Spatial heterogeneity impacts population and community-level dynamics including species-level dispersal patterns, the use and availability of refugia, predator/prey dynamics, and reproductive fitness. Understanding how wild animal populations respond to environmental heterogeneity is essential for their proper management and conservation. In this study, I examine the responses of Willow Flycatchers to spatial heterogeneity in the distribution of their food and habitat resources. Over the course of three breeding seasons, I radio- tracked Willow Flycatchers at Fish Creek in Manti-La Sal National Forest in Utah, recorded detailed behavior data at each radio location, and collected fecal, feather and insect samples. I formulated individual and population-level Bayesian spatial resource selection functions to model Willow Flycatcher foraging and vocalization behavior on multiple scales. These models indicate that vocalization and foraging behavior are spatially segregated within the home ranges of Willow Flycatchers. Further, Willow Flycatchers were found to use mature riparian habitat for vocalizing while they used a variety of habitat types for foraging. The insect samples were used to identify distinct carbon and nitrogen stable isotope signatures for the aquatic and terrestrial insect communities at Fish Creek. In conjunction with the fecal samples, I used the stable isotope signatures to determine the contribution of aquatic versus terrestrial insects to the Willow Flycatcher diet. Aquatic insects comprised a larger proportion of the diet of adult than nestling Willow Flycatchers. This suggests that adult flycatchers consume a diet that is distinct from the one they feed to their nestlings. Finally, I compared space use characteristics in two populations of Willow Flycatchers: a population of the endangered Southwestern Willow Flycatcher at Roosevelt Lake, Arizona and another belonging to a non-endangered subspecies of Willow Flycatcher at Fish Creek, Utah. Differences in space use were found largely among breeding flycatchers while space use characteristics in non-breeding Willow Flycatchers did not differ across populations. This suggests that space use patterns in non-breeding Southwestern Willow Flycatchers may be generalizable to non-breeding flycatchers from non-endangered populations. This study expands our understanding of how Willow Flycatchers respond to spatial heterogeneity while its key findings have management and conservation implications for the species.

<p>Coprophilous ascomycetes are a diverse group of saprobes, of which many belong to three families, Delitschiaceae, Phaeotrichaceae and Sporormiaceae, within the large order Pleosporales. The natural relationships and circumscription of these families are unclear, especially within the family Sporormiaceae, where the generic delimitation have been questioned. There is also a need to understand how different ecological processes affect species richness and occurrence of coprophilous ascomycetes in general. The aim of this thesis was therefore to test earlier classifications of coprophilous taxa within Pleosporales, using phylogenetic analyses of DNA sequences; and to study how the habitat, dung type and herbivores´ food choice may affect the species richness and species composition of coprophilous ascomycetes.</p><p>A phylogenetic study shows that coprophilous taxa have arisen several times within Pleosporales. Sporormiaceae and Delitschiaceae are separate monophyletic groups and should continue to be recognized as two distinct families within Pleosporales. Phaeotrichaceae forms a monophyletic group, and is, unexpectedly, a strongly supported sister-group to Venturiaceae, but if they belong to Pleosporales or not, remains unresolved. Testudinaceae and Zopfiaceae, which previously had an unclear position in Ascomycota, are shown to be members of Pleosporales and should be treated as two separate families. The genus <i>Eremodothis</i> is, however, not related to Testudinaceae, but is nested within Sporormiaceae and should be transferred to <i>Westerdykella</i>.</p><p>The natural relationships within Sporormiaceae are still not fully resolved and consequently, I suggest a rather conservative generic classification, accepting <i>Preussia, Sporormia, Westerdykella</i>, as well as <i>Sporormiella</i>, despite that the latter is not conclusively well supported as monophyletic. Characters previously used in the taxonomy and classification of Sporormiaceae, as choice of substrate, presence or absence of an ostiole, presence or absence of germ slits, and spore ornamentation, were all homoplastic and not very useful for circumscribing monophyletic groups.</p><p>Field-studies of moose (<i>Alces alces</i>), mountain hare (<i>Lepus timidus</i>) and roe deer (<i>Capreolus capreolus</i>) dung resulted in several new species records, which suggests that coprophilous ascomycetes in boreal Sweden are poorly known. Fungal species richness and occurrence on moose dung varied significantly between habitats. Species diversity was negatively associated with amount of insect attack, and insects feeding either on the dung and/or the fungi may be an important factor explaining the observed pattern. Species richness of coprophilous fungi varied also significantly between different dung types. A study of moose, mountain hare, and roe deer dung did not show any consistent patterns in respect to the animals´ digestive system. There was, however, a general strong positive relationship between the total number of ascomycete species and the number of plant species foraged by the three herbivores. Fungal species with large spores (≥ 50 µm) were over-represented on roe deer dung, and under-represented on moose dung, while the reverse was found for species with small spores (<10µm). This suggests that the foraging level of the herbivore, which in turn mirrors species-specific differences in spore dispersal of the fungi, may be an important factor in explaining species richness and diversity of the coprophilous community.</p>

This thesis consists of four papers and the main theme present is dependence, through time as in serial correlation, and across individuals, as in random effects. The individual papers may be grouped in many different ways. As is, the first two are concerned with autoregressive dynamics in a single time series and then a panel context, while the subject of the final two papers is parametric covariance modeling. Though set in a panel context the results in the latter are generally applicable. The approach taken is Bayesian. This choice is prompted by the coherent framework that the Bayesian principle offers for quantifying uncertainty and subsequently making inference in the presence of it. Recent advances in numerical methods have also made the Bayesian choice simpler. In the first paper an existing model to conduct inference directly on the roots of the autoregressive polynomial is extended to include seasonal components and to allow for a polynomial trend of arbitrary degree. The resulting highly flexible model robustifies against misspecification by implicitly averaging over different lag lengths, number of unit roots and specifications for the deterministic trend. An application to the Swedish real GDP illustrates the rich set of information about the dynamics of a time series that can be extracted using this modeling framework. The second paper offers an extension to a panel of time series. Limiting the scope, but at the same time simplifying matters considerably, the mean model is dropped restricting the applicability to non-trending panels. The main motivation of the extension is the construction of a flexible panel unit root test. The proposed approach circumvents the classical confusing problem of stating a relevant null hypothesis. It offers the possibility of more distinct inference with respect to unit root composition in the collection of time series. It also addresses the two important issues of model uncertainty and cross-section correlation. The model is illustrated using a panel of real exchange rates to investigate the purchasing power parity hypothesis. Many interesting panel models imply a structure on the covariance matrix in terms of a small number of parameters. In the third paper, exploiting this structure it is demonstrated how common panel data models lend themselves to direct sampling of the variance parameters. Not necessarily always practical, the implementation can be described by a simple and generally applicable template. For the method to be practical, simple to program and quick to execute, it is essential that the inverse of the covariance matrix can be written as a reasonably simple function of the parameters of interest. Also preferable but in no way necessary is the availability of a computationally convenient expression for the determinant of the covariance matrix as well as a bounded support for the parameters. Using the template, the computations involved in direct sampling and effect selection are illustrated in the context of a one- and two-way random effects model respectively. Having established direct sampling as a viable alternative in the previous paper, the generic template is applied to panel models with serial correlation in the fourth paper. In the case of pure serial correlation, with no random effects present, applying the template and using a Jeffreys type prior leads to very simple computations. In the very general setting of a mixed effects model with autocorrelated errors direct sampling of all variance parameters does not appear to be possible or at least not obviously practical. One important special case is identified in the model with the random individual effects model with autocorrelation. / <p>Diss. Stockholm : Handelshögskolan i Stockholm, 2004 viii s., s. 1-9: sammanfattning, s. 10-116: 4 uppsatser</p>

Coprophilous ascomycetes are a diverse group of saprobes, of which many belong to three families, Delitschiaceae, Phaeotrichaceae and Sporormiaceae, within the large order Pleosporales. The natural relationships and circumscription of these families are unclear, especially within the family Sporormiaceae, where the generic delimitation have been questioned. There is also a need to understand how different ecological processes affect species richness and occurrence of coprophilous ascomycetes in general. The aim of this thesis was therefore to test earlier classifications of coprophilous taxa within Pleosporales, using phylogenetic analyses of DNA sequences; and to study how the habitat, dung type and herbivores´ food choice may affect the species richness and species composition of coprophilous ascomycetes. A phylogenetic study shows that coprophilous taxa have arisen several times within Pleosporales. Sporormiaceae and Delitschiaceae are separate monophyletic groups and should continue to be recognized as two distinct families within Pleosporales. Phaeotrichaceae forms a monophyletic group, and is, unexpectedly, a strongly supported sister-group to Venturiaceae, but if they belong to Pleosporales or not, remains unresolved. Testudinaceae and Zopfiaceae, which previously had an unclear position in Ascomycota, are shown to be members of Pleosporales and should be treated as two separate families. The genus Eremodothis is, however, not related to Testudinaceae, but is nested within Sporormiaceae and should be transferred to Westerdykella. The natural relationships within Sporormiaceae are still not fully resolved and consequently, I suggest a rather conservative generic classification, accepting Preussia, Sporormia, Westerdykella, as well as Sporormiella, despite that the latter is not conclusively well supported as monophyletic. Characters previously used in the taxonomy and classification of Sporormiaceae, as choice of substrate, presence or absence of an ostiole, presence or absence of germ slits, and spore ornamentation, were all homoplastic and not very useful for circumscribing monophyletic groups. Field-studies of moose (Alces alces), mountain hare (Lepus timidus) and roe deer (Capreolus capreolus) dung resulted in several new species records, which suggests that coprophilous ascomycetes in boreal Sweden are poorly known. Fungal species richness and occurrence on moose dung varied significantly between habitats. Species diversity was negatively associated with amount of insect attack, and insects feeding either on the dung and/or the fungi may be an important factor explaining the observed pattern. Species richness of coprophilous fungi varied also significantly between different dung types. A study of moose, mountain hare, and roe deer dung did not show any consistent patterns in respect to the animals´ digestive system. There was, however, a general strong positive relationship between the total number of ascomycete species and the number of plant species foraged by the three herbivores. Fungal species with large spores (≥ 50 µm) were over-represented on roe deer dung, and under-represented on moose dung, while the reverse was found for species with small spores (&lt;10µm). This suggests that the foraging level of the herbivore, which in turn mirrors species-specific differences in spore dispersal of the fungi, may be an important factor in explaining species richness and diversity of the coprophilous community.

This thesis concerns the phylogenetic relationships and the evolution of the gall-inducing wasps belonging to the family Cynipidae. Several previous studies have used morphological data to reconstruct the evolution of the family. DNA sequences from several mitochondrial and nuclear genes where obtained and the first molecular, and combined molecular and morphological, analyses of higher-level relationships in the Cynipidae is presented. A Bayesian approach to data analysis is adopted, and models allowing combined analysis of heterogeneous data, such as multiple DNA data sets and morphology, are developed. The performance of these models is evaluated using methods that allow the estimation of posterior model probabilities, thus allowing selection of most probable models for the use in phylogenetics. The use of Bayesian model averaging in phylogenetics, as opposed to model selection, is also discussed. It is shown that Bayesian MCMC analysis deals efficiently with complex models and that morphology can influence combined-data analyses, despite being outnumbered by DNA data. This emphasizes the utility and potential importance of using morphological data in statistical analyses of phylogeny. The DNA-based and combined-data analyses of cynipid relationships differ from previous studies in two important respects. First, it was previously believed that there was a monophyletic clade of woody rosid gallers but the new results place the non-oak gallers in this assemblage (tribes Pediaspidini, Diplolepidini, and Eschatocerini) outside the rest of the Cynipidae. Second, earlier studies have lent strong support to the monophyly of the inquilines (tribe Synergini), gall wasps that develop inside the galls of other species. The new analyses suggest that the inquilines either originated several times independently, or that some inquilines secondarily regained the ability to induce galls. Possible reasons for the incongruence between morphological and DNA data is discussed in terms of heterogeneity in evolutionary rates among lineages, and convergent evolution of morphological characters.

Statistical models have greatly improved our understanding of the pathogenesis of HIV-1 infection and guided for the treatment of AIDS patients and evaluation of antiretroviral (ARV) therapies. Although various statistical modeling and analysis methods have been applied for estimating the parameters of HIV dynamics via mixed-effects models, a common assumption of distribution is normal for random errors and random-effects. This assumption may lack the robustness against departures from normality so may lead misleading or biased inference. Moreover, some covariates such as CD4 cell count may be often measured with substantial errors. Bivariate clustered (correlated) data are also commonly encountered in HIV dynamic studies, in which the data set particularly exhibits skewness and heavy tails. In the literature, there has been considerable interest in, via tangible computation methods, comparing different proposed models related to HIV dynamics, accommodating skewness (in univariate) and covariate measurement errors, or considering skewness in multivariate outcomes observed in longitudinal studies. However, there have been limited studies that address these issues simultaneously. One way to incorporate skewness is to use a more general distribution family that can provide flexibility in distributional assumptions of random-effects and model random errors to produce robust parameter estimates. In this research, we developed Bayesian hierarchical models in which the skewness was incorporated by using skew-elliptical (SE) distribution and all of the inferences were carried out through Bayesian approach via Markov chain Monte Carlo (MCMC). Two real data set from HIV/AIDS clinical trial were used to illustrate the proposed models and methods. This dissertation explored three topics. First, with an SE distribution assumption, we compared models with different time-varying viral decay rate functions. The effect of skewness on the model fitting was also evaluated. The associations between the estimated decay rates based on the best fitted model and clinical related variables such as baseline HIV viral load, CD4 cell count and longterm response status were also evaluated. Second, by jointly modeling via a Bayesian approach, we simultaneously addressed the issues of outcome with skewness and a covariate process with measurement errors. We also investigated how estimated parameters were changed under linear, nonlinear and semiparametric mixed-effects models. Third, in order to accommodate individual clustering within subjects as well as the correlation between bivariate measurements such as CD4 and CD8 cell count measured during the ARV therapies, bivariate linear mixed-effects models with skewed distributions were investigated. Extended underlying normality assumption with SE distribution assumption was proposed. The impacts of different distributions in SE family on the model fit were also evaluated and compared. Real data sets from AIDS clinical trial studies were used to illustrate the proposed methodologies based on the three topics and compare various potential models with different distribution specifications. The results may be important for HIV/AIDS studies in providing guidance to better understand the virologic responses to antiretroviral treatment. Although this research is motivated by HIV/AIDS studies, the basic concepts of the methods developed here can have generally broader applications in other fields as long as the relevant technical specifications are met. In addition, the proposed methods can be easily implemented by using the publicly available WinBUGS package, and this makes our approach quite accessible to practicing statisticians in the fields.

Röntgenlicht-Freie-Elektronen-Laser (XFEL) schaffen neue Möglichkeiten für die molekulare Strukturbestimmung in Einzelmolekülexperimenten. In dieser Arbeit stelle ich zwei alternative bayessche Verfahren vor, das Orientational Bayes und das Structural Bayes Verfahren, die das Extrahieren der Strukturinformationen aus dünn besetzten und verrauschten Streuungsbildern ermöglichen. Im ersten Verfahren wird ein "Seed"-Modell verwendet, um die zugrunde liegende molekulare Orientierung für jedes aufgezeichnete Streuungsbild separat zu bestimmen. Eine verbesserte molekulare Transformation der bestrahlten Moleküle wird durch Ausrichten und Mitteln dieser Bilder im dreidimensionalen reziproken Raum erhalten. Im Structural Bayes Verfahren wird ein Realraum-Strukturmodell optimiert, sodass es am besten zum gesamten Streuungsbildersatz passt. Auf diese Weise wird ermöglicht, zwischen verschiedenen Strukturmodellen zu unterscheiden. Ich habe die Auflösung bei der Abbildung einzelner Moleküle mit unterschiedlichen Massen für verschiedene XFEL Strahlintensitäten abgeschätzt. Die Ergebnisse zeigen, dass die erreichbare strukturelle Auflösung mit der Molekülmasse wie M^{-1/ 6} steigt. Laut dieser Skalierung ist hierbei, im Gegensatz zur traditionellen Röntgenkristallographie, die hochaufgelöste Strukturbestimmung kleiner Einzelmoleküle, im Vergleich zu großen Molekülen, schwieriger. Als Machbarkeitsnachweis des Orientational Bayes Verfahrens wurde beispielhaft die Elektronendichte eines Glutathion-Moleküls aus 20.000 synthetischen Streuungsbildern, mit durchschnittlich 82 aufgezeichneten elastisch gestreuten Photonen und bis zu 50% zusätzlichem Hintergrundrauschen pro Bild, berechnet. Um die Anwendbarkeit des Structural Bayes Verfahrens in einer de novo Strukturbestimmung zu testen, wurde zudem die Struktur des Glutathion-Moleküls in einer Monte Carlo-Verfeinerungs-Simulation gelöst, für die zufällige Aminosäure-Konformationen als Ausgangsmaterial verwendet wurden. Um zusätzlich zu prüfen, ob mehrere Längenskalen umfassende Strukturänderungen in einem komplexen Molekül unter Verwendung des Structural Bayes Verfahrens rückverfolgbar sind, wurden Konformationsänderungen von drei Immunglobulin-Domänen eines Titin-Moleküls sowie der tRNA-Translokationsvorgang im Ribosom untersucht. Die Ergebnisse zeigen, dass es möglich ist sowohl zwischen unterschiedlichen molekularen Konformationen zu unterscheiden als auch kleinere strukturelle Änderungen, die mit der tRNA-Translokation assoziiert sind, zu erkennen. Insgesamt betrachtet deuten die Ergebnisse dieser Arbeit darauf hin, dass sich mithilfe der beiden hier vorgestellten bayesschen Verfahren die Struktur einzelner Moleküle mit atomarer Auflösung von dünn besetzten und verrauschten Röntgenstreuungsbildern aus XFEL-Einzelmolekülexperimenten für ein breites Spektrum von Molekülmassen bestimmen lässt.

Made available in DSpace on 2015-03-26T13:32:14Z (GMT). No. of bitstreams: 1 texto completo.pdf: 1797227 bytes, checksum: e12639c68c3972023379c9f437bc1e5c (MD5) Previous issue date: 2012-02-16 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The base of agribusiness of sugar cane is the breeding. Can be shown that the great strategy selection of plant would be through the prediction of genotypic values using BLUP (Best Linear Unbiased Predictor) individual (BLUPI). This procedure would use both the information of family and individuals for selection. However this method is rarely used in breeding programs because of operational problems related to obtain data plant. Recently an alternative operationally more practical was proposal and is called BLUPIS (BLUP individual simulated). In this case the data are collected at the level of plot. With this is possible to select the best families, and subsequently, to simulate the number of individuals to be selected within the best families. This work has as aims to develop an algorithm for analysis BLUP under the Bayesian focus with different settings of priors in your modeling, in statistical software R, for possible available to the user and compare it with the Classic REML / BLUP. The results showed that the method with Bayesian BLUPIS performed by the algorithm built with the R program was effective. The algorithm took into account the uncertainties on all parameters, as also allowed the use of a priori information. The Bayesian method is more efficient when considering the relationship information model and the distribution of the prior information (major genotypic effects and variances and heritability smaller). / A base do agronegócio de cana-de-açúcar é o melhoramento genético. Pode ser mostrado que a estratégia ótima de seleção da planta seria através da predição de valores genotípicos usando o BLUP (Best Linear Unbiased Predictor) individual (BLUPI). Este procedimento usaria, simultaneamente, a informação de família e de indivíduos para a seleção. No entanto esse método dificilmente é usado nos programas de melhoramento devido a problemas operacionais relacionados à obtenção dos dados ao nível de planta. Recentemente uma alternativa operacionalmente mais prática foi proposta, e é denominada BLUPIS (BLUP individual simulado). Nesse caso os dados são coletados ao nível de parcela. Com isso é possível selecionar as melhores famílias e, posteriormente, simular o número de indivíduos a serem selecionados dentro das melhores famílias. Este trabalho teve como objetivo desenvolver um algoritmo para análise do BLUPIS sob o enfoque bayesiano, com diferentes definições de distribuições a prioris na sua modelagem, no software estatístico R, para possível disponibilização ao usuário e compará-la com o método clássico REML/BLUP. Os resultados mostraram que o método BLUPIS com enfoque bayesiano realizado através do algoritmo construído junto ao programa R foi eficiente. O algoritmo levou em consideração a incerteza existente sobre todos os parâmetros do modelo, como também possibilitou o uso de priori informativa. O método bayesiano se mostrou mais eficiente, isto é, com efeitos genotípicos maiores e variâncias e herdabilidade menores, quando se consideraram no modelo a informação de parentesco e a distribuição da priori informativa.

Diaconis and Ylvisaker (1979) give necessary conditions for conjugate priors for distributions from the natural exponential family to be proper as well as to have the property of linear posterior expectation of the mean parameter of the family. Their conditions for propriety and linear posterior expectation are also sufficient if the natural parameter space is equal to the set of all d-dimensional real numbers. In this paper their results are extended to characterize when conjugate priors are proper if the natural parameter space is bounded. For the special case where the natural exponential family is through a spherical probability distribution n,we show that the proper conjugate priors can be characterized by the behavior of the moment generating function of n at the boundary of the natural parameter space, or the second-order tail behavior of n. In addition, we show that if these families are non-regular, then linear posterior expectation never holds. The results for this special case are also extended to natural exponential families through elliptical probability distributions.

Dans ce travail, nous avons développé un système expert qui intègre les fonctions suivantes :i) l'identification des profils à partir des mesures sur les plasmas de tokamak, par les méthodes bayésiennes; ii) La prédiction des quantités reconstruites, selon les modèles choisis et; iii) une comparaison intelligente des résultats provenant des deux premières étapes. Ce système comprend une vérification systématique de la cohérence interne des quantités reconstruites, permet la validation automatique des modèles. Avec un modèle validé, il peut aider à la détection de nouveaux effets physique dans une expérience. Trois applications de ce système sont présentées dans ce travail. Le système expert peut détecter automatiquement les défauts dans la reconstruction des profils et fournir (lorsque la reconstruction est valide) des statistiques sur l'accord des modèles avec les données expérimentales, c'est à dire des informations sur la validité du modèle. / In this work we developed an expert system that carries out in an integrated and fully automated way i) a reconstruction of plasma profiles from the measurements, using Bayesian analysis ii) a prediction of the reconstructed quantities, according to some models and iii) an intelligent comparison of the first two steps. This system includes systematic checking of the internal consistency of the reconstructed quantities, enables automated model validation and, if a well-validated model is used, can be applied to help detecting interesting new physics in an experiment. The work shows three applications of this quite general system. The expert system can successfully detect failures in the automated plasma reconstruction and provide (on successful reconstruction cases) statistics of agreement of the models with the experimental data, i.e. information on the model validity.