Organic matter processing and soil evolution in a braided river system

Traditionally, braided river research has considered flow, sediment transport processes and, recently, vegetation dynamics in relation to river morphodynamics. However, if considering the development of woody vegetated patches over a time scale of decades, we must consider the extent to which soil forming processes, particularly related to soil organic matter, impact the alluvial geomorphic-vegetation system. Here we quantify the soil organic matter processing (humification) that occurs on young alluvial landforms. We sampled different geomorphic units, ranging from the active river channel to established river terraces in a braided river system. For each geomorphic unit, soil pits were used to sample sediment/soil layers that were analysed in terms of grain size (<2mm) and organic matter quantity and quality (RockEval method). A principal components analysis was used to identify patterns in the dataset. Results suggest that during the succession from bare river gravels to a terrace soil, there is a transition from small amounts of external organic matter supply provided by sedimentation processes (e.g. organic matter transported in suspension and deposited on bars), to large amounts of autogenic in situ organic matter production due to plant colonisation. This appears to change the time scale and pathways of alluvial succession (bio-geomorphic succession). However, this process is complicated by: the ongoing possibility of local sedimentation, which can serve to isolate surface layers via aggradation from the exogenic supply; and erosion which tends to create fresh deposits upon which organic matter processing must re-start. The result is a complex pattern of organic matter states as well as a general lack of any clear chronosequence within the active river corridor. This state reflects the continual battle between deposition events that can isolate organic matter from the surface, erosion events that can destroy accumulating organic matter and the early ecosystem processes necessary to assist the co-evolution of soil and vegetation. A key question emerges over the extent to which the fresh organic matter deposited in the active zone is capable of significantly transforming the local geochemical environment sufficiently to accelerate soil development.

Development of LRFD Design Procedures for Bridge Piles in Iowa – Field Testing of Steel H-Piles in Clay, Sand, and Mixed Soils and Data Analysis (Volume II), TR-583, 2011

In response to the mandate on Load and Resistance Factor Design (LRFD) implementations by the Federal Highway Administration (FHWA) on all new bridge projects initiated after October 1, 2007, the Iowa Highway Research Board (IHRB) sponsored these research projects to develop regional LRFD recommendations. The LRFD development was performed using the Iowa Department of Transportation (DOT) Pile Load Test database (PILOT). To increase the data points for LRFD development, develop LRFD recommendations for dynamic methods, and validate the results of LRFD calibration, 10 full-scale field tests on the most commonly used steel H-piles (e.g., HP 10 x 42) were conducted throughout Iowa. Detailed in situ soil investigations were carried out, push-in pressure cells were installed, and laboratory soil tests were performed. Pile responses during driving, at the end of driving (EOD), and at re-strikes were monitored using the Pile Driving Analyzer (PDA), following with the CAse Pile Wave Analysis Program (CAPWAP) analysis. The hammer blow counts were recorded for Wave Equation Analysis Program (WEAP) and dynamic formulas. Static load tests (SLTs) were performed and the pile capacities were determined based on the Davisson’s criteria. The extensive experimental research studies generated important data for analytical and computational investigations. The SLT measured load-displacements were compared with the simulated results obtained using a model of the TZPILE program and using the modified borehole shear test method. Two analytical pile setup quantification methods, in terms of soil properties, were developed and validated. A new calibration procedure was developed to incorporate pile setup into LRFD.

Temporal changes of an alfalfa succession and related soil physical properties on the Loess Plateau, China

The objective of this work was to investigate the relationship between changes in the plant community and changes in soil physical properties and water availability, during a succession from alfalfa (Medicago sativa L.) to natural vegetation on the Loess Plateau, China. Data from a succession sere spanning 32 years were collated, and vegetative indexes were compared to changes related to soil bulk density and soil water storage. The alfalfa yield increased for approximately 7 years, then it declined and the alfalfa was replaced by a natural community dominated by Stipa bungeana that began to thrive about 10 years after alfalfa seeding. Soil bulk density increased over time, but the deterioration of the alfalfa was mainly ascribed to a severe reduction in soil water storage, which was lowest around the time when degradation commenced. The results indicated that water consumption by alfalfa could be reduced by reducing plant density. The analysis of the data also suggested that soil water recharge could be facilitated by rotating the alfalfa with other crops, natural vegetation, or bare soil.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Identification of reference genes for expression analysis by real-time quantitative PCR in drought-stressed soybean

The objective of this work was to validate, by quantitative PCR in real time (RT-qPCR), genes to be used as reference in studies of gene expression in soybean in drought-stressed trials. Four genes commonly used in soybean were evaluated: Gmβ-actin, GmGAPDH, GmLectin and GmRNAr18S. Total RNA was extracted from six samples: three from roots in a hydroponic system with different drought intensities (0, 25, 50, 75 and 100 minutes of water stress), and three from leaves of plants grown in sand with different soil moistures (15, 5 and 2.5% gravimetric humidity). The raw cycle threshold (Ct) data were analyzed, and the efficiency of each primer was calculated for an overall analysis of the Ct range among the different samples. The GeNorm application was used to evaluate the best reference gene, according to its stability. The GmGAPDH was the least stable gene, with the highest mean values of expression stability (M), and the most stable genes, with the lowest M values, were the Gmβ-actin and GmRNAr18S, when both root and leaves samples were tested. These genes can be used in RT-qPCR as reference gene for expression analysis.

Bioindicators of soil quality in coffee organic cultivation systems

The objective of this work was to assess the effect of different coffee organic cultivation systems on chemical and biological soil characteristics, in different seasons of the year. The following systems were evaluated: coffee intercropped with one (CJ1), two (CJ2) or three (CJ3) pigeon pea (Cajanus cajan) alleys; coffee planted under full sun (CS); area planted with sweet pepper and snap bean in a conventional tillage system (AC); and secondary forest area (FFR). Row spacing in CJ1, CJ2, CJ3 and CS was 2.0x1.0, 2.8x1.0, 3.6x1.0, and 2.8x1.0 m, respectively. Soil samples were collected at 10-cm depth, during the four seasons of the year. The results were subjected to analysis of variance, principal component analysis, and redundancy analysis. There was an increase in edaphic macrofauna, soil basal respiration, and microbial quotient in the summer. Total macrofauna density was greater in CJ2 followed by CJ3, CS, CJ1, AC and FFR; Coleoptera, Formicidae, and Isoptera were the most abundant groups. There are no significant differences among the areas for soil basal respiration, and the metabolic quotient is higher in CJ1, CJ3, and FFR. Microbial biomass carbon and the contents of K, pH, Ca+Mg, and P show greater values in AC.

Cross-scale analysis of the region effect on vascular plant species diversity in southern and northern European mountain ranges.

Background: The divergent glacial histories of southern and northern Europe affect present-day species diversity at coarse-grained scales in these two regions, but do these effects also penetrate to the more fine-grained scales of local communities?Methodology/Principal Findings: We carried out a cross-scale analysis to address this question for vascular plants in two mountain regions, the Alps in southern Europe and the Scandes in northern Europe, using environmentally paired vegetation plots in the two regions (n = 403 in each region) to quantify four diversity components: (i) total number of species occurring in a region (total gamma-diversity), (ii) number of species that could occur in a target plot after environmental filtering (habitat-specific gamma-diversity), (iii) pair-wise species compositional turnover between plots (plot-to-plot beta-diversity) and (iv) number of species present per plot (plot gamma-diversity). We found strong region effects on total gamma-diversity, habitat-specific gamma-diversity and plot-to-plot beta-diversity, with a greater diversity in the Alps even towards distances smaller than 50 m between plots. In contrast, there was a slightly greater plot alpha-diversity in the Scandes, but with a tendency towards contrasting region effects on high and low soil-acidity plots.Conclusions/Significance: We conclude that there are strong regional differences between coarse-grained (landscape- to regional-scale) diversity components of the flora in the Alps and the Scandes mountain ranges,but that these differences do not necessarily penetrate to the finest-grained (plot-scale) diversity component, at least not on acidic soils. Because different processes can lead to a similar pattern, we discuss the consistency of our results with Quaternary history and other divergent features between the two regions such as habitat connectivity, selection for vagility and environmental differences not accounted for in our analyses

Root distribution of irrigated grapevine rootstocks in a coarse texture soil of the São Francisco Valley, Brazil

An experiment was carried out to determine the root distribution of four grapevine rootstocks (Salt Creek, Dogridge, Courdec 1613, IAC 572) in a coarse texture soil of a commercial growing area in Petrolina County, São Francisco Valley, Brazil. Rootstocks were grafted to a seedless table grape cv. Festival, and irrigated by microsprinkler. Roots were quantified by the trench wall method aided by digital image analysis. Results indicated that roots reached 1 m depth, but few differences among rootstocks were found. All of them presented at least 90 % of the roots distributed until 0.6 m depth, with a greater root presence in the first 0.4 m. The upper 0.6 m can be taken into account as the effective rooting depth for soil and water management.

Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.

Soil nutrient availability and its impact on fruit quality of Tahiti acid lime

The Tahiti acid lime in Brazil is mostly grown in the São Paulo State. The value of this crop production ranks among the ten most important fruits in the country. The Brazilian exports of Tahiti limes have increased in the last years with a corresponding increased demand for superior quality of fresh fruits, which is affected by mineral nutrients. Therefore, this study evaluated nutrient soil availability and its influence on nutritional status of trees based on the determination of leaf and fruit nutrient concentrations, fruit characteristics, and post harvest quality. Eleven commercial groves with trees older than 4-yr and differently managed were studied. Plots with six trees in each grove were sampled for soil (0-20 cm depth layer), leaf and fruit analyses with three replicates. Correlation coefficients were pair wised established for all variables. The results showed that N leaf concentration was well correlated with green color of fruit peel as measured by a color index (r = -0.71**), and which was optimum with Leaf-N around 22 g kg-1. Leaf-Ca was inversely correlated with fruit water loss after 14-day interval from harvest (r = -0.54*) demonstrating that Ca plays an important role in Tahiti fruit shelf-life. Data also suggested that increased fruit K concentration correlated with increased fruit water losses during storage (r >0.58*).

Response of the Thermal Conductivity as a Function of Water Content of a Burnt Mediterranean Loam Soil

The purpose of this research is to explore the variability on the soil thermal conductivity -λ- after a prescribe fire, and to assess the effects of the ashes on the heat transfer once it"s were incorporated into the soil matrix. Sampling plot was located in the Montgrí Massif (NE of Spain). A set of 42 soil samples between surface and 5 cm depth was collected before and after the fire. To characterize the soil chemical and physical variables were analyzed. To determine the vari-ability on the soil λ a dry-out curve per scenario (before and after fire) was determined. SoilRho® method based on ASTM D-5334-08 which was validated by LabFerrer was used. Soil thermal conductivity has shown changes in their values. Indeed, in all moisture scenarios the values of soil λ decreased after soil was burnt. The critical point in the rela-tionship ϴ (λ) for the soil after fire which always was stronger than soil before to be burnt. Soil with"white" ashes showed a high thermal conductivity. An X-Ray diffractometry analysis allowed to clarify and to verify these results. To sum up, we could say that thermal conductivity presents changes when the scenario changes, i.e. before and after to be burnt. On the other hand, the volume of ashes incorporated on the soil increased the differences between no burnt and burnt soil, showing even some improvements on the heat transfer when water content started to govern the process.

Distribution Patterns of Soil Properties in a Rural Mediterranean Area in Northeastern Spain

Soil properties on the Cap de Creus Peninsula, NE Spain depend primarily on scarce agricultural practices and early abandonment. In the study area, 90% of which is mainly covered by Cistus shrubs, 8 environments representing variations in land use/land cover and soil properties at different depths were identified. In each environment variously vegetated areas were selected and sampled. The soils, collected at different depths, were classified as Lithic Xerorthents according to the United States Department of Agriculture system of soil classification (USDA-NRCS 1975). Differences in soil properties were largely found according to the evolution of the plant canopy and the land use history. To identify underlying patterns in soil properties related to environmental evolution, factor analysis was performed and factor scores were used to determine how the factor patterns varied between soil variables, soil depths and selected environments. The three-factor model always accounted for 80% of the total variation in the data at the different soil depths. Organic matter was the more relevant soil property at 0–2 cm depth, whereas active minerals (silt and clay) were found to be the most relevant soil parameters controlling soil dynamics at the other depths investigated. Results showed that vineyards and olive tree soils are poorly developed and present worse conditions for mineral and organic compounds. Analysis of factor scores allowed independent assessment of soils, depth and plant cover and demonstrated that soils present the best physico-chemical characteristics under Erica arborea and meadows. In contrast, soils under Cistus monspeliensis were less nutrient rich and less well structured

VIS-NIR SPECTROMETRY, SOIL PHOSPHATE EXTRACTION METHODS AND INTERACTIONS OF SOIL ATTRIBUTES

The objective of this study was to evaluate the relationships between the spectra in the Vis-NIR range and the soil P concentrations obtained from the PM and Prem extraction methods as well as the effects of these relationships on the construction of models predicting P concentration in Oxisols. Soil samples' spectra and their PM and Prem extraction solutions were determined for the Vis-NIR region between 400 and 2500 nm. Mineralogy and/or organic matter content act as primary attributes allowing correlation of these soil phosphorus fractions with the spectra, mainly at wavelengths between 450-550, 900-1100 nm, near 1400 nm and between 2200-2300 nm. However, the regression models generated were not suitable for quantitative phosphate analysis. Solubilization of organic matter and reactions during the PM extraction process hindered correlations between the spectra and these P soil fractions. For Prem,, the presence of Ca in the extractant and preferential adsorption by gibbsite and iron oxides, particularly goethite, obscured correlations with the spectra.

Spectrophotometric determination of arsenic in soil samples using 2-(5-bromo-2-pyridylazo)-5-di-ethylaminophenol (Br-PADAP)

In this paper, a new, simple and sensitive method for arsenic determination in soil is proposed. This is based on the reduction of silver (I) and iron (III) ions by arsine followed by a complexation reaction of iron (II) with the spectrophotometric reagent Br-PADAP 2-(5-bromo-2-pyridylazo)-5-di-ethylaminophenol. Arsenic determination with a Sandell's sensitivity of 3.1 10-4 cm-2, linear range from 0.1 µg ml-1 to 2.0 µg ml-1 (r560 = 0.9995), molar absorptivity of 2.45 10(5) l mol-1 cm-1 and a concentration detection limit of 1.4 ng ml-1 (3s) were obtained using a 10 ml sample volume. Selectivity was increased with the use of EDTA as a masking agent. The proposed method was applied for arsenic determination in the presence of several ions amounts in digested soil samples. The results revealed that antimony (III), mercury (II), germanium (IV), platinum (IV) interferes at all analyzed proportions. The interferences can be easily removed by the use of EDTA. Precision and accuracy obtained were satisfactory with a R.S.D. < 5 %. Recovery of arsenic in soil samples varied from 95.55 to 102.70 % with a mean of 99.63 %. These results demonstrated that the proposed method is applicable for arsenic analysis in different soil samples.

Elemental analysis of wood materials by external millibeam thick target PIXE

PIXE (Particle Induce X-ray Emission spectrometry) was used for analysing stem bark and stem wood of Scots pine, Norway spruce and Silver birch. Thick samples were irradiated, in laboratory atmosphere, with 3 MeV protons and the beam current was measured indirectly using a photo multiplicator (PM) tube. Both point scans and bulk analyses were performed with the 1 mm diameter proton beam. In bulk analyses, whole bark and sectors of discs of the stem wood were dry ashed at 550 ˚C. The ashes were homogenised by shaking and prepared to target pellets for PIXE analyses. This procedure generated representative samples to be analysed, but the enrichment also enabled quantification of some additional trace elements. The ash contents obtained as a product of the sample preparation procedure also showed to be of great importance in the evaluation of results in environmental studies. Spot scans from the pith of pine wood outwards, showed clearly highest concentrations of manganese, calcium and zinc in the first spot irradiated, or 2-3 times higher than in the surrounding wood. For stem wood from the crown part of a pine this higher concentration level was found in the first four spots/mms, including the pith and the two following growth rings. Zinc showed increasing concentrations outwards in sapwood of the pine stem, with the over-all lowest concentrations in the inner half of the sapwood. This could indicate emigration of this element from sapwood being under transformation to heartwood. Point scans across sapwood of pine and spruce showed more distinct variations in concentrations relative to hearth wood. Higher concentrations of e.g. zinc, calcium and manganese were found in earlywood than in denser latewood. Very high concentrations of iron and copper were also seen for some earlywood increments. The ash content of stem bark is up to and order higher than for the stem wood. However, when the elemental concentration in ashes of bark and wood of the same disc were compared, these are very similar – this when trees are growing at spots with no anthropogenic contamination from the atmosphere. The largest difference was obtained for calcium which appeared at two times high concentrations in ashes of bark than in ashes of the wood (ratio of 2). Pine bark is often used in monitoring of atmospheric pollution, where concentrations in bark samples are compared. Here an alternative approach is suggested: Bark and the underlying stem wood of a pine trees are dry ashed and analysed. The elemental concentration in the bark ash is then compared to the concentration of the same element in the wood ash. Comparing bark to wood includes a normalisation for the varying availability of an element from the soil at different sites. When this comparison is done for the ashes of the materials, a normalisation is also obtained for the general and locally different enrichment of inorganic elements from wood to bark. Already a ratio >2 between the concentration in the bark ash and the concentration in the wood ash could indicate atmospheric pollution. For monitoring where bark is used, this way of “inwards” comparison is suggested - instead of comparing to results from analyses of bark from other trees (read reference areas), growing at sites with different soil and, locally, different climate conditions. This approach also enables evaluation of atmospheric pollution from sampling of only relative few individual trees –preferable during forest felling.