Taxonomy and phylogeny of Ophiostoma spp. with Sporothrix anamorphs and their generic relationships in the Ophiostomatales

The ophiostomatoid fungi included more than 450 species of ascomycetes specifically adapted for insect dispersal. Many of these species have a significant economic impact as sapstaining fungi or tree pathogens harmful to forestry industries, but some are also as opportunistic human pathogens. DNA based studies in recent years have shown that the majority of these fungi belonged in either the Ophiostomatales or Microascales (Sordariomycetes), with a few Sporothrix spp. grouping in the Microstromatales (Ustilaginomycetes). However, most phylogenetic studies have focussed on restricted numbers of taxa sharing similar morphology. The aim of the studies in this thesis was to reconsider the taxonomy of all the ophiostomatoid fungi at the order and family levels, and the status of genera and species with sporothrix-like anamorphs in the Ophiostomatales and Microstromatales. All available published sequence data were screened for reliable sequences representing as many species as possible, and new data were generated where necessary for ex-type or other isolates. The resulting phylogenies enabled the formal redefinition of the Ophiostomatales and Ophiostomataceae, and the description of two new families, the Graphiaceae (Microascales) and Quambalariaceae (Microstromatales). Problems relating to the delineation of Ophiostoma s.l., Leptographium s.l., and Raffaelea s.l. were exposed and discussed, 18 species complexes were defined in the Ophiostomatales, and four genera were formally redefined: Sporothrix, Graphium, Graphilbum and Knoxdaviesia. Forty six new combinations were made, primarily in Sporothrix, Ophiostoma, Graphilbum and Knoxdaviesia. One nomen novum was erected in Ceratocystis and one new Quambalaria species was described. A comprehensive nomenclator for 596 ophiostomatoid species including references to all descriptions, synonymies and phylogenetic data was also compiled. This study represents the first comprehensive, all-inclusive assessment of the taxonomy and nomenclature of the ophisotomatoid fungi based on phylogenetic relationships and the one fungus one name principles. Finally, the immediate and indiscriminate application of the one fungus one name principles in Ophiostoma s.l. and Leptographium s.l. might result in many unnecessary name changes. Thus, several recommendations have been made to ensure nomenclatural stability in these genera in the immediate future and until more robust phylogenies become available that can refine the delineation of these genera.PhDMicrobiology and Plant PathologyUnrestricte

History Matching with Subset Simulation

Computational cost often hinders the calibration of complex computer models. In this context, history matching (HM) is becoming a widespread calibration strategy, with applications in many disciplines. HM uses a statistical approximation, also known as an emulator, to the model output, in order to mitigate computational cost. The process starts with an observation of a physical system. It then produces progressively more accurate emulators to determine a non-implausible domain: a subset of the input space that provides a good agreement between the model output and the data, conditional on the model structure, the sources of uncertainty, and an implausibility measure. In HM, it is essential to generate samples from the nonimplausible domain, in order to run the model and train the emulator until a stopping condition is met. However, this sampling can be very challenging, since the nonimplausible domain can become orders of magnitude smaller than the original input space very quickly. This paper proposes a solution to this problem using subset simulation, a rare event sampling technique that works efficiently in high dimensions. The proposed approach is demonstrated via calibration and robust design examples from the field of aerospace engineering

DNA sequence comparisons of Ophiostoma spp., including Ophiostoma aurorae sp. nov., associated with pine bark beetles in South Africa

Bark beetles (Coleoptera: Scolytinae) are well-recognized vectors of Ophiostoma species. Three non-native bark beetle species infest various Pinus species in South Africa, and they are known to carry at least 12 different species of ophiostomatoid fungi. Some of these fungi have not been identified to species level. The aim of this study was to determine or confirm the identities of Ophiostoma species associated with bark beetles in South Africa using comparisons of DNA sequence data. Identities of Ophiostoma ips, O. floccosum, O. pluriannulatum, O. quercus and O. stenoceras were confirmed. Ophiostoma abietinum, O. piliferum and Pesotum fragrans are recognised for the first time and the new species, O. aurorae sp. nov., is described from pine-infesting bark beetles in South Africa

Non-intrusive stochastic analysis with parameterized imprecise probability models: II. Reliability and rare events analysis

© 2019 Elsevier Ltd Structural reliability analysis for rare failure events in the presence of hybrid uncertainties is a challenging task drawing increasing attentions in both academic and engineering fields. Based on the new imprecise stochastic simulation framework developed in the companion paper, this work aims at developing efficient methods to estimate the failure probability functions subjected to rare failure events with the hybrid uncertainties being characterized by imprecise probability models. The imprecise stochastic simulation methods are firstly improved by the active learning procedure so as to reduce the computational costs. For the more challenging rare failure events, two extended subset simulation based sampling methods are proposed to provide better performances in both local and global parameter spaces. The computational costs of both methods are the same with the classical subset simulation method. These two methods are also combined with the active learning procedure so as to further substantially reduce the computational costs. The estimation errors of all the methods are analyzed based on sensitivity indices and statistical properties of the developed estimators. All these new developments enrich the imprecise stochastic simulation framework. The feasibility and efficiency of the proposed methods are demonstrated with numerical and engineering test examples

Non-intrusive stochastic analysis with parameterized imprecise probability models: I. Performance estimation

© 2019 Elsevier Ltd Uncertainty propagation through the simulation models is critical for computational mechanics engineering to provide robust and reliable design in the presence of polymorphic uncertainty. This set of companion papers present a general framework, termed as non-intrusive imprecise stochastic simulation, for uncertainty propagation under the background of imprecise probability. This framework is composed of a set of methods developed for meeting different goals. In this paper, the performance estimation is concerned. The local extended Monte Carlo simulation (EMCS) is firstly reviewed, and then the global EMCS is devised to improve the global performance. Secondly, the cut-HDMR (High-Dimensional Model Representation) is introduced for decomposing the probabilistic response functions, and the local EMCS method is used for estimating the cut-HDMR component functions. Thirdly, the RS (Random Sampling)-HDMR is introduced to decompose the probabilistic response functions, and the global EMCS is applied for estimating the RS-HDMR component functions. The statistical errors of all estimators are derived, and the truncation errors are estimated by two global sensitivity indices, which can also be used for identifying the influential HDMR components. In the companion paper, the reliability and rare event analysis are treated. The effectiveness of the proposed methods are demonstrated by numerical and engineering examples

A Possible Hidden Population of Spherical Planetary Nebulae

We argue that relative to non-spherical planetary nebulae (PNs), spherical PNs are about an order of magnitude less likely to be detected, at distances of several kiloparsecs. Noting the structure similarity of halos around non-spherical PNs to that of observed spherical PNs, we assume that most unobserved spherical PNs are also similar in structure to the spherical halos around non-spherical PNs. The fraction of non-spherical PNs with detected spherical halos around them, taken from a recent study, leads us to the claim of a large (relative to that of non-spherical PNs) hidden population of spherical PNs in the visible band. Building a toy model for the luminosity evolution of PNs, we show that the claimed detection fraction of spherical PNs based on halos around non-spherical PNs, is compatible with observational sensitivities. We use this result to update earlier studies on the different PN shaping routes in the binary model. We estimate that ~30% of all PNs are spherical, namely, their progenitors did not interact with any binary companion. This fraction is to be compared with the ~3% fraction of observed spherical PNs among all observed PNs. From all PNs, ~15% owe their moderate elliptical shape to the interaction of their progenitors with planets, while \~55% of all PNs owe their elliptical or bipolar shapes to the interaction of their progenitors with stellar companions.Comment: AJ, in pres

DNA-based identification of Quambalaria pitereka causing severe leaf blight of Corymbia citriodora in China

Quambalaria spp. include serious plant pathogens, causing leaf and shoot blight of Corymbia and Eucalyptus spp. In this study, a disease resembling Quambalaria leaf blight was observed on young Corymbia citriodora trees in a plantation in the Guangdong Province of China. Comparisons of rDNA sequence data showed that the causal agent of the disease is Q. pitereka. This study provides the first report of Quambalaria leaf blight from China, and it is also the first time that this pathogen has been found on trees outside the native range of Eucalypts

Exotic Invasive Elm Bark Beetle, \u3cem\u3eScolytus kirschii\u3c/em\u3e, Detected in South Africa

In February 2005, the exotic bark beetle, Scolytus kirschii (Curculionidae: Scolytinae), was detected infesting English elms (Ulmus procera) in Stellenbosch, South Africa. This appears to be the first report of an infestation of Scolytus species in this country. The presence of this beetle is of concern for several reasons. Scolytus kirschii is a serious pest of elms, capable of killing healthy trees, resulting in considerable economic impact. There also exists the possibility that the beetle may undergo a host switch to indigenous trees, with potentially serious ecological consequences. Furthermore, the beetle is capable of being the vector of the pathogens responsible for Dutch elm disease (DED), Ophiostoma ulmi and Ophiostoma novo-ulmi. None of the trees that we inspected in Stellenbosch exhibited symptoms or signs of DED. Isolations from infested host material likewise failed to detect these pathogens. Nonetheless, the damage to the trees by the beetles alone was sufficient to cause tree death. Future directions for research and management of the beetle in its new environment are discussed

Functional perspective of uncertainty quantification for stochastic parametric systems and global sensitivity analysis

Uncertainty exists broadly in real engineering design and analysis. For instance, some mechanical parameters of structures in civil engineering may be of randomness and usually cannot be ignored. Therefore, the process of uncertainty quantification, e.g., the sensitivity analysis on parameters of stochastic systems is, of paramount significance to reasonable engineering design and decision-making. In the present paper, the perspective of functional space analysis on uncertainty quantification and propagation in stochastic systems is firstly stated. On this basis, the global sensitivity index (GSI) is introduced based on the functional Fréchet derivative, of which some basically mathematical and physical properties are studied. Besides, the correspondingly defined importance measure and direction sensitivity of the GSI are also discussed, in terms of their geometric and physical meanings. Moreover, based on the definition of ε-equivalent distribution, the parametric form of the proposed GSI is elaborated in detail. By incorporating the probability density evolution method (PDEM) and the change of probability measure (COM), the numerical algorithm of the GSI and the procedure of sensitivity analysis are illustrated. Four numerical examples, including the analytical function of the linear combination of normal random variables, stability analysis of the rock bolting system of tunnel, the analysis of steadystate confined seepage below the dam, and the stochastic structural analysis of the reinforced concrete frame, are analyzed to demonstrate the effectiveness and significance of the GSI