Interactions Among Fuel Management,Species Composition,Bark Beetles,and Climate Change and the Potential Effects on Forests of the Lake Tahoe Basin

Climate-driven increases in wildfires, drought conditions, and insect outbreaks are critical threats to forest carbon stores. In particular, bark beetles are important disturbance agents although their long-term interactions with future climate change are poorly understood. Droughts and the associated moisture deficit contribute to the onset of bark beetle outbreaks although outbreak extent and severity is dependent upon the density of host trees, wildfire, and forest management. Our objective was to estimate the effects of climate change and bark beetle outbreaks on ecosystem carbon dynamics over the next century in a western US forest. Specifically, we hypothesized that (a) bark beetle outbreaks under climate change would reduce net ecosystem carbon balance (NECB) and increase uncertainty and (b) these effects could be ameliorated by fuels management. We also examined the specific tree species dynamics—competition and release—that determined NECB response to bark beetle outbreaks. Our study area was the Lake Tahoe Basin (LTB), CA and NV, USA, an area of diverse forest types encompassing steep elevation and climatic gradients and representative of mixed-conifer forests throughout the western United States. We simulated climate change, bark beetles, wildfire, and fuels management using a landscape-scale stochastic model of disturbance and succession. We simulated the period 2010–2100 using downscaled climate projections. Recurring droughts generated conditions conducive to large-scale outbreaks; the resulting large and sustained outbreaks significantly increased the probability of LTB forests becoming C sources over decadal time scales, with slower-than-anticipated landscape-scale recovery. Tree species composition was substantially altered with a reduction in functional redundancy and productivity. Results indicate heightened uncertainty due to the synergistic influences of climate change and interacting disturbances. Our results further indicate that current fuel management practices will not be effective at reducing landscape-scale outbreak mortality. Our results provide critical insights into the interaction of drivers (bark beetles, wildfire, fuel management) that increase the risk of C loss and shifting community composition if bark beetle outbreaks become more frequent.     

Does maternal condition or predation risk influence small mammal population dynamics?

There is strong debate over whether the intrinsic traits of individuals or the extrinsic environment exert the greater influence on small mammal population dynamics. We test the roles of maternal effects (an intrinsic factor) and predation risk (an extrinsic factor) in the population dynamics of wild strain house mice using a 2-factor enclosure experiment. Pre-release supplemental feeding with a high-fat diet created female treatment founders that were 6–10% heavier than controls, a condition that we predicted would be passed on as a maternal effect. Predation risk was enhanced using regular application of predator (red fox Vulpes vulpes ) scats. Founder populations of six females and six males released into eight, 15×15 m enclosures showed near exponential population growth over 17 weeks (maximum 3 generations). But there were no responses to either treatment in terms of survival, inherited body weights, fecundity or population size. We suggest that elevated maternal condition may have only minor and transient intergenerational effects with little long-term consequence. We also suggest that the general significance of predator scats as a cue to predation risk to alter prey behaviour may have been overestimated. Hence our results question the role of either factor in causing long-term responses that influence condition to affect population processes.     

Temperature influences the expression of fimbriae and flagella in <Emphasis Type="Italic">Hafnia alvei</Emphasis> strains: an immunofluorescence study

Hafnia alvei, a Gram negative bacillus related to the Enterobacteriaceae family, is considered an opportunistic pathogen of several animal species and humans. In this communication, we describe fimbrial-like structures from different strains of H. alvei that cannot be easily ascribed to any of the previously reported fimbrial types in this species (type I or type III). Polymerase chain reaction (PCR) and immunofluorescence assays were carried out to study fimbriae and flagella in H. alvei strains isolated from different sources. No correlation between the results obtained by PCR and those obtained by phenotypic methods were found, and the antibodies used gave cross or different recognition patterns of the surface structures present in these strains. We report as well that strain and growth temperature influence fimbriation and expression of flagella in human and animal isolates of H. alvei. This study also indicates that the absence of fimbriae have a significant positive influence on the initial adhesion of H. alvei to human epithelial cells.     

Hydrophobia, lectin binding, and molecular order in the stratum corneum of adult and neonatal rats and in human breast cells in culture.

A search for differences due to ANS staining (hydrophobia), Con A and PNA binding capacity, and birefringence was carried out on stratified epithelia of rat skin and human breast cells (HBC) in culture. Microfluorimetric measurements confirm that the ANS fluorescence of the stratum corneum from adults is higher than that of newborns. HBC exhibited an unexpected deep ANS-fluorescence. Differences in the binding capacity of the epithelial layers to Con A and PNA were detected with advancing age. Retardation measurements revealed that the form birefringence of the stratum corneum is higher in adult animals specially as revealed by the fact that its form birefringence curve branch from n = 1.414 to n = 1.479 is steeper, i.e. depict higher values. The strong birefringence of the cytoplasmic tonofilaments presented by cultured human breast cells was considered an unexpected finding and attributed to changes that the cells underwent following the in vitro conditions.     

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples.

     

Thermal analysis of the dentine tubule under hot and cold stimuli using fluid–structure interaction simulation

The objective of this study is to compare the thermal stress changes in the tooth microstructures and the hydrodynamic changes of the dental fluid under hot and cold stimuli. The dimension of the microstructures of eleven cats’ teeth was measured by scanning electron microscopy, and the changes in thermal stress during cold and hot stimulation were calculated by 3D fluid–structure interaction modeling. Evaluation of results, following data validation, indicated that the maximum velocities in cold and hot stimuli were ??410.2?±?17.6 and +?205.1?±?8.7 µm/s, respectively. The corresponding data for maximum thermal stress were ??20.27?±?0.79 and +?10.13?±?0.24 cmHg, respectively. The thermal stress caused by cold stimulus could influence almost 2.9 times faster than that caused by hot stimulus, and the durability of the thermal stress caused by hot stimulus was 71% greater than that by cold stimulus under similar conditions. The maximum stress was on the tip of the odontoblast, while the stress in lateral walls of the odontoblast and terminal fibril was very weak. There is hence a higher possibility of pain transmission with activation of stress-sensitive ion channels at the tip of the odontoblast. The maximum thermal stress resulted from the cold stimulus is double that produced by the hot stimulus. There is a higher possibility of pain transmission in the lateral walls of the odontoblast and terminal fibril by releasing mediators during the cold stimulation than the hot stimulation. These two reasons can be associated with a greater pain sensation due to intake of cold liquids.