895 resultados para Multiple Correspondence Analysis


Relevância:

80.00% 80.00%

Publicador:

Resumo:

Total concentrations of algal pigments, organic C, C, N, P and S were determined in surface sediments from the littoral zone of 21 lakes in ice-free areas of northern Victoria Land (Antarctica) with different climatic and environmental conditions. Concentrations of major ions and nutrients were also determined in water samples from the same lakes. The latter samples had extremely variable chemical compositions; however, all the lakes resulted oligotrophic. Pigment concentrations in surface sediments were comparable to those reported for other Antarctic lakes and lower than those in oligotrophic lakes at lower latitudes. Cyanophyta, Chlorophyta and Bacillariophyta were the main taxa identified. These taxa correspond to those reported in previous microscopy-based studies on Antarctic phytoplankton and phytobenthos. Discriminant Function Analysis and Canonical Correspondence Analysis of data indicate that the distribution of pigments in these Victoria Land lakes depends mainly on their geographical location (particularly the distance from the sea) and nutrient status.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

This study involves samples of Santonian to Eocene age (Cores 516F-125 to 516F-38) taken from the Rio Grande Rise in the South Atlantic Ocean. These samples are from DSDP Site 516 occupied during Leg 72 of the Glomar Challenger (details given in site chapter, Site 516, this volume). Only Santonian to Paleocene cores have been well sampled, and analyses of the Eocene samples are preliminary results. Results of the trace element analyses (Mg, Sr, Mn, Ni, Fe, Na, K) of the carbonate fraction and CaCO3 percentage for each sample can be found in Renard and others (1983). Whole geochemical data are treated by the statistical method of correspondence analysis. Oxygen and carbon isotopic ratios measured on samples close to the Cretaceous/Tertiary boundary are not used in this study.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

The response of phytoplankton assemblages to hydrographical forcing across the southern Brazilian shelf was studied based on data collected during wintertime (June/2012), complemented with MODIS-Aqua satellite imagery. The in situ data set was comprised by water column structure properties (derived from CTD casts), dissolved inorganic nutrients (ammonium, nitrite, nitrate, phosphate and silicate) and phytoplankton biomass [chlorophyll a (Chl a) concentration] and composition. Phytoplankton assemblages were assessed by both microscopy and HPLC-CHEMTAX approaches. A canonical correspondence analysis associating physical, chemical and phytoplankton composition data at surface evinced a tight coupling between the phytoplankton community and hydrographic conditions, with remarkable environmental gradients across three different domains: the pelagic, outer shelf Tropical Water (TW); the mid shelf domain under influence of Subtropical Shelf Water (STSW); and the inner shelf domain mainly under influence of riverine outflow of the Plata River Plume Water (PPW). Results showed that intrusion of low salinity and nutrient-rich PPW stimulated the phytoplankton growth and diversity within the inner shelf region, with enhanced Chl a levels (>1.3 mg/m**3) and a great abundance of diatoms, ciliates, dinoflagellates, raphidophyceans and cryptophytes. Conversely, other diatoms (e.g. Rhizosolenia clevei), tiny species of prochlorophytes and cyanobacteria and a noticeable contribution of dinoflagellates and other flagellates associated with lower Chl a levels (<0.93 mg/m**3), characterized the TW domain, where low nutrient concentrations and deep upper mixed layer were found. The transitional mid shelf domain showed intermediate levels of both nutrients and Chl a (ranging 1.06-1.59 mg/m**3), and phytoplankton was mainly composed by dinoflagellates, such as Dinophysis spp., and gymnodinioids. Results have shown considerable phytoplankton diversity in winter at that section of the southwestern Atlantic Ocean.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Researchers in ecology commonly use multivariate analyses (e.g. redundancy analysis, canonical correspondence analysis, Mantel correlation, multivariate analysis of variance) to interpret patterns in biological data and relate these patterns to environmental predictors. There has been, however, little recognition of the errors associated with biological data and the influence that these may have on predictions derived from ecological hypotheses. We present a permutational method that assesses the effects of taxonomic uncertainty on the multivariate analyses typically used in the analysis of ecological data. The procedure is based on iterative randomizations that randomly re-assign non identified species in each site to any of the other species found in the remaining sites. After each re-assignment of species identities, the multivariate method at stake is run and a parameter of interest is calculated. Consequently, one can estimate a range of plausible values for the parameter of interest under different scenarios of re-assigned species identities. We demonstrate the use of our approach in the calculation of two parameters with an example involving tropical tree species from western Amazonia: 1) the Mantel correlation between compositional similarity and environmental distances between pairs of sites, and; 2) the variance explained by environmental predictors in redundancy analysis (RDA). We also investigated the effects of increasing taxonomic uncertainty (i.e. number of unidentified species), and the taxonomic resolution at which morphospecies are determined (genus-resolution, family-resolution, or fully undetermined species) on the uncertainty range of these parameters. To achieve this, we performed simulations on a tree dataset from southern Mexico by randomly selecting a portion of the species contained in the dataset and classifying them as unidentified at each level of decreasing taxonomic resolution. An analysis of covariance showed that both taxonomic uncertainty and resolution significantly influence the uncertainty range of the resulting parameters. Increasing taxonomic uncertainty expands our uncertainty of the parameters estimated both in the Mantel test and RDA. The effects of increasing taxonomic resolution, however, are not as evident. The method presented in this study improves the traditional approaches to study compositional change in ecological communities by accounting for some of the uncertainty inherent to biological data. We hope that this approach can be routinely used to estimate any parameter of interest obtained from compositional data tables when faced with taxonomic uncertainty.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

We investigate the dynamics of localized solutions of the relativistic cold-fluid plasma model in the small but finite amplitude limit, for slightly overcritical plasma density. Adopting a multiple scale analysis, we derive a perturbed nonlinear Schrödinger equation that describes the evolution of the envelope of circularly polarized electromagnetic field. Retaining terms up to fifth order in the small perturbation parameter, we derive a self-consistent framework for the description of the plasma response in the presence of localized electromagnetic field. The formalism is applied to standing electromagnetic soliton interactions and the results are validated by simulations of the full cold-fluid model. To lowest order, a cubic nonlinear Schrödinger equation with a focusing nonlinearity is recovered. Classical quasiparticle theory is used to obtain analytical estimates for the collision time and minimum distance of approach between solitons. For larger soliton amplitudes the inclusion of the fifth-order terms is essential for a qualitatively correct description of soliton interactions. The defocusing quintic nonlinearity leads to inelastic soliton collisions, while bound states of solitons do not persist under perturbations in the initial phase or amplitude

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Esta tesis doctoral presenta el desarrollo, verificación y aplicación de un método original de regionalización estadística para generar escenarios locales de clima futuro de temperatura y precipitación diarias, que combina dos pasos. El primer paso es un método de análogos: los "n" días cuya configuración atmosférica de baja resolución es más parecida a la del día problema, se seleccionan de un banco de datos de referencia del pasado. En el segundo paso, se realiza un análisis de regresión múltiple sobre los "n" días más análogos para la temperatura, mientras que para la precipitación se utiliza la distribución de probabilidad de esos "n" días análogos para obtener la estima de precipitación. La verificación de este método se ha llevado a cabo para la España peninsular y las Islas Baleares. Los resultados muestran unas buenas prestaciones para temperatura (BIAS cerca de 0.1ºC y media de errores absolutos alrededor de 1.9ºC); y unas prestaciones aceptables para la precipitación (BIAS razonablemente bajo con una media de -18%; error medio absoluto menor que para una simulación de referencia (la persistencia); y una distribución de probabilidad simulada similar a la observada según dos test no-paramétricos de similitud). Para mostrar la aplicabilidad de la metodología desarrollada, se ha aplicado en detalle en un caso de estudio. El método se aplicó a cuatro modelos climáticos bajo diferentes escenarios futuros de emisiones de gases de efecto invernadero, para la región de Aragón, produciendo así proyecciones futuras de precipitación y temperaturas máximas y mínimas diarias. La fiabilidad de la técnica de regionalización fue evaluada de nuevo para el caso de estudio mediante un proceso de verificación. Para determinar la capacidad de los modelos climáticos para simular el clima real, sus simulaciones del pasado (la denominada salida 20C3M) se regionalizaron y luego se compararon con el clima observado (los resultados son bastante robustos para la temperatura y menos concluyentes para la precipitación). Las proyecciones futuras a escala local presentan un aumento significativo durante todo el siglo XXI de las temperaturas máximas y mínimas para todos los futuros escenarios de emisiones considerados. Las simulaciones de precipitación presentan mayores incertidumbres. Además, la aplicabilidad práctica del método se demostró también mediante su utilización para producir escenarios climáticos futuros para otros casos de estudio en los distintos sectores y regiones del mundo. Se ha prestado especial atención a una aplicación en Centroamérica, una región que ya está sufriendo importantes impactos del cambio climático y que tiene un clima muy diferente. ABSTRACT This doctoral thesis presents the development, verification and application of an original downscaling method for daily temperature and precipitation, which combines two statistical approaches. The first step is an analogue approach: the “n” days most similar to the day to be downscaled are selected. In the second step, a multiple regression analysis using the “n” most analogous days is performed for temperature, whereas for precipitation the probability distribution of the “n” analogous days is used to obtain the amount of precipitation. Verification of this method has been carried out for the Spanish Iberian Peninsula and the Balearic Islands. Results show good performance for temperature (BIAS close to 0.1ºC and Mean Absolute Errors around 1.9ºC); and an acceptable skill for precipitation (reasonably low BIAS with a mean of - 18%, Mean Absolute Error lower than for a reference simulation, i.e. persistence, and a well-simulated probability distribution according to two non-parametric tests of similarity). To show the applicability of the method, a study case has been analyzed. The method was applied to four climate models under different future emission scenarios for the region of Aragón, thus producing future projections of daily precipitation and maximum and minimum temperatures. The reliability of the downscaling technique was re-assessed for the study case by a verification process. To determine the ability of the climate models to simulate the real climate, their simulations of the past (the 20C3M output) were downscaled and then compared with the observed climate – the results are quite robust for temperature and less conclusive for the precipitation. The downscaled future projections exhibit a significant increase during the entire 21st century of the maximum and minimum temperatures for all the considered future emission scenarios. Precipitation simulations exhibit greater uncertainties. Furthermore, the practical applicability of the method was demonstrated also by using it to produce future climate scenarios for some other study cases in different sectors and regions of the world. Special attention was paid to an application of the method in Central America, a region that is already suffering from significant climate change impacts and that has a very different climate from others where the method was previously applied.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Em ambiente de elevada pressão, competição e necessidade de criação de diferenciais consistentes que venham contribuir com a longevidade das organizações, nota-se a busca e, às vezes, radicais transformações nos modelos de gestão de negócios e gestão do ser humano no meio empresarial. No campo central dos estudos atuais acerca do comportamento humano e de suas relações com as diversas instituições em que o homem se vê inserido, figuram os esforços voltados à compreensão do papel e valor da contribuição do ser humano ao ambiente de trabalho e fortalecimento das organizações. Crescentes se mostram a preocupação e o entendimento sobre os fatores que impactam o bem-estar geral, o bem-estar no trabalho, a saúde dos trabalhadores e as variáveis emocionais oriundas das relações interpessoais comuns a todo organismo social. A combinação de temas emergentes e ricos em significância como bem-estar no trabalho, satisfação e envolvimento com o trabalho, comprometimento organizacional afetivo, emoções, afetos e sentimentos, caracterizam-se como um vasto e instigante campo de pesquisa para uma adaptação mais ampla do ser humano ao ambiente organizacional. O presente estudo teve como objetivo submeter ao teste empírico as relações entre experiências afetivas no contexto organizacional e três dimensões de bem-estar no trabalho - satisfação no trabalho, envolvimento com o trabalho e comprometimento organizacional afetivo. A amostra foi composta por 253 profissionais de uma indústria metalúrgica de autopeças na grande São Paulo, sendo 213 do sexo masculino e 29 do sexo feminino, com maior freqüência na faixa etária compreendida entre 26 a 30 anos, distribuída entre solteiros e casados. Para a coleta de dados foi utilizado um questionário de auto-preenchimento com quatro escalas que avaliaram afetos positivos e negativos, satisfação no trabalho, envolvimento com o trabalho e comprometimento organizacional afetivo. A análise dos dados foi feita por meio do SPSS, versão 16.0 e diversos sub-programas permitiram realizar análises descritivas bem como calcular modelos de regressão linear para verificar o impacto de afetos positivos e negativos sobre bem-estar no trabalho. Os resultados deste estudo revelaram que o principal preditor das dimensões de bem-estar no trabalho foram os afetos positivos. Assim, parece ser adequado afirmar que bem-estar no trabalho seja um estado psicológico sustentado, em especial, pela vivência de emoções positivas no contexto organizacional. Sugere-se que a promoção da saúde e do bem-estar dentro das organizações sejam focos de estudos futuros, representando valiosa contribuição aos campos de conhecimento da psicologia da saúde e da psicologia organizacional, bem como ao conseqüente fortalecimento dos vínculos entre empresa e trabalhadores.(AU)