982 resultados para STRATIFICATION


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During the Last Glacial Maximum, the climate was substantially colder and the carbon cycle was clearly different from the late Holocene. According to proxy data deep oceanic δ13C was very low, and the atmospheric CO2 concentration also reduced. Several mechanisms have been proposed to explain these changes, but none can fully explain the data, especially the very low deep ocean δ13C values. Oceanic core data show that the deep ocean was very cold and salty, which would lead to enhanced deep ocean stratification. We show that such an enhanced stratification in the coupled climate model CLIMBER-2 helps get very low deep oceanic δ13C values. Indeed the simulated δ13C reaches values as low as −0.8‰ in line with proxy data evidences. Moreover it increases the oceanic carbon reservoir leading to a small, yet robust, atmospheric CO2 drop of approximately 10 ppm.

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During the cold period of the Last Glacial Maximum (LGM, about 21 000 years ago) atmospheric CO2 was around 190 ppm, much lower than the pre-industrial concentration of 280 ppm. The causes of this substantial drop remain partially unresolved, despite intense research. Understanding the origin of reduced atmospheric CO2 during glacial times is crucial to comprehend the evolution of the different carbon reservoirs within the Earth system (atmosphere, terrestrial biosphere and ocean). In this context, the ocean is believed to play a major role as it can store large amounts of carbon, especially in the abyss, which is a carbon reservoir that is thought to have expanded during glacial times. To create this larger reservoir, one possible mechanism is to produce very dense glacial waters, thereby stratifying the deep ocean and reducing the carbon exchange between the deep and upper ocean. The existence of such very dense waters has been inferred in the LGM deep Atlantic from sediment pore water salinity and δ18O inferred temperature. Based on these observations, we study the impact of a brine mechanism on the glacial carbon cycle. This mechanism relies on the formation and rapid sinking of brines, very salty water released during sea ice formation, which brings salty dense water down to the bottom of the ocean. It provides two major features: a direct link from the surface to the deep ocean along with an efficient way of setting a strong stratification. We show with the CLIMBER-2 carbon-climate model that such a brine mechanism can account for a significant decrease in atmospheric CO2 and contribute to the glacial-interglacial change. This mechanism can be amplified by low vertical diffusion resulting from the brine-induced stratification. The modeled glacial distribution of oceanic δ13C as well as the deep ocean salinity are substantially improved and better agree with reconstructions from sediment cores, suggesting that such a mechanism could have played an important role during glacial times.

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In Mediterranean areas, conventional tillage increases soil organic matter losses, reduces soil quality, and contributes to climate change due to increased CO2 emissions. CO2 sequestration rates in soil may be enhanced by appropriate agricultural soil management and increasing soil organic matter content. This study analyzes the stratification ratio (SR) index of soil organic carbon (SOC), nitrogen (N) and C:N ratio under different management practices in an olive grove (OG) in Mediterranean areas (Andalusia, southern Spain). Management practices considered in this study are conventional tillage (CT) and no tillage (NT). In the first case, CT treatments included addition of alperujo (A) and olive leaves (L). A control plot with no addition of olive mill waste was considered (CP). In the second case, NT treatments included addition of chipped pruned branches (NT1) and chipped pruned branches and weeds (NT2). The SRs of SOC increased with depth for all treatments. The SR of SOC was always higher in NT compared to CT treatments, with the highest SR of SOC observed under NT2. The SR of N increased with depth in all cases, ranging between 0.89 (L-SR1) and 39.11 (L-SR3 and L-SR4).The SR of C:N ratio was characterized by low values, ranging from 0.08 (L-SR3) to 1.58 (NT1-SR2) and generally showing higher values in SR1 and SR2 compared to those obtained in SR3 and SR4. This study has evaluated several limitations to the SR index such as the fact that it is descriptive but does not analyze the behavior of the variable over time. In addition, basing the assessment of soil quality on a single variable could lead to an oversimplification of the assessment. Some of these limitations were experienced in the assessment of L, where SR1 of SOC was the lowest of the studied soils. In this case, the higher content in the second depth interval compared to the first was caused by the intrinsic characteristics of this soil's formation process rather than by degradation. Despite the limitations obtained SRs demonstrate that NT with the addition of organic material improves soil quality.

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Priest Pot is an example of the abundant ponds that, collectively, contribute crucially to species diversity. Despite extensive biological study, little has been reported about the physical framework that supports its ecological richness. This article elucidates the physical character of Priest Pot’s water column and thus that of similar water bodies. Vertical thermal microstructure profiles were recorded during summer 2003 and analyzed alongside concurrent meteorological data. During summer stratification, the thermal structure appeared to be dominated by surface heat fluxes. Surface wind stress, limited by sheltering vegetation, caused turbulent overturns once a surface mixed layer was present but appeared to contribute little to setting up the thermal structure. Variations in full-depth mean stratification occurred predominantly over seasonal and ∼5-day time scales, the passage of atmospheric pressure systems being posited as the cause of the latter. In the uppermost ∼0.5 m, where the stratification varied at subdaily time scales, turbulence was active (sensu Ivey and Imberger 1991) when this layer was mixed, with dissipation values ε ∼ 10−8 m2 s−3 and vertical diffusivity KZ = 10−4 — 10−6 m2 s−1. Where the water column was stratified, turbulence was strongly damped by both buoyancy and viscosity, and KZ was an order of magnitude smaller. Vertical transport in the mixed layer occurred via many small overturns (Thorpe scale r.m.s. and maximum values were typically 0.02 m and 0.10 m, respectively), and seston were fully mixed through the water column.

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The recent wide adoption of electronic medical records (EMRs) presents great opportunities and challenges for data mining. The EMR data are largely temporal, often noisy, irregular and high dimensional. This paper constructs a novel ordinal regression framework for predicting medical risk stratification from EMR. First, a conceptual view of EMR as a temporal image is constructed to extract a diverse set of features. Second, ordinal modeling is applied for predicting cumulative or progressive risk. The challenges are building a transparent predictive model that works with a large number of weakly predictive features, and at the same time, is stable against resampling variations. Our solution employs sparsity methods that are stabilized through domain-specific feature interaction networks. We introduces two indices that measure the model stability against data resampling. Feature networks are used to generate two multivariate Gaussian priors with sparse precision matrices (the Laplacian and Random Walk). We apply the framework on a large short-term suicide risk prediction problem and demonstrate that our methods outperform clinicians to a large margin, discover suicide risk factors that conform with mental health knowledge, and produce models with enhanced stability. © 2014 Springer-Verlag London.

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As apex predators in marine ecosystems, seabirds may primarily experience climate change impacts indirectly, via changes to their food webs. Observed seabird population declines have been linked to climate-driven oceanographic and food web changes. However, relationships have often been derived from relatively few colonies and consider only sea surface temperature (SST), so important drivers, and spatial variation in drivers, could remain undetected. Further, ex - plicit climate change projections have rarely been made, so longer-term risks remain unclear. Here, we use tracking data to estimate foraging areas for 11 black-legged kittiwake Rissa tridac - ty la colonies in the UK and Ireland, thus reducing reliance on single colonies and allowing calculation of colony-specific oceanographic conditions. We use mixed models to consider how SST, the potential energy anomaly (indicating density stratification strength) and the timing of seasonal stratification influence kittiwake productivity. Across all colonies, higher breeding success was associated with weaker stratification before breeding and lower SSTs during the breeding season. Eight colonies with sufficient data were modelled individually: higher productivity was associated with later stratification at 3 colonies, weaker stratification at 2, and lower SSTs at one, whilst 2 colonies showed no significant relationships. Hence, key drivers of productivity varied among colonies. Climate change projections, made using fitted models, indicated that breeding success could decline by 21 to 43% between 1961-90 and 2070-99. Climate change therefore poses a longer-term threat to kittiwakes, but as this will be mediated via availability of key prey species, other marine apex predators could also face similar threats.

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This paper explores the evolution of the cross-section income distribution in economies where endogenous neighborhood formation interacts with positive within-neighborhood feedback effects. We study an economy in which the economic success of adults is determined by the characteristics of the families in the neighborhood in which a person grows up. These feedbacks take two forms. First, the tax base of a neighborhood affects the leveI of education investment in offspring. Second, the effectiveness of education investment is affected by a neighborhood's in come distribution, reflecting factors such as role model or labor market connection effects. Conditions are developed under which endogenous stratification, defined as the tendency for families wi th similar incomes to choose to form common communities, will occur. When families are allowed to choose their neighborhoods, wealthy families will have an incentive to segregate themselves from the rest of the population. This resulting stratification is supported by house price differences between ricli and poor communities. Endogenous stratification can lead to pronounced intertemporal inequality as different families provide very different interaction environments for offspring. When the transformation of human capital into in come exhibits constant retums to scale, cross-section in come differences may also grow across time. As a result, endogenous stratification and neighborhood feedbacks can interact to produce long run inequality.

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A mathematical model was developed in order to study the behavior of thermal stratification of liquid in a typical storage tank with porous medium. The model employs a transient stream function-vorticity formulation to predict the development of stream function and temperature fields in a charging process. Parameters analyzed include Biot, Darcy, Reynolds and Richardson numbers, position, and the thickness of the porous medium. The results show the influence of these physical parameters that should be considered for a good design of storage tanks with thermal stratification.

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Includes bibliography

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Includes bibliography

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Incluye Bibliografía

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Includes bibliography