12 resultados para fertility of soil

em Université de Lausanne, Switzerland


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Water movement in unsaturated soils gives rise to measurable electrical potential differences that are related to the flow direction and volumetric fluxes, as well as to the soil properties themselves. Laboratory and field data suggest that these so-called streaming potentials may be several orders of magnitudes larger than theoretical predictions that only consider the influence of the relative permeability and electrical conductivity on the self potential (SP) data. Recent work has improved predictions somewhat by considering how the volumetric excess charge in the pore space scales with the inverse of water saturation. We present a new theoretical approach that uses the flux-averaged excess charge, not the volumetric excess charge, to predict streaming potentials. We present relationships for how this effective excess charge varies with water saturation for typical soil properties using either the water retention or the relative permeability function. We find large differences between soil types and the predictions based on the relative permeability function display the best agreement with field data. The new relationships better explain laboratory data than previous work and allow us to predict the recorded magnitudes of the streaming potentials following a rainfall event in sandy loam, whereas previous models predict values that are three orders of magnitude too small. We suggest that the strong signals in unsaturated media can be used to gain information about fluxes (including very small ones related to film flow), but also to constrain the relative permeability function, the water retention curve, and the relative electrical conductivity function.

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Plants influence the behavior of and modify community composition of soil-dwelling organisms through the exudation of organic molecules. Given the chemical complexity of the soil matrix, soil-dwelling organisms have evolved the ability to detect and respond to these cues for successful foraging. A key question is how specific these responses are and how they may evolve. Here, we review and discuss the ecology and evolution of chemotaxis of soil nematodes. Soil nematodes are a group of diverse functional and taxonomic types, which may reveal a variety of responses. We predicted that nematodes of different feeding guilds use host-specific cues for chemotaxis. However, the examination of a comprehensive nematode phylogeny revealed that distantly related nematodes, and nematodes from different feeding guilds, can exploit the same signals for positive orientation. Carbon dioxide (CO(2)), which is ubiquitous in soil and indicates biological activity, is widely used as such a cue. The use of the same signals by a variety of species and species groups suggests that parts of the chemo-sensory machinery have remained highly conserved during the radiation of nematodes. However, besides CO(2), many other chemical compounds, belonging to different chemical classes, have been shown to induce chemotaxis in nematodes. Plants surrounded by a complex nematode community, including beneficial entomopathogenic nematodes, plant-parasitic nematodes, as well as microbial feeders, are thus under diffuse selection for producing specific molecules in the rhizosphere that maximize their fitness. However, it is largely unknown how selection may operate and how belowground signaling may evolve. Given the paucity of data for certain groups of nematodes, future work is needed to better understand the evolutionary mechanisms of communication between plant roots and soil biota.

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This paper reviews the role of alluvial soils in vegetated gravelly river braid plains. When considering decadal time scales of river evolution, we argue that it becomes vital to consider soil development as an emergent property of the developing ecosystem. Soil processes have been relatively overlooked in accounts of the interactions between braided river processes and vegetation, although soils have been observed on vegetated fluvial landforms. We hypothesise that soil development plays a major role in the transition (speed and pathway) from a fresh sediment deposit to a vegetated soil-covered landform. Disturbance (erosion and/or deposition), vertical sediment structure (process history), vegetation succession, biological activity and water table fluctuation are seen as the main controls on early alluvial soil evolution. Erosion and deposition processes may not only act as soil disturbing agents, but also as suppliers of ecosystem resources, because of their role in delivering and changing access (e.g. through avulsion) to fluxes of water, fine sediments and organic matter. In turn, the associated initial ecosystem may influence further fluvial landform development, such as through the trapping of fine-grained sediments (e.g. sand) by the engineering action of vegetation and the deposit stabilisation by the developing above and belowground biomass. This may create a strong feedback between geomorphological processes, vegetation succession and soil evolution which we summarise in a conceptual model. We illustrate this model by an example from the Allondon River (CH) and identify the research questions that follow.

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Particular bacterial strains in certain natural environments prevent infectious diseases of plant roots. How these bacteria achieve this protection from pathogenic fungi has been analysed in detail in biocontrol strains of fluorescent pseudomonads. During root colonization, these bacteria produce antifungal antibiotics, elicit induced systemic resistance in the host plant or interfere specifically with fungal pathogenicity factors. Before engaging in these activities, biocontrol bacteria go through several regulatory processes at the transcriptional and post-transcriptional levels.

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The long-term impact of irrigation on a Mediterranean sandy soil irrigated with Treated wastewater (TWW) since 1980 was evaluated. The main soil properties (CEC, pH, size distribution, exchangeable cations and chloride, hydraulic conductivity) as well as the organic matter and Cu, Cr and Pb speciation in an irrigated soil and a non-irrigated control soil at various soil depths were monitored and compared during a 2 years experiment. In this first part, the evolution of the physico-chemical soil properties was described. The irrigation with TWW was beneficial with regard to water and nutrient supplying. All the exchangeable cations other than K(+) were higher in the irrigated soil than in the reference one. A part of the exchangeable cations was not fixed on the exchange complex but stored as labile salts or in concentrated soil solution. Despite the very sandy soil texture, both saturated and unsaturated hydraulic conductivity exhibited a significant diminution in the irrigated soil, but remained high enough to allow water percolation during rainy periods and subsequent leaching of accumulated salts, preventing soil salinization. In the irrigated soil, exchangeable sodium percentage (ESP) exhibited high values (20% on average) and the soil organic C was lower than in the reference. No significant effect was noticed on soil mineralogical composition due to irrigation. (C) 2010 Published by Elsevier Ltd.

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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.

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The impact of biocontrol strain Pseudomonas fluorescens CHA0 and of its genetically modified, antibiotic-overproducing derivative CHA0/pME3424 on a reconstructed population of the plant-beneficial Sinorhizobium meliloti bacteria was assessed in gnotobiotic systems. In sterile soil, the final density of the reconstructed S. meliloti population decreased by more than one order of magnitude in the presence of either of the Pseudomonas strains when compared to a control without addition of P. fluorescens. Moreover, there was a change in the proportion of each individual S. meliloti strain within the population. Plant tests also revealed changes in the nodulating S. meliloti population in the presence of strains CHA0 or CHA0/pME3424. In both treatments one S. meliloti strain, f43, was significantly reduced in its root nodule occupancy. Analysis of alfalfa yields showed a slight but statistically significant increase in shoot dry weight when strain CHA0 was added to the reconstructed S. meliloti population whereas no such effect was observed with CHA0/pME3424.

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Studying patterns of species distributions along elevation gradients is frequently used to identify the primary factors that determine the distribution, diversity and assembly of species. However, despite their crucial role in ecosystem functioning, our understanding of the distribution of below-ground fungi is still limited, calling for more comprehensive studies of fungal biogeography along environmental gradients at various scales (from regional to global). Here, we investigated the richness of taxa of soil fungi and their phylogenetic diversity across a wide range of grassland types along a 2800 m elevation gradient at a large number of sites (213), stratified across a region of the Western Swiss Alps (700 km(2)). We used 454 pyrosequencing to obtain fungal sequences that were clustered into operational taxonomic units (OTUs). The OTU diversity-area relationship revealed uneven distribution of fungal taxa across the study area (i.e. not all taxa are everywhere) and fine-scale spatial clustering. Fungal richness and phylogenetic diversity were found to be higher in lower temperatures and higher moisture conditions. Climatic and soil characteristics as well as plant community composition were related to OTU alpha, beta and phylogenetic diversity, with distinct fungal lineages suggesting distinct ecological tolerances. Soil fungi, thus, show lineage-specific biogeographic patterns, even at a regional scale, and follow environmental determinism, mediated by interactions with plants.

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The top soil of a 14.5 km(2) region at la Chaux-de-Fonds in the Swiss Jura is exceptionally rich in cadmium. It contains an average of 1.3 mg per kg of soil. The spatial distribution of the metal has no simple pattern that could be explained by atmospheric deposition or agricultural practices. Thin soil contained most of its Cd at the surface; in thicker soil Cd is mainly concentrated between 60 and 80 cm depth. No specific minerals or soil fractions could account for these accumulation, and the vertical distribution of Cd is best explained by leaching from the topsoil and further adsorption within layers of nearly neutral pH. The local Jurassic sedimentary rocks contained too little Cd to account for the Cd concentrations in the soil. Alpine gravels from glacial till were too sparse in soils to explain such a spreading of Cd. Moreover this origin is contradictory with the fact that Cd is concentrated in the sand fraction of soils. The respective distributions of Fe and Cd in soils, and soil fractions, suggested that the spreading of iron nodules accumulated during the siderolithic period (Eocene) was not the main source of Cd. Atmospheric deposition, and spreading of fertiliser or waste from septic tanks seem the only plausible explanation for the Cd concentrations, but at present few factors allow us to differentiate between them.

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Little is known about the ecology of soil inoculants used for pathogen biocontrol, biofertilization and bioremediation under field conditions. We investigated the persistence and the physiological states of soil-inoculated Pseudomonas protegens (previously Pseudomonas fluorescens) CHA0 (108 CFU g−1 surface soil) in different soil microbial habitats in a planted ley (Medicago sativa L.) and an uncovered field plot. At 72 days, colony counts of the inoculant were low in surface soil (uncovered plot) and earthworm guts (ley plot), whereas soil above the plow pan (uncovered plot), and the rhizosphere and worm burrows present until 1.2 m depth (ley plot) were survival hot spots (105-106 CFU g−1 soil). Interestingly, strain CHA0 was also detected in the subsoil of both plots, at 102-105 CFU g−1 soil between 1.8 and 2 m depth. However, non-cultured CHA0 cells were also evidenced based on immunofluorescence microscopy. Kogure's direct viable counts of nutrient-responsive cells showed that many more CHA0 cells were in a viable but non-culturable (VBNC) or a non-responsive (dormant) state than in a culturable state, and the proportion of cells in those non-cultured states depended on soil microbial habitat. At the most, cells in a VBNC state amounted to 34% (above the plow pan) and those in a dormant state to 89% (in bulk soil between 0.6 and 2 m) of all CHA0 cells. The results indicate that field-released Pseudomonas inoculants may persist at high cell numbers, even in deeper soil layers, and display a combination of different physiological states whose prevalence fluctuates according to soil microbial habitats.

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Very high concentrations of uranium (up to 4000 ppm) were found in a natural soil in the Dischma valley, an alpine region in the Grisons canton in Switzerland. The goal of this study was to examine the redox state and the nature of uranium binding in the soil matrix in order to understand the accumulation mechanism. Pore water profiles collected from Dischma soil revealed the establishment of anoxic conditions with increasing soil depth. A combination of chemical extraction methods and spectroscopy was applied to characterize the redox state and binding environment of uranium in the soil. Bicarbonate extraction under anoxic conditions released most of the uranium indicating that uranium occurs predominantly in the hexavalent form. Surprisingly, the uranium redox state did not vary greatly as a function of depth. X-ray absorption near edge spectroscopy (XANES), confirmed that uranium was present as a mixture of U(VI) and U(IV) with U(VI) dominating. Sequential extractions of soil samples showed that the dissolution of solid organic matter resulted in the simultaneous release of the majority of the soil uranium content (>95%). Extended X-ray absorption fine structure (EXAFS) spectroscopy also revealed that soil-associated uranium in the soil matrix was mainly octahedrally coordinated, with an average of 1.7 axial (at about 1.76 Å) and 4.6 to 5.3 equatorial oxygen atoms (at about 2.36 Å) indicating the dominance of a uranyl-like (UO22+) structure presumably mixed with some U(IV). An additional EXAFS signal (at about 3.2 Å) identified in some spectra suggested that uranium was also bound (via an oxygen atom) to a light element such as carbon, phosphorus or silicon. Gamma spectrometric measurements of soil profiles failed to identify uranium long-life daughter products in the soil which is an indication that uranium originates elsewhere and was transported to its current location by water. Finally, it was found that the release of uranium from the soil was significantly promoted at very low pH values (pH 2) and increased with increasing pH values (between pH 5 and 9).

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In order to evaluate the relationship between the apparent complexity of hillslope soil moisture and the emergent patterns of catchment hydrological behaviour and water quality, we need fine-resolution catchment-wide data on soil moisture characteristics. This study proposes a methodology whereby vegetation patterns obtained from high-resolution orthorectified aerial photographs are used as an indicator of soil moisture characteristics. This enables us to examine a set of hypotheses regarding what drives the spatial patterns of soil moisture at the catchment scale (material properties or topography). We find that the pattern of Juncus effusus vegetation is controlled largely by topography and mediated by the catchment's material properties. Characterizing topography using the topographic index adds value to the soil moisture predictions relative to slope or upslope contributing area (UCA). However, these predictions depart from the observed soil moisture patterns at very steep slopes or low UCAs. Copyright (c) 2012 John Wiley & Sons, Ltd.