988 resultados para soil data requirements


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A resistência mecânica à penetração do solo exerce grande influência sobre o crescimento e desenvolvimento vegetal, uma vez que o crescimento das raízes e o rendimento das culturas variam de forma inversamente proporcional ao seu valor. Por outro lado, a matéria orgânica e o pH do solo também são atributos relevantes ao crescimento das plantas, pois estão diretamente ligados à disponibilidade de nutrientes do solo. No ano agrícola 2005/2006, na Fazenda Experimental de Ensino e Pesquisa da Faculdade de Engenharia/UNESP, município de Selvíria, MS (22 º 23 ' de latitude S; 51 º 27 ' de longitude W), em um cultivo de Eucalyptus camaldulensis, foram analisados: (a) características dendrométricas da planta: volume de madeira (VOL), perímetro à altura do peito (PAP) e altura (ALT); e (b) atributos do solo em profundidade: resistência mecânica à penetração (RP), umidade gravimétrica (UG), matéria orgânica (MO) e o pH, num Latossolo Vermelho distrófico do Cerrado brasileiro. O objetivo foi estudar as correlações lineares e espaciais entre essas variáveis, buscando determinar indicadores de qualidade do solo para o eucalipto. Dados do solo e da planta foram coletados em uma malha geoestatística com 122 pontos amostrais, numa área de 1,98 ha. Os atributos da planta apresentaram média e alta variabilidade dos dados, ao passo que os do solo mostraram variabilidade baixa, média e alta. Os atributos VOL, PAP, ALT, RP, UG, MO e o pH não variaram aleatoriamente, seguindo padrões espaciais bem definidos, com alcances entre 17 e 169 m. As correlações lineares simples entre as características da planta e os atributos do solo foram baixas, porém significativas entre os pares VOL vs RP1, VOL vs RP5, VOL vs MO2 e VOL vs pH1. do ponto de vista espacial, ocorreu significativa variação inversa do VOL com a RP5 e o pH1. O pH do solo, amostrado de 0-0,15 m de profundidade, quando destinado à estimativa da produtividade de madeira do Eucalyptus camaldulensis, apresentou-se como potente indicador da qualidade do solo estudado de Selvíria.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Pós-graduação em Pesquisa e Desenvolvimento (Biotecnologia Médica) - FMB

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Agronomia - FEIS

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The need for biodiversity conservation is increasing at a rate much faster than the acquisition of knowledge of biodiversity, such as descriptions of new species and mapping species distributions. As global changes are winning the race against the acquisition of knowledge, many researchers resort to the use of surrogate groups to aid in conservation decisions. Reductions in taxonomic and numerical resolution are also desirable, because they could allow more rapid the acquisition of knowledge while requiring less effort, if little important information is lost. In this study, we evaluated the congruence among 22 taxonomic groups sampled in a tropical forest in the Amazon basin. Our aim was to evaluate if any of these groups could be used as surrogates for the others in monitoring programs. We also evaluated if the taxonomic or numerical resolution of possible surrogates could be reduced without greatly reducing the overall congruence. Congruence among plant groups was high, whereas the congruence among most animal groups was very low, except for anurans in which congruence values were only slightly lower than for plants. Liana (Bignoniaceae) was the group with highest congruence, even using genera presence-absence data. The congruence among groups was related to environmental factors, specifically the clay and phosphorous contents of soil. Several groups showed strong spatial clumping, but this was unrelated to the congruence among groups. The high degree of congruence of lianas with the other groups suggests that it may be a reasonable surrogate group, mainly for the other plant groups analyzed, if soil data are not available. Although lianas are difficult to count and identify, the number of studies on the ecology of lianas is increasing. Most of these studies have concluded that lianas are increasing in abundance in tropical forests. In addition to the high congruence, lianas are worth monitoring in their own right because they are sensitive to global warming and the increasing frequency and severity of droughts in tropical regions. Our findings suggest that the use of data on surrogate groups with relatively low taxonomic and numerical resolutions can be a reliable shortcut for biodiversity assessments, especially in megadiverse areas with high rates of habitat conversion, where the lack of biodiversity knowledge is pervasive. (c) 2012 Elsevier Ltd. All rights reserved.

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This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

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Through the concerted evaluations of thousands of commercial substances for the qualities of persistence, bioaccumulation, and toxicity as a result of the United Nations Environment Program's Stockholm Convention, it has become apparent that fewer empirical data are available on bioaccumulation than other endpoints and that bioaccumulation models were not designed to accommodate all chemical classes. Due to the number of chemicals that may require further assessment, in vivo testing is cost prohibitive and discouraged due to the large number of animals needed. Although in vitro systems are less developed and characterized for fish, multiple high-throughput in vitro assays have been used to explore the dietary uptake and elimination of pharmaceuticals and other xenobiotics by mammals. While similar processes determine bioaccumulation in mammalian species, a review of methods to measure chemical bioavailability in fish screening systems, such as chemical biotransformation or metabolism in tissue slices, perfused tissues, fish embryos, primary and immortalized cell lines, and subcellular fractions, suggest quantitative and qualitative differences between fish and mammals exist. Using in vitro data in assessments for whole organisms or populations requires certain considerations and assumptions to scale data from a test tube to a fish, and across fish species. Also, different models may incorporate the predominant site of metabolism, such as the liver, and significant presystemic metabolism by the gill or gastrointestinal system to help accurately convert in vitro data into representative whole-animal metabolism and subsequent bioaccumulation potential. The development of animal alternative tests for fish bioaccumulation assessment is framed in the context of in vitro data requirements for regulatory assessments in Europe and Canada.

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The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by process-based modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under http://www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws. We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10 m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25 m resolution.

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To satisfy REACH requirements a high number of data on chemical of interest should be supplied to the European Chemicals Agency. To organize the various kinds of information and help the registrants to choose the best strategy to obtain the needed information limiting at the minimum the use of animal testing, integrated testing strategies (ITSs) schemes can be used. The present work deals with regulatory data requirements for assessing the hazards of chemicals to the aquatic pelagic environment. We present an ITS scheme for organizing and using the complex existing data available for aquatic toxicity assessment. An ITS to optimize the choice of the correct prediction strategy for aquatic pelagic toxicity is described. All existing information (like physico-chemical information), and all the alternative methods (like in silico, in vitro or the acute-to-chronic ratio) are considered. Moreover the weight of evidence approach to combine the available data is included.

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The study was carried out on the main plots (Main Experiment) of a large grassland biodiversity experiment, the Jena Experiment. 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. This data set consists of standard deviation (SD), mean and stability (stab) of soil microbial basal respiration (µl O2/h/g dry soil) and microbial biomass carbon (µg C/g dry soil). Data were derived by taking soil samples and measuring basal and substrate-induced microbial respiration with an oxygen-consumption apparatus. Samples for calculating the spatial stability of soil microbial properties were taken on the 20th of September in 2010. Oxygen consumption of soil microorganisms in fresh soil equivalent to 3.5 g dry weight was measured at 22°C over a period of 24 h. Basal respiration (µlO2/g dry soil/h) was calculated as mean of the oxygen consumption rates of hours 14 to 24 after the start of measurements. Substrate- induced respiration was determined by adding D-glucose to saturate catabolic enzymes of microorganisms according to preliminary studies (4 mg g-1 dry soil solved in 400 µl deionized water). Maximum initial respiratory response (µl O2/g dry soil/ h) was calculated as mean of the lowest three oxygen consumption values within the first 10 h after glucose addition. Microbial biomass carbon (µg C/g dry soil) was calculated as 38 × Maximum initial respiratory response according to prelimiray studies.

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The study was carried out on the main plots (Main Experiment) of a large grassland biodiversity experiment, the Jena Experiment. 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. This data set consists of standard deviation (SD), mean and stability (stab) of soil microbial basal respiration (µl O2/h/g dry soil) and microbial biomass carbon (µg C/g dry soil). Data were derived by taking soil samples and measuring basal and substrate-induced microbial respiration with an oxygen-consumption apparatus. Samples for calculating the temporal stability were taken every year in May/June from 2003 to 2014, except in 2005. Oxygen consumption of soil microorganisms in fresh soil equivalent to 3.5 g dry weight was measured at 22°C over a period of 24 h. Basal respiration (µlO2/g dry soil/h) was calculated as mean of the oxygen consumption rates of hours 14 to 24 after the start of measurements. Substrate- induced respiration was determined by adding D-glucose to saturate catabolic enzymes of microorganisms according to preliminary studies (4 mg g-1 dry soil solved in 400 µl deionized water). Maximum initial respiratory response (µl O2/g dry soil/h) was calculated as mean of the lowest three oxygen consumption values within the first 10 h after glucose addition. Microbial biomass carbon (µg C/g dry soil) was calculated as 38 × Maximum initial respiratory response according to prelimiray studies.

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With regression formulas replaced by equilibrium conditions, a spatial CGE model can substantially reduce data requirements. Detailed regional analyses are thus possible in countries where only limited regional statistics are available. While regional price differentials play important roles in multi-regional settings, transport does not receive much attention in existing models. This paper formulates a spatial CGE model that explicitly considers the transport sector and FOB/CIF prices. After describing the model, performance of our model is evaluated by comparing the benchmark equilibrium for China with survey-based regional I-O and interregional I-O tables for 1987. The structure of Chinese economies is summarized using information obtained from the benchmark equilibrium computation. This includes regional and sectoral production distributions and price differentials. The equilibrium for 1997 facilitates discussion of changes in regional economic structures that China has experienced in the decade.

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The preference utilization ratio, i.e., the share of imports under preferential tariff schemes out of total imports, has been a popular indicator for measuring the usage of preferential tariffs vis-à-vis tariffs on a most-favored-nation basis. A crucial shortcoming of this measure is the data requirements, particularly for import value data classified by tariff schemes, which are not available in most countries. This study proposes an alternative measure for preferential tariff utilization, termed the "tariff exemption ratio." This measure offers the unique advantage of needing only publicly available data, such as those provided by the World Development Indicators, for its computations. We can thus calculate this measure for most countries for an international comparison. Our finding is that tariff exemption ratios differ widely across countries, with a global average of approximately 50%.