33 resultados para Localized hypertrichosis
Resumo:
Phlebiopsis gigantea has been for a long time known as a strong competitor against Heterobasidion annosum and intensively applied as a biological control agent on stump surfaces of Picea abies in Fennoscandia. However, the mechanism underlying its antagonistic activity is still unknown. A primary concern is the possible impact of P. gigantea treatment on resident non-target microbial biota of conifer stumps. Additional risk factor is the potential of P. gigantea to acquire a necrotrophic habit through adaptation to living wood tissues. This study focused on the differential screening of several P. gigantea isolates from diverse geographical sources as well as the use of breeding approach to enhance the biocontrol efficacy against H. annosum infection. The results showed a significant positive correlation between growth rate in wood and high biocontrol efficacy. Furthermore, with aid of breeding approach, several progeny strains were obtained that had better growth rate and control efficacy than parental isolates. To address the issue of the potential of P. gigantea to acquire necrotrophic capability, a combination of histochemical, molecular and transcript profiling (454 sequencing) were used to investigate the interactions between these two fungi and ten year old P. sylvestris seedlings. The results revealed that both P. gigantea and H. annosum provoked strong necrotic lesions, but after prolonged incubation, P. gigantea lesions shrank and ceased to expand further. Tree seedlings pre-treated with P. gigantea further restricted H. annosum-induced necrosis and had elevated transcript levels of genes important for lignification, cell death regulation and jasmonic acid signalling. These suggest that induced localized resistance is a contributory factor for the biocontrol efficacy of P.gigantea, and it has a comparatively limited necrotrophic capability than H. annosum. Finally, to investigate the potential impact of P. gigantea on the stump bacterial biota, 16S rDNA isolated from tissue samples from stumps of P. abies after 1-, 6- and 13-year post treatment was sequenced using bar-coded 454 Titanium pyrosequencing. Proteobacteria were found to be the most abundant at the initial stages of stump decay but were selectively replaced by Acidobacteria at advanced stages of the decay. Moreover, P. gigantea treatment significantly decreased the bacterial richness at initial decay stage in the stumps. Over time, the bacterial community in the stumps gradually recovered and the negative effects of P. gigantea was attenuated.
Resumo:
The Grad–Shafranov reconstruction is a method of estimating the orientation (invariant axis) and cross section of magnetic flux ropes using the data from a single spacecraft. It can be applied to various magnetic structures such as magnetic clouds (MCs) and flux ropes embedded in the magnetopause and in the solar wind. We develop a number of improvements of this technique and show some examples of the reconstruction procedure of interplanetary coronal mass ejections (ICMEs) observed at 1 AU by the STEREO, Wind, and ACE spacecraft during the minimum following Solar Cycle 23. The analysis is conducted not only for ideal localized ICME events but also for non-trivial cases of magnetic clouds in fast solar wind. The Grad–Shafranov reconstruction gives reasonable results for the sample events, although it possesses certain limitations, which need to be taken into account during the interpretation of the model results.
Resumo:
Periglacial processes act on cold, non-glacial regions where the landscape deveploment is mainly controlled by frost activity. Circa 25 percent of Earth's surface can be considered as periglacial. Geographical Information System combined with advanced statistical modeling methods, provides an efficient tool and new theoretical perspective for study of cold environments. The aim of this study was to: 1) model and predict the abundance of periglacial phenomena in subarctic environment with statistical modeling, 2) investigate the most import factors affecting the occurence of these phenomena with hierarchical partitioning, 3) compare two widely used statistical modeling methods: Generalized Linear Models and Generalized Additive Models, 4) study modeling resolution's effect on prediction and 5) study how spatially continous prediction can be obtained from point data. The observational data of this study consist of 369 points that were collected during the summers of 2009 and 2010 at the study area in Kilpisjärvi northern Lapland. The periglacial phenomena of interest were cryoturbations, slope processes, weathering, deflation, nivation and fluvial processes. The features were modeled using Generalized Linear Models (GLM) and Generalized Additive Models (GAM) based on Poisson-errors. The abundance of periglacial features were predicted based on these models to a spatial grid with a resolution of one hectare. The most important environmental factors were examined with hierarchical partitioning. The effect of modeling resolution was investigated with in a small independent study area with a spatial resolution of 0,01 hectare. The models explained 45-70 % of the occurence of periglacial phenomena. When spatial variables were added to the models the amount of explained deviance was considerably higher, which signalled a geographical trend structure. The ability of the models to predict periglacial phenomena were assessed with independent evaluation data. Spearman's correlation varied 0,258 - 0,754 between the observed and predicted values. Based on explained deviance, and the results of hierarchical partitioning, the most important environmental variables were mean altitude, vegetation and mean slope angle. The effect of modeling resolution was clear, too coarse resolution caused a loss of information, while finer resolution brought out more localized variation. The models ability to explain and predict periglacial phenomena in the study area were mostly good and moderate respectively. Differences between modeling methods were small, although the explained deviance was higher with GLM-models than GAMs. In turn, GAMs produced more realistic spatial predictions. The single most important environmental variable controlling the occurence of periglacial phenomena was mean altitude, which had strong correlations with many other explanatory variables. The ongoing global warming will have great impact especially in cold environments on high latitudes, and for this reason, an important research topic in the near future will be the response of periglacial environments to a warming climate.