950 resultados para Molybdenum in the soil
Resumo:
Results from a large scale soil mapping on the North Frisian mainland indicate, that field characteristics, particularly the grain-size, bedding, and degree of compaction, with in general determine the soil units mapped, are closely correlated with each other and with other field and laboratory data. Exchangable ions and the Ca/Mg-ratio, however, indicate no explainable connections with the soil units and with most of the other field characteristics but are determined postsedimentarily by processes of the development of soil and landscape, such as desalting and decalcification, silicate weathering, fresh- and salt-water innundations, salty precipitations, salty groundwater and fertilization. Therefore the Ca/Mg-ratio is not suitable to differentiate between more clayey compacted Knick-marsh soils and less clayey permeable Klei-marsh soils. The results confirm that marsh-soils may only be classified and mapped by means of all available field-data which have to be supplemented by laboratory investigations.
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The data files give the basic field and laboratory data on five ponds in the northeast Siberian Arctic tundra on Samoylov. The files contain water and soil temperature data of the ponds, methane fluxes, measured with closed chambers in the centres without vascular plants and the margins with vascular plants, the contribution of plant mediated fluxes on total methane fluxes, the gas concentrations (methane and dissolved inorganic carbon, oxygen) in the soil and the water column of the ponds, microbial activities (methane production, methane oxidation, aerobic and anaerobic carbon dioxide production), total carbon pools in the different horizons of the bottom soils, soil bulk density, soil substance density, and soil porosity.
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To project the future development of the soil organic carbon (SOC) storage in permafrost environments, the spatial and vertical distribution of key soil properties and their landscape controls needs to be understood. This article reports findings from the Arctic Lena River Delta where we sampled 50 soil pedons. These were classified according to the U.S.D.A. Soil Taxonomy and fall mostly into the Gelisol soil order used for permafrost-affected soils. Soil profiles have been sampled for the active layer (mean depth 58±10 cm) and the upper permafrost to one meter depth. We analyze SOC stocks and key soil properties, i.e. C%, N%, C/N, bulk density, visible ice and water content. These are compared for different landscape groupings of pedons according to geomorphology, soil and land cover and for different vertical depth increments. High vertical resolution plots are used to understand soil development. These show that SOC storage can be highly variable with depth. We recommend the treatment of permafrost-affected soils according to subdivisions into: the surface organic layer, mineral subsoil in the active layer, organic enriched cryoturbated or buried horizons and the mineral subsoil in the permafrost. The major geomorphological units of a subregion of the Lena River Delta were mapped with a land form classification using a data-fusion approach of optical satellite imagery and digital elevation data to upscale SOC storage. Landscape mean SOC storage is estimated to 19.2±2.0 kg C/m**2. Our results show that the geomorphological setting explains more soil variability than soil taxonomy classes or vegetation cover. The soils from the oldest, Pleistocene aged, unit of the delta store the highest amount of SOC per m**2 followed by the Holocene river terrace. The Pleistocene terrace affected by thermal-degradation, the recent floodplain and bare alluvial sediments store considerably less SOC in descending order.
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Oil polluted and not oil polluted soils (crude oil hydrocarbons contents: 20-92500 mg/kg dry soil mass) under natural grass and forest vegetation and in a bog in the Russian tundra were compared in their principal soil ecological parameters, the oil content and the microbial indicators. CFE biomass-C, dehydrogenase and arylsulfatase activity were enhanced with the occurrence of crude oil. Using these parameters for purposes of controlling remediation and recultivation success it is not possible to distinguish bctween promotion of microbial activity by oil carbon or soil organic carbon (SOC). For this reason we think that these parameters are not appropriate to indicate a soil damage by an oil impact. In contrast the metabolie quotient (qC02), calculated as the ratio between soil basal respiration and the SIR biomass-C was adequate to indicate a high crude oil contamination in soil. Also, the ß-glucosidase activity (parameter ß-GL/SOC) was correlated negatively with oil in soil. The indication of a soil damage by using the stress parameter qCO, or the specific enzyme activities (activity/SOC) minimizes the promotion effect of the recent SOC content on microbial parameters. Both biomass methods (SIR, CFE) have technical problems in application for crude oil-contaminated and subarctic soils. CFE does not reflect the low C_mic level of the cold tundra soils. We recommend to test every method for its suitability before any data collection in series as well as application for cold soils and the application of ecophysiological ratios as R_mic/C_mic, C_mic/SOC or enzymatic activity/SOC instead of absolute data.
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This collection contains measurements of vegetation and soil surface cover measured on the plots of the different sub-experiments at the field site of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. The following series of datasets are contained in this collection: 1. Measurements of vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the species that have been sown into the plots to create the gradient of plant diversity.
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Soil temperature (in °C) was determined using a frequency domain sensor probe (WET-2 Sensor, Delta-T Devices, Cambridge, United Kingdom) on 1st August 2013. The device was inserted from the top 6 cm deep (length of the prongs) into the soil. The average of three measurements on the same day was calculated. All data where measured in the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown in the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, or 4 functional groups). Plots were maintained by bi-annual weeding and mowing.
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Soil porosity is the fraction of total volume occupied by pores or voids measured at matric potential 0. To measure soil porosity, soil samples were taken from each plot using sample rings with an internal diameter of 57 mm and height of 40.5 mm (inner volume of Vs=100 cm3). The samples were placed on a sand bed box with water level set to allow saturation of the samples with water. After 48 h the samples were weighed (ms), oven dried at 105 °C and weighed again to determine the dry weight (md). We calculated soil porosity (n [%]) using the density of water (?w=1 g cm?3), n=100 ? (mw-md) / (?w?Vs). To account for the spatial variation of soil properties, three replicates were taken per plot, approximately 2, 3 and 4 weeks after the flood that occurred at the field site during June 2013. Data are the average soil porosity values per plot. All data where measured in the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown in the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, or 4 functional groups). Plots were maintained by bi-annual weeding and mowing.
Resumo:
Soil temperature (in °C) was determined using a PT100 resistance thermometer that was inserted 5 cm into the ground. Soil temperature was recorded every hour of the day during July 2006. The average of five monthly measurements of soil temperature was calculated. All data where measured in the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown in the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, or 4 functional groups). Plots were maintained by bi-annual weeding and mowing.
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With increased warming in the Arctic, permafrost thaw may induce localized physical disturbance of slopes. These disturbances, referred to as active layer detachments (ALDs), redistribute soil across the landscape, potentially releasing previously unavailable carbon (C). In 2007–2008, widespread ALD activity was reported at the Cape Bounty Arctic Watershed Observatory in Nunavut, Canada. Our study investigated organic matter (OM) composition in soil profiles from ALD-impacted and undisturbed areas. Solid-state 13C nuclear magnetic resonance (NMR) and solvent-extractable biomarkers were used to characterize soil OM. Throughout the disturbed upslope profile, where surface soils and vegetation had been removed, NMR revealed low O-alkyl C content and biomarker analysis revealed low concentrations of solvent-extractable compounds suggesting enhanced erosion of labile-rich OM by the ALD. In the disturbed downslope region, vegetation remained intact but displaced material from upslope produced lateral compression ridges at the surface. High O-alkyl content in the surface horizon was consistent with enrichment of carbohydrates and peptides, but low concentrations of labile biomarkers (i.e., sugars) suggested the presence of relatively unaltered labile-rich OM. Decreased O-alkyl content and biomarker concentrations below the surface contrasted with the undisturbed profile and may indicate the loss of well-established pre-ALD surface drainage with compression ridge formation. However, pre-ALD profile composition remains unknown and the observed decreases may result from nominal pre-ALD OM inputs. These results are the first to establish OM composition in ALD-impacted soil profiles, suggesting reallocation of permafrost-derived soil C to areas where degradation or erosion may contribute to increased C losses from disturbed Arctic soils.
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Climate warming is predicted to increase summer air temperatures in the Arctic, warming soils and enhancing microbial decomposition of soil organic matter. Given the size of the soil carbon stores in the Arctic, even a fraction of its release as CO2 to the atmosphere could result in a positive feedback to climate warming. Fertilizers have been used in the past to quickly increase soil solution nutrients pools to mimic predicted concentrations under climate warming. However, because it may have inadvertent affects on the soil microbial community, fertilizer-induced patterns in microbial decomposition may be unrealistic. This study aimed to better understand the proposed mechanism of enhanced microbial decomposition under nutrient addition and warming treatments to discern whether warming alone is enough to stimulate enhanced microbial decomposition, or if nutrients in excess (i.e. chronic high nutrient additions) are necessary to yield such a response. I investigated the impacts of 10 years of greenhouse summer warming, chronic low nutrient factorial addition (5 g N and 1g P m-2 year-1, respectively), and chronic high nutrient factorial addition (10 g N and 5g P m-2 year-1, respectively) treatments on a mesic birch hummock tundra ecosystem near Daring Lake, NWT, Canada. Soil microbial nutrient pools, soil solution nutrient pools, and microbial community structure were measured in the upper organic, lower organic, and uppermost mineral soil depth intervals of all treatment plots in Spring 2014. Interestingly, the low nutrient additions did not yield any significant trends, yet the warming treatment increased soil bacterial richness suggesting a legacy effect of warming from the previous summers. Enhanced microbial nutrient uptake occurred only in the high nutrient addition treatments, and did not significantly alter soil carbon at least within the ten year period of this experiment. Together, these results and the absence of significant impacts of the low nutrient and greenhouse warming treatments suggests that nutrient and carbon cycling in these low arctic soils may be resilient against climate warming, at least over the initial decades.
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The complexity of modern geochemical data sets is increasing in several aspects (number of available samples, number of elements measured, number of matrices analysed, geological-environmental variability covered, etc), hence it is becoming increasingly necessary to apply statistical methods to elucidate their structure. This paper presents an exploratory analysis of one such complex data set, the Tellus geochemical soil survey of Northern Ireland (NI). This exploratory analysis is based on one of the most fundamental exploratory tools, principal component analysis (PCA) and its graphical representation as a biplot, albeit in several variations: the set of elements included (only major oxides vs. all observed elements), the prior transformation applied to the data (none, a standardization or a logratio transformation) and the way the covariance matrix between components is estimated (classical estimation vs. robust estimation). Results show that a log-ratio PCA (robust or classical) of all available elements is the most powerful exploratory setting, providing the following insights: the first two processes controlling the whole geochemical variation in NI soils are peat coverage and a contrast between “mafic” and “felsic” background lithologies; peat covered areas are detected as outliers by a robust analysis, and can be then filtered out if required for further modelling; and peat coverage intensity can be quantified with the %Br in the subcomposition (Br, Rb, Ni).
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Oomycete diseases cause significant losses across a broad range of crop and aquaculture commodities worldwide. These losses can be greatly reduced by disease management practices steered by accurate and early diagnoses of pathogen presence. Determinations of disease potential can help guide optimal crop rotation regimes, varietal selections, targeted control measures, harvest timings and crop post-harvest handling. Pathogen detection prior to infection can also reduce the incidence of disease epidemics. Classical methods for the isolation of oomycete pathogens are normally deployed only after disease symptom appearance. These processes are often-time consuming, relying on culturing the putative pathogen(s) and the availability of expert taxonomic skills for accurate identification; a situation that frequently results in either delayed application, or routine ‘blanket’ over-application of control measures. Increasing concerns about pesticides in the environment and the food chain, removal or restriction of their usage combined with rising costs have focussed interest in the development and improvement of disease management systems. To be effective, these require timely, accurate and preferably quantitatve diagnoses. A wide range of rapid diagnostic tools, from point of care immunodiagnostic kits to next generation nucleotide sequencing have potential application in oomycete disease management. Here we review currently-available as well as promising new technologies in the context of commercial agricultural production systems, considering the impacts of specific biotic and abiotic and other important factors such as speed and ease of access to information and cost effectiveness