Chemical nature of soil humified fractions and their bioactivity

The aim of this work was to evaluate the humus composition from an Ultisol from Campos dos Goytacazes, RJ, Brazil. Soil samples of four depths (0-0.05, 0.05-0.10, 0.10-0.20 and 0.20-0.40 m) and its chemical nature were analysed by elemental composition, E4/E6 ratios and Fourier transformed infrared spectroscopy. The bioactivity of these humified substances was evaluated through their action on maize root growth and H+-ATPase activity of roots microsomes. In topsoil, the content of high condensed alkaline soluble humic substances is greater than that found in the subsuperficial layers. The chemical nature of humic and fulvic acids also varied with the soil depth. The humic acids isolated from the soil samples exhibited higher bioactivity compared with the fulvic acids. Moreover, the results suggest that more condensed humic substances can promote highest stimulation of the microsomal H+-ATPases from maize roots. These data reinforce the concept that the activity of the H+ pumps can be used as a biochemical marker for evaluation of humic substances bioactivity.

Pinpointing Suspect Triplicate Unconfined Compressive Strength Values in a Series of Soil-Additive Strength Determinations, HR-1, Progress Report, 1961

In recent years, various types of organic and inorganic materials have been investigated for use as soil stabilizing agents in the construction of highways and airports. Since the properties and environmental conditions of soils vary so greatly from place to place, a stabilizing agent that is suitable for one type of soil may not be satisfactory for another. As a result, it is often desirable to evaluate several stabilizing agents under varying treatment conditions before deciding on a specific one to be used with a given soil. In addition many research programs have been initiated which investigate the effects of these stabilizing agents upon soils.

Bacterial diversity of soil under eucalyptus assessed by 16S rDNA sequencing analysis

Studies on the impact of Eucalyptus spp. on Brazilian soils have focused on soil chemical properties and isolating interesting microbial organisms. Few studies have focused on microbial diversity and ecology in Brazil due to limited coverage of traditional cultivation and isolation methods. Molecular microbial ecology methods based on PCR amplified 16S rDNA have enriched the knowledge of soils microbial biodiversity. The objective of this work was to compare and estimate the bacterial diversity of sympatric communities within soils from two areas, a native forest (NFA) and an eucalyptus arboretum (EAA). PCR primers, whose target soil metagenomic 16S rDNA were used to amplify soil DNA, were cloned using pGEM-T and sequenced to determine bacterial diversity. From the NFA soil 134 clones were analyzed, while 116 clones were analyzed from the EAA soil samples. The sequences were compared with those online at the GenBank. Phylogenetic analyses revealed differences between the soil types and high diversity in both communities. Soil from the Eucalyptus spp. arboretum was found to have a greater bacterial diversity than the soil investigated from the native forest area.

Evaluation of the Consolid System of Soil Stabilization, MLR-86-10, 1987

The Consolid System by American Consolid Inc. is a three product system that, according to product literature, "enables any soil, found anywhere, to be upgraded to achieve better characteristics necessary in improving road life and quality". Consolid was evaluated along with mixes of cement-fly ash and hydrated lime on two soils. The soils were an A-2-4(0) with zero plasticity index and an A-7-8(18) with a 31 plasticity index. American Consolid Inc. recommended an application rate of 0.10% Consolid 444 and 1.00% Conservex by dry soil weight. The application rate chosen for cement-fly ash was 5% cement and 15% fly ash and for hydrated lime it was 6.5%. Testing involved triaxial testing of specimens after water soaking, unconfined compressive strength of specimens before and after water soaking, and freeze and thaw testing of specimens after water soaking. All specimens were compacted to standard proctor at optimum moisture. The cement-fly ash treated mixes had the highest strength and durability followed by the hydrated lime treated mixes.

Ecology and the challenge of a multifunctional use of soil

Soil zoology and soil ecology have become very active fields of research since the early 1990s. A search in the ISI Web of Science databases showed a steady increase in publications about that theme over the last two decades, and 3,612 bibliographic references were found for that theme for the period of 2004 to 2008. The researches covered mostly soil environmental issues, toxicology and ecology. The issue of theoretical development in soil ecology is discussed, and arguments are presented against the idea that the soil ecology theory is deficient. Finally, the need for a general model of soil function and soil management is discussed and some options are presented to reach this goal.

A new method to simulate the hydrological state of soil under natural conditions

Micro, macro and mesofauna in the soil often respond to fluctuating environmental conditions, resulting in changes of abundance and community structure. Effects of changing soil parameters are normally determined with samples taken in the field and brought to the laboratory, i.e. where natural environmental conditions may not apply. We devised a method (STAFD - soil tubes for artificial flood and drought), which simulates the hydrological state of soil in situ using implanted cores. Control tubes were compared with treatment tubes in which floods of 15, 30, 60 and 90 days, and droughts of 60, 90 and 120 days were simulated in the field. Flooding and drought were found to reduce number of individuals in all soil faunal groups, but the response to drought was slower and not in proportion to the expected decrease of the water content. The results of the simulated floods in particular show the value of the STAFD method for the investigation of such extreme events in natural habitats.

Spatiotemporal dynamics of soil rotifers in a South-Bohemian beech forest

The objective of this work was to determine seasonal variation and vertical distribution of the soil rotifer assemblage in a climax beech forest in South Bohemia. During 2005, soil rotifer was investigated to the species level. Soil samples of 10 cm² and 10 cm in depth were divided into five layers, which were processed separately. Thirty one rotifer species were identified during the investigation. Dominant species significantly changed throughout the seasons. The most abundant species were Encentrum arvicola and Wierzejskiella vagneri among the monogononts, and Adineta steineri, Ceratotrocha cornigera, Habrotrocha filum, Habrotrocha ligula, Macrotrachela plicata, Mniobia tentans, Mniobia incrassata and Mniobia granulosa among the bdelloids. Mean Shannon diversity index varied from 1.99 to 2.63. Total rotifer abundance varied from 212±63 to 513±127 10³ individuals m-2 along the year, with the highest numbers found in May, and the lowest in July. The great part of the community was concentrated in the upper (fresh litter) and second (partially decomposed litter) layers and significantly decreased in the soil vertical profile on all sampling dates. The highest rotifer density of 43 individuals g-1 was found in the upper layer in May.

Functions of the peroxisome proliferator-activated receptor (PPAR) alpha and beta in skin homeostasis, epithelial repair, and morphogenesis.

The three peroxisome proliferator-activated receptors (PPAR alpha, PPAR beta, and PPAR gamma) are ligand-activated transcription factors belonging to the nuclear hormone receptor superfamily. They are regarded as being sensors of physiological levels of fatty acids and fatty acid derivatives. In the adult mouse skin, they are found in hair follicle keratinocytes but not in interfollicular epidermis keratinocytes. Skin injury stimulates the expression of PPAR alpha and PPAR beta at the site of the wound. Here, we review the spatiotemporal program that triggers PPAR beta expression immediately after an injury, and then gradually represses it during epithelial repair. The opposing effects of the tumor necrosis factor-alpha and transforming growth factor-beta-1 signalling pathways on the activity of the PPAR beta promoter are the key elements of this regulation. We then compare the involvement of PPAR beta in the skin in response to an injury and during hair morphogenesis, and underscore the similarity of its action on cell survival in both situations.

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.

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.

Tissue-specific opposing functions of the inflammasome adaptor ASC in the regulation of epithelial skin carcinogenesis.

A chronic inflammatory microenvironment favors tumor progression through molecular mechanisms that are still incompletely defined. In inflammation-induced skin cancers, IL-1 receptor- or caspase-1-deficient mice, or mice specifically deficient for the inflammasome adaptor protein ASC (apoptosis-associated speck-like protein containing a CARD) in myeloid cells, had reduced tumor incidence, pointing to a role for IL-1 signaling and inflammasome activation in tumor development. However, mice fully deficient for ASC were not protected, and mice specifically deficient for ASC in keratinocytes developed more tumors than controls, suggesting that, in contrast to its proinflammatory role in myeloid cells, ASC acts as a tumor-suppressor in keratinocytes. Accordingly, ASC protein expression was lost in human cutaneous squamous cell carcinoma, but not in psoriatic skin lesions. Stimulation of primary mouse keratinocytes or the human keratinocyte cell line HaCaT with UVB induced an ASC-dependent phosphorylation of p53 and expression of p53 target genes. In HaCaT cells, ASC interacted with p53 at the endogenous level upon UVB irradiation. Thus, ASC in different tissues may influence tumor growth in opposite directions: it has a proinflammatory role in infiltrating cells that favors tumor development, but it also limits keratinocyte proliferation in response to noxious stimuli, possibly through p53 activation, which helps suppressing tumors.

Correlation of physical and chemical attributes of soil with sugarcane yield

The objective of this work was to evaluate the correlation between sugarcane yield and some physical and chemical attributes of soil. For this, a 42‑ha test area in Araras, SP, Brazil, was used. Soil properties were determined from samples collected at the beginning of the 2003/2004 harvest season, using a regular 100x100 m grid. Yield assessment was done with a yield monitor (Simprocana). Correlation analyses were performed between sugarcane yield and the following soil properties: pH, pH CaCl2, N, C, cone index, clay content, soil organic matter, P, K, Ca, Mg, H+AL, cation exchange capacity, and base saturation. Correlation coefficients were respectively ‑0.05, ‑0.29, 0.33, 0.41, ‑0.27, 0.22, 0.44, ‑0.24, trace, ‑0.06, 0.01, 0.32, 0.14, and 0.04. Correlations of chemical and physical attributes of soil with sugarcane yield are weak, and, per se, they are not able to explain sugarcane yield variation, which suggests that other variables, besides soil attributes, should be analysed.

Biochar effect on the mineralization of soil organic matter

The objective of this work was to verify whether the addition of biochar to the soil affects the degradation of litter and of soil organic matter (SOM). In order to investigate the effect of biochar on the mineralization of barley straw, soil was incubated with 14C-labelled barley straw with or without unlabelled biochar. To investigate the effect of straw on the mineralization of biochar, soil was incubated with 14C-labelled biochar with or without straw. In addition, to investigate the effect of biochar on old SOM, a soil labelled by applying labelled straw 40 years ago was incubated with different levels of biochar. All experiments had a control treatment, without any soil amendment. The effect of biochar on the straw mineralization was small and nonsignificant. Without biochar, 48±0.2% of the straw carbon was mineralized within the 451 days of the experiment. In comparison, 45±1.6% of C was mineralized after biochar addition of 1.5 g kg-1. In the SOM-labelled soil, the organic matter mineralized more slowly with the increasing doses of biochar. Biochar addition at 7.7 g kg-1 reduced SOM mineralization from 6.6 to 6.3%, during the experimental period. The addition of 15.5 g kg-1 of biochar reduced the mineralized SOM to 5.7%. There is no evidence of increased degradation of either litter or SOM due to biochar addition; consequently, there is no evidence of decreased stability of SOM.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.