properties than single enzyme activities. Multivariate regression analysis showed that soil OM content had the strongest positive effect while soil pH had a negative effect on the two enzyme activity indices. In addition, total phosphorous content had a positive effect on TEI and GME in orchard soils, whereas alkali-hydrolyzable nitrogen and available potassium contents, respectively, had negative and positive effects on these two enzyme indices in cropland soils. The results indicate that land use changes strongly affect soil enzyme activities in agricultural land, where TEI provides a sensitive biological indicator for soil quality.

General Relationships between Abiotic Soil Properties and Soil Biota across Spatial Scales and Different Land-Use Types

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Birkhofer, Klaus; Schöning, Ingo; Alt, Fabian; Herold, Nadine; Klarner, Bernhard; Maraun, Mark; Marhan, Sven; Oelmann, Yvonne; Wubet, Tesfaye; Yurkov, Andrey; Begerow, Dominik; Berner, Doreen; Buscot, François; Daniel, Rolf; Diekötter, Tim; Ehnes, Roswitha B.; Erdmann, Georgia; Fischer, Christiane; Foesel, Bärbel; Groh, Janine; Gutknecht, Jessica; Kandeler, Ellen; Lang, Christa; Lohaus, Gertrud; Meyer, Annabel; Nacke, Heiko; Näther, Astrid; Overmann, Jörg; Polle, Andrea; Pollierer, Melanie M.; Scheu, Stefan; Schloter, Michael; Schulze, Ernst-Detlef; Schulze, Waltraud; Weinert, Jan; Weisser, Wolfgang W.; Wolters, Volkmar; Schrumpf, Marion

2012-01-01

Very few principles have been unraveled that explain the relationship between soil properties and soil biota across large spatial scales and different land-use types. Here, we seek these general relationships using data from 52 differently managed grassland and forest soils in three study regions spanning a latitudinal gradient in Germany. We hypothesize that, after extraction of variation that is explained by location and land-use type, soil properties still explain significant proportions of variation in the abundance and diversity of soil biota. If the relationships between predictors and soil organisms were analyzed individually for each predictor group, soil properties explained the highest amount of variation in soil biota abundance and diversity, followed by land-use type and sampling location. After extraction of variation that originated from location or land-use, abiotic soil properties explained significant amounts of variation in fungal, meso- and macrofauna, but not in yeast or bacterial biomass or diversity. Nitrate or nitrogen concentration and fungal biomass were positively related, but nitrate concentration was negatively related to the abundances of Collembola and mites and to the myriapod species richness across a range of forest and grassland soils. The species richness of earthworms was positively correlated with clay content of soils independent of sample location and land-use type. Our study indicates that after accounting for heterogeneity resulting from large scale differences among sampling locations and land-use types, soil properties still explain significant proportions of variation in fungal and soil fauna abundance or diversity. However, soil biota was also related to processes that act at larger spatial scales and bacteria or soil yeasts only showed weak relationships to soil properties. We therefore argue that more general relationships between soil properties and soil biota can only be derived from future studies that consider

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

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Nicolas Chemidlin Prévost-Bouré

Full Text Available Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2: i to examine their spatial structuring; ii to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (LandesSoil Quality Monitoring Network to evaluate the communities' composition turnovers. The relative importance of processes and filters was assessed by distance-based redundancy analysis. This study demonstrates significant community composition turnover rates for soil bacteria and fungi, which were dependent on the region. Bacterial and fungal community composition turnovers were mainly driven by environmental selection explaining from 10% to 20% of community composition variations, but spatial variables also explained 3% to 9% of total variance. These variables highlighted significant spatial autocorrelation of both communities unexplained by the environmental variables measured and could partly be explained by dispersal limitations. Although the identified filters and their hierarchy were dependent on the region and organism, selection was systematically based on a common group of environmental variables: pH, trophic resources, texture and land use. Spatial autocorrelation was also important at

Investigating the spatial anisotropy of soil radioactivity in the region of Vinaninkarena, Antsirabe-Madagascar

International Nuclear Information System (INIS)

Rabesiranana, N.; Rasolonirina, M.; Solonjara, A.F.; Raoelina Andriambololona

2009-01-01

A study was conducted in the region of Vinaninkarena-Antsirabe, to investigate the spatial distrubition of the environmental radioactivity. Forty-two (42) top soil samples were collected from two different sampling points. They were analyzed for uranium and thorium series by gamma spectrometry. In order to determine radioactivity spatial structure, semi-variance analysis was used. From 82 samples and 840 paired data, semi-variances were computed, variograms charted and modelled. Results showed that spatial dependance ranges vary from 100 m to 300m. Moreover, spatial anisotropy is also detected. Such result allows optimizing sampling design for future mapping of the environmental radioactivity of the region.

Spatial Relationships of Urban Land Use, Soils and Heavy Metal ...

African Journals Online (AJOL)

Soils are the basic and most important resources of any people. Differences in soil's physical and chemical properties are related to the spatial distribution of land uses. Most of these human activities generate toxic substances that are transported considerable distances away from source and become accumulated in soils, ...

Soil nitrate reducing processes – drivers, mechanisms for spatial variation, and significance for nitrous oxide production

Science.gov (United States)

Giles, Madeline; Morley, Nicholas; Baggs, Elizabeth M.; Daniell, Tim J.

2012-01-01

The microbial processes of denitrification and dissimilatory nitrate reduction to ammonium (DNRA) are two important nitrate reducing mechanisms in soil, which are responsible for the loss of nitrate (NO3−) and production of the potent greenhouse gas, nitrous oxide (N2O). A number of factors are known to control these processes, including O2 concentrations and moisture content, N, C, pH, and the size and community structure of nitrate reducing organisms responsible for the processes. There is an increasing understanding associated with many of these controls on flux through the nitrogen cycle in soil systems. However, there remains uncertainty about how the nitrate reducing communities are linked to environmental variables and the flux of products from these processes. The high spatial variability of environmental controls and microbial communities across small sub centimeter areas of soil may prove to be critical in determining why an understanding of the links between biotic and abiotic controls has proved elusive. This spatial effect is often overlooked as a driver of nitrate reducing processes. An increased knowledge of the effects of spatial heterogeneity in soil on nitrate reduction processes will be fundamental in understanding the drivers, location, and potential for N2O production from soils. PMID:23264770

Soil nitrate reducing processes – drivers, mechanisms for spatial variation and significance for nitrous oxide production

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Madeline Eleanore Giles

2012-12-01

Full Text Available The microbial processes of denitrification and dissimilatory nitrate reduction to ammonium (DNRA are two important nitrate reducing mechanisms in soil, which are responsible for the loss of nitrate (NO3-¬ and production of the potent greenhouse gas, nitrous oxide (N2O. A number of factors are known to control these processes, including O2 concentrations and moisture content, N, C, pH and the size and community structure of nitrate reducing organisms responsible for the processes. There is an increasing understanding associated with many of these controls on flux through the nitrogen cycle in soil systems. However, there remains uncertainty about how the nitrate reducing communities are linked to environmental variables and the flux of products from these processes. The high spatial variability of environmental controls and microbial communities across small sub cm areas of soil may prove to be critical in determining why an understanding of the links between biotic and abiotic controls has proved elusive. This spatial effect is often overlooked as a driver of nitrate reducing processes. An increased knowledge of the effects of spatial heterogeneity in soil on nitrate reduction processes will be fundamental in understanding the drivers, location and potential for N2O production from soils.

Fine-scale spatial distribution of plants and resources on a sandy soil in the Sahel

NARCIS (Netherlands)

Rietkerk, M.G.; Ouedraogo, T.; Kumar, L.; Sanou, S.; Langevelde, F. van; Kiema, A.; Koppel, J. van de; Andel, J. van; Hearne, J.; Skidmore, A.K.; Ridder, N. de; Stroosnijder, L.; Prins, H.H.T.

2002-01-01

We studied fine-scale spatial plant distribution in relation to the spatial distribution of erodible soil particles, organic matter, nutrients and soil water on a sandy to sandy loam soil in the Sahel. We hypothesized that the distribution of annual plants would be highly spatially autocorrelated

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

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Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landescommunities' composition turnovers. The relative importance of processes and filters was assessed by distance-based redundancy analysis. This study demonstrates significant community composition turnover rates for soil bacteria and fungi, which were dependent on the region. Bacterial and fungal community composition turnovers were mainly driven by environmental selection explaining from 10% to 20% of community composition variations, but spatial variables also explained 3% to 9% of total variance. These variables highlighted significant spatial autocorrelation of both communities unexplained by the environmental variables measured and could partly be explained by dispersal limitations. Although the identified filters and their hierarchy were dependent on the region and organism, selection was systematically based on a common group of environmental variables: pH, trophic resources, texture and land use. Spatial autocorrelation was also important at coarse (80 to 120 km radius) and/or medium (40 to 65 km radius) spatial scales, suggesting dispersal limitations at these scales.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

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Junguo Hu

Full Text Available Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK and Co-Kriging (Co-OK methods. The results indicated that the root mean squared errors (RMSEs and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193 were less than those for the OK method (1.146 and 1.539 when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

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Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

Spatial distribution of soil moisture in precision farming using integrated soil scanning and field telemetry data

Science.gov (United States)

Kalopesas, Charalampos; Galanis, George; Kalopesa, Eleni; Katsogiannos, Fotis; Kalafatis, Panagiotis; Bilas, George; Patakas, Aggelos; Zalidis, George

2015-04-01

Mapping the spatial variation of soil moisture content is a vital parameter for precision agriculture techniques. The aim of this study was to examine the correlation of soil moisture and conductivity (EC) data obtained through scanning techniques with field telemetry data and to spatially separate the field into discrete irrigation management zones. Using the Veris MSP3 model, geo-referenced data for electrical conductivity and organic matter preliminary maps were produced in a pilot kiwifruit field in Chrysoupoli, Kavala. Data from 15 stratified sampling points was used in order to produce the corresponding soil maps. Fusion of the Veris produced maps (OM, pH, ECa) resulted on the delineation of the field into three zones of specific management interest. An appropriate pedotransfer function was used in order to estimate a capacity soil indicator, the saturated volumetric water content (θs) for each zone, while the relationship between ECs and ECa was established for each zone. Validation of the uniformity of the three management zones was achieved by measuring specific electrical conductivity (ECs) along a transect in each zone and corresponding semivariograms for ECs within each zone. Near real-time data produced by a telemetric network consisting of soil moisture and electrical conductivity sensors, were used in order to integrate the temporal component of the specific management zones, enabling the calculation of time specific volumetric water contents on a 10 minute interval, an intensity soil indicator necessary to be incorporated to differentiate spatially the irrigation strategies for each zone. This study emphasizes the benefits yielded by fusing near real time telemetric data with soil scanning data and spatial interpolation techniques, enhancing the precision and validity of the desired results. Furthermore the use of telemetric data in combination with modern database management and geospatial software leads to timely produced operational results

Measuring lateral saturated soil hydraulic conductivity at different spatial scales

Science.gov (United States)

Di Prima, Simone; Marrosu, Roberto; Pirastru, Mario; Niedda, Marcello

2017-04-01

substratum of Permian sandstone that exhibits very low drainage, thus preventing deep water percolation (Castellini et al., 2016). In the laboratory, small-scale lateral and vertical saturated hydraulic conductivity, Ks,v, were determined by the constant-head permeameter method (Klute and Dirksen, 1986) on 20 soil cubes of 1331 cm3 of volume (Bagarello and Sgroi, 2008), allowing determination of mean Ks anisotropy for the hillslope. In the field, small-scale Ks,v was determined by infiltration runs of the BEST (Lassabatere et al., 2006) type carried out using a ring with an inner diameter of 0.15 m. The BEST-steady algorithm, proposed by Bagarello et al. (2014), was used to analyze the cumulative infiltration curves in order to decrease the failure rate of the BEST algorithms (Di Prima et al., 2016). The in situ Ks,l at an intermediate spatial scale was estimated by a trench test (Blanco-Canqui et al., 2002) carried out on a monolith 50 cm wide, 68 cm long and 34.5 cm deep (the depth to substratum). Finally, the large spatial scale (hillslope-scale) Ks,lvalue was estimated from the outflow of a 8.5 m large drain and from the perched water table levels monitored in the hillslope, following the methodology of Brooks et al. (2004). Anisotropy was not detected, since the soil cube experiments did not revealed significant differences between Ks,v and Ks,l values. The differences between the Ks datasets measured by the cube and the BEST methods were not statistically significant at p = 0.05. These methods yielded Ks values 6.4 and 5.8 times lower than the hillslope-scale Ks,l, respectively. The Ks,l value obtained by the trench experiment in the soil monolith was 1440 mm h-1, which was only 1.5 times higher than the hillslope-scale Ks,l. Probably, the chosen size of soil monolith was sufficient to properly represent the spatial heterogeneity of the soil in the hillslope. This finding need to be confirmed by further trench tests in soil monoliths to be carried out in the studied

Spatial variability of soil carbon stock in the Urucu river basin, Central Amazon-Brazil

Energy Technology Data Exchange (ETDEWEB)

Ceddia, Marcos Bacis, E-mail: marcosceddia@gmail.com [Department of Soil, Institute of Agronomy, Universidade Federal Rural do Rio de Janeiro (UFRRJ), Seropédica, RJ 23890-000 (Brazil); Villela, André Luis Oliveira [Colégio Técnico da UFRRJ, RJ, Seropédica 23890-000 (Brazil); Pinheiro, Érika Flávia Machado [Department of Soil, Institute of Agronomy, Universidade Federal Rural do Rio de Janeiro (UFRRJ), Seropédica, RJ 23890-000 (Brazil); Wendroth, Ole [Department of Plant & Soil Sciences, University of Kentucky, College of Agriculture, Lexington, KY (United States)

2015-09-01

The Amazon Forest plays a major role in C sequestration and release. However, few regional estimates of soil organic carbon (SOC) stock in this ecoregion exist. One of the barriers to improve SOC estimates is the lack of recent soil data at high spatial resolution, which hampers the application of new methods for mapping SOC stock. The aims of this work were: (i) to quantify SOC stock under undisturbed vegetation for the 0–30 and the 0–100 cm under Amazon Forest; (ii) to correlate the SOC stock with soil mapping units and relief attributes and (iii) to evaluate three geostatistical techniques to generate maps of SOC stock (ordinary, isotopic and heterotopic cokriging). The study site is located in the Central region of Amazon State, Brazil. The soil survey covered the study site that has an area of 80 km{sup 2} and resulted in a 1:10,000 soil map. It consisted of 315 field observations (96 complete soil profiles and 219 boreholes). SOC stock was calculated by summing C stocks by horizon, determined as a product of BD, SOC and the horizon thickness. For each one of the 315 soil observations, relief attributes were derived from a topographic map to understand SOC dynamics. The SOC stocks across 30 and 100 cm soil depth were 3.28 and 7.32 kg C m{sup −2}, respectively, which is, 34 and 16%, lower than other studies. The SOC stock is higher in soils developed in relief forms exhibiting well-drained soils, which are covered by Upland Dense Tropical Rainforest. Only SOC stock in the upper 100 cm exhibited spatial dependence allowing the generation of spatial variability maps based on spatial (co)-regionalization. The CTI was inversely correlated with SOC stock and was the only auxiliary variable feasible to be used in cokriging interpolation. The heterotopic cokriging presented the best performance for mapping SOC stock. - Highlights: • The SOC stocks across 30 and 100 cm depth were 3.28 and 7.32 kg C m{sup −2}, respectively. • SOC stocks were 34 and 16

Spatial heterogeneity of soils of the Cerrado-Pantanal ecotone

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Isabela Codolo de Lucena

Full Text Available In areas of the Cerrado-Pantanal ecotone in Brazil, the soil displays features which are inherent to the processes of soil formation, both of the Central Plateau and the Pantanal Plain. Given this premise, the area should be noteworthy for its high level of edaphic heterogeneity. The present study aimed to determine the physical, chemical and physico-hydric attributes that best explain the heterogeneity of soils in areas of the Cerrado-Pantanal ecotone, and to assess whether these attributes differ between the studied fragments and between the Cerrado soils of the Central Plateau and of the Pantanal Plain. One hundred and sixty soil samples were collected and 11 profiles described for five areas of the Cerrado-Pantanal ecotone (15º43' S, 56º04' W. The following classes were identified: typic Concretionary Petric Plinthosol; typic Lithoplintic Petric Plinthosol; typic dystrophic Yellow Latosol; dystrophic Yellow Latosol with plinthite, the last three not yet having been described for this region. The chemical attributes CEC, M, OM, K, P, Mg, Ca and Mn explained 40.49% of the variability of the soils in the region under study, whether differing or not between the studied fragments. Spatial distribution of the attributes varied between random and aggregated, with the chemical attributes CEC, K, Ca and Mg being similar to soils of the Pantanal Plain. Whereas Al, P and Mn, as well as the hydric variables, were similar to the Plateau. On the other hand, the average organic matter content, pH, gravel and pebbles, were characteristic of both the Plateau and the Plain.

Geophysical characterization of soil moisture spatial patterns in a tillage experiment

Science.gov (United States)

Martinez, G.; Vanderlinden, K.; Giráldez, J. V.; Muriel, J. L.

2009-04-01

Knowledge on the spatial soil moisture pattern can improve the characterisation of the hydrological response of either field-plots or small watersheds. Near-surface geophysical methods, such as electromagnetic induction (EMI), provide a means to map such patterns using non-invasive and non-destructive measurements of the soil apparent electrical conductivity (ECa. In this study ECa was measured using an EMI sensor and used to characterize spatially the hydrologic response of a cropped field to an intense shower. The study site is part of a long-term tillage experiment in Southern Spain in which Conventional Tillage (CT), Direct Drilling (DD) and Minimum Tillage (MT) are being evaluated since 1982. Soil ECa was measured before and after a rain event of 115 mm, near the soil surface and at deeper depth (ECas and ECad, respectively) using the EM38-DD EMI sensor. Simultaneously, elevation data were collected at each sampling point to generate a Digital Elevation Model (DEM). Soil moisture during the first survey was close to permanent wilting point and near field capacity during the second survey. For the first survey, both ECas and ECad, were higher in the CT and MT than in the DD plots. After the rain event, rill erosion appeared only in CT and MT plots were soil was uncovered, matching the drainage lines obtained from the DEM. Apparent electrical conductivity increased all over the field plot with higher increments in the DD plots. These plots showed the highest ECas and ECad values, in contrast to the spatial pattern found during the first sampling. Difference maps obtained from the two ECas and ECad samplings showed a clear difference between DD plots and CT and MT plots due to their distinct hydrologic response. Water infiltration was higher in the soil of the DD plots than in the MT and CT plots, as reflected by their ECad increment. Higher ECa increments were observed in the depressions of the terrain, where water and sediments accumulated. On the contrary, the

Spatial distribution of lead concentrations in urban surface soils of New Orleans, Louisiana USA.

Science.gov (United States)

Abel, Michael T; Suedel, Burton; Presley, Steven M; Rainwater, Thomas R; Austin, Galen P; Cox, Stephen B; McDaniel, Les N; Rigdon, Richard; Goebel, Timothy; Zartman, Richard; Leftwich, Blair D; Anderson, Todd A; Kendall, Ronald J; Cobb, George P

2010-10-01

Immediately following hurricane Katrina concern was raised over the environmental impact of floodwaters on the city of New Orleans, especially in regard to human health. Several studies were conducted to determine the actual contaminant distribution throughout the city and surrounding wetlands by analyzing soil, sediment, and water for a variety of contaminants including organics, inorganics, and biologics. Preliminary investigations by The Institute of Environmental and Human Health at Texas Tech University concluded that soils and sediments contained pesticides, semi-volatiles, and metals, specifically arsenic, iron, and lead, at concentrations that could pose a significant risk to human health. Additional studies on New Orleans floodwaters revealed similar constituents as well as compounds commonly found in gasoline. More recently, it has been revealed that lead (Pb), arsenic, and vanadium are found intermittently throughout the city at concentrations greater than the human health soil screening levels (HHSSLs) of 400, 22 (non-cancer endpoint) and 390 μg/g, respectively. Of these, Pb appears to present the greatest exposure hazard to humans as a result of its extensive distribution in city soils. In this study, we spatially evaluated Pb concentrations across greater New Orleans surface soils. We established 128 sampling sites throughout New Orleans at approximately half-mile intervals. A soil sample was collected at each site and analyzed for Pb by ICP-AES. Soils from 19 (15%) of the sites had Pb concentrations exceeding the HHSSL threshold of 400 μg/g. It was determined that the highest concentrations of Pb were found in the south and west portions of the city. Pb concentrations found throughout New Orleans in this study were then incorporated into a geographic information system to create a spatial distribution model that can be further used to predict Pb exposure to humans in the city.

Compilation of functional soil maps for the support of spatial planning and land management in Hungary

Science.gov (United States)

Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor; Fodor, Nándor; Illés, Gábor; Bakacsi, Zsófia; Szabó, József

2015-04-01

The main objective of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project is to significantly extend the potential, how demands on spatial soil related information could be satisfied in Hungary. Although a great amount of soil information is available due to former mappings and surveys, there are more and more frequently emerging discrepancies between the available and the expected data. The gaps are planned to be filled with optimized DSM products heavily based on legacy soil data. Delineation of Areas with Excellent Productivity in the framework of the National Regional Development Plan or delimitation of Areas with Natural Constraints in Hungary according to the common European biophysical criteria are primary issues in national level spatial planning. Impact assessment of the forecasted climate change and the analysis of the possibilities of the adaptation in the agriculture and forestry can be supported by scenario based land management modelling, whose results can be also incorporated in spatial planning. All these challenges require adequate, preferably timely and spatially detailed knowledge of the soil cover. For the satisfaction of these demands the soil conditions of Hungary have been digitally mapped based on the most detailed, available recent and legacy soil data, applying proper DSM techniques. Various soil related information were mapped in three distinct approaches: (i) basic soil properties determining agri-environmental conditions (e.g.: soil type according to the Hungarian genetic classification, rootable depth, sand, silt and clay content by soil layers, pH, OM and carbonate content for the plough layer); (ii) biophysical criteria of natural handicaps (e.g.: poor drainage, unfavourable texture and stoniness, shallow rooting depth, poor chemical properties and soil moisture balance) defined by common European system and (iii) agro-meteorologically modelled yield values for different crops, meteorological

Factors controlling the spatial distribution of soil piping erosion on loess-derived soils: A case study from central Belgium

Science.gov (United States)

Verachtert, E.; Van Den Eeckhaut, M.; Poesen, J.; Deckers, J.

2010-06-01

Collapsible loess-derived soils are prone to soil piping erosion, where enlargement of macropores may lead to a subsurface pipe network and eventually to soil collapse and gully development. This study aims at understanding the main factors controlling spatial patterns of piping in loess-derived soils under a temperate climate. To map the spatial distribution of piping and identify the environmental controls on its distribution, a regional survey was carried out in a 236 km 2 study area in the Flemish Ardennes (Belgium). Orthophotos taken at optimal field conditions (winter) were analyzed to detect piping in open landscapes and ground thruthing was systematically done through field surveys. In total, 137 parcels having 560 collapsed pipes were mapped. Dimensions of the sinkholes and local slope gradient were measured in the field and topographical variables were derived from LiDAR data. Land use plays an important role as 97% of the sites with piping are found under pasture. The probability of piping increases rapidly on hillslopes with gradients exceeding 8% and with a concave profile and plan curvature, enhancing subsurface flow concentration. The zones with soil profiles on shallow loess over a relatively thin layer of homogeneous blue massive clays (Aalbeke Member) are most prone to piping. Soil characteristics are of less importance to explain piping occurrence. Furthermore, the topographical threshold line indicating the critical slope gradient for a given contributing drainage area was determined. This threshold line (negative power relation) is similar to the threshold line for shallow gully initiation.

County-Scale Spatial Variability of Macronutrient Availability Ratios in Paddy Soils

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Mingkai Qu

2014-01-01

Full Text Available Macronutrients (N, P, and K are essential to plants but also can be harmful to the environment when their available concentrations in soil are excessive. Availability ratios (available concentration/total concentration of macronutrients may reflect their transforming potential between fixed and available forms in soil. Understanding their spatial distributions and impact factors can be, therefore, helpful to applying specific measures to modify the availability of macronutrients for agricultural and environmental management purposes. In this study, 636 topsoil samples (0–15 cm were collected from paddy fields in Shayang County, Central China, for measuring soil properties. Factors influencing macronutrient availability ratios were investigated, and total and available concentrations of macronutrients were mapped using geostatistical method. Spatial distribution maps of macronutrient availability ratios were further derived. Results show that (1 availability of macronutrients is controlled by multiple factors, and (2 macronutrient availability ratios are spatially varied and may not always have spatial patterns identical to those of their corresponding total and available concentrations. These results are more useful than traditional soil macronutrient average content data for guiding site-specific field management for agricultural production and environmental protection.

Spatial variability of chemical properties of soil under pasture

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Samuel Ferreira da Silva

2016-04-01

Full Text Available The objective of this study was to analyze the spatial variability of soil chemical attributes under pasture, as well as lime and fertilizer recommendations based on the interpretation of soil chemical analysis from two sampling methods: conventional and systematic depths of 0 to 10 and 10 to 20 cm. The study was conducted at IFES-campus Alegre-ES. Data analysis was performed using descriptive statistics and geostatistics. Results indicate that the spatial method enabled the identification of deficit areas and excessive liming and fertilization, which could not be defined by the conventional method.

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

Science.gov (United States)

Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

2016-04-01

Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under

The Effect of Restoration Treatments on the Spatial Variability of Soil Processes under Longleaf Pine Trees

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John K. Hiers

2012-08-01

Full Text Available The objectives of this study were to (1 characterize tree-based spatial patterning of soil properties and understory vegetation in frequently burned (“reference state” and fire-suppressed longleaf pine forests; and (2 determine how restoration treatments affected patterning. To attain these objectives, we used an experimental manipulation of management types implemented 15 years ago in Florida. We randomly located six mature longleaf pine trees in one reference and four restoration treatments (i.e., burn, control, herbicide, and mechanical, for a total of 36 trees. In addition to the original treatments and as part of a monitoring program, all plots were subjected to several prescribed fires during these 15 years. Under each tree, we sampled mineral soil and understory vegetation at 1 m, 2 m, 3 m and 4 m (vegetation only away from the tree. At these sites, soil carbon and nitrogen were higher near the trunk while graminoids, forbs and saw palmetto covers showed an opposite trend. Our results confirmed that longleaf pine trees affect the spatial patterning of soil and understory vegetation, and this patterning was mostly limited to the restoration sites. We suggest frequent burning as a probable cause for a lack of spatial structure in the “reference state”. We attribute the presence of spatial patterning in the restoration sites to accumulation of organic materials near the base of mature trees.

Evaluating water erosion prediction project model using Cesium-137-derived spatial soil redistribution data

Science.gov (United States)

The lack of spatial soil erosion data has been a major constraint on the refinement and application of physically based erosion models. Spatially distributed models can only be thoroughly validated with distributed erosion data. The fallout cesium-137 has been widely used to generate spatial soil re...

Assessment of Vegetation Density and Soil Macrofauna Relationship in Riparian Forest of Karkhe River for the Determination of Rivers Buffer Zone

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SH. Gholami

2014-06-01

Full Text Available The spatial distribution of soil organisms is influenced by the plant cover, thus resulting in a horizontal mosaic of areas subjected to gradients of nutrient availability and microclimatic conditions.This study was conducted to investigate the spatial variability of soil macrofauna in relation to vegetation density in the riparian forest landscape of Karkhe. The vegetation density was determined by calculating the NDVI index. Soil macrofauna were sampled using 200 sampling points along parallel transects (perpendicular to the river. The maximum distance between samples was 0.5 km. Soil macrofauna were extracted from 50 cm×50 cm×25 cm soil monolith by the hand-sorting procedure. Abundance, diversity (Shannon H’ index, richness (Menhinick index and evenness (Sheldon index were calculated. Soil macrofauna and NDVI data were analyzed using geostatistics (variogram in order to describe and quantify the spatial continuity. The variograms were spherical, revealing the presence of spatial autocorrelation. The range of influence was 1724 m for abundance, 1326 m for diversity, 1825 m for richness, 1450 for evenness and 1977 m for NDVI. The kriging maps showed that the NDVI Index and soil macrofauna had spatial variability. The spatial pattern of soil macrofauna abundance and biodiversity were similar to the spatial pattern of vegetation density as shown in the correlation.

Hydraulic conductivity of indeformed soil columns determination by gamma ray transmission

International Nuclear Information System (INIS)

Moreira, Anderson Camargo; Moraes Cavalcante, Fabio Henrique de; Rocha, Marcos Correa da; Filho, Otavio Portezan; Quinones, Fernando Rodolfo Espinosa; Appoloni, Carlos Roberto

2000-01-01

The spatial variation of the soil structure influences the water movement through its porous geometry, which could cause problems in the development of agricultural cultures and also accelerate processes of soil erosion. The gamma ray transmission method has established efficiency for the non-destructive measurement of moisture temporal and space evolution, and consequently in the determination of the hydraulic conductivity of the soil, K(θ). Columns of undisturbed soil (approximately 0.11 x 0.06 x 0.60 m) were removed from a trench in the Campus of Londrina State University. The used soil was classified like distrophic dark red soil (LRd). The indeformed soil columns were wrapped up with paraffin and gauze and were fixed on the table of measurement. The water vertical infiltration in the soil was accomplished by maintaining a water layer of approximately 0.01 m over an area of soil of 75 x 10 -4 m 2 . Layers of filter papers and foam controlled the flow of water in the soil surface. After the conclusion of the infiltration, began the process of redistribution of the water in the soil column, with the objective to determine the function K(θ) in relation to the depth in the column. The moisture profiles θ(z,t) are obtained using a radioactive source of 241 Am (3.7 x 10 9 Bq; 0.0596 MeV), spectrometric electronic chain, a 2x2'' NaI(Tl) detector and a measurements table , which allows the sample to move vertically. The hydraulic conductivity function was determined, applying the Sisson model , at 10 levels in the soil column and the results exhibit an increase of K(θ) with depth. (author)

Spatial interpolation of soil organic carbon using apparent electrical conductivity as secondary information

Science.gov (United States)

Martinez, G.; Vanderlinden, K.; Ordóñez, R.; Muriel, J. L.

2009-04-01

Soil organic carbon (SOC) spatial characterization is necessary to evaluate under what circumstances soil acts as a source or sink of carbon dioxide. However, at the field or catchment scale it is hard to accurately characterize its spatial distribution since large numbers of soil samples are necessary. As an alternative, near-surface geophysical sensor-based information can improve the spatial estimation of soil properties at these scales. Electromagnetic induction (EMI) sensors provide non-invasive and non-destructive measurements of the soil apparent electrical conductivity (ECa), which depends under non-saline conditions on clay content, water content or SOC, among other properties that determine the electromagnetic behavior of the soil. This study deals with the possible use of ECa-derived maps to improve SOC spatial estimation by Simple Kriging with varying local means (SKlm). Field work was carried out in a vertisol in SW Spain. The field is part of a long-term tillage experiment set up in 1982 with three replicates of conventional tillage (CT) and Direct Drilling (DD) plots with unitary dimensions of 15x65m. Shallow and deep (up to 0.8m depth) apparent electrical conductivity (ECas and ECad, respectively) was measured using the EM38-DD EMI sensor. Soil samples were taken from the upper horizont and analyzed for their SOC content. Correlation coefficients of ECas and ECad with SOC were low (0.331 and 0.175) due to the small range of SOC values and possibly also to the different support of the ECa and SOC data. Especially the ECas values were higher in the DD plots. The normalized ECa difference (ΔECa), calculated as the difference between the normalized ECas and ECad values, distinguished clearly the CT and DD plots, with the DD plots showing positive ΔECa values and CT plots ΔECa negative values. The field was stratified using fuzzy k-means (FKM) classification of ΔECa (FKM1), and ECas and ECad (FKM2). The FKM1 map mainly showed the difference between

Polycyclic aromatic hydrocarbons in surface soil across the Tibetan Plateau: Spatial distribution, source and air–soil exchange

International Nuclear Information System (INIS)

Wang, Chuanfei; Wang, Xiaoping; Gong, Ping; Yao, Tandong

2014-01-01

There are limited data on polycyclic aromatic hydrocarbons (PAHs) in both the atmosphere and soil of the Tibetan Plateau (TP). Concentrations of PAHs were therefore measured in 13 XAD resin-based passive air samplers and 41 surface (0–5 cm) soil samples across the TP. The average concentration of atmospheric PAHs was 5.55 ng/m 3 , which was lower than that reported for other background areas, but higher than the Arctic. Concentrations in the soils fell in a wide range from 5.54 to 389 ng/g, with an average of 59.9 ng/g. Elevation was found to play an important role in determining the spatial distribution of soil PAHs. The air–soil exchange state showed that the soils of the TP will likely remain as a sink for high molecular weight PAHs, but may become a potential “secondary source” for low molecular weight PAHs. Highlights: • The levels of PAHs in air and soil of the Tibetan Plateau were relatively lower than other background region of world. • The soil PAHs concentration decreased with the increase of elevation. • The Tibetan Plateau will likely remain as a sink for high molecular weight PAHs. • The Tibetan Plateau may become a potential “secondary source” for low molecular weight PAHs. -- The Tibetan soil will likely remain as a sink for high molecular weight PAHs, but may become a potential “secondary source” for low molecular weight PAHs

Sediment spatial distribution evaluated by three methods and its relation to some soil properties

Energy Technology Data Exchange (ETDEWEB)

Bacchi, O O.S. . [Centro de Energia Nuclear na Agricultura-CENA/USP, Laboratorio de Fisica do Solo, Piracicaba, SP (Brazil); Reichardt, K [Centro de Energia Nuclear na Agricultura-CENA/USP, Laboratorio de Fisica do Solo, Piracicaba, SP (Brazil); Departamento de Ciencias Exatas, Escola Superior de Agricultura ' Luiz de Queiroz' ESALQ/USP, Piracicaba, SP (Brazil); Sparovek, G [Departamento de Solos e Nutricao de Plantas, Escola Superior de Agricultura ' Luiz de Queiroz' ESALQ/USP, Piracicaba, SP (Brazil)

2003-02-15

An investigation of rates and spatial distribution of sediments on an agricultural field cultivated with sugarcane was undertaken using the {sup 137}Cs technique, USLE and WEPP models. The study was carried out on the Ceveiro watershed of the Piracicaba river basin, state of Sao Paulo, Brazil, experiencing severe soil degradation due to soil erosion. The objectives of the study were to compare the spatial distribution of sediments evaluated by the three methods and its relation to some soil properties. Erosion and sedimentation rates and their spatial distribution estimated by the three methods were completely different. Although not able to show sediment deposition, the spatial distribution of erosion rates evaluated by USLE presented the best correlation with other studied soil properties. (author)

Functional resilience of microbial ecosystems in soil: How important is a spatial analysis?

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König, Sara; Banitz, Thomas; Centler, Florian; Frank, Karin; Thullner, Martin

2015-04-01

Microbial life in soil is exposed to fluctuating environmental conditions influencing the performance of microbially mediated ecosystem services such as biodegradation of contaminants. However, as this environment is typically very heterogeneous, spatial aspects can be expected to play a major role for the ability to recover from a stress event. To determine key processes for functional resilience, simple scenarios with varying stress intensities were simulated within a microbial simulation model and the biodegradation rate in the recovery phase monitored. Parameters including microbial growth and dispersal rates were varied over a typical range to consider microorganisms with varying properties. Besides an aggregated temporal monitoring, the explicit observation of the spatio-temporal dynamics proved essential to understand the recovery process. For a mechanistic understanding of the model system, scenarios were also simulated with selected processes being switched-off. Results of the mechanistic and the spatial view show that the key factors for functional recovery with respect to biodegradation after a simple stress event depend on the location of the observed habitats. The limiting factors near unstressed areas are spatial processes - the mobility of the bacteria as well as substrate diffusion - the longer the distance to the unstressed region the more important becomes the process growth. Furthermore, recovery depends on the stress intensity - after a low stress event the spatial configuration has no influence on the key factors for functional resilience. To confirm these results, we repeated the stress scenarios but this time including an additional dispersal network representing a fungal network in soil. The system benefits from an increased spatial performance due to the higher mobility of the degrading microorganisms. However, this effect appears only in scenarios where the spatial distribution of the stressed area plays a role. With these simulations we

Determination Of Slope Instability Using Spatially Integrated Mapping Framework

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Baharuddin, I. N. Z.; Omar, R. C.; Roslan, R.; Khalid, N. H. N.; Hanifah, M. I. M.

2016-11-01

The determination and identification of slope instability are often rely on data obtained from in-situ soil investigation work where it involves the logistic of machineries and manpower, thus these aspects may increase the cost especially for remote locations. Therefore a method, which is able to identify possible slope instability without frequent ground walkabout survey, is needed. This paper presents the method used in prediction of slope instability using spatial integrated mapping framework which applicable for remote areas such as tropical forest and natural hilly terrain. Spatial data such as geology, topography, land use map, slope angle and elevation were used in regional analysis during desktop study. Through this framework, the occurrence of slope instability was able to be identified and was validate using a confirmatory site- specific analysis.

Spatial variability of nitrogen-15 and its relation to the variability of other soil properties

International Nuclear Information System (INIS)

Selles, F.; Karamanos, R.E.; Kachanoski, R.G.

1986-01-01

The spatial variability of natural 15 N abundance of a cultivated Chernozemic soil and its native prairie counterpart were smaller than that of total N, organic C, and the C/N ratio. Further, the number of samples required to estimate the true mean of total N with a given precision at various probability levels were twofold those required to estimate the true mean of total N with a given precision at various probability levels were twofold those required to determine the mean 15 N abundance of total soil N in the surface horizons may reflect the isotopic composition of the nitrogenous substances entering the soil system or changes in the isotopic composition of soil N due to humification processes, probably induced by variations in topographic and microrelief features of the soil

Factors affecting spatial variation of annual apparent Q₁₀ of soil respiration in two warm temperate forests.

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Junwei Luan

Full Text Available A range of factors has been identified that affect the temperature sensitivity (Q₁₀ values of the soil-to-atmosphere CO₂ flux. However, the factors influencing the spatial distribution of Q₁₀ values within warm temperate forests are poorly understood. In this study, we examined the spatial variation of Q₁₀ values and its controlling factors in both a naturally regenerated oak forest (OF and a pine plantation (PP. Q₁₀ values were determined based on monthly soil respiration (R(S measurements at 35 subplots for each stand from Oct. 2008 to Oct. 2009. Large spatial variation of Q₁₀ values was found in both OF and PP, with their respective ranges from 1.7 to 5.12 and from 2.3 to 6.21. In PP, fine root biomass (FR (R = 0.50, P = 0.002, non-capillary porosity (NCP (R = 0.37, P = 0.03, and the coefficients of variation of soil temperature at 5 cm depth (CV of T₅ (R = -0.43, P = 0.01 well explained the spatial variance of Q₁₀. In OF, carbon pool lability reflected by light fractionation method (LLFOC well explained the spatial variance of Q₁₀ (R = -0.35, P = 0.04. Regardless of forest type, LLFOC and FR correlation with the Q₁₀ values were significant and marginally significant, respectively; suggesting a positive relationship between substrate availability and apparent Q₁₀ values. Parameters related to gas diffusion, such as average soil water content (SWC and NCP, negatively or positively explained the spatial variance of Q₁₀ values. Additionally, we observed significantly higher apparent Q₁₀ values in PP compared to OF, which might be partly attributed to the difference in soil moisture condition and diffusion ability, rather than different substrate availabilities between forests. Our results suggested that both soil chemical and physical characters contributed to the observed large Q₁₀ value variation.

The Relationship between an Invasive Shrub and Soil Moisture: Seasonal Interactions and Spatially Covarying Relations

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Yuhong He

2014-09-01

Full Text Available Recent studies indicate that positive relationships between invasive plants and soil can contribute to further plant invasions. However, it remains unclear whether these relations remain unchanged throughout the growing season. In this study, spatial sequences of field observations along a transect were used to reveal seasonal interactions and spatially covarying relations between one common invasive shrub (Tartarian Honeysuckle, Lonicera tatarica and soil moisture in a tall grassland habitat. Statistical analysis over the transect shows that the contrast between soil moisture in shrub and herbaceous patches vary with season and precipitation. Overall, a negatively covarying relationship between shrub and soil moisture (i.e., drier surface soils at shrub microsites exists during the very early growing period (e.g., May, while in summer a positively covarying phenomenon (i.e., wetter soils under shrubs is usually evident, but could be weakened or vanish during long precipitation-free periods. If there is sufficient rainfall, surface soil moisture and leaf area index (LAI often spatially covary with significant spatial oscillations at an invariant scale (which is governed by the shrub spatial pattern and is about 8 m, but their phase relation in space varies with season, consistent with the seasonal variability of the co-varying phenomena between shrub invasion and soil water content. The findings are important for establishing a more complete picture of how shrub invasion affects soil moisture.

Alaskan soil carbon stocks: spatial variability and dependence on environmental factors

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U. Mishra

2012-09-01

Full Text Available The direction and magnitude of soil organic carbon (SOC changes in response to climate change depend on the spatial and vertical distributions of SOC. We estimated spatially resolved SOC stocks from surface to C horizon, distinguishing active-layer and permafrost-layer stocks, based on geospatial analysis of 472 soil profiles and spatially referenced environmental variables for Alaska. Total Alaska state-wide SOC stock was estimated to be 77 Pg, with 61% in the active-layer, 27% in permafrost, and 12% in non-permafrost soils. Prediction accuracy was highest for the active-layer as demonstrated by highest ratio of performance to deviation (1.5. Large spatial variability was predicted, with whole-profile, active-layer, and permafrost-layer stocks ranging from 1–296 kg C m⁻², 2–166 kg m⁻², and 0–232 kg m⁻², respectively. Temperature and soil wetness were found to be primary controllers of whole-profile, active-layer, and permafrost-layer SOC stocks. Secondary controllers, in order of importance, were found to be land cover type, topographic attributes, and bedrock geology. The observed importance of soil wetness rather than precipitation on SOC stocks implies that the poor representation of high-latitude soil wetness in Earth system models may lead to large uncertainty in predicted SOC stocks under future climate change scenarios. Under strict caveats described in the text and assuming temperature changes from the A1B Intergovernmental Panel on Climate Change emissions scenario, our geospatial model indicates that the equilibrium average 2100 Alaska active-layer depth could deepen by 11 cm, resulting in a thawing of 13 Pg C currently in permafrost. The equilibrium SOC loss associated with this warming would be highest under continuous permafrost (31%, followed by discontinuous (28%, isolated (24.3%, and sporadic (23.6% permafrost areas. Our high-resolution mapping of soil carbon stock reveals the

Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure

Science.gov (United States)

Skvortsova, Elena B.; Mallants, Dirk

2015-01-01

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification

Temporal and spatial dynamics of mineral levels of forage, soil and ...

African Journals Online (AJOL)

Temporal and spatial dynamics of mineral levels of forage, soil and cattle blood ... In the plain lands, local variations occurred for soil phosphorus and magnesium. ... Rangeland improvement and supplementation strategies are suggested to ...

Modeling Spatial Soil Water Dynamics in a Tropical Floodplain, East Africa

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Geofrey Gabiri

2018-02-01

Full Text Available Analyzing the spatial and temporal distribution of soil moisture is critical for ecohydrological processes and for sustainable water management studies in wetlands. The characterization of soil moisture dynamics and its influencing factors in agriculturally used wetlands pose a challenge in data-scarce regions such as East Africa. High resolution and good-quality time series soil moisture data are rarely available and gaps are frequent due to measurement constraints and device malfunctioning. Soil water models that integrate meteorological conditions and soil water storage may significantly overcome limitations due to data gaps at a point scale. The purpose of this study was to evaluate if the Hydrus-1D model would adequately simulate soil water dynamics at different hydrological zones of a tropical floodplain in Tanzania, to determine controlling factors for wet and dry periods and to assess soil water availability. The zones of the Kilombero floodplain were segmented as riparian, middle, and fringe along a defined transect. The model was satisfactorily calibrated (coefficient of determination; R2 = 0.54–0.92, root mean square error; RMSE = 0.02–0.11 on a plot scale using measured soil moisture content at soil depths of 10, 20, 30, and 40 cm. Satisfying statistical measures (R2 = 0.36–0.89, RMSE = 0.03–0.13 were obtained when calibrations for one plot were validated with measured soil moisture for another plot within the same hydrological zone. Results show the transferability of the calibrated Hydrus-1D model to predict soil moisture for other plots with similar hydrological conditions. Soil water storage increased towards the riparian zone, at 262.8 mm/a while actual evapotranspiration was highest (1043.9 mm/a at the fringe. Overbank flow, precipitation, and groundwater control soil moisture dynamics at the riparian and middle zone, while at the fringe zone, rainfall and lateral flow from mountains control soil moisture during the

Spatial data fusion and analysis for soil characterization: a case study in a coastal basin of south-western Sicily (southern Italy

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Donato Sollitto

2012-03-01

Full Text Available Salinization is one of the most serious problems confronting sustainable agriculture in semi-arid and arid regions. Accurate mapping of soil salinization and the associated risk represent a fundamental step in planning agricultural and remediation activities. Geostatistical analysis is very useful for soil quality assessment because it makes it possible to determine the spatial relationships between selected variables and to produce synthetic maps of spatial variation. The main objective of this paper was to map the soil salinization risk in the Delia-Nivolelli alluvial basin (south-western Sicily, southern Italy, using multivariate geostatistical techniques and a set of topographical, physical and soil hydraulic properties. Elevation data were collected from existing topographic maps and analysed preliminarily to improve the estimate precision of sparsely sampled primary variables. For interpolation multi-collocated cokriging was applied to the dataset, including textural and hydraulic properties and electrical conductivity measurements carried out on 128 collected soil samples, using elevation data as auxiliary variable. Spatial dependence among elevation and physical soil properties was explored with factorial kriging analysis (FKA that could isolate and display the sources of variation acting at different spatial scales. FKA isolated significant regionalised factors which give a concise description of the complex soil physical variability at the different selected spatial scales. These factors mapped, allowed the delineation of zones at different salinisation risk to be managed separately to control and prevent salinization risk. The proposed methodology could be a valid support for land use and soil remediation planning at regional scale.

Environmental determinants of the spatial distribution of Alaria alata in Hungary.

Science.gov (United States)

Széll, Z; Tolnai, Z; Sréter, T

2013-11-15

Alaria alata is a potential zoonotic parasite, which is widely distributed in Eurasia. To assess the risk of human infection, it is important to know the spatial distribution pattern of the parasite and factors influencing this pattern. To investigate these relationships, 1612 red fox (Vulpes vulpes) carcasses were randomly collected from the whole Hungarian territory, and the intestines were examined by sedimentation and counting technique. The spatial distribution of the parasite was highly clumped. The topographic positions where the foxes had been shot and the intensity of infections were recorded in geographic information system database. Digitized home ranges of infected and uninfected foxes were analysed on the background of geographic vector data of altitude, land cover types, permanent waters, mean annual temperature, annual precipitation and soil permeability. Multiple regression analysis was performed with environmental parameter values and A. alata scores. Based on the statistical analysis, lack of permanent waters, mean annual temperature, annual precipitation and soil permeability were the major determinants of the spatial distribution of A. alata. It can be explained by the use of biotopes by the intermediate hosts. The lack of permanent waters results in the use of temporary waters by the second intermediate hosts, frogs. The higher temperature, the lower precipitation and the higher soil permeability lead to earlier desiccation of temporary waters, and tadpoles and frogs infected with mesocercariae can be more easily predated by the final hosts (e.g., red foxes). Moreover, temporary waters are more easily contaminated with the faeces of the final hosts containing eggs than permanent waters. Therefore, high infection rate with A. alata can be expected mainly in lowland areas, where the hydrogeography of permanent waters is less complex, the precipitation is lower, the mean temperature and the soil permeability are higher than in highland areas

AN ACTIVE-PASSIVE COMBINED ALGORITHM FOR HIGH SPATIAL RESOLUTION RETRIEVAL OF SOIL MOISTURE FROM SATELLITE SENSORS (Invited)

Science.gov (United States)

Lakshmi, V.; Mladenova, I. E.; Narayan, U.

2009-12-01

Soil moisture is known to be an essential factor in controlling the partitioning of rainfall into surface runoff and infiltration and solar energy into latent and sensible heat fluxes. Remote sensing has long proven its capability to obtain soil moisture in near real-time. However, at the present time we have the Advanced Scanning Microwave Radiometer (AMSR-E) on board NASA’s AQUA platform is the only satellite sensor that supplies a soil moisture product. AMSR-E coarse spatial resolution (~ 50 km at 6.9 GHz) strongly limits its applicability for small scale studies. A very promising technique for spatial disaggregation by combining radar and radiometer observations has been demonstrated by the authors using a methodology is based on the assumption that any change in measured brightness temperature and backscatter from one to the next time step is due primarily to change in soil wetness. The approach uses radiometric estimates of soil moisture at a lower resolution to compute the sensitivity of radar to soil moisture at the lower resolution. This estimate of sensitivity is then disaggregated using vegetation water content, vegetation type and soil texture information, which are the variables on which determine the radar sensitivity to soil moisture and are generally available at a scale of radar observation. This change detection algorithm is applied to several locations. We have used aircraft observed active and passive data over Walnut Creek watershed in Central Iowa in 2002; the Little Washita Watershed in Oklahoma in 2003 and the Murrumbidgee Catchment in southeastern Australia for 2006. All of these locations have different soils and land cover conditions which leads to a rigorous test of the disaggregation algorithm. Furthermore, we compare the derived high spatial resolution soil moisture to in-situ sampling and ground observation networks

Spatial Variability of Soil Physical Properties Obtained with Laboratory Methods and Their Relation to Field Electrical Resistivity Measurements

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Dathe, A.; Nemes, A.; Bloem, E.; Patterson, M.; Gimenez, D.; Angyal, A.; Koestel, J. K.; Jarvis, N.

2017-12-01

Soil spatial heterogeneity plays a critical role for describing water and solute transport processes in the unsaturated zone. Although we have a sound understanding of the physical properties underlying this heterogeneity (like macropores causing preferential water flow), their quantification in a spatial context is still a challenge. To improve existing knowledge and modelling approaches we established a field experiment on an agriculturally used silty clay loam (Stagnosol) in SE Norway. Centimeter to decimeter scale heterogeneities were investigated in the field using electrical resistivity tomography (ERT) in a quasi-3D and a real 3D approach. More than 100 undisturbed soil samples were taken in the 2x1x1 m3plot investigated with 3D ERT to determine soil water retention, saturated and unsaturated hydraulic conductivities and bulk density in the laboratory. A subset of these samples was scanned at the computer tomography (CT) facility at the Swedish University of Agricultural Sciences in Uppsala, Sweden, with special emphasis on characterizing macroporosity. Results show that the ERT measurements captured the spatial distribution of bulk densities and reflected soil water contents. However, ERT could not resolve the large variation observed in saturated hydraulic conductivities from the soil samples. Saturated hydraulic conductivity was clearly related to the macroporosity visible in the CT scans obtained from the respective soil cores. Hydraulic conductivities close to saturation mainly changed with depths in the soil profile and therefore with bulk density. In conclusion, to quantify the spatial heterogeneity of saturated hydraulic conductivities scanning methods with a resolution smaller than the size of macropores have to be used. This is feasible only when the information obtained from for example CT scans of soil cores would be upscaled in a meaningful way.

Using semi-variogram analysis for providing spatially distributed information on soil surface condition for land surface modeling

Science.gov (United States)

Croft, Holly; Anderson, Karen; Kuhn, Nikolaus J.

2010-05-01

The ability to quantitatively and spatially assess soil surface roughness is important in geomorphology and land degradation studies. Soils can experience rapid structural degradation in response to land cover changes, resulting in increased susceptibility to erosion and a loss of Soil Organic Matter (SOM). Changes in soil surface condition can also alter sediment detachment, transport and deposition processes, infiltration rates and surface runoff characteristics. Deriving spatially distributed quantitative information on soil surface condition for inclusion in hydrological and soil erosion models is therefore paramount. However, due to the time and resources involved in using traditional field sampling techniques, there is a lack of spatially distributed information on soil surface condition. Laser techniques can provide data for a rapid three dimensional representation of the soil surface at a fine spatial resolution. This provides the ability to capture changes at the soil surface associated with aggregate breakdown, flow routing, erosion and sediment re-distribution. Semi-variogram analysis of the laser data can be used to represent spatial dependence within the dataset; providing information about the spatial character of soil surface structure. This experiment details the ability of semi-variogram analysis to spatially describe changes in soil surface condition. Soil for three soil types (silt, silt loam and silty clay) was sieved to produce aggregates between 1 mm and 16 mm in size and placed evenly in sample trays (25 x 20 x 2 cm). Soil samples for each soil type were exposed to five different durations of artificial rainfall, to produce progressively structurally degraded soil states. A calibrated laser profiling instrument was used to measure surface roughness over a central 10 x 10 cm plot of each soil state, at 2 mm sample spacing. The laser data were analysed within a geostatistical framework, where semi-variogram analysis quantitatively represented

Land agroecological quality assessment in conditions of high spatial soil cover variability at the Pereslavskoye Opolye.

Science.gov (United States)

Morev, Dmitriy; Vasenev, Ivan

2015-04-01

The essential spatial variability is mutual feature for most natural and man-changed soils at the Central region of European territory of Russia. The original spatial heterogeneity of forest soils has been further complicated by a specific land-use history and human impacts. For demand-driven land-use planning and decision making the quantitative analysis and agroecological interpretation of representative soil cover spatial variability is an important and challenging task that receives increasing attention from private companies, governmental and environmental bodies. Pereslavskoye Opolye is traditionally actively used in agriculture due to dominated high-quality cultivated soddy-podzoluvisols which are relatively reached in organic matter (especially for conditions of the North part at the European territory of Russia). However, the soil cover patterns are often very complicated even within the field that significantly influences on crop yield variability and have to be considered in farming system development and land agroecological quality evaluation. The detailed investigations of soil regimes and mapping of the winter rye yield have been carried in conditions of two representative fields with slopes sharply contrasted both in aspects and degrees. Rye biological productivity and weed infestation have been measured in elementary plots of 0.25 m2 with the following analysis the quality of the yield. In the same plot soil temperature and moisture have been measured by portable devices. Soil sampling was provided from three upper layers by drilling. The results of ray yield detailed mapping shown high differences both in average values and within-field variability on different slopes. In case of low-gradient slope (field 1) there is variability of ray yield from 39.4 to 44.8 dt/ha. In case of expressed slope (field 2) the same species of winter rye grown with the same technology has essentially lower yield and within-field variability from 20 to 29.6 dt/ha. The

Field Scale Spatial Modelling of Surface Soil Quality Attributes in Controlled Traffic Farming

Science.gov (United States)

Guenette, Kris; Hernandez-Ramirez, Guillermo

2017-04-01

The employment of controlled traffic farming (CTF) can yield improvements to soil quality attributes through the confinement of equipment traffic to tramlines with the field. There is a need to quantify and explain the spatial heterogeneity of soil quality attributes affected by CTF to further improve our understanding and modelling ability of field scale soil dynamics. Soil properties such as available nitrogen (AN), pH, soil total nitrogen (STN), soil organic carbon (SOC), bulk density, macroporosity, soil quality S-Index, plant available water capacity (PAWC) and unsaturated hydraulic conductivity (Km) were analysed and compared among trafficked and un-trafficked areas. We contrasted standard geostatistical methods such as ordinary kriging (OK) and covariate kriging (COK) as well as the hybrid method of regression kriging (ROK) to predict the spatial distribution of soil properties across two annual cropland sites actively employing CTF in Alberta, Canada. Field scale variability was quantified more accurately through the inclusion of covariates; however, the use of ROK was shown to improve model accuracy despite the regression model composition limiting the robustness of the ROK method. The exclusion of traffic from the un-trafficked areas displayed significant improvements to bulk density, macroporosity and Km while subsequently enhancing AN, STN and SOC. The ability of the regression models and the ROK method to account for spatial trends led to the highest goodness-of-fit and lowest error achieved for the soil physical properties, as the rigid traffic regime of CTF altered their spatial distribution at the field scale. Conversely, the COK method produced the most optimal predictions for the soil nutrient properties and Km. The use of terrain covariates derived from light ranging and detection (LiDAR), such as of elevation and topographic position index (TPI), yielded the best models in the COK method at the field scale.

Spatial distribution of hydroxylamine and its role in aerobic N2O formation in a Norway spruce forest soil

Science.gov (United States)

Liu, S.; Weymann, D.; Gottselig, N.; Wiekenkamp, I.; Vereecken, H.; Brueggemann, N.

2014-12-01

Hydroxylamine (HA) as a crucial intermediate in the microbial oxidation of ammonium to nitrite (nitrification) is a potential precursor of abiotic N2O formation in the soil. However, the determination of HA concentration in natural soil samples has not been reported until now. Here, we determined the HA concentrations in organic (Oh) and mineral (Ah) layers of 135 soil samples collected from a spruce forest (Wüstebach, Eifel National Park, Germany) using a novel approach, based on the fast extraction of HA from the soil at a pH of 1.7, the oxidation of HA to N2O with Fe3+, and the analysis of produced N2O using gas chromatography (GC). Meanwhile, N2O emission rates were determined by means of aerobic laboratory incubations of 3-g soil in 22-mL vials. Subsequently, the spatial distribution of soil HA concentrations and N2O emission rates in the Oh and Ah layers of the whole sampling area were analyzed using a geostatistical approach. The correlations among soil HA, N2O emission rate, pH, soil C, N, Fe, Mn and soil water content (SWC) were further explored. The HA concentrations ranged from 0.3-44.6 μg N kg-1 dry soil and 0.02-16.2 μg N kg-1 dry soil in the Oh and the Ah layer, respectively. The spatial distribution of HA was similar in both layers, with substantial spatial variability dependent on soil type, tree density and distance to a stream. For example, HA concentration was greater at locations with a thick litter layer or at locations close to the stream. The average N2O emission rate in the Oh layer was 0.38 μg N kg-1 dry soil h-1, 10-fold larger than in the Ah layer. Interestingly, N2O emission rate exhibited high correlation with soil HA content in the Oh (R2 = 0.65, p < 0.01) and Ah (R2 = 0.45, p < 0.05) layer. The results demonstrated that HA is a crucial component for aerobic N2O formation and emission in spruce forest soils. Moreover, HA concentration was negatively correlated with pH and positively correlated with SWC in the Oh layer, while

Spatial distribution and vertical variation of arsenic in Guangdong soil profiles, China

International Nuclear Information System (INIS)

Zhang, H.H.; Yuan, H.X.; Hu, Y.G.; Wu, Z.F.; Zhu, L.A.; Zhu, L.; Li, F.B.; LI, D.Q.

2006-01-01

Total of 260 soil profiles were reported to investigate the arsenic spatial distribution and vertical variation in Guangdong province. The arsenic concentration followed an approximately lognormal distribution. The arsenic geometric mean concentration of 10.4 mg/kg is higher than that of China. An upper baseline concentration of 23.4 mg/kg was estimated for surface soils. The influence of soil properties on arsenic concentration was not important. Arsenic spatial distributions presented similar patterns that high arsenic concentration mainly located in limestone, and sandshale areas, indicating that soil arsenic distribution was dependent on bedrock properties than anthropogenic inputs. Moreover, from A- to C-horizon arsenic geometric mean concentrations had an increasing tendency of 10.4, 10.7 to 11.3 mg/kg. This vertical variation may be related to the lower soil organic matter and soil degradation and erosion. Consequently, the soil arsenic export into surface and groundwaters would reach 1040 t year -1 in the study area. - Soil arsenic movement export is a potential threat to the water quality of the study area

Land degradation assessment by geo-spatially modeling different soil erodibility equations in a semi-arid catchment.

Science.gov (United States)

Saygın, Selen Deviren; Basaran, Mustafa; Ozcan, Ali Ugur; Dolarslan, Melda; Timur, Ozgur Burhan; Yilman, F Ebru; Erpul, Gunay

2011-09-01

Land degradation by soil erosion is one of the most serious problems and environmental issues in many ecosystems of arid and semi-arid regions. Especially, the disturbed areas have greater soil detachability and transportability capacity. Evaluation of land degradation in terms of soil erodibility, by using geostatistical modeling, is vital to protect and reclaim susceptible areas. Soil erodibility, described as the ability of soils to resist erosion, can be measured either directly under natural or simulated rainfall conditions, or indirectly estimated by empirical regression models. This study compares three empirical equations used to determine the soil erodibility factor of revised universal soil loss equation prediction technology based on their geospatial performances in the semi-arid catchment of the Saraykoy II Irrigation Dam located in Cankiri, Turkey. A total of 311 geo-referenced soil samples were collected with irregular intervals from the top soil layer (0-10 cm). Geostatistical analysis was performed with the point values of each equation to determine its spatial pattern. Results showed that equations that used soil organic matter in combination with the soil particle size better agreed with the variations in land use and topography of the catchment than the one using only the particle size distribution. It is recommended that the equations which dynamically integrate soil intrinsic properties with land use, topography, and its influences on the local microclimates, could be successfully used to geospatially determine sites highly susceptible to water erosion, and therefore, to select the agricultural and bio-engineering control measures needed.

The Spatial Variability of Soil Dehydrogenase Activity: A Survey in Urban Soils

OpenAIRE

Kizilkaya, Ridvan; Aşkin, Tayfun

2007-01-01

Information on soil microorganisms and their activity used to determine microbiological characteristics are very important for soil quality and productivity. Studies of enzyme activities provide information on the biochemical processes occurring in soil. There is growing evidence that soil biological parameters may be potential and sensitive indicators of soil ecological conditions and soil management. Soil microbiological parameters may be evaluated statistically due to application of geosta...

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

Science.gov (United States)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

Soil geochemical parameters influencing the spatial distribution of anthrax in Northwest Minnesota, USA

International Nuclear Information System (INIS)

Nath, Samuel; Dere, Ashlee

2016-01-01

Bacillus anthracis is the pathogenic bacterium that causes anthrax, which dwells in soils as highly resilient endospores. B. anthracis spore viability in soil is dependent upon environmental conditions, but the soil properties necessary for spore survival are unclear. In this study we used a range of soil geochemical and physical parameters to predict the spatial distribution of B. anthracis in northwest Minnesota, where 64 cases of anthrax in livestock were reported from 2000 to 2013. Two modeling approaches at different spatial scales were used to identify the soil conditions most correlated to known anthrax cases using both statewide and locally collected soil data. Ecological niche models were constructed using the Maximum Entropy (Maxent) approach and included 11 soil parameters as environmental inputs and recorded anthrax cases as known presences. One ecological niche model used soil data and anthrax presences for the entire state while a second model used locally sampled soil data (n = 125) and a subset of anthrax presences, providing a test of spatial scale. In addition, simple logistic regression models using the localized soil data served as an independent measure of variable importance. Maxent model results indicate that at a statewide level, soil calcium and magnesium concentrations, soil pH, and sand content are the most important properties for predicting soil suitability for B. anthracis while at the local level, clay and sand content along with phosphorous and strontium concentrations are most important. These results also show that the spatial scale of analysis is important when considering soil parameters most important for B. anthracis spores. For example, at a broad scale, B. anthracis spores may require Ca-rich soils and an alkaline pH, but may also concentrate in microenvironments with high Sr concentrations. The study is also one of the first ecological niche models that demonstrates the major importance of soil texture for defining

The spatial relationship between human activities and C, N, P, S in soil based on landscape geochemical interpretation.

Science.gov (United States)

Yu, Huan; He, Zheng-Wei; Kong, Bo; Weng, Zhong-Yin; Shi, Ze-Ming

2016-04-01

The development and formation of chemical elements in soil are affected not only by parent material, climate, biology, and topology factors, but also by human activities. As the main elements supporting life on earth system, the C, N, P, S cycles in soil have been altered by human activity through land-use change, agricultural intensification, and use of fossil fuels. The present study attempts to analyze whether and how a connection can be made between macroscopical control and microcosmic analysis, to estimate the impacts of human activities on C, N, P, S elements in soil, and to determine a way to describe the spatial relationship between C, N, P, S in soil and human activities, by means of landscape geochemical theories and methods. In addition, the disturbances of human activities on C, N, P, S are explored through the analysis of the spatial relationship between human disturbed landscapes and element anomalies, thereby determining the diversified rules of the effects. The study results show that the rules of different landscapes influencing C, N, P, S elements are diversified, and that the C element is closely related to city landscapes; furthermore, the elements N, P, and S are shown to be closely related to river landscapes; the relationships between mine landscapes and the elements C, N, P, S are apparent; the relationships between the elements C, N, P, S and road landscapes are quite close, which shows that road landscapes have significant effects on these elements. Therefore, the conclusion is drawn that the response mechanism analysis of human disturbance and soil chemical element aggregation is feasible, based on the landscape geochemical theories and methods. The spatial information techniques, such as remote sensing and geographic information systems, are effective for research on soil element migration.

Exploratory and spatial data analysis (EDA-SDA) for determining regional background levels and anomalies of potentially toxic elements in soils from Catorce-Matehuala, Mexico

Science.gov (United States)

Chiprés, J.A.; Castro-Larragoitia, J.; Monroy, M.G.

2009-01-01

The threshold between geochemical background and anomalies can be influenced by the methodology selected for its estimation. Environmental evaluations, particularly those conducted in mineralized areas, must consider this when trying to determinate the natural geochemical status of a study area, quantifying human impacts, or establishing soil restoration values for contaminated sites. Some methods in environmental geochemistry incorporate the premise that anomalies (natural or anthropogenic) and background data are characterized by their own probabilistic distributions. One of these methods uses exploratory data analysis (EDA) on regional geochemical data sets coupled with a geographic information system (GIS) to spatially understand the processes that influence the geochemical landscape in a technique that can be called a spatial data analysis (SDA). This EDA-SDA methodology was used to establish the regional background range from the area of Catorce-Matehuala in north-central Mexico. Probability plots of the data, particularly for those areas affected by human activities, show that the regional geochemical background population is composed of smaller subpopulations associated with factors such as soil type and parent material. This paper demonstrates that the EDA-SDA method offers more certainty in defining thresholds between geochemical background and anomaly than a numeric technique, making it a useful tool for regional geochemical landscape analysis and environmental geochemistry studies.

Research Note:Determination of soil hydraulic properties using pedotransfer functions in a semi-arid basin, Turkey

Directory of Open Access Journals (Sweden)

M. Tombul

2004-01-01

Full Text Available Spatial and temporal variations in soil hydraulic properties such as soil moisture q(h and hydraulic conductivity K(q or K(h, may affect the performance of hydrological models. Moreover, the cost of determining soil hydraulic properties by field or laboratory methods makes alternative indirect methods desirable. In this paper, various pedotransfer functions (PTFs are used to estimate soil hydraulic properties for a small semi-arid basin (Kurukavak in the north-west of Turkey. The field measurements were a good fit with the retention curve derived using Rosetta SSC-BD for a loamy soil. To predict parameters to describe soil hydraulic characteristics, continuous PTFs such as Rosetta SSC-BD (Model H3 and SSC-BD-q33q1500 (Model H5 have been applied. Using soil hydraulic properties that vary in time and space, the characteristic curves for three soil types, loam, sandy clay loam and sandy loam have been developed. Spatial and temporal variations in soil moisture have been demonstrated on a plot and catchment scale for loamy soil. It is concluded that accurate site-specific measurements of the soil hydraulic characteristics are the only and probably the most promising method to progress in the future. Keywords: soil hydraulic properties, soil characteristic curves, PTFs

An examination of the spatial variability of CO2 in the profile of managed forest soils

International Nuclear Information System (INIS)

Black, M.; Kellman, L.; Beltrami, H.

2005-01-01

Soil carbon dioxide (CO 2 ) profiles are typically used in soil-gas exchange studies. Although surface flux measuring methods may be more efficient for deriving surface soil CO 2 exchange budgets, they do not provide enough information about the generation of gas through depth. This poses a challenge in quantifying the CO 2 generated from different zones and soil carbon pools through time. The combination of subsurface concentration profiles and estimates of soil diffusivity reveal where CO 2 is being generated in the soil. This combined approach offers greater awareness into processes controlling CO 2 production in soils through depth, and clarifies how soil CO 2 exchange processes in these ecosystems can be changed by management regimes and climate change. Although information about spatial variability in subsurface concentrations within forested soils is limited, it is assumed to be high because of the high spatial variability in soil CO 2 flux estimates and the large variation in vegetation distribution and topography within sites. In this study, the soil CO 2 profile was monitored during the fall of 2004 at depths of 0, 5, 20 and 35 cm at 10 microsites of a clear-cut and an 80 year old intact mixed forest in Atlantic Canada. Microsites were about 10 meters apart and represented a range of microtopographical conditions that typically encompass extremes in soil CO 2 profile patterns. Preliminary results reveal predictable patterns in concentration profiles through depth, and increasing CO 2 concentration with depth, consistent with a large soil source of CO 2 . The significant variability in the soil carbon profile between microsites in the clear-cut and intact forest sites will be investigated to determine if distinct microsite patterns can be identified. The feasibility of using this method for providing process-based versus soil C exchange budgeting information at forested sites will also be examined

Spatial prediction of near surface soil water retention functions using hydrogeophysics and empirical orthogonal functions

Science.gov (United States)

Gibson, Justin; Franz, Trenton E.

2018-06-01

The hydrological community often turns to widely available spatial datasets such as the NRCS Soil Survey Geographic database (SSURGO) to characterize the spatial variability of soil properties. When used to spatially characterize and parameterize watershed models, this has served as a reasonable first approximation when lacking localized or incomplete soil data. Within agriculture, soil data has been left relatively coarse when compared to numerous other data sources measured. This is because localized soil sampling is both expensive and time intense, thus a need exists in better connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, non-invasive, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with spatially exhaustive datasets. In this work, we utilize two common near surface geophysical methods, cosmic-ray neutron probe and electromagnetic induction, to identify temporally stable spatial patterns of measured geophysical properties in three 65 ha agricultural fields in western Nebraska. This is achieved by repeat geophysical observations of the same study area across a range of wet to dry field conditions in order to evaluate with an empirical orthogonal function. Shallow cores were then extracted within each identified zone and water retention functions were generated in the laboratory. Using EOF patterns as a covariate, we quantify the predictive skill of estimating soil hydraulic properties in areas without measurement using a bootstrap validation analysis. Results indicate that sampling locations informed via repeat hydrogeophysical surveys, required only five cores to reduce the cross-validation root mean squared error by an average of 64% as compared to soil parameters predicted by a commonly used benchmark, SSURGO and ROSETTA. The reduction to five strategically located samples within the 65 ha fields reduces sampling efforts by up to ∼90% as compared to

Capturing spatial heterogeneity of soil organic carbon under changing climate

Science.gov (United States)

Mishra, U.; Fan, Z.; Jastrow, J. D.; Matamala, R.; Vitharana, U.

2015-12-01

The spatial heterogeneity of the land surface affects water, energy, and greenhouse gas exchanges with the atmosphere. Designing observation networks that capture land surface spatial heterogeneity is a critical scientific challenge. Here, we present a geospatial approach to capture the existing spatial heterogeneity of soil organic carbon (SOC) stocks across Alaska, USA. We used the standard deviation of 556 georeferenced SOC profiles previously compiled in Mishra and Riley (2015, Biogeosciences, 12:3993-4004) to calculate the number of observations that would be needed to reliably estimate Alaskan SOC stocks. This analysis indicated that 906 randomly distributed observation sites would be needed to quantify the mean value of SOC stocks across Alaska at a confidence interval of ± 5 kg m-2. We then used soil-forming factors (climate, topography, land cover types, surficial geology) to identify the locations of appropriately distributed observation sites by using the conditioned Latin hypercube sampling approach. Spatial correlation and variogram analyses demonstrated that the spatial structures of soil-forming factors were adequately represented by these 906 sites. Using the spatial correlation length of existing SOC observations, we identified 484 new observation sites would be needed to provide the best estimate of the present status of SOC stocks in Alaska. We then used average decadal projections (2020-2099) of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change to investigate whether the location of identified observation sites will shift/change under future climate. Our results showed 12-41 additional observation sites (depending on emission scenarios) will be required to capture the impact of projected climatic conditions by 2100 on the spatial heterogeneity of Alaskan SOC stocks. Our results represent an ideal distribution

Spatiotemporal Dynamics of Soil Penetration Resistance of Recultivated Soil

Directory of Open Access Journals (Sweden)

Zadorozhnaya Galina

2018-03-01

Full Text Available This article examines changes in the spatial distribution of soil penetration resistance in ordinary chernozem (Calcic Chernozem and in the recultivated soil in 2012 and 2014. The measurements were carried out in the field using an Eijkelkamp penetrometer on a regular grid. The depth of measurement was 50 cm, the interval was 5 cm. The indices of variation of soil penetration resistance in space and time have been determined. The degree of spatial dependence of soil penetration resistance has been determined layer by layer. The nature of temporal dynamics of soil penetration resistance of chernozem and technical soil has been described. A significant positive relationship of the structure of chernozem in the two years of the research has been shown. Significant correlations between the data of different years in the technical soil were found to be mostly negative.

Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain

Science.gov (United States)

Gruber, A.; Crow, W. T.; Dorigo, W. A.

2018-02-01

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.

Spatial structure of soil properties at different scales of Mt. Kilimanjaro, Tanzania

Science.gov (United States)

Kühnel, Anna; Huwe, Bernd

2013-04-01

Soils of tropical mountain ecosystems provide important ecosystem services like water and carbon storage, water filtration and erosion control. As these ecosystems are threatened by global warming and the conversion of natural to human-modified landscapes, it is important to understand the implications of these changes. Within the DFG Research Unit "Kilimanjaro ecosystems under global change: Linking biodiversity, biotic interactions and biogeochemical ecosystem processes", we study the spatial heterogeneity of soils and the available water capacity for different land use systems. In the savannah zone of Mt. Kilimanjaro, maize fields are compared to natural savannah ecosystems. In the lower montane forest zone, coffee plantations, traditional home gardens, grasslands and natural forests are studied. We characterize the soils with respect to soil hydrology, emphasizing on the spatial variability of soil texture and bulk density at different scales. Furthermore soil organic carbon and nitrogen, cation exchange capacity and the pH-value are measured. Vis/Nir-Spectroscopy is used to detect small scale physical and chemical heterogeneity within soil profiles, as well as to get information of soil properties on a larger scale. We aim to build a spectral database for these soil properties for the Kilimanjaro region in order to get rapid information for geostatistical analysis. Partial least square regression with leave one out cross validation is used for model calibration. Results for silt and clay content, as well as carbon and nitrogen content are promising, with adjusted R² ranging from 0.70 for silt to 0.86 for nitrogen. Furthermore models for other nutrients, cation exchange capacity and available water capacity will be calibrated. We compare heterogeneity within and across the different ecosystems and state that spatial structure characteristics and complexity patterns in soil parameters can be quantitatively related to biodiversity and functional diversity

Temporal and spatial variation of nitrogen transformations in a coniferous soil.

NARCIS (Netherlands)

Laverman, A.M.; Zoomer, H.R.; van Verseveld, H.W.; Verhoef, H.A.

2000-01-01

Forest soils show a great degree of temporal and spatial variation of nitrogen mineralization. The aim of the present study was to explain temporal variation in nitrate leaching from a nitrogen-saturated coniferous forest soil by potential nitrification, mineralization rates and nitrate uptake by

Modeling the Impacts of Spatial Heterogeneity in the Castor Watershed on Runoff, Sediment, and Phosphorus Loss Using SWAT: I. Impacts of Spatial Variability of Soil Properties.

Science.gov (United States)

Boluwade, Alaba; Madramootoo, Chandra

2013-01-01

Spatial accuracy of hydrologic modeling inputs influences the output from hydrologic models. A pertinent question is to know the optimal level of soil sampling or how many soil samples are needed for model input, in order to improve model predictions. In this study, measured soil properties were clustered into five different configurations as inputs to the Soil and Water Assessment Tool (SWAT) simulation of the Castor River watershed (11-km 2 area) in southern Quebec, Canada. SWAT is a process-based model that predicts the impacts of climate and land use management on water yield, sediment, and nutrient fluxes. SWAT requires geographical information system inputs such as the digital elevation model as well as soil and land use maps. Mean values of soil properties are used in soil polygons (soil series); thus, the spatial variability of these properties is neglected. The primary objective of this study was to quantify the impacts of spatial variability of soil properties on the prediction of runoff, sediment, and total phosphorus using SWAT. The spatial clustering of the measured soil properties was undertaken using the regionalized with dynamically constrained agglomerative clustering and partitioning method. Measured soil data were clustered into 5, 10, 15, 20, and 24 heterogeneous regions. Soil data from the Castor watershed which have been used in previous studies was also set up and termed "Reference". Overall, there was no significant difference in runoff simulation across the five configurations including the reference. This may be attributable to SWAT's use of the soil conservation service curve number method in flow simulation. Therefore having high spatial resolution inputs for soil data may not necessarily improve predictions when they are used in hydrologic modeling.

Determining the spatial variability of wetland soil bulk density, organic matter, and the conversion factor between organic matter and organic carbon across coastal Louisiana, U.S.A.

Science.gov (United States)

Wang, Hongqing; Piazza, Sarai C.; Sharp, Leigh A.; Stagg, Camille L.; Couvillion, Brady R.; Steyer, Gregory D.; McGinnis, Thomas E.

2016-01-01

Soil bulk density (BD), soil organic matter (SOM) content, and a conversion factor between SOM and soil organic carbon (SOC) are often used in estimating SOC sequestration and storage. Spatial variability in BD, SOM, and the SOM–SOC conversion factor affects the ability to accurately estimate SOC sequestration, storage, and the benefits (e.g., land building area and vertical accretion) associated with wetland restoration efforts, such as marsh creation and sediment diversions. There are, however, only a few studies that have examined large-scale spatial variability in BD, SOM, and SOM–SOC conversion factors in coastal wetlands. In this study, soil cores, distributed across the entire coastal Louisiana (approximately 14,667 km2) were used to examine the regional-scale spatial variability in BD, SOM, and the SOM–SOC conversion factor. Soil cores for BD and SOM analyses were collected during 2006–09 from 331 spatially well-distributed sites in the Coastwide Reference Monitoring System network. Soil cores for the SOM–SOC conversion factor analysis were collected from 15 sites across coastal Louisiana during 2006–07. Results of a split-plot analysis of variance with incomplete block design indicated that BD and SOM varied significantly at a landscape level, defined by both hydrologic basins and vegetation types. Vertically, BD and SOM varied significantly among different vegetation types. The SOM–SOC conversion factor also varied significantly at the landscape level. This study provides critical information for the assessment of the role of coastal wetlands in large regional carbon budgets and the estimation of carbon credits from coastal restoration.

Contrasting spatial patterns and ecological attributes of soil bacterial and archaeal taxa across a landscape.

Science.gov (United States)

Constancias, Florentin; Saby, Nicolas P A; Terrat, Sébastien; Dequiedt, Samuel; Horrigue, Wallid; Nowak, Virginie; Guillemin, Jean-Philippe; Biju-Duval, Luc; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2015-06-01

Even though recent studies have clarified the influence and hierarchy of environmental filters on bacterial community structure, those constraining bacterial populations variations remain unclear. In consequence, our ability to understand to ecological attributes of soil bacteria and to predict microbial community response to environmental stress is therefore limited. Here, we characterized the bacterial community composition and the various bacterial taxonomic groups constituting the community across an agricultural landscape of 12 km(2) , by using a 215 × 215 m systematic grid representing 278 sites to precisely decipher their spatial distribution and drivers at this scale. The bacterial and Archaeal community composition was characterized by applying 16S rRNA gene pyrosequencing directly to soil DNA from samples. Geostatistics tools were used to reveal the heterogeneous distribution of bacterial composition at this scale. Soil physical parameters and land management explained a significant amount of variation, suggesting that environmental selection is the major process shaping bacterial composition. All taxa systematically displayed also a heterogeneous and particular distribution patterns. Different relative influences of soil characteristics, land use and space were observed, depending on the taxa, implying that selection and spatial processes might be differentially but not exclusively involved for each bacterial phylum. Soil pH was a major factor determining the distribution of most of the bacterial taxa and especially the most important factor explaining the spatial patterns of α-Proteobacteria and Planctomycetes. Soil texture, organic carbon content and quality were more specific to a few number of taxa (e.g., β-Proteobacteria and Chlorobi). Land management also influenced the distribution of bacterial taxa across the landscape and revealed different type of response to cropping intensity (positive, negative, neutral or hump-backed relationships

Spatial oxygen distribution and nitrous oxide emissions from soil after manure application

DEFF Research Database (Denmark)

Zhu, Kun; Bruun, Sander; Larsen, Morten

2014-01-01

The availability and spatial distribution of oxygen (O2) in agricultural soil are controlling factors in the production and emission of nitrous oxide (N2O) to the atmosphere, but most experiments investigating the effects of various factors on N2O emissions in soil have been conducted without...... to interpret data on N2O emissions following a uniform or layered amendment of manure to agricultural soil. The spatial distribution of O2 and gas emission rates were monitored for 12 h. An anoxic layer formed rapidly around the layered manure, whereas the uniformly distributed manure led to a more widespread...... anoxia. Nitrous oxide emissions increased immediately after depletion of O2 in the manure-amended treatments. Greater understanding and improved knowledge of the spatial distribution of O2 is clearly beneficial and can be used to devise improved application strategies for mitigating N2O emissions from...

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

Science.gov (United States)

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

Directory of Open Access Journals (Sweden)

Holger Hoffmann

Full Text Available We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

Science.gov (United States)

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Mapping The Temporal and Spatial Variability of Soil Moisture Content Using Proximal Soil Sensing

Science.gov (United States)

Virgawati, S.; Mawardi, M.; Sutiarso, L.; Shibusawa, S.; Segah, H.; Kodaira, M.

2018-05-01

In studies related to soil optical properties, it has been proven that visual and NIR soil spectral response can predict soil moisture content (SMC) using proper data analysis techniques. SMC is one of the most important soil properties influencing most physical, chemical, and biological soil processes. The problem is how to provide reliable, fast and inexpensive information of SMC in the subsurface from numerous soil samples and repeated measurement. The use of spectroscopy technology has emerged as a rapid and low-cost tool for extensive investigation of soil properties. The objective of this research was to develop calibration models based on laboratory Vis-NIR spectroscopy to estimate the SMC at four different growth stages of the soybean crop in Yogyakarta Province. An ASD Field-spectrophotoradiometer was used to measure the reflectance of soil samples. The partial least square regression (PLSR) was performed to establish the relationship between the SMC with Vis-NIR soil reflectance spectra. The selected calibration model was used to predict the new samples of SMC. The temporal and spatial variability of SMC was performed in digital maps. The results revealed that the calibration model was excellent for SMC prediction. Vis-NIR spectroscopy was a reliable tool for the prediction of SMC.

Fine-scale spatial distribution of orchid mycorrhizal fungi in the soil of host-rich grasslands.

Science.gov (United States)

Voyron, Samuele; Ercole, Enrico; Ghignone, Stefano; Perotto, Silvia; Girlanda, Mariangela

2017-02-01

Mycorrhizal fungi are essential for the survival of orchid seedlings under natural conditions. The distribution of these fungi in soil can constrain the establishment and resulting spatial arrangement of orchids at the local scale, but the actual extent of occurrence and spatial patterns of orchid mycorrhizal (OrM) fungi in soil remain largely unknown. We addressed the fine-scale spatial distribution of OrM fungi in two orchid-rich Mediterranean grasslands by means of high-throughput sequencing of fungal ITS2 amplicons, obtained from soil samples collected either directly beneath or at a distance from adult Anacamptis morio and Ophrys sphegodes plants. Like ectomycorrhizal and arbuscular mycobionts, OrM fungi (tulasnelloid, ceratobasidioid, sebacinoid and pezizoid fungi) exhibited significant horizontal spatial autocorrelation in soil. However, OrM fungal read numbers did not correlate with distance from adult orchid plants, and several of these fungi were extremely sporadic or undetected even in the soil samples containing the orchid roots. Orchid mycorrhizal 'rhizoctonias' are commonly regarded as unspecialized saprotrophs. The sporadic occurrence of mycobionts of grassland orchids in host-rich stands questions the view of these mycorrhizal fungi as capable of sustained growth in soil. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Influence of environmental factors on the spatial distribution and diversity of forest soil in Latvia

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Raimonds Kasparinskis

2012-02-01

Full Text Available This study was carried out to determine the spatial relationships between environmental factors (Quaternary deposits, topographical situation, land cover, forest site types, tree species, soil texture and soil groups, and their prefix qualifiers (according to the international Food and Agricultural Organization soil classification system World Reference Base for Soil Resources [FAO WRB]. The results show that it is possible to establish relationships between the distribution of environmental factors and soil groups by applying the generalized linear models in data statistical analysis, using the R 2.11.1 software for processing data from 113 sampling plots throughout the forest territory of Latvia.A very high diversity of soil groups in a relatively similar geological structure was revealed. For various reasons there is not always close relationship between the soil group, their prefix qualifiers and Quaternary deposits, as well as between forest site types, the dominant tree species and specific soil group and its prefix qualifiers. Close correlation was established between Quaternary deposits, forest site types, dominant tree species and soil groups within nutrient-poor sediments and very rich deposits containing free carbonates. No significant relationship was detected between the CORINE Land Cover 2005 classes, topographical situation and soil group.

Spatial variation of peat soil properties in the oil-producing region of northeastern Sakhalin

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Lipatov, D. N.; Shcheglov, A. I.; Manakhov, D. V.; Zavgorodnyaya, Yu. A.; Rozanova, M. S.; Brekhov, P. T.

2017-07-01

Morphology and properties of medium-deep oligotrophic peat, oligotrophic peat gley, pyrogenic oligotrophic peat gley, and peat gley soils on subshrub-cotton grass-sphagnum bogs and in swampy larch forests of northeastern Sakhalin have been studied. Variation in the thickness and reserves of litters in the studied bog and forest biogeocenoses has been analyzed. The profile distribution and spatial variability of moisture, density, ash, and pHKCl in separate groups of peat soils have been described. The content and spatial variability of petroleum hydrocarbons have been considered in relation to the accumulation of natural bitumoids by peat soils and the technogenic pressing in the oil-producing region. Variation of each parameter at different distances (10, 50, and 1000 m) has been estimated using a hierarchical sampling scheme. The spatial conjugation of soil parameters has been studied by factor analysis using the principal components method and Spearman correlation coefficients. Regression equations have been proposed to describe relationships of ash content with soil density and content of petroleum hydrocarbons in peat horizons.

Spatial patterns and controls of soil chemical weathering rates along a transient hillslope

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Yoo, K.; Mudd, S.M.; Sanderman, J.; Amundson, Ronald; Blum, A.

2009-01-01

Hillslopes have been intensively studied by both geomorphologists and soil scientists. Whereas geomorphologists have focused on the physical soil production and transport on hillslopes, soil scientists have been concerned with the topographic variation of soil geochemical properties. We combined these differing approaches and quantified soil chemical weathering rates along a grass covered hillslope in Coastal California. The hillslope is comprised of both erosional and depositional sections. In the upper eroding section, soil production is balanced by physical erosion and chemical weathering. The hillslope then transitions to a depositional slope where soil accumulates due to a historical reduction of channel incision at the hillslope's base. Measurements of hillslope morphology and soil thickness were combined with the elemental composition of the soil and saprolite, and interpreted through a process-based model that accounts for both chemical weathering and sediment transport. Chemical weathering of the minerals as they moved downslope via sediment transport imparted spatial variation in the geochemical properties of the soil. Inverse modeling of the field and laboratory data revealed that the long-term soil chemical weathering rates peak at 5 g m- 2 yr- 1 at the downslope end of the eroding section and decrease to 1.5 g m- 2 yr- 1 within the depositional section. In the eroding section, soil chemical weathering rates appear to be primarily controlled by the rate of mineral supply via colluvial input from upslope. In the depositional slope, geochemical equilibrium between soil water and minerals appeared to limit the chemical weathering rate. Soil chemical weathering was responsible for removing 6% of the soil production in the eroding section and 5% of colluvial influx in the depositional slope. These were among the lowest weathering rates reported for actively eroding watersheds, which was attributed to the parent material with low amount of weatherable

Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region

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Penížek, Vít; Zádorová, Tereza; Kodešová, Radka; Vaněk, Aleš

2016-01-01

The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters) influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index) were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree) to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area. PMID:27846230

Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region.

Directory of Open Access Journals (Sweden)

Vít Penížek

Full Text Available The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area.

Temporal and spatial variation of nitrogen transformations in a coniferous forest soils.

NARCIS (Netherlands)

Laverman, A.M.; Zoomer, H.R.; van Verseveld, H.W.; Verhoef, H.A.

2000-01-01

Forest soils show a great degree of temporal and spatial variation of nitrogen mineralization. The aim of the present study was to explain temporal variation in nitrate leaching from a nitrogen-saturated coniferous forest soil by potential nitrification, mineralization rates and nitrate uptake by

Methods of soil organic carbon determination in Brazilian savannah soils

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Juliana Hiromi Sato

2014-08-01

Full Text Available Several methods exist for determining soil organic carbon, and each one has its own advantages and limitations. Consequently, a comparison of the experimental results obtained when these methods are employed is hampered, causing problems in the comparison of carbon stocks in soils. This study aimed at evaluating the analytical procedures used in the determination of carbon and their relationships with soil mineralogy and texture. Wet combustion methods, including Walkley-Black, Mebius and Colorimetric determination as well as dry combustion methods, such as Elemental and Gravimetric Analysis were used. Quantitative textural and mineralogical (kaolinite, goethite and gibbsite analyses were also carried out. The wet digestion methods underestimated the concentration of organic carbon, while the gravimetric method overestimated. Soil mineralogy interfered with the determination of carbon, with emphasis on the gravimetric method that was greatly influenced by gibbsite.

Determination and spatial distribution of 137Cs in soils, mosses and lichens near Kavanayen, Venezuela

International Nuclear Information System (INIS)

LaBrecque, J.J.; Cordoves, P.R.

2007-01-01

The activity of 137 Cs was determined in soils, mosses, lichens and other vegetation along the Caruay River and near the town of Kavanayen. The range of values for the soils was from -1 of 137 Cs (our detection limit) to 14.1 Bq x kg -1 . The range of 137 Cs activities in the mosses ranged from 9.9 to 17.9 Bq x kg -1 with a mean value of 13.4±4 Bq x kg -1 ; all the moss samples were found along the river. While the 137 Cs activities in the lichens ranged from 9.1 to 29.8 Bq x kg -1 ; the two values along the river were about three factors higher than the one near Kavanayen. It was concluded that the 137 Cs activities in the soils, mosses and lichens are much higher along the river in respect to the nearby town of Kavanayen

Spatial Data Mining for Estimating Cover Management Factor of Universal Soil Loss Equation

Science.gov (United States)

Tsai, F.; Lin, T. C.; Chiang, S. H.; Chen, W. W.

2016-12-01

Universal Soil Loss Equation (USLE) is a widely used mathematical model that describes long-term soil erosion processes. Among the six different soil erosion risk factors of USLE, the cover-management factor (C-factor) is related to land-cover/land-use. The value of C-factor ranges from 0.001 to 1, so it alone might cause a thousandfold difference in a soil erosion analysis using USLE. The traditional methods for the estimation of USLE C-factor include in situ experiments, soil physical parameter models, USLE look-up tables with land use maps, and regression models between vegetation indices and C-factors. However, these methods are either difficult or too expensive to implement in large areas. In addition, the values of C-factor obtained using these methods can not be updated frequently, either. To address this issue, this research developed a spatial data mining approach to estimate the values of C-factor with assorted spatial datasets for a multi-temporal (2004 to 2008) annual soil loss analysis of a reservoir watershed in northern Taiwan. The idea is to establish the relationship between the USLE C-factor and spatial data consisting of vegetation indices and texture features extracted from satellite images, soil and geology attributes, digital elevation model, road and river distribution etc. A decision tree classifier was used to rank influential conditional attributes in the preliminary data mining. Then, factor simplification and separation were considered to optimize the model and the random forest classifier was used to analyze 9 simplified factor groups. Experimental results indicate that the overall accuracy of the data mining model is about 79% with a kappa value of 0.76. The estimated soil erosion amounts in 2004-2008 according to the data mining results are about 50.39 - 74.57 ton/ha-year after applying the sediment delivery ratio and correction coefficient. Comparing with estimations calculated with C-factors from look-up tables, the soil erosion

Systems, methods, and software for determining spatially variable distributions of the dielectric properties of a heterogeneous material

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Farrington, Stephen P.

2018-05-15

Systems, methods, and software for measuring the spatially variable relative dielectric permittivity of materials along a linear or otherwise configured sensor element, and more specifically the spatial variability of soil moisture in one dimension as inferred from the dielectric profile of the soil matrix surrounding a linear sensor element. Various methods provided herein combine advances in the processing of time domain reflectometry data with innovations in physical sensing apparatuses. These advancements enable high temporal (and thus spatial) resolution of electrical reflectance continuously along an insulated waveguide that is permanently emplaced in contact with adjacent soils. The spatially resolved reflectance is directly related to impedance changes along the waveguide that are dominated by electrical permittivity contrast due to variations in soil moisture. Various methods described herein are thus able to monitor soil moisture in profile with high spatial resolution.

Potassium availability in soils - forms and spatial distribution

International Nuclear Information System (INIS)

Afari-Sefa, Victor; Kwakye, Peter K.; Nyamiah, Mercy; Okae-Anti, Daniel; Imoro, A. Ziblim

2004-10-01

Potassium forms the third most important plant nutrient limiting plant growth and consequently reducing crop yields. This study was conducted on soil potassium availability, distribution and relationship with other soil properties. Seventeen top soil samples (0-15 cm) were collected from four agro-ecological zones of the Central and Western Regions of Ghana. Water soluble, exchangeable and non-exchangeable forms of K were determined. The exchangeable K was extracted with 1 N-bar NH 4 OAc, 0.1 N-bar HNO 3 , 0.01 M-bar CaCl 2 , Bray No. 1 and 1 N-bar boiling HNO 3 . The non-exchangeable K was extracted with 1 N-bar boiling HNO 3 . Potassium was determined using flame photometer. The results showed that potassium is available in the soil in different forms and amounts. Soils from the forest-savanna transition and coastal savanna zones had relatively higher soil solution K concentration than soils from the moist rainforest and semi-deciduous forest zones. Also, soils of the semi-deciduous forest and forest savanna transition as well as the coastal savanna zones contained 2-3 times exchangeable K of the soils of the moist rainforest. The results also showed that the pH, texture as well as the land use affected K availability in the soils. (author)

Spatial variability of soil carbon across Mexico and the United States

Science.gov (United States)

Vargas, R.; Guevara, M.; Cruz Gaistardo, C.; Paz, F.; de Jong, B.; Etchevers, J.

2015-12-01

Soil organic carbon (SOC) is directly linked to soil quality, food security, and land use/global environmental change. We use publicly available information on SOC and couple it with digital elevation models and derived terrain attributes using a machine learning approach. We found a strong spatial dependency of SOC across the United States, but less spatial dependency of SOC across Mexico. Using High Performance Computing (HPC) we derived a 1 km resolution map of SOC across Mexico and the United States. We tested different machine learning methods (e.g., kernel based, tree based and/or Geo-statistics approaches) for computational efficiency and statistical accuracy. Using random forest combined with geo-statistics we were able to explain >70% of SOC variance for Mexico and >40% in the case of the United States via cross validation. These results compare with other published estimates of SOC at 1km resolution that only explain <30% of SOC variance across the world. Topographic attributes derived from digital elevation models are freely available globally at fine spatial resolution (<100 m), and this information allowed us to make predictions of SOC at fine scales. We further tested this approach using SOC information from the International Soil Carbon Network to predict SOC in other regions of the world. We conclude that this approach (using public information and open source platforms for data analysis) could be implemented to predict detailed explicit information of SOC across different spatial scales.

Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

Science.gov (United States)

Vanwalleghem, T.; Román, A.; Giraldez, J. V.

2016-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

[Spatial characteristics of soil organic carbon and nitrogen storages in Songnen Plain maize belt].

Science.gov (United States)

Zhang, Chun-Hua; Wang, Zong-Ming; Ren, Chun-Ying; Song, Kai-Shan; Zhang, Bai; Liu, Dian-Wei

2010-03-01

By using the data of 382 typical soil profiles from the second soil survey at national and county levels, and in combining with 1:500000 digital soil maps, a spatial database of soil profiles was established. Based on this, the one meter depth soil organic carbon and nitrogen storage in Songnen Plain maize belt of China was estimated, with the spatial characteristics of the soil organic carbon and nitrogen densities as well as the relationships between the soil organic carbon and nitrogen densities and the soil types and land use types analyzed. The soil organic carbon and nitrogen storage in the maize belt was (163.12 +/- 26.48) Tg and (9.53 +/- 1.75) Tg, respectively, mainly concentrated in meadow soil, chernozem, and black soil. The soil organic carbon and nitrogen densities were 5.51-25.25 and 0.37-0.80 kg x m(-2), respectively, and the C/N ratio was about 7.90 -12.67. The eastern and northern parts of the belt had much higher carbon and nitrogen densities than the other parts of the belt, and upland soils had the highest organic carbon density [(19.07 +/- 2.44) kg x m(-2)], forest soils had the highest nitrogen density [(0.82 +/- 0.25) kg x m(-2)], while lowland soils had the lower organic carbon and nitrogen densities.

Spatial Distribution of Polycyclic Aromatic Hydrocarbon (PAH) Concentrations in Soils from Bursa, Turkey.

Science.gov (United States)

Karaca, Gizem

2016-02-01

The objectives of this study were to identify regional variations in soil polycyclic aromatic hydrocarbon (PAH) contamination in Bursa, Turkey, and to determine the distributions and sources of various PAH species and their possible sources. Surface soil samples were collected from 20 different locations. The PAH concentrations in soil samples were analyzed using gas chromatography-mass spectrometry (GC-MS). The total PAH concentrations (∑12 PAH) varied spatially between 8 and 4970 ng/g dry matter (DM). The highest concentrations were measured in soils taken from traffic+barbecue+ residential areas (4970 ng/g DM) and areas with cement (4382 ng/g DM) and iron-steel (4000 ng/g DM) factories. In addition, the amounts of ∑7 carcinogenic PAH ranged from 1 to 3684 ng/g DM, and between 5 and 74 % of the total PAHs consisted of such compounds. Overall, 4-ring PAH compounds (Fl, Pyr, BaA and Chr) were dominant in the soil samples, with 29-82 % of the ∑12 PAH consisting of 4-ring PAH compounds. The ∑12 BaPeq values ranged from 0.1 to 381.8 ng/g DM. Following an evaluation of the molecular diagnostic ratios, it was concluded that the PAH pollution in Bursa soil was related to pyrolytic sources; however, the impact of petrogenic sources should not be ignored.

Spatial variability of isoproturon mineralizing activity within an agricultural field: Geostatistical analysis of simple physicochemical and microbiological soil parameters

Energy Technology Data Exchange (ETDEWEB)

El Sebai, T. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France); Lagacherie, B. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France); Soulas, G. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France); Martin-Laurent, F. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France)]. E-mail: fmartin@dijon.inra.fr

2007-02-15

We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass. - In field spatial variation of isoproturon mineralization mainly results from the spatial heterogeneity of soil pH and microbial C biomass.

Spatial variability of isoproturon mineralizing activity within an agricultural field: Geostatistical analysis of simple physicochemical and microbiological soil parameters

International Nuclear Information System (INIS)

El Sebai, T.; Lagacherie, B.; Soulas, G.; Martin-Laurent, F.

2007-01-01

We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass. - In field spatial variation of isoproturon mineralization mainly results from the spatial heterogeneity of soil pH and microbial C biomass

A Molecular Investigation of Soil Organic Carbon Composition, Variability, and Spatial Distribution Across an Alpine Catchment

Science.gov (United States)

Hsu, H. T.; Lawrence, C. R.; Winnick, M.; Druhan, J. L.; Williams, K. H.; Maher, K.; Rainaldi, G. R.; McCormick, M. E.

2016-12-01

The cycling of carbon through soils is one of the least understood aspects of the global carbon cycle and represents a key uncertainty in the prediction of land-surface response to global warming. Thus, there is an urgent need for advanced characterization of soil organic carbon (SOC) to develop and evaluate a new generation of soil carbon models. We hypothesize that shifts in SOC composition and spatial distribution as a function of soil depth can be used to constrain rates of transformation between the litter layer and the deeper subsoil (extending to a depth of approximately 1 m). To evaluate the composition and distribution of SOC, we collected soil samples from East River, a shale-dominated watershed near Crested Butte, CO, and characterized relative changes in SOC species as a function of depth using elemental analysis (EA), Fourier transform infrared spectroscopy (FT-IR) and bulk C X-ray absorption spectroscopy (XAS). Our results show that total organic carbon (TOC) decreases with depth, and high total inorganic carbon (TIC) content was found in deeper soils (after 75 cm), a characteristic of the bedrock (shale). The distribution of aliphatic C relative to the parent material generally decreases with depth and that polysaccharide can be a substantial component of SOC at various depths. On the other hand, the relative distribution of aromatic C, traditionally viewed as recalcitrant, only makes up a very small part of SOC regardless of depth. These observations confirm that molecular structure is not the only determinant of SOC turnover rate. To study other contributors to SOC decomposition, we studied changes in the spatial correlation of SOC and minerals using X-ray fluorescence spectroscopy (XRF) and scanning transmission X-ray microscopy (STXM). We found that aromatics mostly locate on the surface of small soil aggregates (1-10 μm). Polysaccharides and proteins, both viewed as labile traditionally, are more evenly distributed over the interior of the

Spatial distribution of Cd and Cu in soils in Shenyang Zhangshi Irrigation Area (SZIA), China*

Science.gov (United States)

Sun, Li-na; Yang, Xiao-bo; Wang, Wen-qing; Ma, Li; Chen, Su

2008-01-01

Heavy metal contamination of soils, derived from sewage irrigation, mining and inappropriate utilization of various agrochemicals and pesticides, and so on, has been of wide concern in the last several decades. The Shenyang Zhangshi Irrigation Area (SZIA) in China is a representative area of heavy metal contamination of soils resulting from sewage irrigation for about 30 years. This study investigated the spatial distribution and temporal variation of soil cadmium (Cd) and copper (Cu) contamination in the SZIA. The soil samples were collected from the SZIA in 1990 and 2004; Cd and Cu in soils was analyzed and then the spatial distribution and temporal variation of Cd and Cu in soils were modeled using Kriging methods. The results show that long-term sewage irrigation had caused serious Cd and Cu contamination in soils. The mean and the maximum of soil Cd are markedly higher than the levels in second grade standard soil (LSGSS) in China, and the maximum of soil Cu is close to the LSGSS in China in 2004 and is more than the LSGSS in China in 1990. The contamination magnitude of soil Cd and the soil extent of Cd contamination had evidently increased since sewage irrigation ceased in 1992. The contamination magnitude of soil Cu and the soil extent of Cu contamination had evidently increased in topsoil, but obviously decresed in subsoil. The soil contamination of Cd and Cu was mainly related to Cd and Cu reactivation of contaminated sediments in Shenyang Xi River and the import of Cd and Cu during irrigation. The eluviation of Cd and Cu in contaminated topsoil with rainfall and irrigation water was another factor of temporal-spatial variability of Cd and Cu contamination in soils. PMID:18357631

[Application of spatially explicit landscape model in soil loss study in Huzhong area].

Science.gov (United States)

Xu, Chonggang; Hu, Yuanman; Chang, Yu; Li, Xiuzhen; Bu, Renchang; He, Hongshi; Leng, Wenfang

2004-10-01

Universal Soil Loss Equation (USLE) has been widely used to estimate the average annual soil loss. In most of the previous work on soil loss evaluation on forestland, cover management factor was calculated from the static forest landscape. The advent of spatially explicit forest landscape model in the last decade, which explicitly simulates the forest succession dynamics under natural and anthropogenic disturbances (fire, wind, harvest and so on) on heterogeneous landscape, makes it possible to take into consideration the change of forest cover, and to dynamically simulate the soil loss in different year (e.g. 10 years and 20 years after current year). In this study, we linked a spatially explicit landscape model (LANDIS) with USLE to simulate the soil loss dynamics under two scenarios: fire and no harvest, fire and harvest. We also simulated the soil loss with no fire and no harvest as a control. The results showed that soil loss varied periodically with simulation year, and the amplitude of change was the lowest under the control scenario and the highest under the fire and no harvest scenario. The effect of harvest on soil loss could not be easily identified on the map; however, the cumulative effect of harvest on soil loss was larger than that of fire. Decreasing the harvest area and the percent of bare soil increased by harvest could significantly reduce soil loss, but had no significant effects on the dynamic of soil loss. Although harvest increased the annual soil loss, it tended to decrease the variability of soil loss between different simulation years.

Spatial Variability of Soil Morphorlogical and Physico-Chemical ...

African Journals Online (AJOL)

Spatial Variability of Soil Morphorlogical and Physico-Chemical Properties in Ladoke Akintola University of Technology Cashew Plantation, Ogbomoso. ... Colour (AP, B1 B2 and B3), structure (B2 and B3), stoniness (B1, B2 and B3), concretion (AP B1, B2 and B3) and boundary forms (B1, B2 and B3) have extremely ...

Spatial effects of aboveground biomass on soil ecological parameters and trace gas fluxes in a savannah ecosystem of Mount Kilimanjaro

Science.gov (United States)

Becker, Joscha; Gütlein, Adrian; Sierra Cornejo, Natalia; Kiese, Ralf; Hertel, Dietrich; Kuzyakov, Yakov

2015-04-01

The savannah biome is a hotspot for biodiversity and wildlife conservation in Africa and recently got in the focus of research on carbon sequestration. Savannah ecosystems are under strong pressure from climate and land-use change, especially around populous areas like the Mt. Kilimanjaro region. Savannah vegetation in this area consists of grassland with isolated trees and is therefore characterized by high spatial variation of canopy cover, aboveground biomass and root structure. Canopy structure is known to affect microclimate, throughfall and evapotranspiration and thereby controls soil moisture conditions. Consequently, the canopy structure is a major regulator for soil ecological parameters and soil-atmospheric trace gas exchange (CO2, N2O, CH4) in water limited environments. The spatial distribution of these parameters and the connection between above and belowground processes are important to understand and predict ecosystem changes and estimate its vulnerability. Our objective was to determine trends and changes of soil parameters and relate their spatial variability to the vegetation structure. We chose three trees from each of the two most dominant species (Acacia nilotica and Balanites aegyptiaca) in our research area. For each tree, we selected transects with nine sampling points of the same relative distances to the stem. Distances were calculated in relation to the crown radius. At these each sampling point a soil core was taken and separated in 0-10 cm and 10-30 cm depth. We measured soil carbon (C) and nitrogen (N) storage, microbial biomass carbon C and N, soil respiration as well as root biomass and -density, soil temperature and soil water content. Each tree was characterized by crown spread, leaf area index and basal area. Preliminary results show that C and N stocks decreased about 50% with depth independently of distance to the tree. Soil water content under the tree crown increased with depth while it decreased under grass cover. Microbial

Post-fire spatial patterns of soil nitrogen mineralization and microbial abundance.

Directory of Open Access Journals (Sweden)

Erica A H Smithwick

Full Text Available Stand-replacing fires influence soil nitrogen availability and microbial community composition, which may in turn mediate post-fire successional dynamics and nutrient cycling. However, fires create patchiness at both local and landscape scales and do not result in consistent patterns of ecological dynamics. The objectives of this study were to (1 quantify the spatial structure of microbial communities in forest stands recently affected by stand-replacing fire and (2 determine whether microbial variables aid predictions of in situ net nitrogen mineralization rates in recently burned stands. The study was conducted in lodgepole pine (Pinus contorta var. latifolia and Engelmann spruce/subalpine fir (Picea engelmannii/Abies lasiocarpa forest stands that burned during summer 2000 in Greater Yellowstone (Wyoming, USA. Using a fully probabilistic spatial process model and Bayesian kriging, the spatial structure of microbial lipid abundance and fungi-to-bacteria ratios were found to be spatially structured within plots two years following fire (for most plots, autocorrelation range varied from 1.5 to 10.5 m. Congruence of spatial patterns among microbial variables, in situ net N mineralization, and cover variables was evident. Stepwise regression resulted in significant models of in situ net N mineralization and included variables describing fungal and bacterial abundance, although explained variance was low (R²<0.29. Unraveling complex spatial patterns of nutrient cycling and the biotic factors that regulate it remains challenging but is critical for explaining post-fire ecosystem function, especially in Greater Yellowstone, which is projected to experience increased fire frequencies by mid 21(st Century.

A soil-landscape framework for understanding spatial and temporal variability in biogeochemical processes in catchments

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McGuire, K. J.; Bailey, S. W.; Ross, D. S.

2017-12-01

Heterogeneity in biophysical properties within catchments challenges how we quantify and characterize biogeochemical processes and interpret catchment outputs. Interactions between the spatiotemporal variability of hydrological states and fluxes and soil development can spatially structure catchments, leading to a framework for understanding patterns in biogeochemical processes. In an upland, glaciated landscape at the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, we are embracing the structure and organization of soils to understand the spatial relations between runoff production zones, distinct soil-biogeochemical environments, and solute retention and release. This presentation will use observations from the HBEF to demonstrate that a soil-landscape framework is essential in understanding the spatial and temporal variability of biogeochemical processes in this catchment. Specific examples will include how laterally developed soils reveal the location of active runoff production zones and lead to gradients in primary mineral dissolution and the distribution of weathering products along hillslopes. Soil development patterns also highlight potential carbon and nitrogen cycling hotspots, differentiate acidic conditions, and affect the regulation of surface water quality. Overall, this work demonstrates the importance of understanding the landscape-level structural organization of soils in characterizing the variation and extent of biogeochemical processes that occur in catchments.

Relative spatial soil geochemical variability along two transects across the United States and Canada

Science.gov (United States)

Garrett, Robert G.

2009-01-01

To support the development of protocols for the proposed North American Soil Geochemical Landscapes project, whose objective is to establish baselines for the geochemistry of North American soils, two continental-scale transects across the United States and Canada were sampled in 2004. The sampling employed a spatially stratified random sampling design in order to estimate the variability between 40-km linear sampling units, within them, at sample sites, and due to sample preparation and analytical chemical procedures. The 40-km scale was chosen to be consistent with the density proposed for the continental-scale project. The two transects, north–south (N–S) from northern Manitoba to the USA–Mexico border near El Paso, Texas, and east–west (E–W) from the Virginia shore north of Washington, DC, to north of San Francisco, California, closely following the 38th parallel, have been studied individually. The purpose of this study was to determine if statistically significant systematic spatial variation occurred along the transects. Data for 38 major, minor and trace elements in A- and C-horizon soils where less than 5% of the data were below the detection limit were investigated by Analysis of Variance (ANOVA). A total of 15 elements (K, Na, As, Ba, Be, Ce, La, Mn, Nb, P, Rb, Sb, Th, Tl and W) demonstrated statistically significant (p<0.05) variability at the between-40-km scale for both horizons along both transects. Only Cu failed to demonstrate significant variability at the between-40-km scale for both soil horizons along both transects.

Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

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Arnaud eDechesne

2014-12-01

Full Text Available Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates inter-studies comparisons. However, it is clear that the presence and activity of pesticide degraders is often highly spatially variable with coefficients of variation often exceeding 50% and frequently displays nonrandom spatial patterns. A few controlling factors have tentatively been identified across pesticide classes: they include some soil characteristics (pH and some agricultural management practices (pesticide application, tillage, while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance of spatial heterogeneity on the fate of pesticides in soil has been difficult to obtain but modelling and experimental systems that do not include soil’s full complexity reveal that this heterogeneity must be considered to improve prediction of pesticide biodegradation rates or of leaching risks. Overall, studying the spatial heterogeneity of pesticide biodegradation is a relatively new field at the interface of agronomy, microbial ecology, and geosciences and a wealth of novel data is being collected from these different disciplinary perspectives. We make suggestions on possible avenues to take full advantage of these investigations for a better understanding and prediction of the fate of pesticides in soil.

Farmer data sourcing. The case study of the spatial soil information maps in South Tyrol.

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Della Chiesa, Stefano; Niedrist, Georg; Thalheimer, Martin; Hafner, Hansjörg; La Cecilia, Daniele

2017-04-01

Nord-Italian region South Tyrol is Europe's largest apple growing area exporting ca. 15% in Europe and 2% worldwide. Vineyards represent ca. 1% of Italian production. In order to deliver high quality food, most of the farmers in South Tyrol follow sustainable farming practices. One of the key practice is the sustainable soil management, where farmers collect regularly (each 5 years) soil samples and send for analyses to improve cultivation management, yield and finally profitability. However, such data generally remain inaccessible. On this regard, in South Tyrol, private interests and the public administration have established a long tradition of collaboration with the local farming industry. This has granted to the collection of large spatial and temporal database of soil analyses along all the cultivated areas. Thanks to this best practice, information on soil properties are centralized and geocoded. The large dataset consist mainly in soil information of texture, humus content, pH and microelements availability such as, K, Mg, Bor, Mn, Cu Zn. This data was finally spatialized by mean of geostatistical methods and several high-resolution digital maps were created. In this contribution, we present the best practice where farmers data source soil information in South Tyrol. Show the capability of a large spatial-temporal geocoded soil dataset to reproduce detailed digital soil property maps and to assess long-term changes in soil properties. Finally, implication and potential application are discussed.

Mapping of soil organic carbon stocks for spatially explicit assessments of climate change mitigation potential

International Nuclear Information System (INIS)

Vågen, Tor-Gunnar; Winowiecki, Leigh A

2013-01-01

Current methods for assessing soil organic carbon (SOC) stocks are generally not well suited for understanding variations in SOC stocks in landscapes. This is due to the tedious and time-consuming nature of the sampling methods most commonly used to collect bulk density cores, which limits repeatability across large areas, particularly where information is needed on the spatial dynamics of SOC stocks at scales relevant to management and for spatially explicit targeting of climate change mitigation options. In the current study, approaches were explored for (i) field-based estimates of SOC stocks and (ii) mapping of SOC stocks at moderate to high resolution on the basis of data from four widely contrasting ecosystems in East Africa. Estimated SOC stocks for 0–30 cm depth varied both within and between sites, with site averages ranging from 2 to 8 kg m −2 . The differences in SOC stocks were determined in part by rainfall, but more importantly by sand content. Results also indicate that managing soil erosion is a key strategy for reducing SOC loss and hence in mitigation of climate change in these landscapes. Further, maps were developed on the basis of satellite image reflectance data with multiple R-squared values of 0.65 for the independent validation data set, showing variations in SOC stocks across these landscapes. These maps allow for spatially explicit targeting of potential climate change mitigation efforts through soil carbon sequestration, which is one option for climate change mitigation and adaptation. Further, the maps can be used to monitor the impacts of such mitigation efforts over time. (letter)

Spatial and temporal variation of archaeal, bacterial and fungal communities in agricultural soils

NARCIS (Netherlands)

de Cassia Pereira e Silva, Michele; Franco Dias, Armando Cavalcante; van Elsas, Jan Dirk; Salles, Joana Falcao

2012-01-01

Background: Soil microbial communities are in constant change at many different temporal and spatial scales. However, the importance of these changes to the turnover of the soil microbial communities has been rarely studied simultaneously in space and time. Methodology/Principal Findings: In this

Environmental determinants of the spatial distribution of Echinococcus multilocularis in Hungary.

Science.gov (United States)

Tolnai, Z; Széll, Z; Sréter, T

2013-12-06

Human alveolar echinococcosis, caused by the metacestode stage of Echinococcus multilocularis, is one of the most pathogenic zoonoses in the temperate and arctic region of the Northern Hemisphere. To investigate the spatial distribution of E. multilocularis and the factors influencing this distribution in the recently identified endemic area of Hungary, 1612 red fox (Vulpes vulpes) carcasses were randomly collected from the whole Hungarian territory from November 2008 to February 2009 and from November 2012 to February 2013. The topographic positions of foxes were recorded in geographic information system database. The digitized home ranges and the vector data were used to calculate the altitude, mean annual temperature, annual precipitation, soil water retention, soil permeability, areas of land cover types and the presence and buffer zone of permanent water bodies within the fox territories. The intestinal mucosa from all the foxes was tested by sedimentation and counting technique. Multiple regression analysis was performed with environmental parameter values and E. multilocularis counts. The spatial distribution of the parasite was clumped. Based on statistical analysis, mean annual temperature and annual precipitation were the major determinants of the spatial distribution of E. multilocularis in Hungary. It can be attributed to the sensitivity of E. multilocularis eggs to high temperatures and desiccation. Although spreading and emergence of the parasite was observed in Hungary before 2009, the prevalence and intensity of infection did not change significantly between the two collection periods. It can be explained by the considerably lower annual precipitation before the second collection period. Copyright © 2013 Elsevier B.V. All rights reserved.

Exploring the Role of the Spatial Characteristics of Visible and Near-Infrared Reflectance in Predicting Soil Organic Carbon Density

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Long Guo

2017-10-01

Full Text Available Soil organic carbon stock plays a key role in the global carbon cycle and the precision agriculture. Visible and near-infrared reflectance spectroscopy (VNIRS can directly reflect the internal physical construction and chemical substances of soil. The partial least squares regression (PLSR is a classical and highly commonly used model in constructing soil spectral models and predicting soil properties. Nevertheless, using PLSR alone may not consider soil as characterized by strong spatial heterogeneity and dependence. However, considering the spatial characteristics of soil can offer valuable spatial information to guarantee the prediction accuracy of soil spectral models. Thus, this study aims to construct a rapid and accurate soil spectral model in predicting soil organic carbon density (SOCD with the aid of the spatial autocorrelation of soil spectral reflectance. A total of 231 topsoil samples (0–30 cm were collected from the Jianghan Plain, Wuhan, China. The spectral reflectance (350–2500 nm was used as auxiliary variable. A geographically-weighted regression (GWR model was used to evaluate the potential improvement of SOCD prediction when the spatial information of the spectral features was considered. Results showed that: (1 The principal components extracted from PLSR have a strong relationship with the regression coefficients at the average sampling distance (300 m based on the Moran’s I values. (2 The eigenvectors of the principal components exhibited strong relationships with the absorption spectral features, and the regression coefficients of GWR varied with the geographical locations. (3 GWR displayed a higher accuracy than that of PLSR in predicting the SOCD by VNIRS. This study aimed to help people realize the importance of the spatial characteristics of soil properties and their spectra. This work also introduced guidelines for the application of GWR in predicting soil properties by VNIRS.

Evaluation of spatial variability of metal bioavailability in soils using geostatistics

DEFF Research Database (Denmark)

Owsianiak, Mikolaj; Hauschild, Michael Zwicky; Rosenbaum, Ralph K.

2012-01-01

Soil properties show signifficant spatial variability at local, regional and continental scales. This is a challenge for life cycle impact assessment (LCIA) of metals, because fate, bioavailability and effect factors are controlled by environmental chemistry and can vary orders of magnitude...... is performed using ArcGIS Geostatistical Analyst. Results show that BFs of copper span a range of 6 orders of magnitude, and have signifficant spatial variability at local and continental scales. The model nugget variance is signifficantly higher than zero, suggesting the presence of spatial variability...

Bright soil units on Mars determined from ISM imaging spectrometer data

Science.gov (United States)

Murchie, Scott; Mustard, John

1993-01-01

The lithology of bright Martian soil provides evidence for chemical and physical processes that have modified the planet's surface. Data from the ISM imaging spectrometer, which observed much of the equatorial region at a spatial resolution of approximately 22 km, cover the NIR wavelength range critical to ascertaining the presence and abundance of Fe-containing phases, hydroxylated silicates, and H2O in the bright soil. ISM data previously have revealed spatial variations in depth of the 3.0-microns H2O absorption suggesting differences in water content, a weak absorption at 2.2 microns indicative of metal-OH in phyllosilicate, and variations in the 1-micron Fe absorption indicative of differences in Fe mineralogy. This paper summarizes first results of a systematic investigation of spectral heterogeneity in bright soils observed by ISM. At least seven 'units' with distinctive properties were discriminated. Comparison of their spatial distributions with Viking data shows that they generally correspond with previously recognized morphologic, color, and thermal features. These correspondences and the units' spectral attributes provide evidence for lithologic differences between the soils in different geologic settings.

Quantifying the heterogeneity of soil compaction, physical soil properties and soil moisture across multiple spatial scales

Science.gov (United States)

Coates, Victoria; Pattison, Ian; Sander, Graham

2016-04-01

England's rural landscape is dominated by pastoral agriculture, with 40% of land cover classified as either improved or semi-natural grassland according to the Land Cover Map 2007. Since the Second World War the intensification of agriculture has resulted in greater levels of soil compaction, associated with higher stocking densities in fields. Locally compaction has led to loss of soil storage and an increased in levels of ponding in fields. At the catchment scale soil compaction has been hypothesised to contribute to increased flood risk. Previous research (Pattison, 2011) on a 40km2 catchment (Dacre Beck, Lake District, UK) has shown that when soil characteristics are homogeneously parameterised in a hydrological model, downstream peak discharges can be 65% higher for a heavy compacted soil than for a lightly compacted soil. However, at the catchment scale there is likely to be a significant amount of variability in compaction levels within and between fields, due to multiple controlling factors. This research focusses in on one specific type of land use (permanent pasture with cattle grazing) and areas of activity within the field (feeding area, field gate, tree shelter, open field area). The aim was to determine if the soil characteristics and soil compaction levels are homogeneous in the four areas of the field. Also, to determine if these levels stayed the same over the course of the year, or if there were differences at the end of the dry (October) and wet (April) periods. Field experiments were conducted in the River Skell catchment, in Yorkshire, UK, which has an area of 120km2. The dynamic cone penetrometer was used to determine the structural properties of the soil, soil samples were collected to assess the bulk density, organic matter content and permeability in the laboratory and the Hydrosense II was used to determine the soil moisture content in the topsoil. Penetration results show that the tree shelter is the most compacted and the open field area

Simulated optimization of crop yield through irrigation system design and operation based on the spatial variability of soil hydrodynamic properties

International Nuclear Information System (INIS)

Gurovich, L.; Stern, J.; Ramos, R.

1983-01-01

Spatial autocorrelation and kriging techniques were applied to soil infiltrability data from a 20 hectare field, to separate homogeneous irrigation units. Border irrigation systems were designed for each unit and combinations of units by using DESIGN, a computer model based on soil infiltrability and hydraulics of surface water flow, which enables optimal irrigation systems to be designed. Water depths effectively infiltrated at different points along the irrigation run were determined, and the agronomic irrigation efficiency of the unit evaluated. A modification of Hanks' evapotranspiration model, PLANTGRO, was used to evaluate plant growth, relative crop yield and soil-water economy throughout the growing season, at several points along each irrigation unit. The effect of different irrigation designs on total field yield and total water used for irrigation was evaluated by integrating yield values corresponding to each point, volume and inflow time during each irrigation. For relevant data from winter wheat grown in the central area of Chile during 1981, simulation by an interactive and sequentially recurrent use of DESIGN and PLANTGRO models, was carried out. The results obtained indicate that, when a field is separated into homogeneous irrigation units on the basis of the spatial variability of soil infiltrability and the border irrigation systems are designed according to soil characteristics, both a significant yield increase and less water use can be obtained by comparison with other criteria of field zonification for irrigation management. The use of neutrometric determinations to assess soil-water content during the growing season, as a validation of the results obtained in this work, is discussed. (author)

Spatial variability of soil carbon, pH, available phosphorous and potassium in organic farm located in Mediterranean Croatia

Science.gov (United States)

Bogunović, Igor; Pereira, Paulo; Šeput, Miranda

2016-04-01

Soil organic carbon (SOC), pH, available phosphorus (P), and potassium (K) are some of the most important factors to soil fertility. These soil parameters are highly variable in space and time, with implications to crop production. The aim of this work is study the spatial variability of SOC, pH, P and K in an organic farm located in river Rasa valley (Croatia). A regular grid (100 x 100 m) was designed and 182 samples were collected on Silty Clay Loam soil. P, K and SOC showed moderate heterogeneity with coefficient of variation (CV) of 21.6%, 32.8% and 51.9%, respectively. Soil pH record low spatial variability with CV of 1.5%. Soil pH, P and SOC did not follow normal distribution. Only after a Box-Cox transformation, data respected the normality requirements. Directional exponential models were the best fitted and used to describe spatial autocorrelation. Soil pH, P and SOC showed strong spatial dependence with nugget to sill ratio with 13.78%, 0.00% and 20.29%, respectively. Only K recorded moderate spatial dependence. Semivariogram ranges indicate that future sampling interval could be 150 - 200 m in order to reduce sampling costs. Fourteen different interpolation models for mapping soil properties were tested. The method with lowest Root Mean Square Error was the most appropriated to map the variable. The results showed that radial basis function models (Spline with Tension and Completely Regularized Spline) for P and K were the best predictors, while Thin Plate Spline and inverse distance weighting models were the least accurate. The best interpolator for pH and SOC was the local polynomial with the power of 1, while the least accurate were Thin Plate Spline. According to soil nutrient maps investigated area record very rich supply with K while P supply was insufficient on largest part of area. Soil pH maps showed mostly neutral reaction while individual parts of alkaline soil indicate the possibility of penetration of seawater and salt accumulation in the

Spatial distribution patterns of soil mite communities and their relationships with edaphic factors in a 30-year tillage cornfield in northeast China.

Science.gov (United States)

Liu, Jie; Gao, Meixiang; Liu, Jinwen; Guo, Yuxi; Liu, Dong; Zhu, Xinyu; Wu, Donghui

2018-01-01

Spatial distribution is an important topic in community ecology and a key to understanding the structure and dynamics of populations and communities. However, the available information related to the spatial patterns of soil mite communities in long-term tillage agroecosystems remains insufficient. In this study, we examined the spatial patterns of soil mite communities to explain the spatial relationships between soil mite communities and soil parameters. Soil fauna were sampled three times (August, September and October 2015) at 121 locations arranged regularly within a 400 m × 400 m monitoring plot. Additionally, we estimated the physical and chemical parameters of the same sampling locations. The distribution patterns of the soil mite community and the edaphic parameters were analyzed using a range of geostatistical tools. Moran's I coefficient showed that, during each sampling period, the total abundance of the soil mite communities and the abundance of the dominant mite populations were spatially autocorrelated. The soil mite communities demonstrated clear patchy distribution patterns within the study plot. These patterns were sampling period-specific. Cross-semivariograms showed both negative and positive cross-correlations between soil mite communities and environmental factors. Mantel tests showed a significant and positive relationship between soil mite community and soil organic matter and soil pH only in August. This study demonstrated that in the cornfield, the soil mite distribution exhibited strong or moderate spatial dependence, and the mites formed patches with sizes less than one hundred meters. In addition, in this long-term tillage agroecosystem, soil factors had less influence on the observed pattern of soil mite communities. Further experiments that take into account human activity and spatial factors should be performed to study the factors that drive the spatial distribution of soil microarthropods.

Soil erosion evolution and spatial correlation analysis in a typical karst geomorphology using RUSLE with GIS

Science.gov (United States)

Zeng, Cheng; Wang, Shijie; Bai, Xiaoyong; Li, Yangbing; Tian, Yichao; Li, Yue; Wu, Luhua; Luo, Guangjie

2017-07-01

Although some scholars have studied soil erosion in karst landforms, analyses of the spatial and temporal evolution of soil erosion and correlation analyses with spatial elements have been insufficient. The lack of research has led to an inaccurate assessment of environmental effects, especially in the mountainous area of Wuling in China. Soil erosion and rocky desertification in this area influence the survival and sustainability of a population of 0.22 billion people. This paper analyzes the spatiotemporal evolution of soil erosion and explores its relationship with rocky desertification using GIS technology and the revised universal soil loss equation (RUSLE). Furthermore, this paper analyzes the relationship between soil erosion and major natural elements in southern China. The results are as follows: (1) from 2000 to 2013, the proportion of the area experiencing micro-erosion and mild erosion was at increasing risk in contrast to areas where moderate and high erosion are decreasing. The area changes in this time sequence reflect moderate to high levels of erosion tending to convert into micro-erosion and mild erosion. (2) The soil erosion area on the slope, at 15-35°, accounted for 60.59 % of the total erosion area, and the corresponding soil erosion accounted for 40.44 %. (3) The annual erosion rate in the karst region decreased much faster than in the non-karst region. Soil erosion in all of the rock outcrop areas indicates an improving trend, and dynamic changes in soil erosion significantly differ among the various lithological distribution belts. (4) The soil erosion rate decreased in the rocky desertification regions, to below moderate levels, but increased in the severe rocky desertification areas. The temporal and spatial variations in soil erosion gradually decreased in the study area. Differences in the spatial distribution between lithology and rocky desertification induced extensive soil loss. As rocky desertification became worse, the erosion

Soil erosion evolution and spatial correlation analysis in a typical karst geomorphology using RUSLE with GIS

Directory of Open Access Journals (Sweden)

C. Zeng

2017-07-01

Full Text Available Although some scholars have studied soil erosion in karst landforms, analyses of the spatial and temporal evolution of soil erosion and correlation analyses with spatial elements have been insufficient. The lack of research has led to an inaccurate assessment of environmental effects, especially in the mountainous area of Wuling in China. Soil erosion and rocky desertification in this area influence the survival and sustainability of a population of 0.22 billion people. This paper analyzes the spatiotemporal evolution of soil erosion and explores its relationship with rocky desertification using GIS technology and the revised universal soil loss equation (RUSLE. Furthermore, this paper analyzes the relationship between soil erosion and major natural elements in southern China. The results are as follows: (1 from 2000 to 2013, the proportion of the area experiencing micro-erosion and mild erosion was at increasing risk in contrast to areas where moderate and high erosion are decreasing. The area changes in this time sequence reflect moderate to high levels of erosion tending to convert into micro-erosion and mild erosion. (2 The soil erosion area on the slope, at 15–35°, accounted for 60.59 % of the total erosion area, and the corresponding soil erosion accounted for 40.44 %. (3 The annual erosion rate in the karst region decreased much faster than in the non-karst region. Soil erosion in all of the rock outcrop areas indicates an improving trend, and dynamic changes in soil erosion significantly differ among the various lithological distribution belts. (4 The soil erosion rate decreased in the rocky desertification regions, to below moderate levels, but increased in the severe rocky desertification areas. The temporal and spatial variations in soil erosion gradually decreased in the study area. Differences in the spatial distribution between lithology and rocky desertification induced extensive soil loss. As rocky desertification

Temporal and spatial influences incur reconfiguration of Arctic heathland soil bacterial community structure.

Science.gov (United States)

Hill, Richard; Saetnan, Eli R; Scullion, John; Gwynn-Jones, Dylan; Ostle, Nick; Edwards, Arwyn

2016-06-01

Microbial responses to Arctic climate change could radically alter the stability of major stores of soil carbon. However, the sensitivity of plot-scale experiments simulating climate change effects on Arctic heathland soils to potential confounding effects of spatial and temporal changes in soil microbial communities is unknown. Here, the variation in heathland soil bacterial communities at two survey sites in Sweden between spring and summer 2013 and at scales between 0-1 m and, 1-100 m and between sites (> 100 m) were investigated in parallel using 16S rRNA gene T-RFLP and amplicon sequencing. T-RFLP did not reveal spatial structuring of communities at scales structuring effects may not confound comparison between plot-scale treatments, temporal change is a significant influence. Moreover, the prominence of two temporally exclusive keystone taxa suggests that the stability of Arctic heathland soil bacterial communities could be disproportionally influenced by seasonal perturbations affecting individual taxa. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

Temporal and spatial variations of soil CO2, CH4 and N2O fluxes at three differently managed grasslands

Directory of Open Access Journals (Sweden)

D. Imer

2013-09-01

Full Text Available A profound understanding of temporal and spatial variabilities of soil carbon dioxide (CO2, methane (CH4 and nitrous oxide (N2O fluxes between terrestrial ecosystems and the atmosphere is needed to reliably quantify these fluxes and to develop future mitigation strategies. For managed grassland ecosystems, temporal and spatial variabilities of these three soil greenhouse gas (GHG fluxes occur due to changes in environmental drivers as well as fertilizer applications, harvests and grazing. To assess how such changes affect soil GHG fluxes at Swiss grassland sites, we studied three sites along an altitudinal gradient that corresponds to a management gradient: from 400 m a.s.l. (intensively managed to 1000 m a.s.l. (moderately intensive managed to 2000 m a.s.l. (extensively managed. The alpine grassland was included to study both effects of extensive management on CH4 and N2O fluxes and the different climate regime occurring at this altitude. Temporal and spatial variabilities of soil GHG fluxes and environmental drivers on various timescales were determined along transects of 16 static soil chambers at each site. All three grasslands were N2O sources, with mean annual soil fluxes ranging from 0.15 to 1.28 nmol m−2 s−1. Contrastingly, all sites were weak CH4 sinks, with soil uptake rates ranging from −0.56 to −0.15 nmol m−2 s−1. Mean annual soil and plant respiration losses of CO2, measured with opaque chambers, ranged from 5.2 to 6.5 μmol m−2 s−1. While the environmental drivers and their respective explanatory power for soil N2O emissions differed considerably among the three grasslands (adjusted r2 ranging from 0.19 to 0.42, CH4 and CO2 soil fluxes were much better constrained (adjusted r2 ranging from 0.46 to 0.80 by soil water content and air temperature, respectively. Throughout the year, spatial heterogeneity was particularly high for soil N2O and CH4 fluxes. We found permanent hot spots for soil N2O emissions as well as

EXTRAPOLATING THE SUITABILITY OF SOILS AS NATURAL REACTORS USING AN EXISTING SOIL MAP: APPLICATION OF PEDOTRANSFER FUNCTIONS, SPATIAL INTEGRATION AND VALIDATION PROCEDURES

Directory of Open Access Journals (Sweden)

Yameli Guadalupe Aguilar Duarte

2011-04-01

Full Text Available The aim of this study was the spatial identification of the suitability of soils as reactors in the treatment of swine wastewater in the Mexican state of Yucatan, as well as the development of a map with validation procedures. Pedotransfer functions were applied to the existing soils database. A methodological approach was adopted that allowed the spatialization of pedotransfer function data points. A map of the suitability of soil associations as reactors was produced, as well as a map of the level of accuracy of the associations using numerical classification technique, such as discriminant analysis. Soils with the highest suitability indices were found to be Vertisols, Stagnosols, Nitisols and Luvisols. Some 83.9% of the area of Yucatan is marginally suitable for the reception of swine wastewater, 6.5% is moderately suitable, while 6% is suitable. The percentages of the spatial accuracy of the pedotransfer functions range from 62% to 95% with an overall value of 71.5%. The methodological approach proved to be practical, accurate and inexpensive.

Application of spatial Markov chains to the analysis of the temporal-spatial evolution of soil erosion.

Science.gov (United States)

Liu, Ruimin; Men, Cong; Wang, Xiujuan; Xu, Fei; Yu, Wenwen

Soil and water conservation in the Three Gorges Reservoir Area of China is important, and soil erosion is a significant issue. In the present study, spatial Markov chains were applied to explore the impacts of the regional context on soil erosion in the Xiangxi River watershed, and Thematic Mapper remote sensing data from 1999 and 2007 were employed. The results indicated that the observed changes in soil erosion were closely related to the soil erosion levels of the surrounding areas. When neighboring regions were not considered, the probability that moderate erosion transformed into slight and severe erosion was 0.8330 and 0.0049, respectively. However, when neighboring regions that displayed intensive erosion were considered, the probabilities were 0.2454 and 0.7513, respectively. Moreover, the different levels of soil erosion in neighboring regions played different roles in soil erosion. If the erosion levels in the neighboring region were lower, the probability of a high erosion class transferring to a lower level was relatively high. In contrast, if erosion levels in the neighboring region were higher, the probability was lower. The results of the present study provide important information for the planning and implementation of soil conservation measures in the study area.

Spatial variability of caesium-137 activities in soils in the Jura mountains

International Nuclear Information System (INIS)

Pimou-Heumou, G.; Lucot, E.; Crini, N.; Briot, M.; Badot, P.M.

2011-01-01

275 soil samples were taken in the catchment area of the upper part of the Doubs river located in the Jura mountains according to a sampling strategy designed to evaluate the extent of the spatial variability of 137 Cs activities and to identify its main sources. 137 Cs activities ranged between about 1000 and 12000 Bq.m -2 with an average of approximately 3600 Bq.m -2 . The spatial variability of the contamination is high: 137 Cs activity shows statistically significant links with altitude, soil organic matter and land cover, whereas the other studied parameters, i.e. soil type and topographic position, do not constitute significant sources of variation. These results are discussed in terms of evaluation of the radioactive contamination on a regional scale. They show that to be satisfactory, a sampling strategy must necessarily take into account the various types of land cover. (authors)

Interpolation Approaches for Characterizing Spatial Variability of Soil Properties in Tuz Lake Basin of Turkey

Science.gov (United States)

Gorji, Taha; Sertel, Elif; Tanik, Aysegul

2017-12-01

Soil management is an essential concern in protecting soil properties, in enhancing appropriate soil quality for plant growth and agricultural productivity, and in preventing soil erosion. Soil scientists and decision makers require accurate and well-distributed spatially continuous soil data across a region for risk assessment and for effectively monitoring and managing soils. Recently, spatial interpolation approaches have been utilized in various disciplines including soil sciences for analysing, predicting and mapping distribution and surface modelling of environmental factors such as soil properties. The study area selected in this research is Tuz Lake Basin in Turkey bearing ecological and economic importance. Fertile soil plays a significant role in agricultural activities, which is one of the main industries having great impact on economy of the region. Loss of trees and bushes due to intense agricultural activities in some parts of the basin lead to soil erosion. Besides, soil salinization due to both human-induced activities and natural factors has exacerbated its condition regarding agricultural land development. This study aims to compare capability of Local Polynomial Interpolation (LPI) and Radial Basis Functions (RBF) as two interpolation methods for mapping spatial pattern of soil properties including organic matter, phosphorus, lime and boron. Both LPI and RBF methods demonstrated promising results for predicting lime, organic matter, phosphorous and boron. Soil samples collected in the field were used for interpolation analysis in which approximately 80% of data was used for interpolation modelling whereas the remaining for validation of the predicted results. Relationship between validation points and their corresponding estimated values in the same location is examined by conducting linear regression analysis. Eight prediction maps generated from two different interpolation methods for soil organic matter, phosphorus, lime and boron parameters

Detecting small-scale spatial differences and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

Science.gov (United States)

Hoffmann, Mathias; Jurisch, Nicole; Garcia Alba, Juana; Albiac Borraz, Elisa; Schmidt, Marten; Huth, Vytas; Rogasik, Helmut; Rieckh, Helene; Verch, Gernot; Sommer, Michael; Augustin, Jürgen

2017-04-01

Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (ΔSOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial and temporal changes in SOC stocks, particularly pronounced on arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in ΔSOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal ΔSOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal as well as small-scale spatial dynamics of ΔSOC. Therefore, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot) was used. To verify our method, results were compared with ΔSOC observed by soil resampling. AC measurements were performed from 2010 to 2014 under a silage maize/winter fodder rye/sorghum-Sudan grass hybrid/alfalfa crop rotation at a colluvial depression located in the hummocky ground moraine landscape of NE Germany. Widespread in large areas of the formerly glaciated Northern Hemisphere, this depression type is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity in soil properties, such as SOC and nitrogen (Nt). After monitoring the initial stage during 2010, soil erosion was experimentally simulated by incorporating topsoil material from an eroded midslope soil into the plough layer of the colluvial depression. SOC stocks were quantified before and after soil manipulation and at the end

Linking spatial patterns of soil redistribution traced with 137Cs and soil nutrients in a Mediterranean mountain agroecosystem (NE Spain)

Science.gov (United States)

Quijano, Laura; Gaspar, Leticia; Navas, Ana

2016-04-01

Mediterranean mountain agroecosystems are prone to soil loss mainly due to the accelerated erosion as a consequence of human induced changes from agriculture and grazing practices over the last centuries and the climatic conditions (i.e. irregular and scarce precipitations and drought periods). Soil erosion leads to soil degradation inducing the loss of soil functions. The progressive decline of soil functions thereof soil quality is associated to a decrease of soil productivity and can threat the sustainability of cultivated soils. The use of fallout 137Cs as a soil movement tracer provides useful data to identify areas where loss and gain of 137Cs occurs and that of soil. This study aims to address soil movement and soil nutrient dynamics closely related to the status of soil degradation. A rain-fed cereal field (1.6 ha) representative of Mediterranean mountain agricultural landscapes (42°25'41''N 1°13'8''W) was selected to examine the effects of soil redistribution processes on the spatial variability of soil organic carbon (SOC) and nitrogen (SON) and their relationships with soil properties and topographic characteristics. From the hydrological point of view, the field is isolated due to the effect of landscape features and man-made structures. Climate is continental Mediterranean with an average annual rainfall of 500 mm and soils are Calcisols. The reference inventories of 137Cs and soil nutrients were established from 21 soil samples collected in nearby undisturbed areas under typical Mediterranean vegetation cover. A total of 156 bulk soil samples (30-50 cm depth) and 156 topsoil samples (5 cm) were collected on a 10 m grid. 137Cs and soil nutrients loss and gain areas were identified by comparing the reference inventories with the values of inventories at the sampling points. A new approach to characterize and measure active (ACF) and stable (SCF) carbon fraction contents by using a dry combustion method based on the oxidation temperature of carbon

Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

Science.gov (United States)

Hoffmann, Mathias; Jurisch, Nicole; Garcia Alba, Juana; Albiac Borraz, Elisa; Schmidt, Marten; Huth, Vytas; Rogasik, Helmut; Rieckh, Helene; Verch, Gernot; Sommer, Michael; Augustin, Jürgen

2017-03-01

Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (ΔSOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial (10-30 m) and temporal changes in SOC stocks, particularly pronounced in arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in ΔSOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal ΔSOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal dynamics as well as small-scale spatial differences of ΔSOC using measurements of the net ecosystem carbon balance (NECB) as a proxy. To estimate the NECB, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot) were used. To verify our method, results were compared with ΔSOC observed by soil resampling. Soil resampling and AC measurements were performed from 2010 to 2014 at a colluvial depression located in the hummocky ground moraine landscape of northeastern Germany. The measurement site is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity regarding SOC and nitrogen (Nt) stocks. Tendencies and magnitude of ΔSOC values derived by AC measurements and repeated soil inventories corresponded well. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual ΔSOC. Hence, we were able to confirm that AC-based C budgets are able

NMR relaxation in natural soils: Fast Field Cycling and T1-T2 Determination by IR-MEMS

Science.gov (United States)

Haber-Pohlmeier, S.; Pohlmeier, A.; Stapf, S.; van Dusschoten, D.

2009-04-01

Soils are natural porous media of highest importance for food production and sustainment of water resources. For these functions, prominent properties are their ability of water retainment and transport, which are mainly controlled by pore size distribution. The latter is related to NMR relaxation times of water molecules, of which the longitudinal relaxation time can be determined non-invasively by fast-field cycling relaxometry (FFC) and both are obtainable by inversion recovery - multi-echo- imaging (IR-MEMS) methods. The advantage of the FFC method is the determination of the field dependent dispersion of the spin-lattice relaxation rate, whereas MRI at high field is capable of yielding spatially resolved T1 and T2 times. Here we present results of T1- relaxation time distributions of water in three natural soils, obtained by the analysis of FFC data by means of the inverse Laplace transformation (CONTIN)1. Kaldenkirchen soil shows relatively broad bimodal distribution functions D(T1) which shift to higher relaxation rates with increasing relaxation field. These data are compared to spatially resolved T1- and T2 distributions, obtained by IR-MEMS. The distribution of T1 corresponds well to that obtained by FFC.

Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

Science.gov (United States)

Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

1998-01-01

The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data.

Science.gov (United States)

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960-2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60-70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly

Determination of wind erosion intensity on heavy clay soils

Directory of Open Access Journals (Sweden)

Jana Kozlovsky Dufková

2010-01-01

Full Text Available Wind erosion, common problem of light-textured soils, was determined on heavy clay soils in the foothills of Bílé Karpaty Mountains, Czech Republic. Soil erodibility by wind was determined from the Map of potential erodibility of soil by wind and from the calculation of potential and real soil loss by wind. All the determinations show underestimation of soil erodibility by wind on heavy clay soils, because methods that are used for this are based above all on the assessment of clay particles content and the presumption the more clay particles soil contains, the less vulnerable to wind erosion is. The potential erodibility of soil by wind is 0,09 t . ha−1 per year. The determined value does not exceed the tolerable soil loss limit 10 t . ha−1 per year for deep soils. The real average erodibility of soil by wind has the highest value 1,47 g . m−2 on November 30th, 2008. Other soil losses that do not exceed the tolerable soil loss limit 1,4 g . m−2, were determined on March 18th and 28th, 2008. Big difficulties come with the assessment of the erodibility of heavy clay soils in the areas, where soil erosion ve­ri­fia­bly exists, but it is not assessable by objective calculating methods. Evident necessity of new know­ledge concerning the determination of wind erosion intensity follows from the results.

Spatial patterns of soil pH and the factors that influence them in plantation forests of northern China

Science.gov (United States)

Hong, Songbai; Liu, Yongwen; Piao, Shilong

2017-04-01

Climate and anthropogenic activities such as afforestation and nitrogen deposition all impact soil pH. Understanding the spatial pattern of soil pH and the factors that influence it can provide basic information for generating appropriate strategies for soil resource management and protection, especially in light of increasing anthropogenic influences and climate change. In this study, we investigated the spatial and vertical pattern of soil pH and evaluated the influence of climate and nitrogen deposition using 1647 soil profiles 1 meter in depth from 549 plots in plantation forests of northern China. We found that soil pH decreased from the southwest to the northeast in the study region and had a similar spatial pattern before and after afforestation. Furthermore, our results show that climate and nitrogen deposition fundamentally influence the pattern of soil pH. Specifically, increasing precipitation significantly decreased soil pH (with a mean rate of 0.3 for every 100 mm rainfall, ppH (0.13 for every degree centigrade, ppH (ppH directly and indirectly through climate-plant-soil interactions. As the risks from both climate change and nitrogen deposition increase, there is an urgent need to further understanding of soil pH dynamics and to develop informed policies to protect soil resources.

Soil hydrophobicity: comparative study of usual determination methods

Directory of Open Access Journals (Sweden)

Eduardo Saldanha Vogelmann

2015-02-01

Full Text Available Hydrophobic or water repellent soils slowly absorb water because of the low wett ability of the soil particles which are coated with hydrophobic organic substances. These pose significant effects on plant growth, water infiltration and retention, surface runoff and erosion. The objective of this study was to compare the performance of tension micro-infiltrometer(TMI and the water drop penetration time (WDPT methods in the determination of the hydrophobicity index of eighteen soils from southern Brazil. Soil samples were collected from the 0-5cm soil layer to determine particle size distribution, organic matter content, hydrophobicity index of soil aggregates and droplet penetration time of disaggregated and sieved soil samples. For the TMI method the soil samples were subjected to minor changes due to the use of macroaggregates to preserve the distribution of solid constituents in the soil. Due to the homogeneity of the soil samples the WDPT method gave smaller coefficients of variation unlike the TMI method where the soil structure is preserved. However, both methods had low coefficients of variation, and are thus effective for determining the soil hydrophobicity, especially when the log hydrophobicity index or log WDPT is >1.

[Analysis of Cr in soil by LIBS based on conical spatial confinement of plasma].

Science.gov (United States)

Lin, Yong-Zeng; Yao, Ming-Yin; Chen, Tian-Bing; Li, Wen-Bing; Zheng, Mei-Lan; Xu, Xue-Hong; Tu, Jian-Ping; Liu, Mu-Hua

2013-11-01

The present study is to improve the sensitivity of detection and reduce the limit of detection in detecting heavy metal of soil by laser induced breakdown spectroscopy (LIBS). The Cr element of national standard soil was regarded as the research object. In the experiment, a conical cavity with small diameter end of 20 mm and large diameter end of 45 mm respectively was installed below the focusing lens near the experiment sample to mainly confine the signal transmitted by plasma and to some extent to confine the plasma itself in the LIBS setup. In detecting Cr I 425.44 nm, the beast delay time gained from experiment is 1.3 micros, and the relative standard deviation is below 10%. Compared with the setup of non-spatial confinement, the spectral intensity of Cr in the soil sample was enhanced more than 7%. Calibration curve was established in the Cr concentration range from 60 to 400 microg x g(-1). Under the condition of spatial confinement, the liner regression coefficient and the limit of detection were 0.997 71 and 18.85 microg x g(-1) respectively, however, the regression coefficient and the limit of detection were 0.991 22 and 36.99 microg x g(-1) without spatial confinement. So, this shows that conical spatial confinement can/improve the sensitivity of detection and enhance the spectral intensity. And it is a good auxiliary function in detecting Cr in the soil by laser induced breakdown spectroscopy.

Soil water content evaluation considering time-invariant spatial pattern and space-variant temporal change

Science.gov (United States)

Hu, W.; Si, B. C.

2013-10-01

Soil water content (SWC) varies in space and time. The objective of this study was to evaluate soil water content distribution using a statistical model. The model divides spatial SWC series into time-invariant spatial patterns, space-invariant temporal changes, and space- and time-dependent redistribution terms. The redistribution term is responsible for the temporal changes in spatial patterns of SWC. An empirical orthogonal function was used to separate the total variations of redistribution terms into the sum of the product of spatial structures (EOFs) and temporally-varying coefficients (ECs). Model performance was evaluated using SWC data of near-surface (0-0.2 m) and root-zone (0-1.0 m) from a Canadian Prairie landscape. Three significant EOFs were identified for redistribution term for both soil layers. EOF1 dominated the variations of redistribution terms and it resulted in more changes (recharge or discharge) in SWC at wetter locations. Depth to CaCO3 layer and organic carbon were the two most important controlling factors of EOF1, and together, they explained over 80% of the variations in EOF1. Weak correlation existed between either EOF2 or EOF3 and the observed factors. A reasonable prediction of SWC distribution was obtained with this model using cross validation. The model performed better in the root zone than in the near surface, and it outperformed conventional EOF method in case soil moisture deviated from the average conditions.

Using high-resolution soil moisture modelling to assess the uncertainty of microwave remotely sensed soil moisture products at the correct spatial and temporal support

NARCIS (Netherlands)

Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M.

Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture

Geographical ecology of the palms (Arecaceae): determinants of diversity and distributions across spatial scales

DEFF Research Database (Denmark)

Eiserhardt, Wolf L.; Svenning, J.-C.; Kissling, W. Daniel

2011-01-01

, and dispersal again at all scales. For species richness, climate and dispersal appear to be important at continental to global scales, soil at landscape and broader scales, and topography at landscape and finer scales. Some scale–predictor combinations have not been studied or deserve further attention, e......Background The palm family occurs in all tropical and sub-tropical regions of the world. Palms are of high ecological and economical importance, and display complex spatial patterns of species distributions and diversity. Scope This review summarizes empirical evidence for factors that determine...... palm species distributions, community composition and species richness such as the abiotic environment (climate, soil chemistry, hydrology and topography), the biotic environment (vegetation structure and species interactions) and dispersal. The importance of contemporary vs. historical impacts...

Understanding spatial heterogeneity in soil carbon and nitrogen cycling in regenerating tropical dry forests

Science.gov (United States)

Waring, B. G.; Powers, J. S.; Branco, S.; Adams, R.; Schilling, E.

2015-12-01

Tropical dry forests (TDFs) currently store significant amounts of carbon in their biomass and soils, but these highly seasonal ecosystems may be uniquely sensitive to altered climates. The ability to quantitatively predict C cycling in TDFs under global change is constrained by tremendous spatial heterogeneity in soil parent material, land-use history, and plant community composition. To explore this variation, we examined soil carbon and nitrogen dynamics in 18 permanent plots spanning orthogonal gradients of stand age and soil fertility. Soil C and N pools, microbial biomass, and microbial extracellular enzyme activities were most variable at small (m2) spatial scales. However, the ratio of organic vs. inorganic N cycling was consistently higher in forest stands dominated by slow-growing, evergreen trees that associate with ectomycorrhizal fungi. Similarly, although bulk litter stocks and turnover rates varied greatly among plots, litter decomposition tended to be slower in ectomycorrhizae-dominated stands. Soil N cycling tended to be more conservative in older plots, although the relationship between stand age and element cycling was weak. Our results emphasize that microscale processes, particularly interactions between mycorrhizal fungi and free-living decomposers, are important controls on ecosystem-scale element cycling.

Mapping and determinism of soil microbial community distribution across an agricultural landscape.

Science.gov (United States)

Constancias, Florentin; Terrat, Sébastien; Saby, Nicolas P A; Horrigue, Walid; Villerd, Jean; Guillemin, Jean-Philippe; Biju-Duval, Luc; Nowak, Virginie; Dequiedt, Samuel; Ranjard, Lionel; Chemidlin Prévost-Bouré, Nicolas

2015-06-01

Despite the relevance of landscape, regarding the spatial patterning of microbial communities and the relative influence of environmental parameters versus human activities, few investigations have been conducted at this scale. Here, we used a systematic grid to characterize the distribution of soil microbial communities at 278 sites across a monitored agricultural landscape of 13 km². Molecular microbial biomass was estimated by soil DNA recovery and bacterial diversity by 16S rRNA gene pyrosequencing. Geostatistics provided the first maps of microbial community at this scale and revealed a heterogeneous but spatially structured distribution of microbial biomass and diversity with patches of several hundreds of meters. Variance partitioning revealed that both microbial abundance and bacterial diversity distribution were highly dependent of soil properties and land use (total variance explained ranged between 55% and 78%). Microbial biomass and bacterial richness distributions were mainly explained by soil pH and texture whereas bacterial evenness distribution was mainly related to land management. Bacterial diversity (richness, evenness, and Shannon index) was positively influenced by cropping intensity and especially by soil tillage, resulting in spots of low microbial diversity in soils under forest management. Spatial descriptors also explained a small but significant portion of the microbial distribution suggesting that landscape configuration also shapes microbial biomass and bacterial diversity. © 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Spatial Heterogeneity and Sources of Soil Carbon in Southern African Savannas

Science.gov (United States)

Macko, S.; Wang, L.; Okin, G.

2007-12-01

Soil organic carbon (SOC) is one of the largest and most dynamic reservoirs of C on Earth, with nearly twice as much C stored in SOC than in the biosphere and atmosphere combined. SOC storage in global tropical savannas constitutes approximately 56 Gt of C, which rises to 216 Gt of C (i.e., about 17% of the terrestrial non- agricultural SOC), when woodlands, shrublands, and desert scrub are included. Savannas cover about 20% of the global land surface, including about one-half of Africa, Australia and South America. The shared dominance of trees and grasses in savannas, the dominant physiognomy in southern Africa, add more complexity to soil C pool partitioning and dynamics than is found in landscapes with a single physiognomy. Here, the spatial variability of the soil C pool was investigated with particular emphasis on understanding the contribution to SOC from trees and grasses at two savanna sites of the Kalahari Transect, one wet and the other dry. Using a combination of stable isotope techniques and geostatistics, the results showed that spatial patterns of soil δ13 C exist and were related to the distributions of woody (C3) and herbaceous (C4) vegetation at both sites. Heterogeneity of the sources of SOC, as well as heterogeneity in the amount of SOC, was greater at the dry site relative to the wet site. At the dry site, the grasses were the major contributor to soil C whereas in the wet site, woody vegetation was the major contributor, regardless of the location with respect to woody canopies.

Denitrification potential of riparian soils in relation to multiscale spatial environmental factors: a case study of a typical watershed, China.

Science.gov (United States)

Wei, Jianbing; Feng, Hao; Cheng, Quanguo; Gao, Shiqian; Liu, Haiyan

2017-02-01

The objective of this study was to test the hypothesis that environmental regulators of riparian zone soil denitrification potential differ according to spatial scale within a watershed; consequently, a second objective was to provide spatial strategies for conserving and restoring the purification function of runoff in riparian ecosystems. The results show that soil denitrification in riparian zones was more heterogeneous at the profile scale than at the cross-section and landscape scales. At the profile scale, biogeochemical factors (including soil total organic carbon, total nitrogen, and nitrate-nitrogen) were the major direct regulators of the spatial distribution of soil denitrification enzyme activity (DEA). At the cross-section scale, factors included distance from river bank and vegetation density, while landscape-scale factors, including topographic index, elevation, and land use types, indirectly regulated the spatial distribution of DEA. At the profile scale, soil DEA was greatest in the upper soil layers. At the cross-section scale, maximum soil DEA occurred in the mid-part of the riparian zone. At the landscape scale, soil DEA showed an increasing trend towards downstream sites, except for those in urbanized areas.

Influence of land use and meteorological factors on the spatial distribution of Toxocara canis and Toxocara cati eggs in soil in urban areas.

Science.gov (United States)

Gao, Xiang; Wang, Hongbin; Li, Jianxin; Qin, Hongyu; Xiao, Jianhua

2017-01-15

Soil which has been contaminated by Toxocara spp. eggs is considered as one of the main infection sources of Toxocariasis in animals and humans. The present study conducted a detailed investigation into the spatial patterns of Toxocara canis (T. canis) and Toxocara cati (T. cati) eggs in soil in urban area of northeastern Mainland China, and assessed the inter-relationships between meteorological factors, land use and the distribution of the Toxocara spp. eggs. Polymerase chain reaction (PCR) was used for the determination of T. canis and T. cati eggs contamination in soil samples. Between April 2014 and May 2015, 9420 soil samples were subjected to PCR examination and 7027 sheep (74.6%) were determined to be positive for T. canis and T. cati eggs. Subsequently, we evaluated the effect of land use, and meteorological factors on the spatial distribution of T. canis and T. cati eggs based on a maximum entropy model. Jackknife analysis revealed that the area of residential land, wood and grass land and precipitation may influence the occurrence of T. canis and T. cati eggs in soil. Our findings indicate that land use and meteorological factors may be important variables affecting transmission of Toxocariasis and should be taken into account in the development of future surveillance programmes for Toxocariasis. Copyright © 2016 Elsevier B.V. All rights reserved.

SAMPLING ADAPTIVE STRATEGY AND SPATIAL ORGANISATION ESTIMATION OF SOIL ANIMAL COMMUNITIES AT VARIOUS HIERARCHICAL LEVELS OF URBANISED TERRITORIES

Directory of Open Access Journals (Sweden)

Baljuk J.A.

2014-12-01

Full Text Available In work the algorithm of adaptive strategy of optimum spatial sampling for studying of the spatial organisation of communities of soil animals in the conditions of an urbanization have been presented. As operating variables the principal components obtained as a result of the analysis of the field data on soil penetration resistance, soils electrical conductivity and density of a forest stand, collected on a quasiregular grid have been used. The locations of experimental polygons have been stated by means of program ESAP. The sampling has been made on a regular grid within experimental polygons. The biogeocoenological estimation of experimental polygons have been made on a basis of A.L.Belgard's ecomorphic analysis. The spatial configuration of biogeocoenosis types has been established on the basis of the data of earth remote sensing and the analysis of digital elevation model. The algorithm was suggested which allows to reveal the spatial organisation of soil animal communities at investigated point, biogeocoenosis, and landscape.

Comparison of spatial interpolation methods for soil moisture and its application for monitoring drought.

Science.gov (United States)

Chen, Hui; Fan, Li; Wu, Wei; Liu, Hong-Bin

2017-09-26

Soil moisture data can reflect valuable information on soil properties, terrain features, and drought condition. The current study compared and assessed the performance of different interpolation methods for estimating soil moisture in an area with complex topography in southwest China. The approaches were inverse distance weighting, multifarious forms of kriging, regularized spline with tension, and thin plate spline. The 5-day soil moisture observed at 167 stations and daily temperature recorded at 33 stations during the period of 2010-2014 were used in the current work. Model performance was tested with accuracy indicators of determination coefficient (R 2 ), mean absolute percentage error (MAPE), root mean square error (RMSE), relative root mean square error (RRMSE), and modeling efficiency (ME). The results indicated that inverse distance weighting had the best performance with R 2 , MAPE, RMSE, RRMSE, and ME of 0.32, 14.37, 13.02%, 0.16, and 0.30, respectively. Based on the best method, a spatial database of soil moisture was developed and used to investigate drought condition over the study area. The results showed that the distribution of drought was characterized by evidently regional difference. Besides, drought mainly occurred in August and September in the 5 years and was prone to happening in the western and central parts rather than in the northeastern and southeastern areas.

Effects of Long-Term CO2 Enrichment on Soil-Atmosphere CH4 Fluxes and the Spatial Micro-Distribution of Methanotrophic Bacteria.

Science.gov (United States)

Karbin, Saeed; Guillet, Cécile; Kammann, Claudia I; Niklaus, Pascal A

2015-01-01

Effects of elevated atmospheric CO2 concentrations on plant growth and associated C cycling have intensively been studied, but less is known about effects on the fluxes of radiatively active trace gases other than CO2. Net soil-atmosphere CH4 fluxes are determined by the balance of soil microbially-driven methane (CH4) oxidation and methanogenesis, and both might change under elevated CO2. Here, we studied CH4 dynamics in a permanent grassland exposed to elevated CO2 for 14 years. Soil-atmosphere fluxes of CH4 were measured using large static chambers, over a period of four years. The ecosystem was a net sink for atmospheric CH4 for most of the time except summer to fall when net CH4 emissions occurred. We did not detect any elevated CO2 effects on CH4 fluxes, but emissions were difficult to quantify due to their discontinuous nature, most likely because of ebullition from the saturated zone. Potential methanotrophic activity, determined by incubation of fresh sieved soil under standardized conditions, also did not reveal any effect of the CO2 treatment. Finally, we determined the spatial micro-distribution of methanotrophic activity at less than 5× atmospheric (10 ppm) and elevated (10000 ppm) CH4 concentrations, using a novel auto-radiographic technique. These analyses indicated that domains of net CH4 assimilation were distributed throughout the analyzed top 15 cm of soils, with no dependence on CH4 concentration or CO2 treatment. Our investigations suggest that elevated CO2 exerts no or only minor effects on CH4 fluxes in the type of ecosystem we studied, at least as long as soil moisture differences are small or absent as was the case here. The autoradiographic analyses further indicate that the spatial niche of CH4 oxidation does not shift in response to CO2 enrichment or CH4 concentration, and that the same type of methanotrophs may oxidize CH4 from atmospheric and soil-internal sources.

A comparison of spatial interpolation methods for soil temperature over a complex topographical region

Science.gov (United States)

Wu, Wei; Tang, Xiao-Ping; Ma, Xue-Qing; Liu, Hong-Bin

2016-08-01

Soil temperature variability data provide valuable information on understanding land-surface ecosystem processes and climate change. This study developed and analyzed a spatial dataset of monthly mean soil temperature at a depth of 10 cm over a complex topographical region in southwestern China. The records were measured at 83 stations during the period of 1961-2000. Nine approaches were compared for interpolating soil temperature. The accuracy indicators were root mean square error (RMSE), modelling efficiency (ME), and coefficient of residual mass (CRM). The results indicated that thin plate spline with latitude, longitude, and elevation gave the best performance with RMSE varying between 0.425 and 0.592 °C, ME between 0.895 and 0.947, and CRM between -0.007 and 0.001. A spatial database was developed based on the best model. The dataset showed that larger seasonal changes of soil temperature were from autumn to winter over the region. The northern and eastern areas with hilly and low-middle mountains experienced larger seasonal changes.

Spatially explicit analysis of metal transfer to biota: influence of soil contamination and landscape.

Directory of Open Access Journals (Sweden)

Clémentine Fritsch

Full Text Available Concepts and developments for a new field in ecotoxicology, referred to as "landscape ecotoxicology," were proposed in the 1990s; however, to date, few studies have been developed in this emergent field. In fact, there is a strong interest in developing this area, both for renewing the concepts and tools used in ecotoxicology as well as for responding to practical issues, such as risk assessment. The aim of this study was to investigate the spatial heterogeneity of metal bioaccumulation in animals in order to identify the role of spatially explicit factors, such as landscape as well as total and extractable metal concentrations in soils. Over a smelter-impacted area, we studied the accumulation of trace metals (TMs: Cd, Pb and Zn in invertebrates (the grove snail Cepaea sp and the glass snail Oxychilus draparnaudi and vertebrates (the bank vole Myodes glareolus and the greater white-toothed shrew Crocidura russula. Total and CaCl(2-extractable concentrations of TMs were measured in soils from woody patches where the animals were captured. TM concentrations in animals exhibited a high spatial heterogeneity. They increased with soil pollution and were better explained by total rather than CaCl(2-extractable TM concentrations, except in Cepaea sp. TM levels in animals and their variations along the pollution gradient were modulated by the landscape, and this influence was species and metal specific. Median soil metal concentrations (predicted by universal kriging were calculated in buffers of increasing size and were related to bioaccumulation. The spatial scale at which TM concentrations in animals and soils showed the strongest correlations varied between metals, species and landscapes. The potential underlying mechanisms of landscape influence (community functioning, behaviour, etc. are discussed. Present results highlight the need for the further development of landscape ecotoxicology and multi-scale approaches, which would enhance our

Spatial distribution and source identification of heavy metals in surface soils in a typical coal mine city, Lianyuan, China.

Science.gov (United States)

Liang, Jie; Feng, Chunting; Zeng, Guangming; Gao, Xiang; Zhong, Minzhou; Li, Xiaodong; Li, Xin; He, Xinyue; Fang, Yilong

2017-06-01

In this study, we investigated the pollution degree and spatial distribution of heavy metals and determined their sources in topsoil in a typical coal mine city, Lianyuan, Hunan Province, China. We collected 6078 soil surface samples in different land use types. And the concentrations of Zn, Cd, Cu, Hg, Pb, Sb, As, Mo, V, Mn, Fe and Cr were measured. The average contents of all heavy metals were lower than their corresponding Grade II values of Chinese Soil Quality Standard with the exception of Hg. However, average contents of twelve heavy metals, except for Mn, exceeded their background level in soils in Hunan Province. Based on one-way analysis of variance (ANOVA), the contents of Cu, Zn, Cd, Pb, Hg, Mo and V were related to the anthropogenic source and there were statistically significant differences in their concentrations among different land use patterns. The spatial variation of heavy metal was visualized by GIS. The PMF model was used to ascertain contamination sources of twelve heavy metals and apportion their source contributions in Lianyuan soils. The results showed that the source contributions of the natural source, atmospheric deposition, industrial activities and agricultural activities accounted for 33.6%, 26.05%, 23.44% and 16.91%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Environmental factors at different spatial scales governing soil fauna community patterns in fragmented forests.

NARCIS (Netherlands)

Martins da Silva, P.; Berg, M.P.; Serrano, A.R.M.; Dubs, F.; Sousa, J.P.

2012-01-01

Spatial and temporal changes in community structure of soil organisms may result from a myriad of processes operating at a hierarchy of spatial scales, from small-scale habitat conditions to species movements among patches and large-sale landscape features. To disentangle the relative importance of

Laboratory Tests for Dispersive Soil Viscosity Determining

Science.gov (United States)

Ter-Martirosyan, Z. G.; Ter-Martirosyan, A. Z.; Sobolev, E. S.

2017-11-01

There are several widespread methods for soil viscosity determining now. The standard shear test device and torsion test apparatus are the most commonly used installations to do that. However, the application of them has a number of disadvantages. Therefore, the specialists of Moscow State University of Civil Engineering proposed a new device to determine the disperse soil viscosity on the basis of a stabilometer with the B-type camera (viscosimeter). The paper considers the construction of a viscosimeter and the technique for determining soil viscosity inside this tool as well as some experimental verification results of its work.

L-band HIgh Spatial Resolution Soil Moisture Mapping using SMALL UnManned Aerial Systems

Science.gov (United States)

Dai, E.; Venkitasubramony, A.; Gasiewski, A. J.; Stachura, M.; Elston, J. S.; Walter, B.; Lankford, D.; Corey, C.

2017-12-01

Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 provided new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of 36 km. However, there exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters. Compared with other methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site and Yuma Colorado Irrigation Research Foundation (IRF) site in 2015 and 2016, respectively, using LDCR Revision A and Tempest sUAS. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. LDCR Revision B has been built and integrated into SuperSwift sUAS and additional field experiments will be performed at IRF in 2017. In Revision B the IF signal is sampled at 80 MS/s to enable digital correlation and RFI mitigation capabilities, in addition to analog correlation. [1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C

The effect of short-range spatial variability on soil sampling uncertainty

Energy Technology Data Exchange (ETDEWEB)

Perk, Marcel van der [Department of Physical Geography, Utrecht University, P.O. Box 80115, 3508 TC Utrecht (Netherlands)], E-mail: m.vanderperk@geo.uu.nl; De Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria [Agenzia per la Protezione dell' Ambiente e per i Servizi Tecnici (APAT), Servizio Laboratori, Misure ed Attivita di Campo, Via di Castel Romano, 100-00128 Roma (Italy); Fajgelj, Ales; Sansone, Umberto [International Atomic Energy Agency (IAEA), Agency' s Laboratories Seibersdorf, A-1400 Vienna (Austria); Jeran, Zvonka; Jacimovic, Radojko [Jozef Stefan Institute, Jamova 39, 1000 Ljubljana (Slovenia)

2008-11-15

This paper aims to quantify the soil sampling uncertainty arising from the short-range spatial variability of elemental concentrations in the topsoils of agricultural, semi-natural, and contaminated environments. For the agricultural site, the relative standard sampling uncertainty ranges between 1% and 5.5%. For the semi-natural area, the sampling uncertainties are 2-4 times larger than in the agricultural area. The contaminated site exhibited significant short-range spatial variability in elemental composition, which resulted in sampling uncertainties of 20-30%.

The effect of short-range spatial variability on soil sampling uncertainty.

Science.gov (United States)

Van der Perk, Marcel; de Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Fajgelj, Ales; Sansone, Umberto; Jeran, Zvonka; Jaćimović, Radojko

2008-11-01

This paper aims to quantify the soil sampling uncertainty arising from the short-range spatial variability of elemental concentrations in the topsoils of agricultural, semi-natural, and contaminated environments. For the agricultural site, the relative standard sampling uncertainty ranges between 1% and 5.5%. For the semi-natural area, the sampling uncertainties are 2-4 times larger than in the agricultural area. The contaminated site exhibited significant short-range spatial variability in elemental composition, which resulted in sampling uncertainties of 20-30%.

A spatial application of a vegetation productivity equation for neo-soil reconstruction

International Nuclear Information System (INIS)

Burley, J.B.

1999-01-01

Reclamation specialists are interested in the application of recently developed soil productivity equations for post-mining reclamation planning and design. This paper presents the application of one recently developed soil productivity equation to a surface coal mine site in Mercer County, North Dakota. Geographic information systems (GIS) technology (Map*Factory 1.1) was combined with a soil productivity equation developed by the author to generate a GIS script to calculate a site's pre-mining productivity per 10 meter grid cell and then summed to calculate the grand and the expected average soil productivity for the site, resulting in a pre-mining baseline numerical spatial scores. Several post-mining alternatives were evaluated to study various soil management strategies to restore post-mining soil productivity, including: an abandoned mine landscape treatment, a reconstructed topsoil treatment with graded gentile slopes, and a reconstructed topsoil treatment with soil improvements. The results indicated that the abandoned mine scenario was significantly different than the other three treatments (ple0.05), with the reconstructed topsoil treatment with soil amendments generating the greatest estimated productivity

Digital mapping of soil properties in Zala County, Hungary for the support of county-level spatial planning and land management

Science.gov (United States)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Fodor, Nándor; Bakacsi, Zsófia; Szabó, József; Illés, Gábor

2014-05-01

:100.000 Geological Map of Hungary and the map of groundwater depth were used as auxiliary environmental covariables. Various soil related information were mapped in three distinct sets: (i) basic soil properties determining agri-environmental conditions (soil type according to the Hungarian genetic classification, rootable depth, sand and clay content for the 1st and 2nd soil layers, pH, OM and carbonate content for the plough layer); (ii) biophysical criteria of natural handicaps defined by common European system and (iii) agro-meteorologically modelled yield values for different crops, meteorological and management scenarios. The applied method(s) for the spatial inference of specific themes was/were suitably selected: regression and classification trees for categorical data, indicator kriging for probabilistic management of criterion information; and typically regression kriging for quantitative data. Our paper will present the mapping processes themselves, the resulted maps and some conclusions drawn from the experiences. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and by the European Union with the co-financing of the European Social Fund (TÁMOP-4.2.2.A-11/1/KONV-2012-0013.).

Spatial and seasonal dynamics of surface soil carbon in the Luquillo Experimental Forest, Puerto Rico.

Science.gov (United States)

Hongqing Wang; Joseph D. Cornell; Charles A.S. Hall; David P. Marley

2002-01-01

We developed a spatially-explicit version of the CENTURY soil model to characterize the storage and flux of soil organic carbon (SOC, 0–30 cm depth) in the Luquillo Experimental Forest (LEF), Puerto Rico as a function of climate, vegetation, and soils. The model was driven by monthly estimates of average air temperature, precipitation, and potential evapotranspiration...

Estimating the spatial distribution of soil moisture based on Bayesian maximum entropy method with auxiliary data from remote sensing

Science.gov (United States)

Gao, Shengguo; Zhu, Zhongli; Liu, Shaomin; Jin, Rui; Yang, Guangchao; Tan, Lei

2014-10-01

Soil moisture (SM) plays a fundamental role in the land-atmosphere exchange process. Spatial estimation based on multi in situ (network) data is a critical way to understand the spatial structure and variation of land surface soil moisture. Theoretically, integrating densely sampled auxiliary data spatially correlated with soil moisture into the procedure of spatial estimation can improve its accuracy. In this study, we present a novel approach to estimate the spatial pattern of soil moisture by using the BME method based on wireless sensor network data and auxiliary information from ASTER (Terra) land surface temperature measurements. For comparison, three traditional geostatistic methods were also applied: ordinary kriging (OK), which used the wireless sensor network data only, regression kriging (RK) and ordinary co-kriging (Co-OK) which both integrated the ASTER land surface temperature as a covariate. In Co-OK, LST was linearly contained in the estimator, in RK, estimator is expressed as the sum of the regression estimate and the kriged estimate of the spatially correlated residual, but in BME, the ASTER land surface temperature was first retrieved as soil moisture based on the linear regression, then, the t-distributed prediction interval (PI) of soil moisture was estimated and used as soft data in probability form. The results indicate that all three methods provide reasonable estimations. Co-OK, RK and BME can provide a more accurate spatial estimation by integrating the auxiliary information Compared to OK. RK and BME shows more obvious improvement compared to Co-OK, and even BME can perform slightly better than RK. The inherent issue of spatial estimation (overestimation in the range of low values and underestimation in the range of high values) can also be further improved in both RK and BME. We can conclude that integrating auxiliary data into spatial estimation can indeed improve the accuracy, BME and RK take better advantage of the auxiliary

Determination of unsaturated hydraulic conductivity of alfisol soil in ...

African Journals Online (AJOL)

The hydrolic conductivity of soil measures the ease at which water moves through the soil by determining the flux density of water passing through the soil. The estimation of hydraulic conductivity indicates how fluids flow throuhg a substance and thus determine the water balance in the soil profile. The trend lines of ...

Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

DEFF Research Database (Denmark)

Dechesne, Arnaud; Badawi, N.; Aamand, Jens

2014-01-01

across pesticide classes: they include some soil characteristics (pH) and some agricultural management practices (pesticide application, tillage), while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance......Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we...... critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates...

Soil pH, total phosphorus, climate and distance are the major factors influencing microbial activity at a regional spatial scale

DEFF Research Database (Denmark)

Cao, Haichuan; Chen, Ruirui; Wang, Libing

2016-01-01

Considering the extensive functional redundancy in microbial communities and great difficulty in elucidating it based on taxonomic structure, studies on the biogeography of soil microbial activity at large spatial scale are as important as microbial community structure. Eighty-four soil samples...... scaling clearly revealed that soil microbial activities showed distinct differentiation at different sites over a regional spatial scale, which were strongly affected by soil pH, total P, rainfall, temperature, soil type and location. In addition, microbial community structure was greatly influenced...... scales. There are common (distance, climate, pH and soil type) but differentiated aspects (TP, SOC and N) in the biogeography of soil microbial community structure and activity....

Spatial distribution of heavy metals in soil, water, and vegetables of farms in Sanandaj, Kurdistan, Iran.

Science.gov (United States)

Maleki, Afshin; Amini, Hassan; Nazmara, Shahrokh; Zandi, Shiva; Mahvi, Amir Hossein

2014-01-01

Heavy metals are ubiquitous elsewhere in nature and their measurement in environment is necessary to develop health management strategies. In this study, we aimed to find out concentrations and spatial patterns of heavy metals in main farms of Sanandaj in Kurdistan, Iran. Over May to October 2012, six farms were selected to analyze concentrations and spatial patterns of several heavy metals, namely aluminum (Al), arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) in their soil, irrigation water, and edible vegetables. Overall, 36 samples of soil and water and 72 samples of vegetables including coriander (Coriandrum sativum), dill (Anethum graveolens), radish (Raphanus sativus) root and radish leaf were collected. The concentrations of metals were determined by inductively coupled plasma optical emission spectrometry. The spatial surfaces of heavy metals were created using geospatial information system. The order of metals in soil was Al > Zn > Ni > Cu > Cr > Pb > Co > As > Cd while in water it was Cr > Co > Zn > Pb > Cu > Ni > Al = As = Cd. The order of heavy metals in vegetables was Al > Zn > Cu > Cr > Ni > Pb > Co > As > Cd. Totally, the minimum concentrations of Al, Cu, Pb, and Zn were found in radish root while the maximum of Al, Co, Cr, and Ni were found in radish leaf. The minimum concentrations of Cd and Cr and maximum concentrations of Cu and Zn were also deciphered in dill. Noteworthy, coriander had the minimum concentrations of Co and Ni. The concentrations of Cr and Pb in vegetables were more than maximum allowable limits of the Food and Agriculture Organization (FAO) and the World Health Organization (WHO). In summary, albeit the concentrations of heavy metals in soil and water samples were below FAO and the WHO standards, vegetables were contaminated by chromium and lead.

Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings.

Science.gov (United States)

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P

2017-09-15

Major end users of Digital Soil Mapping (DSM) such as policy makers and agricultural extension workers are faced with choosing the appropriate remote sensing data. The objective of this research is to analyze the spatial resolution effects of different remote sensing images on soil prediction models in two smallholder farms in Southern India called Kothapally (Telangana State), and Masuti (Karnataka State), and provide empirical guidelines to choose the appropriate remote sensing images in DSM. Bayesian kriging (BK) was utilized to characterize the spatial pattern of exchangeable potassium (K ex ) in the topsoil (0-15 cm) at different spatial resolutions by incorporating spectral indices from Landsat 8 (30 m), RapidEye (5 m), and WorldView-2/GeoEye-1/Pleiades-1A images (2 m). Some spectral indices such as band reflectances, band ratios, Crust Index and Atmospherically Resistant Vegetation Index from multiple images showed relatively strong correlations with soil K ex in two study areas. The research also suggested that fine spatial resolution WorldView-2/GeoEye-1/Pleiades-1A-based and RapidEye-based soil prediction models would not necessarily have higher prediction performance than coarse spatial resolution Landsat 8-based soil prediction models. The end users of DSM in smallholder farm settings need select the appropriate spectral indices and consider different factors such as the spatial resolution, band width, spectral resolution, temporal frequency, cost, and processing time of different remote sensing images. Overall, remote sensing-based Digital Soil Mapping has potential to be promoted to smallholder farm settings all over the world and help smallholder farmers implement sustainable and field-specific soil nutrient management scheme. Copyright © 2017 Elsevier Ltd. All rights reserved.

Environment and geographic distance differ in relative importance for determining fungal community of rhizosphere and bulk soil.

Science.gov (United States)

Zhang, Kaoping; Adams, Jonathan M; Shi, Yu; Yang, Teng; Sun, Ruibo; He, Dan; Ni, Yingying; Chu, Haiyan

2017-09-01

Rhizospheric fungi play major roles in both natural and agricultural ecosystems. However, little is known about the determinants of their diversity and biogeographic patterns. Here, we compared fungal communities in rhizosphere and bulk soils of wheat fields in the North China Plain. The rhizosphere had a lower fungal diversity (observed OTUs and Chao1) than bulk soil, and a distinct fungal community structure in rhizosphere compared with bulk soil. The relative importance of environmental factors and geographic distance for fungal distribution differed between rhizosphere and bulk soil. Environmental factors were the primary cause of variations in total fungal community and major fungal phyla in bulk soil. By contrast, fungal communities in soils loosely attached to roots were predictable from both environmental factors and influences of geographic distance. Communities in soils tightly attached to roots were mainly determined by geographic distance. Our results suggest that both contemporary environment processes (present-day abiotic and biotic environment characters) and historical processes (spatial isolation, dispersal limitation occurred in the past) dominate variations of fungal communities in wheat fields, but their relative importance of all these processes depends on the proximity of fungal community to the plant roots. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Spatial distribution of soil organic carbon stocks in France

Directory of Open Access Journals (Sweden)

M. P. Martin

2011-05-01

Full Text Available Soil organic carbon plays a major role in the global carbon budget, and can act as a source or a sink of atmospheric carbon, thereby possibly influencing the course of climate change. Changes in soil organic carbon (SOC stocks are now taken into account in international negotiations regarding climate change. Consequently, developing sampling schemes and models for estimating the spatial distribution of SOC stocks is a priority. The French soil monitoring network has been established on a 16 km × 16 km grid and the first sampling campaign has recently been completed, providing around 2200 measurements of stocks of soil organic carbon, obtained through an in situ composite sampling, uniformly distributed over the French territory.

We calibrated a boosted regression tree model on the observed stocks, modelling SOC stocks as a function of other variables such as climatic parameters, vegetation net primary productivity, soil properties and land use. The calibrated model was evaluated through cross-validation and eventually used for estimating SOC stocks for mainland France. Two other models were calibrated on forest and agricultural soils separately, in order to assess more precisely the influence of pedo-climatic variables on SOC for such soils.

The boosted regression tree model showed good predictive ability, and enabled quantification of relationships between SOC stocks and pedo-climatic variables (plus their interactions over the French territory. These relationships strongly depended on the land use, and more specifically, differed between forest soils and cultivated soil. The total estimate of SOC stocks in France was 3.260 ± 0.872 PgC for the first 30 cm. It was compared to another estimate, based on the previously published European soil organic carbon and bulk density maps, of 5.303 PgC. We demonstrate that the present estimate might better represent the actual SOC stock distributions of France, and consequently that the

Accounting for the measurement error of spectroscopically inferred soil carbon data for improved precision of spatial predictions.

Science.gov (United States)

Somarathna, P D S N; Minasny, Budiman; Malone, Brendan P; Stockmann, Uta; McBratney, Alex B

2018-08-01

Spatial modelling of environmental data commonly only considers spatial variability as the single source of uncertainty. In reality however, the measurement errors should also be accounted for. In recent years, infrared spectroscopy has been shown to offer low cost, yet invaluable information needed for digital soil mapping at meaningful spatial scales for land management. However, spectrally inferred soil carbon data are known to be less accurate compared to laboratory analysed measurements. This study establishes a methodology to filter out the measurement error variability by incorporating the measurement error variance in the spatial covariance structure of the model. The study was carried out in the Lower Hunter Valley, New South Wales, Australia where a combination of laboratory measured, and vis-NIR and MIR inferred topsoil and subsoil soil carbon data are available. We investigated the applicability of residual maximum likelihood (REML) and Markov Chain Monte Carlo (MCMC) simulation methods to generate parameters of the Matérn covariance function directly from the data in the presence of measurement error. The results revealed that the measurement error can be effectively filtered-out through the proposed technique. When the measurement error was filtered from the data, the prediction variance almost halved, which ultimately yielded a greater certainty in spatial predictions of soil carbon. Further, the MCMC technique was successfully used to define the posterior distribution of measurement error. This is an important outcome, as the MCMC technique can be used to estimate the measurement error if it is not explicitly quantified. Although this study dealt with soil carbon data, this method is amenable for filtering the measurement error of any kind of continuous spatial environmental data. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatial modeling of litter and soil carbon stocks with associated uncertainty on forest land in the conterminous United States

Science.gov (United States)

Cao, B.; Domke, G. M.; Russell, M.; McRoberts, R. E.; Walters, B. F.

2017-12-01

Forest ecosystems contribute substantially to carbon (C) storage. The dynamics of litter decomposition, translocation and stabilization into soil layers are essential processes in the functioning of forest ecosystems, as they control the cycling of soil organic matter and the accumulation and release of C to the atmosphere. Therefore, the spatial distributions of litter and soil C stocks are important in greenhouse gas estimation and reporting and inform land management decisions, policy, and climate change mitigation strategies. In this study, we explored the effects of spatial aggregation of climatic, biotic, topographic and soil input data on national estimates of litter and soil C stocks and characterized the spatial distribution of litter and soil C stocks in the conterminous United States. Data from the Forest Inventory and Analysis (FIA) program within the US Forest Service were used with vegetation phenology data estimated from LANDSAT imagery (30 m) and raster data describing relevant environmental parameters (e.g. temperature, precipitation, topographic properties) for the entire conterminous US. Litter and soil C stocks were estimated and mapped through geostatistical analysis and statistical uncertainty bounds on the pixel level predictions were constructed using a Monte Carlo-bootstrap technique, by which credible variance estimates for the C stocks were calculated. The sensitivity of model estimates to spatial aggregation depends on geographic region. Further, using long-term (30-year) climate averages during periods with strong climatic trends results in large differences in litter and soil C stock estimates. In addition, results suggest that local topographic aspect is an important variable in litter and soil C estimation at the continental scale.

Spatial variability of isoproturon mineralizing activity within an agricultural field: geostatistical analysis of simple physicochemical and microbiological soil parameters.

Science.gov (United States)

El Sebai, T; Lagacherie, B; Soulas, G; Martin-Laurent, F

2007-02-01

We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass.

Using high-resolution radar images to determine vegetation cover for soil erosion assessments.

Science.gov (United States)

Bargiel, D; Herrmann, S; Jadczyszyn, J

2013-07-30

Healthy soils are crucial for human well-being. Because soils are threatened worldwide, politicians recognize the need for soil protection. For example, the European Commission has launched the Thematic Strategy for Soil Protection, which requests the European member states to identify high risk areas for soil degradation. Most states use the Universal Soil Loss Equation (USLE) to assess soil erosion risk at the national scale. The USLE includes different factors, one of them is the vegetation cover and management factor (C factor). Modern satellite-based radar sensors now provide highly accurate vegetation cover data, enabling opportunities to improve the accuracy of the C factor. The presented study proves the suitability for C factor determination based on a multi-temporal classification of high-resolution radar images. Further USLE factors were derived from existing data sources (meteorological data, soil maps, digital elevation model) to conduct an USLE-based soil erosion assessment. The resulting map illustrates a qualitative assessment for soil erosion risk within a plot of about 7*12 km in an agricultural region in Poland that is very susceptible to soil erosion processes. A high erosion risk of more than 10 tonnes per ha and year was assessed to occur on 13.6% (646 ha) of the agricultural areas within the investigated plot. Further 7.8% (372 ha) of agricultural land is threaten by a medium risk of 5-10 tonnes per ha and year. Such a spatial information about areas of high or medium soil erosion risk are crucial for the development of strategies for the protection of soils. Copyright © 2013 Elsevier Ltd. All rights reserved.

Spatial Variations of Heavy Metals in the Soils of Vegetable-Growing Land along Urban-Rural Gradient of Nanjing, China

Science.gov (United States)

Fang, Shi-Bo; Hu, Hao; Sun, Wan-Chun; Pan, Jian-Jun

2011-01-01

China has experienced rapid urbanization in recent years. The acceleration of urbanization has created wealth and opportunity as well as intensified ecological and environmental problems, especially soil pollution. Our study concentrated on the variation of heavy metal content due to urbanization in the vegetable-growing soil. Laws and other causes of the spatial-temporal variation in heavy metal content of vegetable-growing soils were analyzed for the period of urbanization in Nanjing (the capital of Jiangsu province in China). The levels of Cu, Zn, Pb, Cd and Hg in samples of vegetable-growing soil were detected. The transverse, vertical spatio-temporal variation of heavy metals in soil was analyzed on the base of field investigations and laboratory analysis. The results show that: (1) in soil used for vegetable production, the levels of heavy metals decreased gradually from urban to rural areas; the levels of the main heavy metals in urban areas are significantly higher than suburban and rural areas; (2) the means of the levels of heavy metals, calculated by subtracting the sublayer (15–30 cm) from the toplayer (0–15 cm), are all above zero and large in absolute value in urban areas, but in suburban and rural areas, the means are all above or below zero and small in absolute value. The causes of spatial and temporal variation were analyzed as follows: one cause was associated with mellowness of the soil and the length of time the soil had been used for vegetable production; the other cause was associated with population density and industrial intensity decreasing along the urban to rural gradient (i.e., urbanization levels can explain the distribution of heavy metals in soil to some extent). Land uses should be planned on the basis of heavy metal pollution in soil, especially in urban and suburban regions. Heavily polluted soils have to be expected from food production. Further investigation should be done to determine whether and what kind of agricultural

Evaluating spatial interaction of soil property with non-point source pollution at watershed scale: The phosphorus indicator in Northeast China

Energy Technology Data Exchange (ETDEWEB)

Ouyang, Wei, E-mail: wei@itc.nl; Huang, Haobo; Hao, Fanghua; Shan, Yushu; Guo, Bobo

2012-08-15

To better understand the spatial dynamics of non-point source (NPS) phosphorus loading with soil property at watershed scale, integrated modeling and soil chemistry is crucial to ensure that the indicator is functioning properly and expressing the spatial interaction at two depths. Developments in distributed modeling have greatly enriched the availability of geospatial data analysis and assess the NPS pollution loading response to soil property over larger area. The 1.5 km-grid soil sampling at two depths was analyzed with eight parameters, which provided detailed spatial and vertical soil data under four main types of landuses. The impacts of landuse conversion and agricultural practice on soil property were firstly identified. Except for the slightly bigger total of potassium (TK) and cadmium (Cr), the other six parameters had larger content in 20-40 cm surface than the top 20 cm surface. The Soil and Water Assessment Tool was employed to simulate the loading of NPS phosphorus. Overlaying with the landuse distribution, it was found that the NPS phosphorus mainly comes from the subbasins dominated with upland and paddy rice. The linear correlations of eight soil parameters at two depths with NPS phosphorus loading in the subbasins of upland and paddy rice were compared, respectively. The correlations of available phosphorus (AP), total phosphorus (TP), total nitrogen (TN) and TK varied in two depths, and also can assess the loading. The soil with lower soil organic carbon (SOC) presented a significant higher risk for NPS phosphorus loading, especially in agricultural area. The Principal Component Analysis showed that the TP and zinc (Zn) in top soil and copper (Cu) and Cr in subsurface can work as indicators. The analysis suggested that the application of soil property indicators is useful for assessing NPS phosphorus loss, which is promising for water safety in agricultural area. -- Highlights: Black-Right-Pointing-Pointer Spatial dynamics of NPS phosphorus

Evaluating spatial interaction of soil property with non‐point source pollution at watershed scale: The phosphorus indicator in Northeast China

International Nuclear Information System (INIS)

Ouyang, Wei; Huang, Haobo; Hao, Fanghua; Shan, Yushu; Guo, Bobo

2012-01-01

To better understand the spatial dynamics of non-point source (NPS) phosphorus loading with soil property at watershed scale, integrated modeling and soil chemistry is crucial to ensure that the indicator is functioning properly and expressing the spatial interaction at two depths. Developments in distributed modeling have greatly enriched the availability of geospatial data analysis and assess the NPS pollution loading response to soil property over larger area. The 1.5 km-grid soil sampling at two depths was analyzed with eight parameters, which provided detailed spatial and vertical soil data under four main types of landuses. The impacts of landuse conversion and agricultural practice on soil property were firstly identified. Except for the slightly bigger total of potassium (TK) and cadmium (Cr), the other six parameters had larger content in 20–40 cm surface than the top 20 cm surface. The Soil and Water Assessment Tool was employed to simulate the loading of NPS phosphorus. Overlaying with the landuse distribution, it was found that the NPS phosphorus mainly comes from the subbasins dominated with upland and paddy rice. The linear correlations of eight soil parameters at two depths with NPS phosphorus loading in the subbasins of upland and paddy rice were compared, respectively. The correlations of available phosphorus (AP), total phosphorus (TP), total nitrogen (TN) and TK varied in two depths, and also can assess the loading. The soil with lower soil organic carbon (SOC) presented a significant higher risk for NPS phosphorus loading, especially in agricultural area. The Principal Component Analysis showed that the TP and zinc (Zn) in top soil and copper (Cu) and Cr in subsurface can work as indicators. The analysis suggested that the application of soil property indicators is useful for assessing NPS phosphorus loss, which is promising for water safety in agricultural area. -- Highlights: ► Spatial dynamics of NPS phosphorus pollution with soil

Persistent organic pollutants in the Tibetan surface soil: Spatial distribution, air–soil exchange and implications for global cycling

International Nuclear Information System (INIS)

Wang Xiaoping; Sheng Jiujiang; Gong Ping; Xue Yonggang; Yao Tandong; Jones, Kevin C.

2012-01-01

There are limited data on persistent organic pollutants (POPs) in the soils of the Tibetan Plateau. This paper presents data from a survey of organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) in 40 background surface (0–5 cm) soils of the Tibetan Plateau. Soil concentrations (pg/g, dw) ranged as follows: DDTs, 13-7700; HCHs, 64-847; HCB, 24-564; sum of 15 PCBs, 75-1021; and sum of 9 PBDEs, below detection limit −27. Soil DDT, HCB, PCB and PBDE concentrations were strongly influenced by soil organic carbon content. HCH concentrations were clearly associated with the proximity to source regions in south Asia. The air–soil equilibrium status of POPs suggested the Tibetan soils may be partial “secondary sources” of HCB, low molecular weight PCBs and HCHs and will likely continue to be “sinks” for the less volatile DDE and DDT. - Highlights: ► Soil organic carbon content influence the spatial distribution of persistent organic pollutants. ► The Tibetan soil acts as “secondary sources” for HCB, low molecular weight PCBs and HCHs. ► The Tibetan soil will continue to be “sinks” for DDE and DDT. - Tibetan soils may be potential “secondary sources” of the HCB, low molecular weight PCBs and HCHs that are observed in air.

Estimating spatially distributed soil texture using time series of thermal remote sensing - a case study in central Europe

Science.gov (United States)

Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten

2016-09-01

For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. This approach will improve the generation of spatially distributed topsoil maps, particularly for hydrologic modeling purposes, and will expand the usage of thermal remote sensing products.

Assessment of spatial distribution of soil heavy metals using ANN-GA, MSLR and satellite imagery.

Science.gov (United States)

Naderi, Arman; Delavar, Mohammad Amir; Kaboudin, Babak; Askari, Mohammad Sadegh

2017-05-01

This study aims to assess and compare heavy metal distribution models developed using stepwise multiple linear regression (MSLR) and neural network-genetic algorithm model (ANN-GA) based on satellite imagery. The source identification of heavy metals was also explored using local Moran index. Soil samples (n = 300) were collected based on a grid and pH, organic matter, clay, iron oxide contents cadmium (Cd), lead (Pb) and zinc (Zn) concentrations were determined for each sample. Visible/near-infrared reflectance (VNIR) within the electromagnetic ranges of satellite imagery was applied to estimate heavy metal concentrations in the soil using MSLR and ANN-GA models. The models were evaluated and ANN-GA model demonstrated higher accuracy, and the autocorrelation results showed higher significant clusters of heavy metals around the industrial zone. The higher concentration of Cd, Pb and Zn was noted under industrial lands and irrigation farming in comparison to barren and dryland farming. Accumulation of industrial wastes in roads and streams was identified as main sources of pollution, and the concentration of soil heavy metals was reduced by increasing the distance from these sources. In comparison to MLSR, ANN-GA provided a more accurate indirect assessment of heavy metal concentrations in highly polluted soils. The clustering analysis provided reliable information about the spatial distribution of soil heavy metals and their sources.

GEMAS: Molybdenum Spatial Distribution Patterns in European Soil

Science.gov (United States)

Cicchella, Domenico; Zuzolo, Daniela; Demetriades, Alecos; De Vivo, Benedetto; Eklund, Mikael; Ladenberger, Anna; Negrel, Philippe; O'Connor, Patrick

2017-04-01

Molybdenum is an essential trace element for both plants and animals as well as for human being. It is one such trace element for which potential health concerns have been raised but for which few data exist and little investigation or interpretation of distributions in soils has been made. The main goal of this study was to fill this gap. Molybdenum (Mo) concentrations are reported for the similar spatial distribution patterns mainly governed by geology (parent material and mineralisation), as well as weathering, soil formation and climate since the last glaciations period. The dominant feature is represented by low Mo concentrations over the coarse-grained sandy deposits of the last glaciations in central northern Europe while the most extensive anomalies occur in Scandinavian soils. The highest Mo concentration value occurs to the North of Oslo close to one of the largest porphyry Mo deposit of the World. Some interesting anomalous patterns occur also in Italy in correspondence with alkaline volcanics, in Spain and Greece associated with sulfides mineralizations and in Slovenia and Croatia where are probably related to the long weathering history of karstic residual soils. Anomalous concentrations in some areas of Ireland represent a clear example of how an excess of molybdenum has produced potentially toxic pastures. In fact, these give rise to problems particularly in young cattle when excess molybdenum in the herbage acts as an antagonist, which militates against efficient copper absorption by the animal.

Geochemical Background and Baseline Values Determination and Spatial Distribution of Heavy Metal Pollution in Soils of the Andes Mountain Range (Cajamarca-Huancavelica, Peru)

Science.gov (United States)

Santos-Francés, Fernando; Alonso Rojo, Pilar; García Sánchez, Antonio

2017-01-01

Concentrations of seven heavy metals (Cd, Cr, Cu, Hg, Ni, Pb, and Zn) and one metalloid (As) as well as various parameters (pH, organic carbon, granulometric analysis and cation exchange capacity) were analyzed in 77 soil samples collected in the mining areas of La Zanja and Colquirrumi (Department of Cajamarca) and Julcani (Department of Huancavelica). Our study proposed geochemical baseline values for heavy metals in a natural region (La Zanja) from samples collected during the period of the environmental impact study (2006), that is, from an earlier period which occurred at the beginning of the exploitation of the current gold mine. The baseline values obtained were as follows: 8.26 mg·kg−1 for Cr; 56.97 mg·kg−1 for Ni; 22, 20 mg·kg−1 for the Cu; 47.42 mg·kg−1 for Zn; 27.50 mg·kg−1 for As; 4.36 mg·kg−1 for Cd; 4.89 mg·kg−1 for Hg, and 44.87 mg·kg−1 for Pb. Through the use of different indices of heavy metal contamination (geo-accumulation index (Igeo), improved Nemerow index (IIN) and potential ecological risk index (RI)), the degree of pollution caused by mining activities in two areas, Colquirrumi and Julcani, which have a high density of mining sites in operation, was determined. The values obtained from these indices indicated that the Colquirrumi region was the most contaminated, followed by Julcani. The area of La Zanja, despite being free of mining operations, presented slight diffuse pollution. Several positive correlations were obtained, with a high level of significance, between pH, organic carbon content, cation exchange capacity, and the Cr, Pb and Ni concentrations of the soils. The spatial distribution of the heavy metals was realized by means of the interpolation method of ordinary kriging. The results obtained and the experience gained in this work were necessary to facilitate the identification of soil contamination processes in high altitude areas of the Andes Western Cordillera (Peru) as a basis for taking appropriate

Geochemical Background and Baseline Values Determination and Spatial Distribution of Heavy Metal Pollution in Soils of the Andes Mountain Range (Cajamarca-Huancavelica, Peru).

Science.gov (United States)

Santos-Francés, Fernando; Martinez-Graña, Antonio; Alonso Rojo, Pilar; García Sánchez, Antonio

2017-07-31

Concentrations of seven heavy metals (Cd, Cr, Cu, Hg, Ni, Pb, and Zn) and one metalloid (As) as well as various parameters (pH, organic carbon, granulometric analysis and cation exchange capacity) were analyzed in 77 soil samples collected in the mining areas of La Zanja and Colquirrumi (Department of Cajamarca) and Julcani (Department of Huancavelica). Our study proposed geochemical baseline values for heavy metals in a natural region (La Zanja) from samples collected during the period of the environmental impact study (2006), that is, from an earlier period which occurred at the beginning of the exploitation of the current gold mine. The baseline values obtained were as follows: 8.26 mg kg-1 for Cr; 56.97 mg kg-1 for Ni; 22, 20 mg kg-1 for the Cu; 47.42 mg kg-1 for Zn; 27.50 mg kg-1 for As; 4.36 mg kg-1 for Cd; 4.89 mg kg-1 for Hg, and 44.87 mg kg-1 for Pb. Through the use of different indices of heavy metal contamination (geo-accumulation index (Igeo), improved Nemerow index (IIN) and potential ecological risk index (RI)), the degree of pollution caused by mining activities in two areas, Colquirrumi and Julcani, which have a high density of mining sites in operation, was determined. The values obtained from these indices indicated that the Colquirrumi region was the most contaminated, followed by Julcani. The area of La Zanja, despite being free of mining operations, presented slight diffuse pollution. Several positive correlations were obtained, with a high level of significance, between pH, organic carbon content, cation exchange capacity, and the Cr, Pb and Ni concentrations of the soils. The spatial distribution of the heavy metals was realized by means of the interpolation method of ordinary kriging. The results obtained and the experience gained in this work were necessary to facilitate the identification of soil contamination processes in high altitude areas of the Andes Western Cordillera (Peru) as a basis for taking appropriate measures when restoring

Determination of Pu in soil samples

International Nuclear Information System (INIS)

Torres C, C. O.; Hernandez M, H.; Romero G, E. T.; Vega C, H. R.

2016-10-01

The irreversible consequences of accidents occurring in nuclear plants and in nuclear fuel reprocessing sites are mainly the distribution of different radionuclides in different matrices such as the soil. The distribution in the superficial soil is related to the internal and external exposure to the radiation of the affected population. The internal contamination with radionuclides such as Pu is of great relevance to the nuclear forensic science, where is important to know the chemical and isotopic compositions of nuclear materials. The objective of this work is to optimize the radiochemical separation of plutonium (Pu) from soil samples and to determine their concentration. The soil samples were prepared using acid digestion assisted by microwave; purification of Pu was carried out with AG1X8 resin using ion exchange chromatography. Pu isotopes were measured using ICP-SFMS. In order to reduce the interference due to the presence of "2"3"8UH "+ in the samples, a solvent removal system (Apex) was used. In addition, the limit of detection and quantification of Pu was determined. It was found that the recovery efficiency of Pu in soil samples ranges from 70 to 93%. (Author)

Effect of Variable Spatial Scales on USLE-GIS Computations

Science.gov (United States)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

Concentrations, sources and spatial distribution of polycyclic aromatic hydrocarbons in soils from Beijing, Tianjin and surrounding areas, North China

International Nuclear Information System (INIS)

Wang Wentao; Massey Simonich, Staci L.; Xue Miao; Zhao Jingyu; Zhang Na; Wang Rong; Cao Jun; Tao Shu

2010-01-01

The concentrations, profiles, sources and spatial distribution of polycyclic aromatic hydrocarbons (PAHs) were determined in 40 surface soil samples collected from Beijing, Tianjin and surrounding areas, North China in 2007, and all sampling sites were far from industrial areas, roadsides and other pollution sources, and across a range of soil types in remote, rural villages and urban areas. The total concentrations of 16 PAHs ranged from 31.6 to 1475.0 ng/g, with an arithmetic average of 336.4 ng/g. The highest PAH concentrations were measured in urban soils, followed by rural village soils and soils from remote locations. The remote-rural village-urban PAH concentration gradient was related to population density, gross domestic product (GDP), long-range atmospheric transport and different types of land use. In addition, the PAH concentration was well correlated with the total organic carbon (TOC) concentration of the soil. The PAH profile suggested that coal combustion and biomass burning were primary PAH sources. - The concentration, profiles and possible sources of PAHs in Beijing, Tianjin and surrounding area soils were studied and related to population density and gross domestic product (GDP).

Spatial changes in the prokaryotic community structure across a soil catena

Science.gov (United States)

Semenov, Mikhail; Zhuravleva, Anna; Tkhakakhova, Azida

2017-04-01

Mesorelief is a complex biogeochemical factor regulating hydrothermal regimes of the surface soil layer, the type of plant cover, etc., and, therefore, influences on soil microbial community structure. A natural model of soil sequence across the slope is a soil catena. Soils forming on various mesorelief positions significantly differ in physicochemical and biological properties, leading to the changes in spatial distribution of various bacterial and archaeal taxa across the soil catena. The aim of this study was to determine soil microbial community structure of different ecosystems corresponding to three mesorelief positions within the soil catena. The catena was located at the right bank of the Oka River (Moscow region, Russian Federation). Soil samples were taken at depths of 0-20 cm, 20-40 cm, and 40-60 cm from three sites within the transect of 960 m with elevation of 80 m, corresponding to the autonomous (AU), transitional (TR) (both Luvisols), and accumulative (AC) (Fluvisol Umbric) positions of the landscape. The dominant vegetation of studied sites were rootstock- and loose bunchgrasses of the fallow ecosystem (AU), a secondary small-leaved forest of the forest ecosystem (TR), and a meadow-bog association of the meadow-bog ecosystem (AC). The distances between the sites were 680 m (AU and TR), and 280 m (TR and AC). The soil samples were homogenized, and the total community DNA of three replicates was extracted using the FastDNA® SPIN kit for Soil. All DNA replicates were combined in a pooled sample and the DNA was used for PCR with specific primers for the 16S V3 and V4 regions. The products were purified and submitted to Illumina MiSeq sequencing. Obtained sequence data were evaluated using the MiSeq Reporter Metagenomics Workflow and QIIME. Quantification of the bacterial and archaeal metabolically active cells was quantified by the FISH-method. Verrucomicrobia, Proteobacteria, Firmictutes and Actinobacteria were the major phyla in autonomous site

Soil variability in mountain areas

OpenAIRE

Zanini, E.; Freppaz, M.; Stanchi, S.; Bonifacio, E.; Egli, M.

2015-01-01

The high spatial variability of soils is a relevant issue at local and global scales, and determines the complexity of soil ecosystem functions and services. This variability derives from strong dependencies of soil ecosystems on parent materials, climate, relief and biosphere, including human impact. Although present in all environments, the interactions of soils with these forming factors are particularly striking in mountain areas.

The mARM3D spatially distributed soil evolution model: Three-dimensional model framework and analysis of hillslope and landform responses

Science.gov (United States)

Cohen, Sagy; Willgoose, Garry; Hancock, Greg

2010-10-01

We present a three-dimensional landscape-pedogenesis model, mARM3D (matrices ARMOUR 3D), which simulates soil evolution as a function of erosion and pedogenic processes. The model simulates the discretized soil profile for points on a spatial grid. The approach, using transition matrices, is computationally efficient and allows the simulation of large-scale spatial coupling and long-term soil evolution. We study the effect of the depth-dependent soil-weathering rate (i.e., the rate of soil particle breakdown) and bedrock-lowering rate (i.e., the rate of conversion of bedrock to soil). The difference in depth-dependent weathering functions has a significant effect on the in-profile soil properties through depth, specifically particle size grading. However, the depth dependency has a relatively minor effect on the surface properties of the soil profile, with all weathering functions generating very similar surface properties. The surface properties were a function of the cumulative amount of weathering (i.e., the integral of the weathering function over exhumation) with finer surface grading for higher weathering rates. Soil thickness could be estimated without explicitly modeling soil thickness. Thickness was negatively correlated with surface median grain size. As thickness decreases, the surface grading coarsens. This was driven by surface erosion, where as surface grading coarsens, erosion decreases and the soil deepens. Weathering and erosion interact to spatially organize the surface soil grading with a log-log relationship between surface grading, contributing area, and local slope. This relationship was independent of the weathering function. This relationship might be useful for the spatial description of soil properties in digital soil mapping.

An exploration of spatial risk assessment for soil protection: estimating risk and establishing priority areas for soil protection.

Science.gov (United States)

Kibblewhite, M G; Bellamy, P H; Brewer, T R; Graves, A R; Dawson, C A; Rickson, R J; Truckell, I; Stuart, J

2014-03-01

Methods for the spatial estimation of risk of harm to soil by erosion by water and wind and by soil organic matter decline are explored. Rates of harm are estimated for combinations of soil type and land cover (as a proxy for hazard frequency) and used to estimate risk of soil erosion and loss of soil organic carbon (SOC) for 1 km(2)pixels. Scenarios are proposed for defining the acceptability of risk of harm to soil: the most precautionary one corresponds to no net harm after natural regeneration of soil (i.e. a 1 in 20 chance of exceeding an erosion rate of soils and a carbon stock decline of 0 tha(-1)y(-1) for organic soils). Areas at higher and lower than possible acceptable risk are mapped. The veracity of boundaries is compromised if areas of unacceptable risk are mapped to administrative boundaries. Errors in monitoring change in risk of harm to soil and inadequate information on risk reduction measures' efficacy, at landscape scales, make it impossible to use or monitor quantitative targets for risk reduction adequately. The consequences for priority area definition of expressing varying acceptable risk of harm to soil as a varying probability of exceeding a fixed level of harm, or, a varying level of harm being exceeded with a fixed probability, are discussed. Soil data and predictive models for rates of harm to soil would need considerable development and validation to implement a priority area approach robustly. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparison of spatial interpolation techniques to predict soil properties in the colombian piedmont eastern plains

Directory of Open Access Journals (Sweden)

Mauricio Castro Franco

2017-07-01

Full Text Available Context: Interpolating soil properties at field-scale in the Colombian piedmont eastern plains is challenging due to: the highly and complex variable nature of some processes; the effects of the soil; the land use; and the management. While interpolation techniques are being adapted to include auxiliary information of these effects, the soil data are often difficult to predict using conventional techniques of spatial interpolation. Method: In this paper, we evaluated and compared six spatial interpolation techniques: Inverse Distance Weighting (IDW, Spline, Ordinary Kriging (KO, Universal Kriging (UK, Cokriging (Ckg, and Residual Maximum Likelihood-Empirical Best Linear Unbiased Predictor (REML-EBLUP, from conditioned Latin Hypercube as a sampling strategy. The ancillary information used in Ckg and REML-EBLUP was indexes calculated from a digital elevation model (MDE. The “Random forest” algorithm was used for selecting the most important terrain index for each soil properties. Error metrics were used to validate interpolations against cross validation. Results: The results support the underlying assumption that HCLc captured adequately the full distribution of variables of ancillary information in the Colombian piedmont eastern plains conditions. They also suggest that Ckg and REML-EBLUP perform best in the prediction in most of the evaluated soil properties. Conclusions: Mixed interpolation techniques having auxiliary soil information and terrain indexes, provided a significant improvement in the prediction of soil properties, in comparison with other techniques.

Spatial Variations of Soil Gas Geochemistry in the Tangshan Area of Northern China

Directory of Open Access Journals (Sweden)

Ying Li

2013-01-01

Full Text Available The concentrations of Hg, Rn, H2, He and CO2 in soil gases at 756 sites were measured in the Tangshan area where Ms 7.8 earthquake occurred in 1976 and is characterized by complex tectonic structures and high seismic hazard. The results showed that, spatial variations of the gaseous anomalies, especially hydrogen and helium have spatial congruence along the tectonic lines, which can be attributed to their deep sources and the migration paths formed by the faults. A better congruence of radon and carbon dioxide is highlighted which indicates that carbon dioxide acts as the carrier gas for radon in this area. Two geochemical anomaly zones of soil gas were found in the area wherein all the studied gases exhibited anomalies or high values, related to the faults and earthquakes.

The role of spatial heterogeneity of the environment in soil fauna recovery after fires

Science.gov (United States)

Gongalsky, K. B.; Zaitsev, A. S.

2016-12-01

Forest fires are almost always heterogeneous, leaving less-disturbed sites that are potentially suitable as habitats for soil-dwelling creatures. The recovery of large soil animal communities after fires is therefore dependent on the spatial structure of the burned habitats. The role of locally less disturbed sites in the survival of soil macrofauna communities along with traditionally considered immigration from the surrounding undisturbed habitats is shown by the example of burnt areas located in three geographically distant regions of European Russia. Such unburned soil cover sites (perfugia) occupy 5-10% of the total burned habitats. Initially, perfugia are characterized by much higher (200-300% of the average across a burned area) diversity and abundance of soil fauna. A geostatistical method made it possible to estimate the perfugia size for soil macrofauna at 3-8 m.

Spatial heterogeneity of soils of the Cerrado-Pantanal ecotone

OpenAIRE

Lucena, Isabela Codolo de; Amorim, Ricardo Santos Silva; Lobo, Francisco de Almeida; Baldoni, Raquel Negrão; Matos, Dalva Maria da Silva

2014-01-01

In areas of the Cerrado-Pantanal ecotone in Brazil, the soil displays features which are inherent to the processes of soil formation, both of the Central Plateau and the Pantanal Plain. Given this premise, the area should be noteworthy for its high level of edaphic heterogeneity. The present study aimed to determine the physical, chemical and physico-hydric attributes that best explain the heterogeneity of soils in areas of the Cerrado-Pantanal ecotone, and to assess whether these attributes ...

Spatial Variability of Tree Transpiration Along a Soil Drainage Gradient of Boreal Black Spruce Forest

Science.gov (United States)

Angstmann, J. L.; Ewers, B. E.; Kwon, H.; Bond-Lamberty, B.; Amiro, B.; Gower, S. T.

2008-12-01

Boreal forests are an integral component in obtaining a predictive understanding of global climate change because they comprise 33% of the world's forests and store large amounts of carbon. Much of this carbon storage is a result of peat formation in cold, poorly-drained soils. Transpiration plays a crucial role in the interaction between carbon and water cycles due to stomatal control of these fluxes. The primary focus of this study is to quantify the spatial variability and drivers of tree transpiration in boreal forest stands across a well- to poorly-drained soil drainage gradient. Species composition of this region of boreal forest changes during succession in well-drained soils from being primarily dominated by Picea mariana with co-dominant Pinus banksiana and Populus tremuloides in younger stands to being dominated solely by Picea marianain older stands. Poorly-drained soils are dominated by Picea mariana and change little with succession. Previous work in well-drained stands showed that 1) tree transpiration changed substantially with stand age due to sapwood-to-leaf area ratio dynamics and 2) minimum leaf water potential (Ψ) was kept constant to prevent excessive cavitation. We hypothesized that 1) minimum Ψ would be constant, 2) transpiration would be proportional to the sapwood-to-leaf area ratio across a soil drainage gradient, and 3) spatial relationships between trees would vary depending on stomatal responses to vapor pressure deficit (D). We tested these hypotheses by measuring Ψ of 33 trees and sap flux from 204 trees utilizing cyclic sampling constructed to study spatial relationships. Measurements were conducted at a 42-year-old stand representing maximum tree diversity during succession. There were no significant differences between growing season averaged Ψ in well- (-0.35 and -1.37 for pre-dawn and mid-day respectively) and poorly- drained soil conditions (-0.38 and -1.41 for pre-dawn and mid-day respectively) for Picea mariana. Water use

Spatial variability of soil magnetic susceptibility in an agricultural field located in Eastern Ukraine

Science.gov (United States)

Menshov, Oleksandr; Pereira, Paulo; Kruglov, Oleksandr

2015-04-01

Magnetic susceptibility (MS) have been used to characterize soil properties. It gives an indirect information about heavy metals content and degree of human impacts on soil contamination derived from atmospheric pollution (Girault et al., 2011). This method is inexpensive in relation to chemical analysis and very useful to track soil pollution, since several toxic components deposited on soil surface are rich in particulates produced by oxidation processes (Boyko et al., 2004; Morton-Bernea et al., 2009). Thus, identify the spatial distribution of MS is of major importance, since can give an indirect information of high metals content (Dankoub et al., 2012). This allows also to distinguish the pedogenic and technogenic origin magnetic signal. For example Ukraine chernozems contain fine-grained oxidized magnetite and maghemite of pedogenic origin formed by weathering of the parent material (Jeleńska et al., 2004). However, to a correct understanding of variables distribution, the identification of the most accurate interpolation method is fundamental for a better interpretation of map information (Pereira et al., 2013). The objective of this work is to study the spatial variability of soil MS in an agricultural fields located in the Tcherkascy Tishki area (50.11°N, 36.43 °E, 162 m a.s.l), Ukraine. Soil MS was measured in 77 sampling points in a north facing slope. To estimate the best interpolation method, several interpolation methods were tested, as inverse distance to a weight (IDW) with the power of 1,2,3,4 and 5, Local Polynomial (LP) with the power of 1 and 2, Global Polynomial (GP), radial basis functions - spline with tension (SPT), completely regularized spline (CRS), multiquatratic (MTQ), inverse multiquatratic (IMTQ), and thin plate spline (TPS) - and some geostatistical methods as, ordinary kriging (OK), Simple Kriging (SK) and Universal Kriging (UK), used in previous works (Pereira et al., 2014). On average, the soil MS of the studied plot had 686

Calibration of a Gamma Spectrometry System Used for the Determination of Cs-137 in Spanish Soils

International Nuclear Information System (INIS)

Barreraa, M.; Romero, M. L.; Valino, F.

2008-01-01

The document describes the methodology used at CIEMAT in order to determine, by gamma spectrometry, the background levels of the radionuclide Cs-137 in soils of the Spanish peninsular territory. the work is a part of an extensive research project developed jointly by the University of the Basque Country (UPV-EHU) and the CIEMAT, endellite Content and migration of radiocaesium and radiostrontium in Spanish soils, which is funded by the Plan I+D of the Spanish Nuclear Security Council (CSN). The objective of the project is to establish the reference levels of man-made radionuclides in Spanish soils, with respect to which the evaluation of a possible posterior accidental release of radioactive material could be appraised. The activity concentration of the fission products Cs-137 has been determined in 34 soil cores extracted from representative Spanish soils type zones. This publication describes the experimental system employed, its calibration, the particular conditions applied to perform the measurements, as well as the experimental validation of the methodology. The activity profiles and inventories of the radioactive element so obtained are also presented. The estimation of the background Cs-137 reference levels, will provide a basis for later applications as the study of the spatial distribution in the region, the determination of the correlation between the deposited activity and the meteorological conditions, or the calculation of the specific migration parameters of the radioactive elements in Mediterranean conditions. (Author) 15 refs

Spatial distribution and sources of heavy metals in natural pasture soil around copper-molybdenum mine in Northeast China.

Science.gov (United States)

Wang, Zhiqiang; Hong, Chen; Xing, Yi; Wang, Kang; Li, Yifei; Feng, Lihui; Ma, Silu

2018-06-15

The characterization of the content and source of heavy metals are essential to assess the potential threat of metals to human health. The present study collected 140 topsoil samples around a Cu-Mo mine (Wunugetushan, China) and investigated the concentrations and spatial distribution pattern of Cr, Ni, Zn, Cu, Mo and Cd in soil using multivariate and geostatistical analytical methods. Results indicated that the average concentrations of six heavy metals, especially Cu and Mo, were obviously higher than the local background values. Correlation analysis and principal component analysis divided these metals into three groups, including Cr and Ni, Cu and Mo, Zn and Cd. Meanwhile, the spatial distribution maps of heavy metals indicated that Cr and Ni in soil were no notable anthropogenic inputs and mainly controlled by natural factors because their spatial maps exhibited non-point source contamination. The concentrations of Cu and Mo gradually decreased with distance away from the mine area, suggesting that human mining activities may be crucial in the spreading of contaminants. Soil contamination of Zn were associated with livestock manure produced from grazing. In addition, the environmental risk of heavy metal pollution was assessed by geo-accumulation index. All the results revealed that the spatial distribution of heavy metals in soil were in agreement with the local human activities. Investigating and identifying the origin of heavy metals in pasture soil will lay the foundation for taking effective measures to preserve soil from the long-term accumulation of heavy metals. Copyright © 2018 Elsevier Inc. All rights reserved.

Spatially Resolved Carbon Isotope and Elemental Analyses of the Root-Rhizosphere-Soil System to Understand Below-ground Nutrient Interactions

Science.gov (United States)

Denis, E. H.; Ilhardt, P.; Tucker, A. E.; Huggett, N. L.; Rosnow, J. J.; Krogstad, E. J.; Moran, J.

2017-12-01

The intimate relationships between plant roots, rhizosphere, and soil are fostered by the release of organic compounds from the plant (through various forms of rhizodeposition) into soil and the simultaneous harvesting and delivery of inorganic nutrients from the soil to the plant. This project's main goal is to better understand the spatial controls on bi-directional nutrient exchange through the rhizosphere and how they impact overall plant health and productivity. Here, we present methods being developed to 1) spatially track the release and migration of plant-derived organics into the rhizosphere and soil and 2) map the local inorganic geochemical microenvironments within and surrounding the rhizosphere. Our studies focused on switchgrass microcosms containing soil from field plots at the Kellogg Biological Station (Hickory Corners, Michigan), which have been cropped with switchgrass for nearly a decade. We used a 13CO2 tracer to label our samples for both one and two diel cycles and tracked subsequent movement of labeled organic carbon using spatially specific δ13C analysis (with 50 µm resolution). The laser ablation-isotope ratio mass spectrometry (LA-IRMS) approach allowed us to map the extent of 13C-label migration into roots, rhizosphere, and surrounding soil. Preliminary results show the expected decrease of organic exudates with distance from a root and that finer roots (<0.1 mm) incorporated more 13C-label than thicker roots, which likely correlates to specific root growth rates. We are adapting both laser induced breakdown spectroscopy (LIBS) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) to spatially map inorganic nutrient content in the exact same samples used for LA-IRMS analysis. Both of these methods provide rapid surface mapping of a wide range of elements (with high dynamic range) at 150 μm spatial resolution. Preliminary results show that, based on elemental content, we can distinguish between roots, rhizosphere

Spatial vulnerability assessments by regression kriging

Science.gov (United States)

Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor

2016-04-01

Two fairly different complex environmental phenomena, causing natural hazard were mapped based on a combined spatial inference approach. The behaviour is related to various environmental factors and the applied approach enables the inclusion of several, spatially exhaustive auxiliary variables that are available for mapping. Inland excess water (IEW) is an interrelated natural and human induced phenomenon causes several problems in the flat-land regions of Hungary, which cover nearly half of the country. The term 'inland excess water' refers to the occurrence of inundations outside the flood levee that originate from sources differing from flood overflow, it is surplus surface water forming due to the lack of runoff, insufficient absorption capability of soil or the upwelling of groundwater. There is a multiplicity of definitions, which indicate the complexity of processes that govern this phenomenon. Most of the definitions have a common part, namely, that inland excess water is temporary water inundation that occurs in flat-lands due to both precipitation and groundwater emerging on the surface as substantial sources. Radon gas is produced in the radioactive decay chain of uranium, which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on soil physical and meteorological parameters and can enter and accumulate in the buildings. Health risk originating from indoor radon concentration attributed to natural factors is characterized by geogenic radon potential (GRP). In addition to geology and meteorology, physical soil properties play significant role in the determination of GRP. Identification of areas with high risk requires spatial modelling, that is mapping of specific natural hazards. In both cases external environmental factors determine the behaviour of the target process (occurrence/frequncy of IEW and grade of GRP respectively). Spatial auxiliary

Using high-resolution soil moisture modelling to assess the uncertainty of microwave remotely sensed soil moisture products at the correct spatial and temporal support

Science.gov (United States)

Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M.

2012-04-01

Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture content throughout the river basin. Space-borne remote sensing may provide this information with a high temporal and spatial resolution and with a global coverage. Currently three microwave soil moisture products are available: AMSR-E, ASCAT and SMOS. The quality of these satellite-based products is often assessed by comparing them with in-situ observations of soil moisture. This comparison is however hampered by the difference in spatial and temporal support (i.e., resolution, scale), because the spatial resolution of microwave satellites is rather low compared to in-situ field measurements. Thus, the aim of this study is to derive a method to assess the uncertainty of microwave satellite soil moisture products at the correct spatial support. To overcome the difference in support size between in-situ soil moisture observations and remote sensed soil moisture, we used a stochastic, distributed unsaturated zone model (SWAP, van Dam (2000)) that is upscaled to the support of different satellite products. A detailed assessment of the SWAP model uncertainty is included to ensure that the uncertainty in satellite soil moisture is not overestimated due to an underestimation of the model uncertainty. We simulated unsaturated water flow up to a depth of 1.5m with a vertical resolution of 1 to 10 cm and on a horizontal grid of 1 km2 for the period Jan 2010 - Jun 2011. The SWAP model was first calibrated and validated on in-situ data of the REMEDHUS soil moisture network (Spain). Next, to evaluate the satellite products, the model was run for areas in the proximity of 79 meteorological stations in Spain, where model results were aggregated to the correct support of the satellite

The spatial distribution of exoenzyme activities across the soil micro-landscape, as measured in micro- and macro-aggregates, and ecosystem processes

DEFF Research Database (Denmark)

Kim, Haryun; Nunan, Naoise; Dechesne, Arnaud

2015-01-01

The spatial ecology of soil microbial communities and their functioning is an understudied aspect of soil microbial ecology. Much of our understanding of the spatial organisation of microbial communities has been obtained at scales that are inappropriate for identifying how microbial functioning ...

[Temporal-spatial distribution of agricultural diffuse nitrogen pollution and relationship with soil respiration and nitrification].

Science.gov (United States)

Wei, Ouyang; Cai, Guan-Qing; Huang, Hao-Bo; Geng, Xiao-Jun

2014-06-01

The soil respiration, nitrification and denitrification processes play an important role on soil nitrogen transformation and diffuse nitrogen loading. These processes are also the chains for soil circle. In this study, the Zhegao watershed located north of Chaohu Lake was selected to explore the interactions of these processes with diffuse nitrogen pollution. The BaPS (Barometric Process Separation) was applied to analyze the soil respiration, nitrification and denitrification processes in farmland and forest. The SWAT (Soil and Water Assessment Tool) simulated the temporal and spatial pattern of diffuse nitrogen loading. As the expanding of farmland and higher level of fertilization, the yearly mean loading of diffuse nitrogen increased sustainably from 1980-1995 to 1996-2012. The monthly loading in 1996-2012 was also higher than that in the period of 1980-1995, which closely related to the precipitation. The statistical analysis indicated that there was a significant difference between two periods. The yearly averaged loading of the whole watershed in 1996-2012 was 10.40 kg x hm(-2), which was 8.10 kg x hm(-2) in 1980-1995. The variance analysis demonstrated that there was also a big difference between the spatial distributions of two periods. The forest soil had much higher soil respiration than the farmland soil. But the farmland had higher nitrification and denitrification rates. The more intensive nitrogen transformation in the farmland contributed to the less diffuse nitrogen loading. As the nitrification rate of farmland was higher than denitrification rate, agricultural diffuse nitrate nitrogen loading would increase and organic nitrogen loading would reduce. The analysis of soil respiration, nitrification and denitrification is helpful for the study of soil nitrogen circle form the aspect of soil biology, which also benefits the control of agricultural diffuse nitrogen pollution.

Spatial estimation of foliar phosphorus in different species of the genus Coffea based on soil properties

Directory of Open Access Journals (Sweden)

Samuel de Assis Silva

2014-10-01

Full Text Available Information underlying analyses of coffee fertilization systems should consider both the soil and the nutritional status of plants. This study investigated the spatial relationship between phosphorus (P levels in coffee plant tissues and soil chemical and physical properties. The study was performed using two arabica and one canephora coffee variety. Sampling grids were established in the areas, and the points georeferenced. The assessed properties of the soil were levels of available phosphorus (P-Mehlich, remaining phosphorus (P-rem and particle size, and of the plant tissue, phosphorus levels (foliar P. The data were subjected to descriptive statistical analysis, correlation analysis, cluster analysis, and probability tests. Geostatistical and trend analyses were only performed for pairs of variables with significant linear correlation. The spatial variability for foliar P content was high for the variety Catuai and medium for the other evaluated plants. Unlike P-Mehlich, the variability in P-rem of the soil indicated the nutritional status of this nutrient in the plant.

Development of an Objective High Spatial Resolution Soil Moisture Index

Science.gov (United States)

Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

2015-12-01

Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective

Windthrow and fallow-forest successions impacts in soil carbon stocks and GHG fluxes spatial variability and dynamics in the Central Russia' reserve spruce ecosystems

Science.gov (United States)

Vasenev, Ivan; Ivanov, Alexey; Komarova, Tatyana; Valentini, Riccardo

2015-04-01

and cover have been accompanied by researches of soil regimes (temperature, moisture, pH, oxidation-reduction potential, microbiological activity) and transformations of representative topsoil materials at the different stages of windthrow soil successions. Since 2012 soil CO2 fluxes have been analyzed every ten days in situ by method of exposition chambers with infra red gas analyzer (Li-Cor 820). At the same periods soil gas fluxes have been sampled from the exposition chambers into vials with the following CH4 and N2O analysis by gas chromatograph. The carried out researches have shown sharp increase of rates of typomorphic soil forming processes within windthrow hole and mound soil successions: (a) lateral input of organic matter in soils of fresh holes - up to 2-3 kg m-2y-1; (b) fulvic acid formation - up to 100-200 g m-2y-1 in soils of young holes and mounds; (c) Al-Fe-humus migration - up to 0.7-1.2 kg cm m-2y-1; (d) humus-accumulated and eluvial horizon development - up to 1-2 mm y-1. The conducted researches have shown high temporal and spatial variability of CO2 fluxes due to soil cover and windthrow complex patterns, windthrow or fallow-forest succession stage and age, air and soil temperature (up to R = 0.64 for taiga, and R = 0.75 for fallow), soil moisture (up to R = -0.65/0.66 both for taiga and fallow) and some other characteristics of the studied objects. Soil CO2 emission is essentially decreased with fallow-forest age. Maximum CO2 fluxes have been observed between 12:00 and 16:00. Within fallow-forest succession the maximum CH4 emission has been fixed in first (grass) stage, and N2O fluxes increase due to temperature rise and moisture decreasing. Usually there is stronger effect on GHG fluxes by air temperature than soil one due to comparatively thin layer of soil organic and/or humus-accumulative subhorizons with maximum biological activity that usually determines the total rate of GHG principal soil fluxes. Unfavorable seasonal climatic conditions

Influence of Surface Roughness Spatial Variability and Temporal Dynamics on the Retrieval of Soil Moisture from SAR Observations

Directory of Open Access Journals (Sweden)

Jesús Álvarez-Mozos

2009-01-01

Full Text Available Radar-based surface soil moisture retrieval has been subject of intense research during the last decades. However, several difficulties hamper the operational estimation of soil moisture based on currently available spaceborne sensors. The main difficulty experienced so far results from the strong influence of other surface characteristics, mainly roughness, on the backscattering coefficient, which hinders the soil moisture inversion. This is especially true for single configuration observations where the solution to the surface backscattering problem is ill-posed. Over agricultural areas cultivated with winter cereal crops, roughness can be assumed to remain constant along the growing cycle allowing the use of simplified approaches that facilitate the estimation of the moisture content of soils. However, the field scale spatial variability and temporal variations of roughness can introduce errors in the estimation of soil moisture that are difficult to evaluate. The objective of this study is to assess the impact of roughness spatial variability and roughness temporal variations on the retrieval of soil moisture from radar observations. A series of laser profilometer measurements were performed over several fields in an experimental watershed from September 2004 to March 2005. The influence of the observed roughness variability and its temporal variations on the retrieval of soil moisture is studied using simulations performed with the Integral Equation Model, considering different sensor configurations. Results show that both field scale roughness spatial variability and its temporal variations are aspects that need to be taken into account, since they can introduce large errors on the retrieved soil moisture values.

Determination of Spatial Chromium Contamination of the Environment around Industrial Zones

Science.gov (United States)

Homa, Dereje; Haile, Ermias

2016-01-01

This study was conducted to determine the spatial levels of chromium contamination of water, agricultural soil, and vegetables in the leather tanning industrial areas using spectrophotometric methods. The results showed elevated accumulation of total Cr ranging from 10.85 ± 0.885 mg/L to 39.696 ± 0.326 mg/L, 16.225 ± 0.12 mg/Kg to 1581.667 ± 0.122 mg/Kg, and 1.0758 ± 0.05348 mg/Kg to 11.75 ± 0.206 mg/Kg in water, agricultural soil, and vegetable samples, respectively. The highest levels of chromium (VI) found from the speciation study were 2.23 ± 0.032 mg/Kg and 0.322 ± 0.07 mg/L in soil and water samples, respectively, which decreased with distance from the tannery. Among the vegetables, the highest load of Cr(VI) was detected in onion root (0.048 ± 0.065 mg/Kg) and the lowest (0.004 ± 0.007 mg/Kg) in fruit of green pepper. The detected levels of Cr in all of the suggested samples were above the WHO permissible limits. The variations of the levels Cr(III) and Cr(VI) contamination of the environment with distance from the tannery were statistically significant (p = 0.05). Similarly, significant difference in the levels of Cr among the tested vegetables was recorded. The levels increased with decreasing distance from the effluent channel. PMID:28044079

Determination of Spatial Chromium Contamination of the Environment around Industrial Zones

Directory of Open Access Journals (Sweden)

Dereje Homa

2016-01-01

Full Text Available This study was conducted to determine the spatial levels of chromium contamination of water, agricultural soil, and vegetables in the leather tanning industrial areas using spectrophotometric methods. The results showed elevated accumulation of total Cr ranging from 10.85±0.885 mg/L to 39.696±0.326 mg/L, 16.225±0.12 mg/Kg to 1581.667±0.122 mg/Kg, and 1.0758±0.05348 mg/Kg to 11.75±0.206 mg/Kg in water, agricultural soil, and vegetable samples, respectively. The highest levels of chromium (VI found from the speciation study were 2.23±0.032 mg/Kg and 0.322±0.07 mg/L in soil and water samples, respectively, which decreased with distance from the tannery. Among the vegetables, the highest load of Cr(VI was detected in onion root (0.048±0.065 mg/Kg and the lowest (0.004±0.007 mg/Kg in fruit of green pepper. The detected levels of Cr in all of the suggested samples were above the WHO permissible limits. The variations of the levels Cr(III and Cr(VI contamination of the environment with distance from the tannery were statistically significant (p=0.05. Similarly, significant difference in the levels of Cr among the tested vegetables was recorded. The levels increased with decreasing distance from the effluent channel.

Determination of Spatial Chromium Contamination of the Environment around Industrial Zones.

Science.gov (United States)

Homa, Dereje; Haile, Ermias; Washe, Alemayehu P

2016-01-01

This study was conducted to determine the spatial levels of chromium contamination of water, agricultural soil, and vegetables in the leather tanning industrial areas using spectrophotometric methods. The results showed elevated accumulation of total Cr ranging from 10.85 ± 0.885 mg/L to 39.696 ± 0.326 mg/L, 16.225 ± 0.12 mg/Kg to 1581.667 ± 0.122 mg/Kg, and 1.0758 ± 0.05348 mg/Kg to 11.75 ± 0.206 mg/Kg in water, agricultural soil, and vegetable samples, respectively. The highest levels of chromium (VI) found from the speciation study were 2.23 ± 0.032 mg/Kg and 0.322 ± 0.07 mg/L in soil and water samples, respectively, which decreased with distance from the tannery. Among the vegetables, the highest load of Cr(VI) was detected in onion root (0.048 ± 0.065 mg/Kg) and the lowest (0.004 ± 0.007 mg/Kg) in fruit of green pepper. The detected levels of Cr in all of the suggested samples were above the WHO permissible limits. The variations of the levels Cr(III) and Cr(VI) contamination of the environment with distance from the tannery were statistically significant ( p = 0.05). Similarly, significant difference in the levels of Cr among the tested vegetables was recorded. The levels increased with decreasing distance from the effluent channel.

Determination of soil-entrapped methane

Energy Technology Data Exchange (ETDEWEB)

Alberto, M.C.R.; Neue, H.U.; Lantin, R.S.; Aduna, J.B. [Soil and Water Sciences Division, Manila (Philippines)

1996-12-31

A sampling method was developed and modified to sample soil from paddy fields for entrapped methane determination. A 25-cm long plexiglass tube (4.4-cm i.d.) fitted with gas bag was used to sample soil and entrapped gases to a depth of 15-cm. The sampling tube was shaken vigorously to release entrapped gases. Headspace gas in sampling tube and gas bag was analyzed for methane. The procedure was verified by doing field sampling weekly at an irrigated ricefield in the IRRI Research Farm on a Maahas clay soil. The modified sampling method gave higher methane concentration because it eliminated gas losses during sampling. The method gave 98% {+-} 5 recovery of soil-entrapped methane. Results of field sampling showed that the early growth stage of the rice plant, entrapped methane increased irrespective of treatment. This suggests that entrapped methane increased irrespective of treatment. This suggests that entrapped methane was primarily derived from fermentation of soil organic matter at the early growth stage. At the latter stage, the rice plant seems to be the major carbon source for methane production. 7 refs., 4 figs., 4 tabs.

Processing and statistical analysis of soil-root images

Science.gov (United States)

Razavi, Bahar S.; Hoang, Duyen; Kuzyakov, Yakov

2016-04-01

Importance of the hotspots such as rhizosphere, the small soil volume that surrounds and is influenced by plant roots, calls for spatially explicit methods to visualize distribution of microbial activities in this active site (Kuzyakov and Blagodatskaya, 2015). Zymography technique has previously been adapted to visualize the spatial dynamics of enzyme activities in rhizosphere (Spohn and Kuzyakov, 2014). Following further developing of soil zymography -to obtain a higher resolution of enzyme activities - we aimed to 1) quantify the images, 2) determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). To this end, we incubated soil-filled rhizoboxes with maize Zea mays L. and without maize (control box) for two weeks. In situ soil zymography was applied to visualize enzymatic activity of β-glucosidase and phosphatase at soil-root interface. Spatial resolution of fluorescent images was improved by direct application of a substrate saturated membrane to the soil-root system. Furthermore, we applied "spatial point pattern analysis" to determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). Our results demonstrated that distribution of hotspots at rhizosphere is clumped (aggregated) compare to control box without plant which showed regular (dispersed) pattern. These patterns were similar in all three replicates and for both enzymes. We conclude that improved zymography is promising in situ technique to identify, analyze, visualize and quantify spatial distribution of enzyme activities in the rhizosphere. Moreover, such different patterns should be considered in assessments and modeling of rhizosphere extension and the corresponding effects on soil properties and functions. Key words: rhizosphere, spatial point pattern, enzyme activity, zymography, maize.

Cacao Crop Management Zones Determination Based on Soil Properties and Crop Yield

Directory of Open Access Journals (Sweden)

Perla Silva Matos de Carvalho

Full Text Available ABSTRACT: The use of management zones has ensured yield success for numerous agricultural crops. In spite of this potential, studies applying precision agricultural techniques to cacao plantations are scarce or almost nonexistent. The aim of the present study was to delineate management zones for cacao crop, create maps combining soil physical properties and cacao tree yield, and identify what combinations best fit within the soil chemical properties. The study was conducted in 2014 on a cacao plantation in a Nitossolo Háplico Eutrófico (Rhodic Paleudult in Bahia, Brazil. Soil samples were collected in a regular sampling grid with 120 sampling points in the 0.00-0.20 m soil layer, and pH(H2O, P, K+, Ca2+, Mg2+, Na+, H+Al, Fe, Zn, Cu, Mn, SB, V, TOC, effective CEC, CEC at pH 7.0, coarse sand, fine sand, clay, and silt were determined. Yield was measured in all the 120 points every month and stratified into annual, harvest, and early-harvest cacao yields. Data were subjected to geostatistical analysis, followed by ordinary kriging interpolation. The management zones were defined through a Fuzzy K-Means algorithm for combinations between soil physical properties and cacao tree yield. Concordance analysis was carried out between the delineated zones and soil chemical properties using Kappa coefficients. The zones that best classified the soil chemical properties were defined from the early-harvest cacao yield map associated with the clay or sand fractions. Silt content proved to be an inadequate variable for defining management zones for cacao production. The delineated management zones described the spatial variability of the soil chemical properties, and are therefore important for site-specific management in the cacao crop.

Elaboration of a framework for the compilation of countrywide, digital maps for the satisfaction of recent demands on spatial, soil related information in Hungary

Science.gov (United States)

Pásztor, László; Dobos, Endre; Szabó, József; Bakacsi, Zsófia; Laborczi, Annamária

2013-04-01

There is a heap of evidences that demands on soil related information have been significant worldwide and it is still increasing. Soil maps were typically used for long time to satisfy these demands. By the spread of GI technology, spatial soil information systems (SSIS) and digital soil mapping (DSM) took the role of traditional soil maps. Due to the relatively high costs of data collection, new conventional soil surveys and inventories are getting less and less frequent, which fact valorises legacy soil information and the systems which are serving the their digitally processed version. The existing data contain a wealth of information that can be exploited by proper methodology. Not only the degree of current needs for soil information has changed but also its nature. Traditionally the agricultural functions of soils were focussed on, which was also reflected in the methodology of data collection and mapping. Recently the multifunctionality of soils is getting to gain more and more ground; consequently information related to additional functions of soils becomes identically important. The new types of information requirements however cannot be fulfilled generally with new data collections at least not on such a level as it was done in the frame of traditional soil surveys. Soil monitoring systems have been established for the collection of recent information on the various elements of the DPSIR (Driving Forces-Pressures-State-Impacts-Responses) framework, but the primary goal of these systems has not been mapping by all means. And definitely this is the case concerning the two recently working Hungarian soil monitoring systems. In Hungary, presently soil data requirements are fulfilled with the recently available datasets either by their direct usage or after certain specific and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable

Spatial heavy metals Zn and Cr distribution in soil samples taken from Tatra Mountains

International Nuclear Information System (INIS)

Stobinski, M.; Misiak, R.; Kubica, B.

2008-03-01

The basic issue of presented report is showing the spatial heavy metals (Zn and Cr) distribution in soil samples taken from High Mts area. The expertise was done using two analytical techniques: AAS (atomic absorption spectroscopy) and micro-PIXIE (proton induced X-ray emission).Given heavy metals concentration were originated either from soil surface (10 cm depth) or from the whole soil profile. Our evaluation indicates that the Zn and Cr levels measured for mountains region were comparable to the data presented by other authors. Furthermore, the amount of heavy metals is strongly correlated with its natural concentration in parental rock.We also observed that zinc was prone to accumulate in surface, rich in organic matter, soil levels. (author)

Simulating maize yield and bomass with spatial variability of soil field capacity

Science.gov (United States)

Ma, Liwang; Ahuja, Lajpat; Trout, Thomas; Nolan, Bernard T.; Malone, Robert W.

2015-01-01

Spatial variability in field soil properties is a challenge for system modelers who use single representative values, such as means, for model inputs, rather than their distributions. In this study, the root zone water quality model (RZWQM2) was first calibrated for 4 yr of maize (Zea mays L.) data at six irrigation levels in northern Colorado and then used to study spatial variability of soil field capacity (FC) estimated in 96 plots on maize yield and biomass. The best results were obtained when the crop parameters were fitted along with FCs, with a root mean squared error (RMSE) of 354 kg ha–1 for yield and 1202 kg ha–1 for biomass. When running the model using each of the 96 sets of field-estimated FC values, instead of calibrating FCs, the average simulated yield and biomass from the 96 runs were close to measured values with a RMSE of 376 kg ha–1 for yield and 1504 kg ha–1 for biomass. When an average of the 96 FC values for each soil layer was used, simulated yield and biomass were also acceptable with a RMSE of 438 kg ha–1 for yield and 1627 kg ha–1 for biomass. Therefore, when there are large numbers of FC measurements, an average value might be sufficient for model inputs. However, when the ranges of FC measurements were known for each soil layer, a sampled distribution of FCs using the Latin hypercube sampling (LHS) might be used for model inputs.

Assessment of spatial distribution of soil loss over the upper basin of Miyun reservoir in China based on RS and GIS techniques.

Science.gov (United States)

Chen, Tao; Niu, Rui-qing; Wang, Yi; Li, Ping-xiang; Zhang, Liang-pei; Du, Bo

2011-08-01

Soil conservation planning often requires estimates of the spatial distribution of soil erosion at a catchment or regional scale. This paper applied the Revised Universal Soil Loss Equation (RUSLE) to investigate the spatial distribution of annual soil loss over the upper basin of Miyun reservoir in China. Among the soil erosion factors, which are rainfall erosivity (R), soil erodibility (K), slope length (L), slope steepness (S), vegetation cover (C), and support practice factor (P), the vegetative cover or C factor, which represents the effects of vegetation canopy and ground covers in reducing soil loss, has been one of the most difficult to estimate over broad geographic areas. In this paper, the C factor was estimated based on back propagation neural network and the results were compared with the values measured in the field. The correlation coefficient (r) obtained was 0.929. Then the C factor and the other factors were used as the input to RUSLE model. By integrating the six factor maps in geographical information system (GIS) through pixel-based computing, the spatial distribution of soil loss over the upper basin of Miyun reservoir was obtained. The results showed that the annual average soil loss for the upper basin of Miyun reservoir was 9.86 t ha(-1) ya(-1) in 2005, and the area of 46.61 km(2) (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.9% very low, 21.89% low, 6.18% moderate, 2.89% severe, and 1.84% very severe. Thus, by using RUSLE in a GIS environment, the spatial distribution of water erosion can be obtained and the regions which susceptible to water erosion and need immediate soil conservation planning and application over the upper watershed of Miyun reservoir in China can be identified.

Simultaneous determination of radium and uranium in soil

International Nuclear Information System (INIS)

Yamamoto, Takashi; Yuki, Eiji; Ishida, Tatsuo

1977-01-01

Radium and uranium contents in soil are the fundamental indexes for natural radioactivity. In this connection, the simultaneous determination of Ra and U has been studied. To a soil sample, 133 Ba is added and the mixture is dried. It is decomposed with sulfuric and nitric acids. Then a Ba-carrier is added, and the insoluble residue (Ra analysis sample) and the solution (U analysis sample) are obtained for simultaneous determination of Ra and U. The rates of recovery of Ra and U in soil are both over 90%. (Mori, K.)

Spatial analysis and hazard assessment on soil total nitrogen in the middle subtropical zone of China

Science.gov (United States)

Lu, Peng; Lin, Wenpeng; Niu, Zheng; Su, Yirong; Wu, Jinshui

2006-10-01

Nitrogen (N) is one of the main factors affecting environmental pollution. In recent years, non-point source pollution and water body eutrophication have become increasing concerns for both scientists and the policy-makers. In order to assess the environmental hazard of soil total N pollution, a typical ecological unit was selected as the experimental site. This paper showed that Box-Cox transformation achieved normality in the data set, and dampened the effect of outliers. The best theoretical model of soil total N was a Gaussian model. Spatial variability of soil total N at NE60° and NE150° directions showed that it had a strip anisotropic structure. The ordinary kriging estimate of soil total N concentration was mapped. The spatial distribution pattern of soil total N in the direction of NE150° displayed a strip-shaped structure. Kriging standard deviations (KSD) provided valuable information that will increase the accuracy of total N mapping. The probability kriging method is useful to assess the hazard of N pollution by providing the conditional probability of N concentration exceeding the threshold value, where we found soil total N>2.0g/kg. The probability distribution of soil total N will be helpful to conduct hazard assessment, optimal fertilization, and develop management practices to control the non-point sources of N pollution.

Modelling the soil microclimate: does the spatial or temporal resolution of input parameters matter?

Directory of Open Access Journals (Sweden)

Anna Carter

2016-01-01

Full Text Available The urgency of predicting future impacts of environmental change on vulnerable populations is advancing the development of spatially explicit habitat models. Continental-scale climate and microclimate layers are now widely available. However, most terrestrial organisms exist within microclimate spaces that are very small, relative to the spatial resolution of those layers. We examined the effects of multi-resolution, multi-extent topographic and climate inputs on the accuracy of hourly soil temperature predictions for a small island generated at a very high spatial resolution (<1 m2 using the mechanistic microclimate model in NicheMapR. Achieving an accuracy comparable to lower-resolution, continental-scale microclimate layers (within about 2–3°C of observed values required the use of daily weather data as well as high resolution topographic layers (elevation, slope, aspect, horizon angles, while inclusion of site-specific soil properties did not markedly improve predictions. Our results suggest that large-extent microclimate layers may not provide accurate estimates of microclimate conditions when the spatial extent of a habitat or other area of interest is similar to or smaller than the spatial resolution of the layers themselves. Thus, effort in sourcing model inputs should be focused on obtaining high resolution terrain data, e.g., via LiDAR or photogrammetry, and local weather information rather than in situ sampling of microclimate characteristics.

Spatial and Temporal Evaluation of Soil Erosion with RUSLE: A case Study in an Olive Orchard Microcathment in Spain

Science.gov (United States)

Soil loss is commonly estimated using the Revised Universal Soil Loss Equation (RUSLE). Since RUSLE is an empirically based soil loss model derived from surveys on plots, the high spatial and temporal variability of erosion in Mediterranean environments and scale effects provo...

Spatial variability of steady-state infiltration into a two-layer soil system on burned hillslopes

Science.gov (United States)

Kinner, D.A.; Moody, J.A.

2010-01-01

Rainfall-runoff simulations were conducted to estimate the characteristics of the steady-state infiltration rate into 1-m2 north- and south-facing hillslope plots burned by a wildfire in October 2003. Soil profiles in the plots consisted of a two-layer system composed of an ash on top of sandy mineral soil. Multiple rainfall rates (18.4-51.2 mm h-1) were used during 14 short-duration (30 min) and 2 long-duration simulations (2-4 h). Steady state was reached in 7-26 min. Observed spatially-averaged steady-state infiltration rates ranged from 18.2 to 23.8 mm h-1 for north-facing and from 17.9 to 36.0 mm h-1 for south-facing plots. Three different theoretical spatial distribution models of steady-state infiltration rate were fit to the measurements of rainfall rate and steady-state discharge to provided estimates of the spatial average (19.2-22.2 mm h-1) and the coefficient of variation (0.11-0.40) of infiltration rates, overland flow contributing area (74-90% of the plot area), and infiltration threshold (19.0-26 mm h-1). Tensiometer measurements indicated a downward moving pressure wave and suggest that infiltration-excess overland flow is the runoff process on these burned hillslope with a two-layer system. Moreover, the results indicate that the ash layer is wettable, may restrict water flow into the underlying layer, and increase the infiltration threshold; whereas, the underlying mineral soil, though coarser, limits the infiltration rate. These results of the spatial variability of steady-state infiltration can be used to develop physically-based rainfall-runoff models for burned areas with a two-layer soil system. ?? 2010 Elsevier B.V.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

Science.gov (United States)

Mishra, U.; Riley, W. J.

2015-07-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained

Development of spatial heterogeneity in vegetation and soil properties after land abandonment in a semi-arid ecosystem

NARCIS (Netherlands)

Lesschen, J.P.; Cammeraat, L.H.; Kooijman, A.M.; van Wesemael, B.

2008-01-01

To mitigate erosion on abandoned fields in semi-arid ecosystems, it is important to understand how vegetation and soil properties and patterns develop after land abandonment. Our objective was to investigate the development of spatial heterogeneity in vegetation and soil properties after land

Climate and soil attributes determine plant species turnover in global drylands.

Science.gov (United States)

Ulrich, Werner; Soliveres, Santiago; Maestre, Fernando T; Gotelli, Nicholas J; Quero, José L; Delgado-Baquerizo, Manuel; Bowker, Matthew A; Eldridge, David J; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R; Hernández, Rosa M; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A; Raveh, Eran; Romão, Roberto L; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2014-12-01

Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake's beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R 2 )), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R 2 )) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate

Climate and soil attributes determine plant species turnover in global drylands

Science.gov (United States)

Maestre, Fernando T.; Gotelli, Nicholas J.; Quero, José L.; Delgado-Baquerizo, Manuel; Bowker, Matthew A.; Eldridge, David J.; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I.; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R.; Hernández, Rosa M.; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L.; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A.; Raveh, Eran; Romão, Roberto L.; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2015-01-01

Aim Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. Location 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Methods Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake’s beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R2)), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Results Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R2)) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Main conclusions Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These

Tree species, spatial heterogeneity, and seasonality drive soil fungal abundance, richness, and composition in Neotropical rainforests.

Science.gov (United States)

Kivlin, Stephanie N; Hawkes, Christine V

2016-12-01

Tropical ecosystems remain poorly understood and this is particularly true for belowground soil fungi. Soil fungi may respond to plant identity when, for example, plants differentially allocate resources belowground. However, spatial and temporal heterogeneity in factors such as plant inputs, moisture, or nutrients can also affect fungal communities and obscure our ability to detect plant effects in single time point studies or within diverse forests. To address this, we sampled replicated monocultures of four tree species and secondary forest controls sampled in the drier and wetter seasons over 2 years. Fungal community composition was primarily related to vegetation type and spatial heterogeneity in the effects of vegetation type, with increasing divergence partly reflecting greater differences in soil pH and soil moisture. Across wetter versus drier dates, fungi were 7% less diverse, but up to four-fold more abundant. The combined effects of tree species and seasonality suggest that predicted losses of tropical tree diversity and intensification of drought have the potential to cascade belowground to affect both diversity and abundance of tropical soil fungi. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Using a spatial and tabular database to generate statistics from terrain and spectral data for soil surveys

Science.gov (United States)

Horvath , E.A.; Fosnight, E.A.; Klingebiel, A.A.; Moore, D.G.; Stone, J.E.; Reybold, W.U.; Petersen, G.W.

1987-01-01

A methodology has been developed to create a spatial database by referencing digital elevation, Landsat multispectral scanner data, and digitized soil premap delineations of a number of adjacent 7.5-min quadrangle areas to a 30-m Universal Transverse Mercator projection. Slope and aspect transformations are calculated from elevation data and grouped according to field office specifications. An unsupervised classification is performed on a brightness and greenness transformation of the spectral data. The resulting spectral, slope, and aspect maps of each of the 7.5-min quadrangle areas are then plotted and submitted to the field office to be incorporated into the soil premapping stages of a soil survey. A tabular database is created from spatial data by generating descriptive statistics for each data layer within each soil premap delineation. The tabular data base is then entered into a data base management system to be accessed by the field office personnel during the soil survey and to be used for subsequent resource management decisions.Large amounts of data are collected and archived during resource inventories for public land management. Often these data are stored as stacks of maps or folders in a file system in someone's office, with the maps in a variety of formats, scales, and with various standards of accuracy depending on their purpose. This system of information storage and retrieval is cumbersome at best when several categories of information are needed simultaneously for analysis or as input to resource management models. Computers now provide the resource scientist with the opportunity to design increasingly complex models that require even more categories of resource-related information, thus compounding the problem.Recently there has been much emphasis on the use of geographic information systems (GIS) as an alternative method for map data archives and as a resource management tool. Considerable effort has been devoted to the generation of tabular

Spatial variation in soil active-layer geochemistry across hydrologic margins in polar desert ecosystems

Directory of Open Access Journals (Sweden)

J. E. Barrett

2009-12-01

Full Text Available Polar deserts are characterized by severe spatial-temporal limitations of liquid water. In soil active layers of the Antarctic Dry Valleys, liquid water is infrequently available over most of the arid terrestrial landscape. However, soils on the margins of glacial melt-water streams and lakes are visibly wet during the brief Austral summer when temperatures permit the existence of liquid water. We examined the role of these hydrologic margins as preferential zones for the transformation and transport of nutrient elements and solutes in an environment where geochemical weathering and biological activity is strictly limited by the dearth of liquid water. We report on hydropedological investigations of aquatic-terrestrial transition zones adjacent to 11 stream and lake systems in the Antarctic Dry Valleys. Our results show that wetted zones extended 1–11 m from the edges of lotic and lentic systems. While capillary demand and surface evaporation drive a one-way flux of water through these zones, the scale of these transition zones is determined by the topography and physical characteristics of the surrounding soils. Nutrient concentrations and fluxes appear to be influenced by both the hydrology and microbial-mediated biogeochemical processes. Salt concentrations are enriched near the distal boundary of the wetted fronts due to evapo-concentration of pore water in lake margin soils, while organic matter, ammonium and phosphate concentrations are highest in stream channel sediments where potential for biological activity is greatest. Thus, in the Antarctic Dry Valleys, intermittently wet soils on the margins of streams and lakes are important zones of both geochemical cycling and biological activity.

Topographic Controls on Spatial Patterns of Soil Texture and Moisture in a Semi-arid Montane Catchment with Aspect-Dependent Vegetation

Science.gov (United States)

Lehman, B. M.; Niemann, J. D.

2008-12-01

Soil moisture exerts significant control over the partitioning of latent and sensible energy fluxes, the magnitude of both vertical and lateral water fluxes, the physiological and water-use characteristics of vegetation, and nutrient cycling. Considerable progress has been made in determining how soil characteristics, topography, and vegetation influence spatial patterns of soil moisture in humid environments at the catchment, hillslope, and plant scales. However, understanding of the controls on soil moisture patterns beyond the plant scale in semi-arid environments remains more limited. This study examines the relationships between the spatial patterns of near surface soil moisture (upper 5 cm), terrain indices, and soil properties in a small, semi-arid, montane catchment. The 8 ha catchment, located in the Cache La Poudre River Canyon in north-central Colorado, has a total relief of 115 m and an average elevation of 2193 m. It is characterized by steep slopes and shallow, gravelly/sandy soils with scattered granite outcroppings. Depth to bedrock ranges from 0 m to greater than 1 m. Vegetation in the catchment is highly correlated with topographic aspect. In particular, north-facing hillslopes are predominately vegetated by ponderosa pines, while south-facing slopes are mostly vegetated by several shrub species. Soil samples were collected at a 30 m resolution to characterize soil texture and bulk density, and several datasets consisting of more than 300 point measurements of soil moisture were collected using time domain reflectometry (TDR) between Fall 2007 and Summer 2008 at a 15 m resolution. Results from soil textural analysis performed with sieving and the ASTM standard hydrometer method show that soil texture is finer on the north-facing hillslope than on the south-facing hillslope. Cos(aspect) is the best univariate predictor of silts, while slope is the best predictor of coarser fractions up to fine gravel. Bulk density increases with depth but shows no

The effects of spatial variability of the aggressiveness of soil on system reliability of corroding underground pipelines

International Nuclear Information System (INIS)

Sahraoui, Yacine; Chateauneuf, Alaa

2016-01-01

In this paper, a probabilistic methodology is presented for assessing the time-variant reliability of corroded underground pipelines subjected to space-variant soil aggressiveness. The Karhunen-Loève expansion is used to model the spatial variability of soil as a correlated stochastic field. The pipeline is considered as a series system for which the component and system failure probabilities are computed by Monte Carlo simulations. The probabilistic model provides a realistic time and space modelling of stochastic variations, leading to appropriate estimation of the lifetime distribution. The numerical analyses allow us to investigate the impact of various parameters on the reliability of underground pipelines, such as the soil aggressiveness, the pipe design variables, the soil correlation length and the pipeline length. The results show that neglecting the effect of spatial variability leads to pessimistic estimation of the residual lifetime and can lead to condemn prematurely the structure. - Highlights: • The role of soil heterogeneity in pipeline reliability assessment has been shown. • The impact of pipe length and soil correlation length has been examined. • The effect of the uncertainties related to design variables has been observed. • Pipe thickness design for homogeneous reliability has been proposed.

Multi-element determination of soil solution by INAA

International Nuclear Information System (INIS)

Qian Qinfang; Wu Shuiqing; Tian Jibing

1992-01-01

One of the factors influencing crop growth is the effective elemental contents, especially trace elements, under the circumstances of the same concentrations of N, P and K in soil. In order to obtain the data of effective elemental contents in soil, a novel method was introduced. In this method, soil solution was extracted by a squeezer. The concentrations of elements in soil solution were determined by INAA. Study on the compositions and the contents of elements in soil solution will provide information on making a suitable soil environment for plant growth and on rational and economical manuring

A global map of mangrove forest soil carbon at 30 m spatial resolution

Science.gov (United States)

Sanderman, Jonathan; Hengl, Tomislav; Fiske, Greg; Solvik, Kylen; Adame, Maria Fernanda; Benson, Lisa; Bukoski, Jacob J.; Carnell, Paul; Cifuentes-Jara, Miguel; Donato, Daniel; Duncan, Clare; Eid, Ebrahem M.; Ermgassen, Philine zu; Ewers Lewis, Carolyn J.; Macreadie, Peter I.; Glass, Leah; Gress, Selena; Jardine, Sunny L.; Jones, Trevor G.; Ndemem Nsombo, Eugéne; Mizanur Rahman, Md; Sanders, Christian J.; Spalding, Mark; Landis, Emily

2018-05-01

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m‑3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha‑1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.

Impact of spatial organization on a novel auxotrophic interaction among soil microbes.

Science.gov (United States)

Jiang, Xue; Zerfaß, Christian; Feng, Song; Eichmann, Ruth; Asally, Munehiro; Schäfer, Patrick; Soyer, Orkun S

2018-06-01

A key prerequisite to achieve a deeper understanding of microbial communities and to engineer synthetic ones is to identify the individual metabolic interactions among key species and how these interactions are affected by different environmental factors. Deciphering the physiological basis of species-species and species-environment interactions in spatially organized environments requires reductionist approaches using ecologically and functionally relevant species. To this end, we focus here on a defined system to study the metabolic interactions in a spatial context among the plant-beneficial endophytic fungus Serendipita indica, and the soil-dwelling model bacterium Bacillus subtilis. Focusing on the growth dynamics of S. indica under defined conditions, we identified an auxotrophy in this organism for thiamine, which is a key co-factor for essential reactions in the central carbon metabolism. We found that S. indica growth is restored in thiamine-free media, when co-cultured with B. subtilis. The success of this auxotrophic interaction, however, was dependent on the spatial and temporal organization of the system; the beneficial impact of B. subtilis was only visible when its inoculation was separated from that of S. indica either in time or space. These findings describe a key auxotrophic interaction in the soil among organisms that are shown to be important for plant ecosystem functioning, and point to the potential importance of spatial and temporal organization for the success of auxotrophic interactions. These points can be particularly important for engineering of minimal functional synthetic communities as plant seed treatments and for vertical farming under defined conditions.

Modelling shallow landslide susceptibility by means of a subsurface flow path connectivity index and estimates of soil depth spatial distribution

Directory of Open Access Journals (Sweden)

C. Lanni

2012-11-01

Full Text Available Topographic index-based hydrological models have gained wide use to describe the hydrological control on the triggering of rainfall-induced shallow landslides at the catchment scale. A common assumption in these models is that a spatially continuous water table occurs simultaneously across the catchment. However, during a rainfall event isolated patches of subsurface saturation form above an impeding layer and their hydrological connectivity is a necessary condition for lateral flow initiation at a point on the hillslope.

Here, a new hydrological model is presented, which allows us to account for the concept of hydrological connectivity while keeping the simplicity of the topographic index approach. A dynamic topographic index is used to describe the transient lateral flow that is established at a hillslope element when the rainfall amount exceeds a threshold value allowing for (a development of a perched water table above an impeding layer, and (b hydrological connectivity between the hillslope element and its own upslope contributing area. A spatially variable soil depth is the main control of hydrological connectivity in the model. The hydrological model is coupled with the infinite slope stability model and with a scaling model for the rainfall frequency–duration relationship to determine the return period of the critical rainfall needed to cause instability on three catchments located in the Italian Alps, where a survey of soil depth spatial distribution is available. The model is compared with a quasi-dynamic model in which the dynamic nature of the hydrological connectivity is neglected. The results show a better performance of the new model in predicting observed shallow landslides, implying that soil depth spatial variability and connectivity bear a significant control on shallow landsliding.

Soil pH Errors Propagation from Measurements to Spatial Predictions - Cost Benefit Analysis and Risk Assessment Implications for Practitioners and Modelers

Science.gov (United States)

Owens, P. R.; Libohova, Z.; Seybold, C. A.; Wills, S. A.; Peaslee, S.; Beaudette, D.; Lindbo, D. L.

2017-12-01

The measurement errors and spatial prediction uncertainties of soil properties in the modeling community are usually assessed against measured values when available. However, of equal importance is the assessment of errors and uncertainty impacts on cost benefit analysis and risk assessments. Soil pH was selected as one of the most commonly measured soil properties used for liming recommendations. The objective of this study was to assess the error size from different sources and their implications with respect to management decisions. Error sources include measurement methods, laboratory sources, pedotransfer functions, database transections, spatial aggregations, etc. Several databases of measured and predicted soil pH were used for this study including the United States National Cooperative Soil Survey Characterization Database (NCSS-SCDB), the US Soil Survey Geographic (SSURGO) Database. The distribution of errors among different sources from measurement methods to spatial aggregation showed a wide range of values. The greatest RMSE of 0.79 pH units was from spatial aggregation (SSURGO vs Kriging), while the measurement methods had the lowest RMSE of 0.06 pH units. Assuming the order of data acquisition based on the transaction distance i.e. from measurement method to spatial aggregation the RMSE increased from 0.06 to 0.8 pH units suggesting an "error propagation". This has major implications for practitioners and modeling community. Most soil liming rate recommendations are based on 0.1 pH unit increments, while the desired soil pH level increments are based on 0.4 to 0.5 pH units. Thus, even when the measured and desired target soil pH are the same most guidelines recommend 1 ton ha-1 lime, which translates in 111 ha-1 that the farmer has to factor in the cost-benefit analysis. However, this analysis need to be based on uncertainty predictions (0.5-1.0 pH units) rather than measurement errors (0.1 pH units) which would translate in 555-1,111 investment that

[Three-dimension temporal and spatial dynamics of soil water for the artificial vegetation in the center of Taklimakan desert under saline water drip-irrigation].

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Ding, Xin-yuan; Zhou, Zhi-bin; Xu, Xin-wen; Lei, Jia-qiang; Lu, Jing-jing; Ma, Xue-xi; Feng, Xiao

2015-09-01

Three-dimension temporal and spatial dynamics of the soil water characteristics during four irrigating cycles of months from April to July for the artificial vegetation in the center of Taklimakan Desert under saline water drip-irrigation had been analyzed by timely measuring the soil water content in horizontal and vertical distances 60 cm and 120 cm away from the irrigating drips, respectively. Periodic spatial and temporal variations of soil water content were observed. When the precipitation effect was not considered, there were no significant differences in the characteristics of soil water among the irrigation intervals in different months, while discrepancies were obvious in the temporal and spatial changes of soil moisture content under the conditions of rainfall and non-rainfall. When it referred to the temporal changes of soil water, it was a little higher in April but a bit lower in July, and the soil water content in June was the highest among four months because some remarkable events of precipitation happened in this month. However, as a whole, the content of soil moisture was reduced as months (from April to July) went on and it took a decreasing tendency along with days (1-15 d) following a power function. Meanwhile, the characteristics of soil water content displayed three changeable stages in an irrigation interval. When it referred to the spatial distributions of soil water, the average content of soil moisture was reduced along with the horizontal distance following a linear regression function, and varied with double peaks along with the vertical distance. In addition, the spatial distribution characteristics of the soil water were not influenced by the factors of precipitation and irrigating time but the physical properties of soil.

Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra - coupling field observations with remote sensing data

Science.gov (United States)

Mikola, Juha; Virtanen, Tarmo; Linkosalmi, Maiju; Vähä, Emmi; Nyman, Johanna; Postanogova, Olga; Räsänen, Aleksi; Kotze, D. Johan; Laurila, Tuomas; Juutinen, Sari; Kondratyev, Vladimir; Aurela, Mika

2018-05-01

Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm-3 in bare soil and lichen tundra and 89 g dm-3 in other LCTs. Total moss biomass varied from 0 to 820 g m-2, total vascular shoot mass from 7 to 112 g m-2 and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 °C in bare soil and lichen tundra, and varied from 5 to 9 °C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14-34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6-15 % of variation. NDVI

GEOMORPHIC AND HYDROLOGIC INTERACTIONS IN THE DETERMINATION OF EQUILIBRIUM SOIL DEPTH

Science.gov (United States)

Nicotina, L.; Rinaldo, A.; Tarboton, D. G.

2009-12-01

In this work we propose numerical studies of the interactions between hydrology and geomorphology in the formation of the actual soil depth that drives ecologic and hydrologic processes. Sediment transport and geomorphic landscape evolution processes (i.e. erosion/deposition vs. soil production) strongly influence hydrology, carbon sequestration, soil formation and stream water chemistry. The process of rock conversion into soil originates a strong hydrologic control through the formation of the soil depth that participates to hydrologic processes, influence vegetation type and patterns and actively participate in the co-evolution mechanisms that shape the landscape. The description of spatial patterns in hydrology is usually constrained by the availability of field data, especially when dealing with quantities that are not easily measurable. In these circumstances it is deemed fundamental the capability of deriving hydrologic boundary conditions from physically based approaches. Here we aim, in a general framework, at the formulation of an integrated approach for the prediction of soil depth by mean of i) soil production models and ii) geomorphic transport laws. The processes that take place in the critical zone are driven by the extension of it and have foundamental importance over short time scales as well as on geologic time scales (i.e. as biota affects climate that drives hydrology and thus contributes on shaping the landscape). Our study aims at the investigation of the relationships between soil depth, topography and runoff production, we also address the mechanisms that bring to the development of actual patterns of soil depths which at the same time influence runoff. We use a schematic representation of the hydrologic processes that relies on the description of the topography (throuh a topographic wetness index) and the spatially variable soil depths. Such a model is applied in order to investigate the development of equilibrium soil depth patterns under

Comparison of Chemical Extraction Methods for Determination of Soil Potassium in Different Soil Types

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Zebec, V.; Rastija, D.; Lončarić, Z.; Bensa, A.; Popović, B.; Ivezić, V.

2017-12-01

Determining potassium supply of soil plays an important role in intensive crop production, since it is the basis for balancing nutrients and issuing fertilizer recommendations for achieving high and stable yields within economic feasibility. The aim of this study was to compare the different extraction methods of soil potassium from arable horizon of different types of soils with ammonium lactate method (KAL), which is frequently used as analytical method for determining the accessibility of nutrients and it is a common method used for issuing fertilizer recommendations in many Europe countries. In addition to the ammonium lactate method (KAL, pH 3.75), potassium was extracted with ammonium acetate (KAA, pH 7), ammonium acetate ethylenediaminetetraacetic acid (KAAEDTA, pH 4.6), Bray (KBRAY, pH 2.6) and with barium chloride (K_{BaCl_2 }, pH 8.1). The analyzed soils were extremely heterogeneous with a wide range of determined values. Soil pH reaction ( {pH_{H_2 O} } ) ranged from 4.77 to 8.75, organic matter content ranged from 1.87 to 4.94% and clay content from 8.03 to 37.07%. In relation to KAL method as the standard method, K_{BaCl_2 } method extracts 12.9% more on average of soil potassium, while in relation to standard method, on average KAA extracts 5.3%, KAAEDTA 10.3%, and KBRAY 27.5% less of potassium. Comparison of analyzed extraction methods of potassium from the soil is of high precision, and most reliable comparison was KAL method with KAAEDTA, followed by a: KAA, K_{BaCl_2 } and KBRAY method. Extremely significant statistical correlation between different extractive methods for determining potassium in the soil indicates that any of the methods can be used to accurately predict the concentration of potassium in the soil, and that carried out research can be used to create prediction model for concentration of potassium based on different methods of extraction.

The Determinants of VAT Introduction : A Spatial Duration Analysis

NARCIS (Netherlands)

Cizek, P.; Lei, J.; Ligthart, J.E.

2012-01-01

Abstract: The spatial survival models typically impose frailties, which characterize unobserved heterogeneity, to be spatially correlated. This specification relies highly on a pre-determinate covariance structure of the errors. However, the spatial effect may not only exist in the unobserved

Application of spatial time domain reflectometry measurements in heterogeneous, rocky substrates

Science.gov (United States)

Gonzales, C.; Scheuermann, A.; Arnold, S.; Baumgartl, T.

2016-10-01

Measurement of soil moisture across depths using sensors is currently limited to point measurements or remote sensing technologies. Point measurements have limitations on spatial resolution, while the latter, although covering large areas may not represent real-time hydrologic processes, especially near the surface. The objective of the study was to determine the efficacy of elongated soil moisture probes—spatial time domain reflectometry (STDR)—and to describe transient soil moisture dynamics of unconsolidated mine waste rock materials. The probes were calibrated under controlled conditions in the glasshouse. Transient soil moisture content was measured using the gravimetric method and STDR. Volumetric soil moisture content derived from weighing was compared with values generated from a numerical model simulating the drying process. A calibration function was generated and applied to STDR field data sets. The use of elongated probes effectively assists in the real-time determination of the spatial distribution of soil moisture. It also allows hydrologic processes to be uncovered in the unsaturated zone, especially for water balance calculations that are commonly based on point measurements. The elongated soil moisture probes can potentially describe transient substrate processes and delineate heterogeneity in terms of the pore size distribution in a seasonally wet but otherwise arid environment.

Uncertainty in soil physical data at river basin scale – a review

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P. van der Keur

2006-01-01

Full Text Available For hydrological modelling studies at the river basin scale, decision makers need guidance in assessing the implications of uncertain data used by modellers as an input to modelling tools. Simulated solute transport through the unsaturated zone is associated with uncertainty due to spatial variability of soil hydraulic properties and derived hydraulic model parameters. In general for modelling studies at the river basin scale spatially available data at various scales must be aggregated to an appropriate scale. Estimating soil properties at unsampled points by means of geostatistical techniques require reliable information on the spatial structure of soil data. In this paper this information is assessed by reviewing current developments in the field of soil physical data uncertainty and adopting a classification system. Then spatial variability and structure is inspected by reviewing experimental work on determining spatial length scales for soil physical (and soil chemical data. Available literature on spatial length scales for soil physical- and chemical properties is reviewed and their use in facilitating change of spatial support discussed. Uncertainty associated to the derivation of hydraulic properties from soil physical properties in this context is also discussed.

Spatial Variations of Soil Gas Geochemistry in the Tangshan Area of Northern China

OpenAIRE

Ying Li; Jianguo Du; Xin Wang; Xiaocheng Zhou; Chao Xie; Yueju Cui

2013-01-01

The concentrations of Hg, Rn, H2, He and CO2 in soil gases at 756 sites were measured in the Tangshan area where Ms 7.8 earthquake occurred in 1976 and is characterized by complex tectonic structures and high seismic hazard. The results showed that, spatial variations of the gaseous anomalies, especially hydrogen and helium have spatial congruence along the tectonic lines, which can be attributed to their deep sources and the migration paths formed by the faults. A better congruence of radon ...

GlobalSoilMap France: High-resolution spatial modelling the soils of France up to two meter depth.

Science.gov (United States)

Mulder, V L; Lacoste, M; Richer-de-Forges, A C; Arrouays, D

2016-12-15

This work presents the first GlobalSoilMap (GSM) products for France. We developed an automatic procedure for mapping the primary soil properties (clay, silt, sand, coarse elements, pH, soil organic carbon (SOC), cation exchange capacity (CEC) and soil depth). The procedure employed a data-mining technique and a straightforward method for estimating the 90% confidence intervals (CIs). The most accurate models were obtained for pH, sand and silt. Next, CEC, clay and SOC were found reasonably accurate predicted. Coarse elements and soil depth were the least accurate of all models. Overall, all models were considered robust; important indicators for this were 1) the small difference in model diagnostics between the calibration and cross-validation set, 2) the unbiased mean predictions, 3) the smaller spatial structure of the prediction residuals in comparison to the observations and 4) the similar performance compared to other developed GlobalSoilMap products. Nevertheless, the confidence intervals (CIs) were rather wide for all soil properties. The median predictions became less reliable with increasing depth, as indicated by the increase of CIs with depth. In addition, model accuracy and the corresponding CIs varied depending on the soil variable of interest, soil depth and geographic location. These findings indicated that the CIs are as informative as the model diagnostics. In conclusion, the presented method resulted in reasonably accurate predictions for the majority of the soil properties. End users can employ the products for different purposes, as was demonstrated with some practical examples. The mapping routine is flexible for cloud-computing and provides ample opportunity to be further developed when desired by its users. This allows regional and international GSM partners with fewer resources to develop their own products or, otherwise, to improve the current routine and work together towards a robust high-resolution digital soil map of the world

Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind

Directory of Open Access Journals (Sweden)

M. Liu

2012-02-01

Full Text Available In this paper, simulations with the Soil Water Atmosphere Plant (SWAP model are performed to quantify the spatial variability of both potential and actual evapotranspiration (ET, and soil moisture content (SMC caused by topography-induced spatial wind and radiation differences. To obtain the spatially distributed ET/SMC patterns, the field scale SWAP model is applied in a distributed way for both pointwise and catchment wide simulations. An adapted radiation model from r.sun and the physically-based meso-scale wind model METRAS PC are applied to obtain the spatial radiation and wind patterns respectively, which show significant spatial variation and correlation with aspect and elevation respectively. Such topographic dependences and spatial variations further propagate to ET/SMC. A strong spatial, seasonal-dependent, scale-relevant intra-catchment variability in daily/annual ET and less variability in SMC can be observed from the numerical experiments. The study concludes that topography has a significant effect on ET/SMC in the humid region where ET is a energy limited rather than water availability limited process. It affects the spatial runoff generation through spatial radiation and wind, therefore should be applied to inform hydrological model development. In addition, the methodology used in the study can serve as a general method for physically-based ET estimation for data sparse regions.

Comparison of different interpolation methods for spatial distribution of soil organic carbon and some soil properties in the Black Sea backward region of Turkey

Science.gov (United States)

Göl, Ceyhun; Bulut, Sinan; Bolat, Ferhat

2017-10-01

The purpose of this research is to compare the spatial variability of soil organic carbon (SOC) in four adjacent land uses including the cultivated area, the grassland area, the plantation area and the natural forest area in the semi - arid region of Black Sea backward region of Turkey. Some of the soil properties, including total nitrogen, SOC, soil organic matter, and bulk density were measured on a grid with a 50 m sampling distance on the top soil (0-15 cm depth). Accordingly, a total of 120 samples were taken from the four adjacent land uses. Data was analyzed using geostatistical methods. The methods used were: Block kriging (BK), co - kriging (CK) with organic matter, total nitrogen and bulk density as auxiliary variables and inverse distance weighting (IDW) methods with the power of 1, 2 and 4. The methods were compared using a performance criteria that included root mean square error (RMSE), mean absolute error (MAE) and the coefficient of correlation (r). The one - way ANOVA test showed that differences between the natural (0.6653 ± 0.2901) - plantation forest (0.7109 ± 0.2729) areas and the grassland (1.3964 ± 0.6828) - cultivated areas (1.5851 ± 0.5541) were statistically significant at 0.05 level (F = 28.462). The best model for describing spatially variation of SOC was CK with the lowest error criteria (RMSE = 0.3342, MAE = 0.2292) and the highest coefficient of correlation (r = 0.84). The spatial structure of SOC could be well described by the spherical model. The nugget effect indicated that SOC was moderately dependent on the study area. The error distributions of the model showed that the improved model was unbiased in predicting the spatial distribution of SOC. This study's results revealed that an explanatory variable linked SOC increased success of spatial interpolation methods. In subsequent studies, this case should be taken into account for reaching more accurate outputs.

Spatial Distribution of Heavy Metals and the Environmental Quality of Soil in the Northern Plateau of Spain by Geostatistical Methods.

Science.gov (United States)

Santos-Francés, Fernando; Martínez-Graña, Antonio; Zarza, Carmelo Ávila; Sánchez, Antonio García; Rojo, Pilar Alonso

2017-05-26

The environmental quality of soil in the central part of the Northern Plateau of Spain has been analyzed by studying the heavy metal content of 166 samples belonging to the horizons A, B and C of 89 soil profiles. The analysis to assess the environmental risk of heavy metals in the soil was carried out by means of the spatial distribution of nine heavy metals and the use of several pollution indices. The results showed that the concentration values of heavy metals (x ± S) in the superficial soil horizons were the following: With a total of 6.71 ± 3.51 mg kg -1, the contents of Cd is 0.08 ± 0.06 mg kg-1, Co is 6.49 ± 3.21 mg kg-1, Cu is 17.19 ± 10.69 mg kg-1, Cr is 18.68 ± 12.28 mg kg-1, Hg is 0.083 ± 0.063 mg kg-1, Ni is 12.05 ± 6.76 mg kg-1, Pb is 14.10 ± 11.32 mg kg-1 and Zn is 35.31 ± 14.63 mg kg-1. These nine metals exceed the values of the natural geological background level of Tertiary period sediments and rocks that form part of the Northern Plateau in Spain. Nemerow and Potential Ecological Risk indices were calculated, with the "improved" Nemerow index allowing pollution within the soil superficial horizons to be determined. The data obtained indicated that the majority of the soil (54.61%) showed low to moderate contamination, 22.31% showed moderate contamination and 21.54% of the samples were not contaminated. If we consider the Potential of Ecological Risk Index (RI), the largest percentage of soil samples showed low (70.79%) to moderate (25.38%) ecological risk of potential contamination, where the rest of the soil presented a considerable risk of contamination. The nine trace elements were divided into three principal components: PC1 (Cu, Cr, Ni, Co and Zn), PC2 (As and Hg) and PC3 (Cd). All metals accumulated in the soil came from parent rock, agricultural practices and the run-off of residual waters towards rivers and streams caused by industrial development and an increase in population density. Finally, cartography of the spatial

Soil bacteria and fungi respond on different spatial scales to invasion by the legume Lespedeza cuneata

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Anthony C Yannarell

2011-06-01

Full Text Available The spatial scale on which microbial communities respond to plant invasions may provide important clues as to the nature of potential invader-microbe interactions. Lespedeza cuneata (Dum. Cours. G. Don is an invasive legume that may benefit from associations with mycorrhizal fungi; however, it has also been suggested that the plant is allelopathetic and may alter the soil chemistry of invaded sites through secondary metabolites in its root exudates or litter. Thus, L. cuneata invasion may interact with soil microorganisms on a variety of scales. We investigated L. cuneata-related changes to soil bacterial and fungal communities at two spatial scales using multiple sites from across its invaded N. American range. Using whole community DNA fingerprinting, we characterized microbial community variation at the scale of entire invaded sites and at the scale of individual plants. Based on permutational multivariate analysis of variance, soil bacterial communities in heavily invaded sites were significantly different from those of uninvaded sites, but bacteria did not show any evidence of responding at very local scales around individual plants. In contrast, soil fungi did not change significantly at the scale of entire sites, but there were significant differences between fungal communities of native versus exotic plants within particular sites. The differential scaling of bacterial and fungal responses indicates that L. cuneata interacts differently with soil bacteria and soil fungi, and these microorganisms may play very different roles in the invasion process of this plant.

Cadmium Accumulation in Small Mammals: Species Traits, Soil Properties, and Spatial Habitat Use

NARCIS (Netherlands)

Brink, van den N.W.; Lammertsma, D.R.; Dimmers, W.J.; Boerwinkel, M.C.

2011-01-01

In this study, the impact of species-specific spatial habitat use, diet preferences, and soil concentrations and properties on the accumulation of cadmium in small mammals was investigated. The results show that for the wood mouse (Apodemus sylvaticus), a mobile species with a large range in diet

Spatial Pattern Determination of Biodiversity Threats at Landscape Level (Case Study: Golestan Province

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R. Mirzaei

2015-06-01

Full Text Available Mapping spatial patterns of potential biodiversity threats is one of the important steps for effective conservation planning and activities. To determine the spatial patterns of threats in Golestan province, 12 criteria in four main groups including structural (fractal coefficient of perimeter, circularity ratio of area, average slope, compositional aspects of biodiversity (presence of species at risk, non-biological threats (distance to city, distance to village, distance to road, distance to infrastructure, distance to agricultural land, soil pollution, risk of fire and isolation (Nearest Neighbor Index were used. These data layers were digitized in GIS environment and were weighted through Analytical Hierarchy Process. A weighted linear combination was then used to map the spatial pattern of biodiversity threats in the province. Compositional aspect (0.59, non-biological threats (0.23, isolation (0.11, and structural aspect (0.07 were relatively weighted in the order of importance. Central parts of the province and patches in the northern and southern parts were recognized to be more exposed to biodiversity threats. The central parts of the province were mostly threatened by urban, industrial, road and agricultural development, whereas the northern and southern parts were recognized as areas of conservation importance having a variety of threatened birds.

Using scaling factors for evaluating spatial and temporal variability of soil hydraulic properties within one elevation transect

Science.gov (United States)

Nikodem, Antonín; Kodešová, Radka; Jakšík, Ondřej; Fér, Miroslav; Klement, Aleš

2016-04-01

This study was carried out in Southern Moravia, in the Czech Republic. The original soil unit in the wider area is a Haplic Chernozem developed on loess. The intensive agricultural exploitation in combination with terrain morphology has resulted in a highly diversified soil spatial pattern. Nowadays the original soil unit is preserved only on top of relatively flat parts, and is gradually transformed by water erosion up to Regosols on the steepest slopes, while colluvial soils are formed in terrain depressions and at toe slopes due to sedimentation of previously eroded material. Soils within this area has been intensively investigated during the last several years (e.g. Jakšík et al., 2015; Vašát et al., 2014, 2015a,b). Soil sampling (disturbed and undisturbed 100-cm3 soil samples) was performed at 5 points of one elevation transect in November 2010 (after wheat sowing) and August 2011 (after wheat harvest). Disturbed soil samples were used to determine basic soil properties (grain size distribution and organic carbon content etc.). Undisturbed soil samples were used to determine the soil water retention curves and the hydraulic conductivity functions using the multiple outflow tests in Tempe cells and a numerical inversion with HYDRUS 1-D. Scaling factors (alpha-h for pressure head, alpha-theta for soil water contents and alpha-k for hydraulic conductivities) were used here to express soil hydraulic properties variability. Evaluated scaling factors reflected position within the elevation transect as well as time of soil sampling. In general large values of alpha-h, lower values of alpha-k and similar values of alpha-theta were obtained in 2010 in comparison to values obtained in 2011, which indicates development of soil structure during the vegetation season. Jakšík, O., Kodešová, R., Kubiš, A., Stehlíková, I., Drábek, O., Kapička, A. (2015): Soil aggregate stability within morphologically diverse areas. Catena, 127, 287-299. Vašát, R., Kode

Integrated spatial assessment of wind erosion risk in Hungary

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L. Pásztor

2016-11-01

Full Text Available Wind erosion susceptibility of Hungarian soils was mapped on the national level integrating three factors of the complex phenomenon of deflation (physical soil features, wind characteristics, and land use and land cover. Results of wind tunnel experiments on erodibility of representative soil samples were used for the parametrization of a countrywide map of soil texture compiled for the upper 5 cm layer of soil, which resulted in a map representing threshold wind velocity exceedance. Average wind velocity was spatially estimated with 0.5′ resolution using the Meteorological Interpolation based on Surface Homogenised Data Basis (MISH method elaborated for the spatial interpolation of surface meteorological elements. The probability of threshold wind velocity exceedance was determined based on values predicted by the soil texture map at the grid locations. Ratio values were further interpolated to a finer 1 ha resolution using sand and silt content of the uppermost (0–5 cm layer of soil as spatial co-variables. Land cover was also taken into account, excluding areas that are not relevant to wind erosion (forests, water bodies, settlements, etc., to spatially assess the risk of wind erosion. According to the resulting map of wind erosion susceptibility, about 10 % of the total area of Hungary can be identified as susceptible to wind erosion. The map gives more detailed insight into the spatial distribution of wind-affected areas in Hungary compared to previous studies.

Sample sizes to control error estimates in determining soil bulk density in California forest soils

Science.gov (United States)

Youzhi Han; Jianwei Zhang; Kim G. Mattson; Weidong Zhang; Thomas A. Weber

2016-01-01

Characterizing forest soil properties with high variability is challenging, sometimes requiring large numbers of soil samples. Soil bulk density is a standard variable needed along with element concentrations to calculate nutrient pools. This study aimed to determine the optimal sample size, the number of observation (n), for predicting the soil bulk density with a...

Soil resources, land cover changes and rural areas: towards a spatial mismatch?

Science.gov (United States)

Ferrara, Agostino; Salvati, Luca; Sabbi, Alberto; Colantoni, Andrea

2014-04-15

The present study analyzes the impact of long-term urban expansion on soil depletion in Emilia-Romagna, an agricultural-specialized region of northern Italy. Using settlement density maps at three points in time (1945, 1971 and 2001) dense and diffused urbanization trends were assessed and correlated with soil quality. Non-urbanized land decreased from 11.8% in 1945 to 6.3% in 2001. Urbanization dynamics between 1945 and 1971 reflect the increase of dense settlements around pre-existing urban centers. To the contrary, a discontinuous, low- and medium-density urban expansion along the road network and in the most fertile lowland areas was observed between 1971 and 2001. Overall, urbanization consumed soils with progressively higher quality. However, a diverging trend was observed in the two investigated time intervals: soil with high quality was occupied by compact and dense settlements during 1945-1971 and by discontinuous, medium- and low-density settlements during 1971-2001. These findings document the polarization in areas with low and high soil capital and may reflect disparities in agricultural production and increasing environmental degradation. Moreover, the analysis shows a diverging trend between land and soil consumption patterns suggesting that the edification of pervious land is an unreliable indicator of soil quality depletion. Taken together, the results of this study illustrate the (increasing) spatial mismatch between agricultural land and high-quality soils as a consequence of urbanization-driven landscape transformations and may inform measures to contain soil depletion driven by economic growth. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatial distribution of heavy metals in the surface soil of source-control stormwater infiltration devices - Inter-site comparison.

Science.gov (United States)

Tedoldi, Damien; Chebbo, Ghassan; Pierlot, Daniel; Branchu, Philippe; Kovacs, Yves; Gromaire, Marie-Christine

2017-02-01

Stormwater runoff infiltration brings about some concerns regarding its potential impact on both soil and groundwater quality; besides, the fate of contaminants in source-control devices somewhat suffers from a lack of documentation. The present study was dedicated to assessing the spatial distribution of three heavy metals (copper, lead, zinc) in the surface soil of ten small-scale infiltration facilities, along with several physical parameters (soil moisture, volatile matter, variable thickness of the upper horizon). High-resolution samplings and in-situ measurements were undertaken, followed by X-ray fluorescence analyses and spatial interpolation. Highest metal accumulation was found in a relatively narrow area near the water inflow zone, from which concentrations markedly decreased with increasing distance. Maximum enrichment ratios amounted to >20 in the most contaminated sites. Heavy metal patterns give a time-integrated vision of the non-uniform infiltration fluxes, sedimentation processes and surface flow pathways within the devices. This element indicates that the lateral extent of contamination is mainly controlled by hydraulics. The evidenced spatial structure of soil concentrations restricts the area where remediation measures would be necessary in these systems, and suggests possible optimization of their hydraulic functioning towards an easier maintenance. Heterogeneous upper boundary conditions should be taken into account when studying the fate of micropollutants in infiltration facilities with either mathematical modeling or soil coring field surveys. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatial and temporal variability of soil moisture in a restored reach of an Alpine river

Science.gov (United States)

Luster, Jörg

2010-05-01

In order to assess the effects of river restoration on water quality, the biogeochemical functions of restored river reaches have to be quantified, and soil moisture is a key environmental variable controlling this functionality. Restored sections of rivers often are characterized by a dynamic mosaic of riparian zones with varying exposure to flooding. In this presentation, the spatial and temporal variability of soil moisture in riparian soils of a restored reach of the Alpine river Thur in northeastern Switzerland is shown. The study was part of the interdisciplinary project cluster RECORD, which was initiated to advance the mechanistic understanding of coupled hydrological and ecological processes in river corridors. The studied river reach comprised the following three functional processing zones (FPZ) representing a lateral successional gradient with decreasing hydrological connectivity (i.e. decreasing flooding frequency and duration). (i) The grass zone developed naturally on a gravel bar after restoration of the channelized river section (mainly colonized by canary reed grass Phalaris arundinacae). The soil is loamy sand to sandy loam composed of up to 80 cm thick fresh sediments trapped and stabilized by the grass roots. (ii) The bush zone is composed of young willow trees (Salix viminalis) planted during restoration to stabilize older overbank deposits with a loamy fine earth. (iii) The mixed forest is a mature riparian hardwood forest with ash and maple as dominant trees developed on older overbank sediments with a silty loamy fine earth. The study period was between spring 2009 and winter 2009/2010 including three flood events in June, July and December 2009. The first and third flood inundated the grass zone and lower part of the bush zone while the second flood was bigger and swept through all the FPZs. Water contents in several soil depths were measured continuously in 30 minute intervals using Decagon EC-5 and EC-TM sensors. There were six spatial

The History of Electromagnetic Induction Techniques in Soil Survey

Science.gov (United States)

Brevik, Eric C.; Doolittle, Jim

2014-05-01

Electromagnetic induction (EMI) has been used to characterize the spatial variability of soil properties since the late 1970s. Initially used to assess soil salinity, the use of EMI in soil studies has expanded to include: mapping soil types; characterizing soil water content and flow patterns; assessing variations in soil texture, compaction, organic matter content, and pH; and determining the depth to subsurface horizons, stratigraphic layers or bedrock, among other uses. In all cases the soil property being investigated must influence soil apparent electrical conductivity (ECa) either directly or indirectly for EMI techniques to be effective. An increasing number and diversity of EMI sensors have been developed in response to users' needs and the availability of allied technologies, which have greatly improved the functionality of these tools. EMI investigations provide several benefits for soil studies. The large amount of georeferenced data that can be rapidly and inexpensively collected with EMI provides more complete characterization of the spatial variations in soil properties than traditional sampling techniques. In addition, compared to traditional soil survey methods, EMI can more effectively characterize diffuse soil boundaries and identify included areas of dissimilar soils within mapped soil units, giving soil scientists greater confidence when collecting spatial soil information. EMI techniques do have limitations; results are site-specific and can vary depending on the complex interactions among multiple and variable soil properties. Despite this, EMI techniques are increasingly being used to investigate the spatial variability of soil properties at field and landscape scales.

Spatial representation of organic carbon and active-layer thickness of high latitude soils in CMIP5 earth system models

Energy Technology Data Exchange (ETDEWEB)

Mishra, Umakant; Drewniak, Beth; Jastrow, Julie D.; Matamala, Roser M.; Vitharana, U. W. A.

2017-08-01

Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (F.SMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for redudng existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Modellntercomparison Project Phase 5 { CMIP5) ESMs with those predicted from geospatial predictions, based on observation data for the state of Alaska, USA. For the geospatial modeling. we used soil profile observations {585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m-2) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors. when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primaly factors leading to observed differences were ( 1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate

Evaluating of the spatial heterogeneity of soil loss tolerance and its effects on erosion risk in the carbonate areas of southern China

Directory of Open Access Journals (Sweden)

Y. Li

2017-05-01

Full Text Available Soil loss tolerance (T value is one of the criteria in determining the necessity of erosion control measures and ecological restoration strategy. However, the validity of this criterion in subtropical karst regions is strongly disputed. In this study, T value is calculated based on soil formation rate by using a digital distribution map of carbonate rock assemblage types. Results indicated a spatial heterogeneity and diversity in soil loss tolerance. Instead of only one criterion, a minimum of three criteria should be considered when investigating the carbonate areas of southern China because the one region, one T value concept may not be applicable to this region. T value is proportionate to the amount of argillaceous material, which determines the surface soil thickness of the formations in homogenous carbonate rock areas. Homogenous carbonate rock, carbonate rock intercalated with clastic rock areas and carbonate/clastic rock alternation areas have T values of 20, 50 and 100 t/(km2 a, and they are extremely, severely and moderately sensitive to soil erosion. Karst rocky desertification (KRD is defined as extreme soil erosion and reflects the risks of erosion. Thus, the relationship between T value and erosion risk is determined using KRD as a parameter. The existence of KRD land is unrelated to the T value, although this parameter indicates erosion sensitivity. Erosion risk is strongly dependent on the relationship between real soil loss (RL and T value rather than on either erosion intensity or the T value itself. If RL > > T, then the erosion risk is high despite of a low RL. Conversely, if T > > RL, then the soil is safe although RL is high. Overall, these findings may clarify the heterogeneity of T value and its effect on erosion risk in a karst environment.

Development of effective methods for determination of boron in soils and soil solutions

Directory of Open Access Journals (Sweden)

Мaruan Tanasheva

2012-12-01

Full Text Available This paper is related to serious ecological problem in agriculture: soil degradation in rice fields in South Kazakhstan and in particular, to boron toxicity in rice, which resulted in reduced crop yields. The following abiotic factors were studied to determine the ability of boron to accumulate in rice fields: soil type, soil properties like salinity and acidity', season (level of precipitation, water logging /water shortage. The results shows that the severity of boron excess for fertility of rice crop which depends on boron ionic composition in soil. Adverse impact of both boron deficiency and boron excess are discussed. The necessity of boron fertilizers is shown for soils with high boron mobility.

[Occurrence and spatial differentiation of polycyclic aromatic hydrocarbons in surface soils from Shenzhen, China].

Science.gov (United States)

Zhang, Di; Cao, Shan-Ping; Sun, Jian-Lin; Zeng, Hui

2014-02-01

188 surface soil samples were collected in Shenzhen of China to determine the occurrence and spatial differentiation of polycyclic aromatic hydrocarbons (PAHs), based on which we studied the correlation between PAHs concentrations and urbanization levels, as well as the PAHs ecological risk. The total concentrations of 28 PAHs (sigma28 PAHs), 16 EPA PAHs (sigma 16 PAHs) and 7 carcinogenic PAHs (sigma7 CarPAHs) ranged from 5 to 7939 ng x g(-1), 2 to 6745 ng x g(-1) and not detected to 3786 ng x g(-1), respectively. 8 kinds of land use types according to sigma16 PAHs average levels in descending order were: transportation lands, commercial lands, industrial lands, agricultural lands, residential lands, urban green space, orchards and woodland. And sigma16 PAHs of construction and non-construction lands samples were mainly derived from combustion of various fossil fuels with contribution of 75.1% and 68.2%, respectively. Significant positive correlation was also found between PAHs concentrations of high molecular weight and urbanization levels. And PAHs pollution in the top soils of Shenzhen was at a low-end level of the world.

Assessment of Multi-frequency Electromagnetic Induction for Determining Soil Moisture Patterns at the Hillslope Scale

Science.gov (United States)

Tromp-van Meerveld, I.; McDonnell, J.

2009-05-01

We present an assessment of electromagnetic induction (EM) as a potential rapid and non-invasive method to map soil moisture patterns at the Panola (GA, USA) hillslope. We address the following questions regarding the applicability of EM measurements for hillslope hydrological investigations: (1) Can EM be used for soil moisture measurements in areas with shallow soils?; (2) Can EM represent the temporal and spatial patterns of soil moisture throughout the year?; and (3) can multiple frequencies be used to extract additional information content from the EM approach and explain the depth profile of soil moisture? We found that the apparent conductivity measured with the multi-frequency GEM-300 was linearly related to soil moisture measured with an Aqua-pro capacitance sensor below a threshold conductivity and represented the temporal patterns in soil moisture well. During spring rainfall events that wetted only the surface soil layers the apparent conductivity measurements explained the soil moisture dynamics at depth better than the surface soil moisture dynamics. All four EM frequencies (7290, 9090, 11250, and 14010 Hz) were highly correlated and linearly related to each other and could be used to predict soil moisture. This limited our ability to use the four different EM frequencies to obtain a soil moisture profile with depth. The apparent conductivity patterns represented the observed spatial soil moisture patterns well when the individually fitted relationships between measured soil moisture and apparent conductivity were used for each measurement point. However, when the same (master) relationship was used for all measurement locations, the soil moisture patterns were smoothed and did not resemble the observed soil moisture patterns very well. In addition, the range in calculated soil moisture values was reduced compared to observed soil moisture. Part of the smoothing was likely due to the much larger measurement area of the GEM-300 compared to the Aqua

Spectral estimation of soil properties in siberian tundra soils and relations with plant species composition

DEFF Research Database (Denmark)

Bartholomeus, Harm; Schaepman-Strub, Gabriela; Blok, Daan

2012-01-01

yields a good prediction model for K and a moderate model for pH. Using these models, soil properties are determined for a larger number of samples, and soil properties are related to plant species composition. This analysis shows that variation of soil properties is large within vegetation classes......Predicted global warming will be most pronounced in the Arctic and will severely affect permafrost environments. Due to its large spatial extent and large stocks of soil organic carbon, changes to organic matter decomposition rates and associated carbon fluxes in Arctic permafrost soils...

Radiocaesium forms in soil - problems of experimental determination

International Nuclear Information System (INIS)

Davydov, D.; Davydov, Yu.; Voronik, N.; Titov, A.; Toropova, N.

2006-01-01

A method for determining Cs form in soil is proposed based on the comparison of the experimental data on desorption of Cs radionuclide from the soil contaminated as a result of the Chernobyl accident and from the soil samples on which Cs was absorbed in laboratory (Cs was introduced in ionic form in solution). The data obtained on desorption of Cs from different soils show that Cs radionuclide is present in the soil contaminated as a result of the Chernobyl accident predominantly in an ionic form (sorbed on the different soil fractions). It has also been found that the ratio of 144 Ce/ 137 Cs radionuclides is much higher in solution than in the soil. At the same time the data on sorption of Cs and Ce radionuclides on different soils from solution 0.1M HCI + 0.1M KCI + 0.1M FeCI 3 show that the sorption ability of Cs is higher than the sorption ability of Ce for all the soil types investigated. Hence, it can be assumed that the mechanism of the radionuclides extraction is desorption rather than dissolution of the matrix particles, since in the letter case extraction value of the radionuclides would not be different. The fact that the ratio of 144 Ce/ 137 Cs radionuclides in solution remains higher than in soil independent on the distance from the Chernobyl NPP indicates that the form of the radionuclides does not change with the distance from the reactor. In order to determine what type of molecules Cs radionuclide can be bound to in soil the experiments on sorption of Cs on sandy soil in the presence of humic acid in solution has been carried out. The data obtained show that the presence of humic acids has none or little effect on the sorption of Cs. This indicates that interaction of Cs radionuclides with humic acid is week and these molecules can not be responsible for binding Cs in soil. (author)

Harvest traffic monitoring and soil physical response in a pine plantation

Science.gov (United States)

Emily A. Carter; Timothy P. McDonald; John L. Torbert

2000-01-01

Mechanized forest harvest operations induce changes in soil physical properties, which have the potential to impact soil sustainability and forest productivity. The assessment of soil compaction and its spatial variability has been determined previously through the identification and tabulation of visual soil disturbance classes and soil physical changes associated...

Decoding implicit information from the soil map of Belgium and implications for spatial modelling and soil classification

Science.gov (United States)

Dondeyne, Stefaan; Legrain, Xavier; Colinet, Gilles; Van Ranst, Eric; Deckers, Jozef

2014-05-01

(Anthrosols) are distinguished for their specific profile development (code "..m"). Obviously, when assessing soil organic carbon content these soil types need particular consideration. Soils in the Campine region with anthropogenic layers only 30 to 40 cm thick, not being Anthrosols, got a specific suffix code ("…3"). Still, as these soils may have a buried Ah horizon of up to 20 cm, their soil organic carbon content can be comparable to those of Anthrosols. The buried Ah horizon is however not explicitly mapped; its presence needs to be inferred from other environmental information. In conclusion, conventional soil maps convey more information than what transpires from just the explicit legend's semantics. Although a challenge, decoding the implicit information should be particularly useful for spatial modeling. The cases also point to the importance of classifying soil characteristics explicitly, wherever possible, and in particularly when soil maps are integrated into geographical information systems.

Centimeter-scale spatial variability in 2-methyl-4-chlorophenoxyacetic acid mineralization increases with depth in agricultural soil

DEFF Research Database (Denmark)

Badawi, Nora; Johnsen, Anders R.; Sørensen, Jan

2013-01-01

Mineralization of organic chemicals in soil is typically studied using large homogenized samples, but little is known about the small-scale spatial distribution of mineralization potential. We studied centimeter-scale spatial distribution of 2-methyl-4-chlorophenoxyacetic acid (MCPA) mineralization...... was mineralized in all samples in the plow layer, but only about 60% in the transition zone immediately below the plow layer showed mineralization; at greater depth even fewer samples showed mineralization. A patchy spatial distribution of mineralization activity was observed from right below the plow layer...... activity at different depths (8-115 cm) in a Danish agricultural soil profi le using a 96-well microplate C-radiorespirometric method for small-volume samples. The heterotrophic microbial population and specifi c MCPA degraders decreased 10- to 100-fold from the plow layer to a depth of 115 cm. MCPA...

Small scale spatial variability and pattern of soil respiration and water content in wet and a dry temperate grasslands and bare soil

Czech Academy of Sciences Publication Activity Database

Fóti, S.; Nagy, Z.; Balogh, J.; Bartha, S.; Acosta, Manuel; Czóbel, S.; Péli, E.; Marek, Michal V.; Tuba, Z.

2009-01-01

Roč. 28, č. 4 (2009), s. 389-398 ISSN 1335-342X Institutional research plan: CEZ:AV0Z60870520 Institutional support: RVO:67179843 Keywords : chamber technique * coefficient of variation * semivariance * Soil respiration * spatial pattern Subject RIV: EH - Ecology, Behaviour

Soil salinity and acidity : spatial variabil[it]y and effects on rice production in West Africa's mangrove zone

NARCIS (Netherlands)

Sylla, M.

1994-01-01

In the mangrove environment of West Africa, high spatial and temporal variability of soil constraints (salinity and acidity) to rice production is a problem for the transfer and adoption of new agronomic techniques, for land use planning, and for soil and water management. Recently, several

Spatial changes in soil organic carbon density and storage of cultivated soils in China from 1980 to 2000

Science.gov (United States)

Yu, Yanyan; Guo, Zhengtang; Wu, Haibin; Kahmann, Julia A.; Oldfield, Frank

2009-06-01

We address the spatial changes in organic carbon density and storage in cultivated soils in China from 1980 to 2000 on the basis of measured data from individual studies and those acquired during the second national soil survey in China. The results show a carbon gain in ˜66% of the cultivated area of China as a whole with the increase in soil organic carbon (SOC) density mostly ranging from 10% to 30%. Soil organic carbon density increased in fluvi-aquic soils (fluvisols, Food and Agriculture Organization (FAO) of the United Nations) in north China, irrigated silting soils (calcaric fluvisols) in northwest China, latosolic red earths (haplic acrisols/alisols), and paddy soils (fluvisols/cambisols) in south China. In contrast, significant decreases are observed in black soils (phaeozems) in northeast China and latosols (haplic acrisols) in southwest China. No significant changes are detected in loessial soils (calcaric regosols) and dark loessial soils (calcisols) in the loess plateau region. The total SOC storage and average density in the upper 20 cm in the late 1990s are estimated to be ˜5.37 Pg C and 2.77 kg/m2, respectively, compared with the values of ˜5.11 Pg C and 2.63 kg/m2 in the early 1980s. This reveals an increase of SOC storage of 0.26 Pg C and suggests an overall carbon sink for cultivated soils in China, which has contributed 2-3% to the global terrestrial ecosystem carbon absorption from 1980 to 2000. Statistical analyses suggest an insignificant contribution to the observed SOC increase from climate change, and we infer that it is mostly attributable to improved agricultural practices. Despite the SOC density increases over 20 years, the SOC density of the cultivated soils in China in the late 1990s is still ˜30% lower compared to their uncultivated counterparts in comparable soil types, suggesting a considerable potential for SOC restoration through improving management practices. Assuming a restoration of ˜50% of the lost SOC in the next 30

Uranium determination in soil samples using Eichrom resins

International Nuclear Information System (INIS)

Marabini, S.; Serdeiro, Nelidad H.

2003-01-01

Traditionally, the radiochemical methods for uranium activity determination in soil samples by alpha spectrometry, use some techniques like solvent extraction, precipitation and ion exchange in the separation and purification stages. In the last years, some new materials have been developed for using in extraction chromatography, specific for actinides determinations. In the present method the long and tedious stages were eliminated, and the reagents consumption and concentration were minimised. This new procedure was applied to soils since it is one of the most complex matrices. In order to reduce time and chemical reagents, the soil samples up to 0,5 g were leached with nitric, hydrofluoric and perchloric acids in hermetic sealed recipients of Teflon at 150 C degrees during 5 hours. UTEVA Eichrom resin was used for uranium separation and purification. The uranium activity concentration was determined by alpha spectrometry. Several standard samples were analysed and the results are presented. (author)

Spatial and temporal variability of grass cover in two olive grove catchments on contrasting soil types

Science.gov (United States)

Aguilera, Laura; Taguas, Encarnación V.; Gimeno, Enrique; Gómez, José A.

2013-04-01

Mediterranean climate conditions -characterized by the concentration of the precipitation in the seasons of autumn and spring, the low temperatures in winter and extremely warm and dry summers- determine that ground cover by adventitious (or cover crop) vegetation shows significant seasonal and annual variability. In addition, its spatial variability associates also, partially, to water availability among the landscape. This is especially relevant in olive orchards, an agricultural system under high erosion risk in the region where the establishment of herbaceous cover has proved to improve soil protection reducing erosion risk, as well as the improvement of soil properties (Gómez et al., 2009). All these benefits are based on small scale studies where full ground cover by the cover crop is relatively easy to obtain. However, few information is available about the actual ground cover achieved at farm scale, although preliminary observations suggests that this might be extremely variable (Gómez and Giráldez, 2009). This study presents the preliminary results evaluating the spatial and temporal evolution of ground cover by adventitious vegetation (the preferred option by farmers to achieve a cover crop) in two commercial olive farms during 2 hydrological years (2011-2012). The study was conducted in two farms located in the province of Cordoba, Southern Spain. Both were olive orchards grown under deficit irrigation systems and present a gauge station where rainfall, runoff and sediment loads have been measured from the year 2005. The soil management in "La Conchuela" farm was based in the use of herbicide in the line of olive trees to keep the bare soil all year round, and the application of selective herbicide in the lane between the olive trees to promote the grown of graminaceae grasses . In addition, the grass is mechanically killed in June. In the another farm, "Arroyo Blanco", the grass spontaneous cover is allowed until mid-spring in which is also

Spatial distribution and pollution assessment of heavy metals in urban soils from southwest China

Institute of Scientific and Technical Information of China (English)

Guanghui Guo; FengchangWu; Fazhi Xie; Ruiqing Zhang

2012-01-01

To identify the concentrations and sources of heavy metals,and to assess soil environmental quality,63 soil samples were collected in Yibin City,Sichuan Province,China.Mean concentrations of As,Pb,Zn,and Cu were 10.55,61.23,138.88 and 56.35 mg/kg,respectively.As concentrations were comparable to background values,while Pb,Zn,and Cu concentrations were higher than their corresponding background values.Industrial areas exhibited the highest concentrations of As,Pb,Zn,and Cu,while the lowest concentrations occurred in parks.Statistical analysis was performed and two cluster groups of metals were identified with Pb,Zn,and Cu in one group and As in the other.Spatial distribution maps indicated that Pb,Zn,and Cu were mainly controlled by anthropogenic activities,whereas As could be mainly accounted for by soil parent materials.Pollution index values of As,Pb,Zn,and Cu varied in the range of 0.24-1.93,0.66-7.24,0.42-4.19,and 0.62-5.25,with mean values of 0.86,1.98,1.61,and 1.78,respectively.The integrated pollution index(IPI)values of these metals varied from 0.82 to 3.54,with a mean of 1.6 and more than 90% of soil samples were moderately or highly contaminated with heavy metals.The spatial distribution of IPI showed that newer urban areas displayed relatively lower heavy metal contamination in comparison with older urban areas.

A knowledge-based approach to estimating the magnitude and spatial patterns of potential threats to soil biodiversity.

Science.gov (United States)

Orgiazzi, Alberto; Panagos, Panos; Yigini, Yusuf; Dunbar, Martha B; Gardi, Ciro; Montanarella, Luca; Ballabio, Cristiano

2016-03-01

Because of the increasing pressures exerted on soil, below-ground life is under threat. Knowledge-based rankings of potential threats to different components of soil biodiversity were developed in order to assess the spatial distribution of threats on a European scale. A list of 13 potential threats to soil biodiversity was proposed to experts with different backgrounds in order to assess the potential for three major components of soil biodiversity: soil microorganisms, fauna, and biological functions. This approach allowed us to obtain knowledge-based rankings of threats. These classifications formed the basis for the development of indices through an additive aggregation model that, along with ad-hoc proxies for each pressure, allowed us to preliminarily assess the spatial patterns of potential threats. Intensive exploitation was identified as the highest pressure. In contrast, the use of genetically modified organisms in agriculture was considered as the threat with least potential. The potential impact of climate change showed the highest uncertainty. Fourteen out of the 27 considered countries have more than 40% of their soils with moderate-high to high potential risk for all three components of soil biodiversity. Arable soils are the most exposed to pressures. Soils within the boreal biogeographic region showed the lowest risk potential. The majority of soils at risk are outside the boundaries of protected areas. First maps of risks to three components of soil biodiversity based on the current scientific knowledge were developed. Despite the intrinsic limits of knowledge-based assessments, a remarkable potential risk to soil biodiversity was observed. Guidelines to preliminarily identify and circumscribe soils potentially at risk are provided. This approach may be used in future research to assess threat at both local and global scale and identify areas of possible risk and, subsequently, design appropriate strategies for monitoring and protection of soil

Manganese contents of soils as determined by activation analysis

International Nuclear Information System (INIS)

El-Kholi, A.F.; Hamdy, A.A.; Al Metwally, A.I.; El-Damaty, A.H.

1976-01-01

The object of this investigation is to determine total manganese by means of neutron activation analysis and evaluate this technique in comparison with the corresponding data obtained by conventional chemical analysis. Data obtained revealed that the values of total manganese in calcareous soils obtained by both chemical analysis and that by neutron activation analysis were similar. Therefore, activation analysis could be recommended as a quick laboratory, less tedious, and time consuming method for the determination of Mn content in both soils and plants than the conventional chemical techniques due to its great specificity, sensitivity and simplicity. Statistical analysis showed that there is a significant correlation at 5% probability level between manganese content in Soybean plant and total manganese determined by activation and chemical analysis giving the evidence that in the case of those highly calcareous soils of low total manganese content this fraction has to be considered as far as available soil manganese is concerned

Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data

Directory of Open Access Journals (Sweden)

J. Mikola

2018-05-01

Full Text Available Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm−3 in bare soil and lichen tundra and 89 g dm−3 in other LCTs. Total moss biomass varied from 0 to 820 g m−2, total vascular shoot mass from 7 to 112 g m−2 and vascular leaf area index (LAI from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 °C in bare soil and lichen tundra, and varied from 5 to 9 °C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14–34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer

[Soil carbohydrates: their determination methods and indication functions].

Science.gov (United States)

Zhang, Wei; Xie, Hongtu; He, Hongbo; Zheng, Lichen; Wang, Ge

2006-08-01

Soil carbohydrates are the important component of soil organic matter, and play an important role in soil aggregation formation. Their hydrolysis methods involve sulfur acid (H2SO4), hydrochloric acid (HCl), and trifluoroacetic acid (TFA) hydrolysis, and their determination methods include colorimetry, gas-liquid chromatography (GLC) , high performance liquid chromatography (HPLC), and high performance anion-exchange chromatography with pulsed amperometric detection (HPAE-PAD). This paper summarized the methods of carbohydrates' hydrolysis, purification and detection, with focus on the derived methods of GLC, and briefly introduced the indication functions of carbohydrates in soil organic matter turnover.

Determination of 230Th in soils

International Nuclear Information System (INIS)

Alvarez, A.; Palomares, J.

1988-01-01

A method for the determination of 230Th in environmental soils is described. Hydroxides formed, previous fusion with sodium peroxide are dissolved with HNO3 8N. The thorium is coprecipitated with F3La and purified by anion exchange (AG 1x8 50-100 mesh). Thorium is electroplated onto a stainless steel disc, 230xh is counted by alpha spectrometry and 234'fn u;;ed as tracer by beta counting. The chemical yield for 1g of soil sample is 60-80%. Minimum detectable activities are about 2 mBq/g

Temporal and spatial heterogeneity of soil CO2 efflux in a Norway spruce stand

Czech Academy of Sciences Publication Activity Database

Kurajdová, Jana; Acosta, Manuel; Pavelka, Marian

2006-01-01

Roč. 2006, č. 19 (2006), s. 1 ISSN 1803-1013 R&D Projects: GA MŠk OC 627.001 Institutional research plan: CEZ:AV0Z60870520 Keywords : soil CO2 efflux * Norway spruce stand * temperature * spatial and temporal heterogeneity * stand density Subject RIV: ED - Physiology

Methods of pH determination in Calcareous soils of Oman: The effect of Electrolyte and soil solution ratio

International Nuclear Information System (INIS)

Al-Busaidi, A.; Cookson, P.

2002-01-01

Determination of pH assists in understanding many reactions that occur in soil. Soil pH values are highly sensitive to the procedure used for determination. In this study, pH was measured in different electrolytes [distilled water (pHw), 0.01MCaCl2 (pHCa), 1MKCl (pHk), and 0.01MBaCl2 (pHba)] with different soil: electrolyte ratios (i.e. 1:1, 1:2.5 and 1:5). The objective was to determine the effect of each electrolyte and dilution ratio on pH of saline and non-saline soils from Oman. It was found that ph values varied significantly between electrolytes and with different dilution ratios. Linear regression equations were generated between electrolytes, dilution ratios and were mostly significant. Soil pH values determined in different electrolytes were significantly interrelated. Water appeared as a highly suitable solvent for soil pH measurements because it is simple and values familiar to soil users. However, alkaline errors and electrode instabilities due to liquid junction and soluble salt effects, affected soil pH measurements, especially in water, and resulted in alkaline errors during pH measurements. Errors were minimized when pH was measured in electrolytes rather than in water. (author)

Assessment of produced water contaminated soils to determine remediation requirements

International Nuclear Information System (INIS)

Clodfelter, C.

1995-01-01

Produced water and drilling fluids can impact the agricultural properties of soil and result in potential regulatory and legal liabilities. Produced water typically is classified as saline or a brine and affects surface soils by increasing the sodium and chloride content. Sources of produced water which can lead to problems include spills from flowlines and tank batteries, permitted surface water discharges and pit areas, particularly the larger pits including reserve pits, emergency pits and saltwater disposal pits. Methods to assess produced water spills include soil sampling with various chemical analyses and surface geophysical methods. A variety of laboratory analytical methods are available for soil assessment which include electrical conductivity, sodium adsorption ratio, cation exchange capacity, exchangeable sodium percent and others. Limiting the list of analytical parameters to reduce cost and still obtain the data necessary to assess the extent of contamination and determine remediation requirements can be difficult. The advantage to using analytical techniques is that often regulatory remediation standards are tied to soil properties determined from laboratory analysis. Surface geophysical techniques can be an inexpensive method to rapidly determine the extent and relative magnitude of saline soils. Data interpretations can also provide an indication of the horizontal as well as the vertical extent of impacted soils. The following discussion focuses on produced water spills on soil and assessment of the impacted soil. Produced water typically contains dissolved hydrocarbons which are not addressed in this discussion

Determination of strontium-90 in soil samples

Energy Technology Data Exchange (ETDEWEB)

Chang, C C

1976-06-01

The determination of /sup 90/Sr in soil by tri-n-butyl phosphate (TBP) is often interfered with iron which is always present in soil sample. Based on the method given by the U.S. Environmental Protection Agency, HClO/sub 4/ is added to remove iron ions while the soil sample is analyzed with TBP. The effect of different concentrations of HClO/sub 4/ on extraction yield of iron and chemical yield of yttrium is investigated. The experimental results show that 2N HClO/sub 4/ is the optimum concentration. The chemical yield of yttrium can reach about 60 percent, and all iron ions can be removed. This method has successfully been applied to analyze the soil samples taken from the site of the nuclear power plant in North Taiwan.

A spatially-based modeling framework for assessing the risks of soil-associated metals to bats

International Nuclear Information System (INIS)

Hernout, Béatrice V.; Somerwill, Kate E.; Arnold, Kathryn E.; McClean, Colin J.; Boxall, Alistair B.A.

2013-01-01

Populations of some species of bats are declining in some regions of Europe. These declines are probably due to a range of pressures, including climate change, urbanization and exposure to toxins such as metals. This paper describes the development, paramaterisation and application of a spatially explicit modeling framework to predict the risks of soil-associated metals (lead, copper, zinc and cadmium) to bat health. Around 5.9% of areas where bats reside were predicted to have lead levels that pose a risk to bat health. For copper, this value was 2.8%, for cadmium it was 0.6% and for zinc 0.5%. Further work is therefore warranted to explore the impacts of soil-associated metals on bat populations in the UK. - Highlights: ► A modeling framework is presented to estimate risks of contaminants to wildlife. ► The model has been applied to soil metal contamination and bat species. ► Results indicate that lead and copper pose the greatest risk to bat health. ► A risk is predicted for up to 6% of areas where bats reside in England and Wales. - Application of a novel, spatially explicit risk assessment framework indicates that the health of insectivorous bat species in some regions of the UK may be at threat from exposure to soil associated metals.

Mapping fields of 137Cs contamination in soils in the context of their stability and hierarchical spatial structure

Science.gov (United States)

Korobova, E.; Romanov, S.

2009-04-01

Technogenic radioisotopes now dispersed in the environment are involved in natural and technogenic processes forming specific geochemical fields and serving as tracers of modern mass migration and geofield transformation. Cs-137 radioisotopes having a comparatively long life time are known for a fast fixation by the top soil layer; radiocesium activity can be measured in the surface layer in field conditions. This makes 137Cs rather convenient for the study and modeling a behavior of toxic elements in soils [1-3, 5] and for the investigation of relative stability and hierarchical fractal structures of the soil contamination of the atmospheric origin [2]. The objective of the experimental study performed on the test site in Bryansk region was to find and prove polycentric regularities in the structure of 137Cs contamination field formed after the Chernobyl accident in natural conditions. Such a character of spatial variability can be seen on the maps showing different soil parameters and chemical element distribution measured in grids [3-5]. The research was undertaken to support our idea of the regular patterns in the contamination field structure that enables to apply a mathematical theory of the field to the geochemical fields modeling on the basis of a limited number of direct measurements sufficient to reproduce the configuration and main parameters of the geochemical field structure on the level of the elementary landscape geochemical system (top-slope-bottom). Cs-137 field measurements were verified by a direct soil sampling. Soil cores dissected into subsamples with increments of 2, 5 and 10 cm, were taken to the depth of 40 cm at points with various surface activity located at different elements of relief. According to laboratory measurements 137Cs inventory in soils varied from 344 to 3448 kBq/m2 (983 kBq/m2 on the average). From 95,1% to 98,0% to of the total inventory was retained in the top 20-cm soil layer. This confirmed that field gamma spectrometry

Observing and modeling links between soil moisture, microbes and CH4 fluxes from forest soils

Science.gov (United States)

Christiansen, Jesper; Levy-Booth, David; Barker, Jason; Prescott, Cindy; Grayston, Sue

2017-04-01

Soil moisture is a key driver of methane (CH4) fluxes in forest soils, both of the net uptake of atmospheric CH4 and emission from the soil. Climate and land use change will alter spatial patterns of soil moisture as well as temporal variability impacting the net CH4 exchange. The impact on the resultant net CH4 exchange however is linked to the underlying spatial and temporal distribution of the soil microbial communities involved in CH4 cycling as well as the response of the soil microbial community to environmental changes. Significant progress has been made to target specific CH4 consuming and producing soil organisms, which is invaluable in order to understand the microbial regulation of the CH4 cycle in forest soils. However, it is not clear as to which extent soil moisture shapes the structure, function and abundance of CH4 specific microorganisms and how this is linked to observed net CH4 exchange under contrasting soil moisture regimes. Here we report on the results from a research project aiming to understand how the CH4 net exchange is shaped by the interactive effects soil moisture and the spatial distribution CH4 consuming (methanotrophs) and producing (methanogens). We studied the growing season variations of in situ CH4 fluxes, microbial gene abundances of methanotrophs and methanogens, soil hydrology, and nutrient availability in three typical forest types across a soil moisture gradient in a temperate rainforest on the Canadian Pacific coast. Furthermore, we conducted laboratory experiments to determine whether the net CH4 exchange from hydrologically contrasting forest soils responded differently to changes in soil moisture. Lastly, we modelled the microbial mediation of net CH4 exchange along the soil moisture gradient using structural equation modeling. Our study shows that it is possible to link spatial patterns of in situ net exchange of CH4 to microbial abundance of CH4 consuming and producing organisms. We also show that the microbial