999 resultados para CLIMATIC MODEL


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Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

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The evaluations of the effect of the climatic conditions and of the intensity of forest management in the trunk of the Gmelina arborea Linn. Roxb. trees are restricted to its physical-mechanical properties and use. The present work has as objective to study the radial variations of the wood anatomy of the gmelina trees sampled in plantations of 30 sites in Costa Rica, characterized by two climatic conditions (tropical dry and humid) and three intensities of forest management (intensive, moderate and without management). The results of the analyses demonstrated the existence of radial variation of the different anatomical parameters, except for the fiber lumen diameter and multiple vessels in the wood of the gmelina trees. For the wood anatomical elements, fibers (width, lumen diameter, and length), vessels (multiple vessels, diameter and frequency) and radial parenchyma (height) relationships were observed with the climate (tropical humid and dry). The radial variations of the wood anatomical elements were, also, influenced by the management regimes of the gmelina trees.

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Using data from a logging experiment in the eastern Brazilian Amazon region, we develop a matrix growth and yield model that captures the dynamic effects of harvest system choice on forest structure and composition. Multinomial logistic regression is used to estimate the growth transition parameters for a 10-year time step, while a Poisson regression model is used to estimate recruitment parameters. The model is designed to be easily integrated with an economic model of decisionmaking to perform tropical forest policy analysis. The model is used to compare the long-run structure and composition of a stand arising from the choice of implementing either conventional logging techniques or more carefully planned and executed reduced-impact logging (RIL) techniques, contrasted against a baseline projection of an unlogged forest. Results from log and leave scenarios show that a stand logged according to Brazilian management requirements will require well over 120 years to recover its initial commercial volume, regardless of logging technique employed. Implementing RIL, however, accelerates this recovery. Scenarios imposing a 40-year cutting cycle raise the possibility of sustainable harvest volumes, although at significantly lower levels than is implied by current regulations. Meeting current Brazilian forest policy goals may require an increase in the planned total area of permanent production forest or the widespread adoption of silvicultural practices that increase stand recovery and volume accumulation rates after RIL harvests. Published by Elsevier B.V.

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Predicting the potential geographical distribution of a species is particularly important for pests with strong invasive abilities. Tetranychus evansi Baker & Pritchard, possibly native to South America, is a spider mite pest of solanaceous crops. This mite is considered an invasive species in Africa and Europe. A CLIMEX model was developed to predict its global distribution. The model results fitted the known records of T. evansi except for some records in dry locations. Dryness as well as excess moisture stresses play important roles in limiting the spread of the mite in the tropics. In North America and Eurasia its potential distribution appears to be essentially limited by cold stress. Detailed potential distribution maps are provided for T. evansi in the Mediterranean Basin and in Japan. These two regions correspond to climatic borders for the species. Mite establishment in these areas can be explained by their relatively mild winters. The Mediterranean region is also the main area where tomato is grown in open fields in Europe and where the pest represents a threat. According to the model, the whole Mediterranean region has the potential to be extensively colonized by the mite. Wide expansion of the mite to new areas in Africa is also predicted. Agricultural issues highlighted by the modelled distribution of the pest are discussed.

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Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.

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Using a dynamic systems model specifically developed for Piracicaba, Capivari and Jundia River Water Basins (BH-PCJ) as a tool to help to analyze water resources management alternatives for policy makers and decision takers, five simulations for 50 years timeframe were performed. The model estimates water supply and demand, as well as wastewater generation from the consumers at BH-PCJ. A run was performed using mean precipitation value constant, and keeping the actual water supply and demand rates, the business as usual scenario. Under these considerations, it is expected an increment of about similar to 76% on water demand, that similar to 39% of available water volume will come from wastewater reuse, and that waste load increases to similar to 91%. Falkenmark Index will change from 1,403 m(3) person(-1) year(-1) in 2004, to 734 m(3) P(-1) year(-1) by 2054, and the Sustainability Index from 0.44 to 0.20. Another four simulations were performed by affecting the annual precipitation by 90 and 110%; considering an ecological flow equal to 30% of the mean daily flow; and keeping the same rates for all other factors except for ecological flow and household water consumption. All of them showed a tendency to a water crisis in the near future at BH-PCJ.

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Experimental results obtained from a greenhouse trial with common bean (Phaseolus vulgaris L) plants performed to test model hypotheses regarding the onset of limiting hydraulic conditions and the shape of the transpiration reduction curve in the falling rate phase are presented. According to these hypotheses based on simulations with an upscaled single-root model, the matric flux potential at the onset of limiting hydraulic conditions is as a function of root length density and potential transpiration rate, while the relative transpiration in the falling rate phase equals the relative matric flux potential. Transpiration of bean plants in water stressed pots with four different soils was determined daily by weighing and compared to values obtained from non-stressed pots. This procedure allowed determining the onset of the falling rate phase and corresponding soil hydraulic conditions. At the onset of the falling rate phase, the value of matric flux potential M(I) showed to differ in order of magnitude from the model predicted value for three out of four soils. This difference between model and experiment can be explained by the heterogeneity of the root distribution which is not considered by the model. An empirical factor to deal with this heterogeneity should be included in the model to improve predictions. Comparing the predictions of relative transpiration in the falling rate phase using a linear shape with water content, pressure head or matric flux potential, the matric flux potential based reduction function, in agreement with the hypothesis, showed the best performance, while the pressure head based equation resulted in the highest deviations between observed and predicted values of relative transpiration rates. (C) 2010 Elsevier B.V. All rights reserved.

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introduction of conservation practices in degraded agricultural land will generally recuperate soil quality, especially by increasing soil organic matter. This aspect of soil organic C (SOC) dynamics under distinct cropping and management systems can be conveniently analyzed with ecosystem models such as the Century Model. In this study, Century was used to simulate SOC stocks in farm fields of the Ibiruba region of north central Rio Grande do Sul state in Southern Brazil. The region, where soils are predominantly Oxisols, was originally covered with subtropical woodlands and grasslands. SOC dynamics was simulated with a general scenario developed with historical data on soil management and cropping systems beginning with the onset of agriculture in 1900. From 1993 to 2050, two contrasting scenarios based on no-tillage soil management were established: the status quo scenario, with crops and agricultural inputs as currently practiced in the region and the high biomass scenario with increased frequency of corn in the cropping system, resulting in about 80% higher biomass addition to soils. Century simulations were in close agreement with SOC stocks measured in 2005 in the Oxisols with finer texture surface horizon originally under woodlands. However, simulations in the Oxisols with loamy surface horizon under woodlands and in the grassland soils were not as accurate. SOC stock decreased from 44% to 50% in fields originally under woodland and from 20% to 27% in fields under grasslands with the introduction of intensive annual grain crops with intensive tillage and harrowing operations. The adoption of conservation practices in the 1980s led to a stabilization of SOC stocks followed by a partial recovery of native stocks. Simulations to 2050 indicate that maintaining status quo would allow SOC stocks to recover from 81% to 86% of the native stocks under woodland and from 80% to 91 % of the native stocks under grasslands. Adoption of a high biomass scenario would result in stocks from 75% to 95% of the original stocks under woodlands and from 89% to 102% in the grasslands by 2050. These simulations outcomes underline the importance of cropping system yielding higher biomass to further increase SOC content in these Oxisols. This application of the Century Model could reproduce general trends of SOC loss and recovery in the Oxisols of the Ibiruba region. Additional calibration and validation should be conducted before extensive usage of Century as a support tool for soil carbon sequestration projects in this and other regions can be recommended. (C) 2009 Elsevier B.V. All rights reserved.

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This article reports major results from collaborative research between France and Brazil on soil and water systems, carried out in the Upper Amazon Basin. It reveals the weathering processes acting in the partly inundated, low elevation plateaus of the Basin, mostly covered by evergreen forest. Our findings are based on geochemical data and mineral spectroscopy that probe the crystal chemistry of Fe and Al in mineral phases (mainly kaolinite, Al- and Fe-(hydr)oxides) of tropical soils (laterites). These techniques reveal crystal alterations in mineral populations of different ages and changes of metal speciation associated with mineral or organic phases. These results provide an integrated model of soil formation and changes (from laterites to podzols) in distinct hydrological compartments of the Amazon landscapes and under altered water regimes. (C) 2010 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

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The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

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Warm-season grasses are economically important for cattle production in tropical regions, and tools to aid in management and research of these forages would be highly beneficial. Crop simulation models synthesize numerous physiological processes and are important research tools for evaluating production of warm-season grasses. This research was conducted to adapt the perennial CROPGRO Forage model to simulate growth of the tropical species palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. Xaraes] and to describe model adaptation for this species. In order to develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation and partitioning during a 2-year experiment with Xaraes palisadegrass in Piracicaba, SP, Brazil. Starting with parameters for the bahiagrass (Paspalum notatum Flugge) perennial forage model, dormancy effects had to be minimized, and partitioning to storage tissue/root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area (SLA) and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield per cycle was 3573 kg ha(-1), with a RMSE of 538 kg DM ha(-1) (D-Stat = 0.838, simulated/observed ratio = 1.028). The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of palisadegrass and can be used to simulate growth. (C) 2010 Elsevier B.V. All rights reserved.

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We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

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Correct modeling of root water uptake partitioning over depth is an important issue in hydrological and crop growth models. Recently a physically based model to describe root water uptake was developed at single root scale and upscaled to the root system scale considering a homogeneous distribution of roots per soil layer. Root water uptake partitioning is calculated over soil layers or compartments as a function of respective soil hydraulic conditions, specifically the soil matric flux potential, root characteristics and a root system efficiency factor to compensate for within-layer root system heterogeneities. The performance of this model was tested in an experiment performed in two-compartment split-pot lysimeters with sorghum plants. The compartments were submitted to different irrigation cycles resulting in contrasting water contents over time. The root system efficiency factor was determined to be about 0.05. Release of water from roots to soil was predicted and observed on several occasions during the experiment; however, model predictions suggested root water release to occur more often and at a higher rate than observed. This may be due to not considering internal root system resistances, thus overestimating the ease with which roots can act as conductors of water. Excluding these erroneous predictions from the dataset, statistical indices show model performance to be of good quality.

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This study evaluated the influence of gastrointestinal environmental factors (pH, digestive enzymes, food components, medicaments) on the survival of Lactobacillus casei Shirota and Lactobacillus casei LC01, using a semi-dynamic in vitro model that simulates the transit of microorganisms through the human GIT. The strains were first exposed to different simulated gastric juices for different periods of time (0, 30, 60 and 120 min), and then to simulated intestinal fluids for zero, 120, 180 and 240 min, in a step-wise format. The number of viable cells was determined after each step. The influence of food residues (skim milk) in the fluids and resistance to medicaments commonly used for varied therapeutic purposes (analgesics, antiarrhythmics, antibiotics, antihistaminics, proton pump inhibitors, etc.) were also evaluated. Results indicated that survival of both cultures was pH and time dependent, and digestive enzymes had little influence. Milk components presented a protective effect, and medicaments, especially anti-inflammatory drugs, influenced markedly the viability of the probiotic cultures, indicating that the beneficial effects of the two probiotic cultures to health are dependent of environmental factors encountered in the human gastrointestinal tract.

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Objective: Protein-energy malnutrition (PEM) is an important public health problem affecting millions of people worldwide. Hematopoietic tissue requires a high nutrient supply, and a reduction in leukocytes, especially lymphocytes, suggests that some nutritional deficiencies might be altering bone marrow function and decreasing its ability to produce lymphocytes. In this study, we evaluated the effect that PEM has on lymphocyte subtypes and the cell cycle of CD5(+) cells. Methods: Swiss mice were subjected to PEM using a low-protein diet containing 4% protein. When the experimental group had lost about 20% of their original body weight, we collected blood and bone marrow cells and evaluated the hemogram, the myelogram, bone marrow lymphoid markers using flow cytometry, and the cell cycle in CD5(+) bone marrow. Results: Malnourished animals presented anemia, reticulocytopenia, and leukopenia with lymphopenia. The bone marrow was hypocellular, and flow cytometric analyses of bone marrow cells showed cells that were CD45(+) (91.2%), CD2(+) (84.9%), CD5(+) (37.3%), CD3(+) (23.5%), CD19(+) (43.3%), CD22(+) (34.7%), CD19(+)/CD2(+) (51.2%), CD19(+)/CD3(+)(24.0%), CD19(+)/CD5(+) (13.2%), CD22(+)/CD2(+) (40.1%), CD22(+)/CD3(+) (30.3%), and CD22(+)/CD5(+) (1.1%) in malnourished animals and CD45(+) (97.5%), CD2(+) (42.9%), CD5(+) (91.5%), CD3(+) (92.0%), CD19(+) (52.0%), CD22(+) (75.6%), CD19(+)/CD2(+) (62.0%), CD19(+)/CD3(+) (55.4%), CD19(+)/CO5(+) (6.7%), CD22(+)/CD2(+) (70.3%), CD22(+)/CD3(+) (55.9%), and CD22(+)/ CD5(+) (8.4%) in control animals. Malnourished animals also presented more CD5(+) cells in the G0 phase of cell cycle development. Conclusion: Malnourished animals presented bone marrow hypoplasia, maturation interruption, prominent lymphopenia with depletion in the lymphoid lineage, and changes in cellular development. We suggest that these changes are some of the primary causes of lymphopenia in cases of PEM and partly explain the increase in susceptibility to infections found in malnourished individuals. Published by Elsevier Inc.