Drought frequency and intensity has been predicted to increase under many climate change scenarios. It is therefore critical to understand the response of forests to potential climate change in an effort to mitigate adverse impacts. The purpose of this study was to explore the regional effects of different drought severities on tree growth and mortality. Specifically, we investigated changes in growth and mortality rates across the southeastern United States under various drought and stand conditions using 1991-2005 Forest Health and Monitoring (FHM) plot data from Alabama, Georgia, and Virginia. Drought effects were examined for three species groups (pines, oaks, and mesophytic species) using the Palmer drought severity index (PDSI) as an indicator of drought severity. Stand variables, including total basal area, total tree density, tree species richness, slope, and stand age, were used to account for drought effects under varying stand conditions. The pines and mesophytic species exhibited significant reductions in growth rate with increasing drought severity. However, no significant difference in growth rate was observed within the oak species group. Mean mortality rates within the no-drought class were significantly lower than those within the other three drought classes, among which no significant differences were found, for both pines and mesophytic species. Mean mortality rates were not significantly different among drought classes for oaks. Total basal area, total tree density, and stand age were negatively related to growth and positively related to mortality, which suggests that older and denser stands are more susceptible to drought damage. The effect of basal area on growth increased with drought severity for the oak and mesophytic species groups. Tree species richness was negatively related to mortality for the pine and mesophytic species groups, indicating that stands with more species suffer less mortality. Slope was positively related to mortality within the mesophytic species group, and its effect increased with drought severity, indicating a higher mortality on sites of greater slope during severe-drought conditions. Our findings indicate that pines and mesophytic species are sensitive to drought, while oaks are tolerant of drought. The observed differential growth and mortality rates among species groups may alter the species composition of southeastern U.S. forests if drought episodes become more frequent and/or intense due to climate change. The significant effects of stand conditions on drought responses observed in our study also suggest that forest management may be used as a tool to mitigate drought effects.

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In the present study, Quantitative Structure-Activity Relationship (QSAR) and Linear Solvation Energy Relationship (LSER) techniques were used to develop predictive models for adsorption of organic contaminants by multi-walled carbon nanotubes (MWCNTs). Adsorption data for 29 aromatic compounds from literature (i.e., the training data) including some of the experimental results obtained in our laboratory were used to develop predictive models with multiple linear regression analysis. The generated QSAR (r(2) = 0.88), and LSER (r(2) = 0.83) equations were validated externally using an independent validation data set of 30 aromatic compounds. External validation accuracies indicated the success of parameter selection, data fitting ability, and the prediction strength of the developed models. Finally, the combination of training and validation data were used to obtain a combined LSER equation (r(2) = 0.83) that would be used for predicting adsorption of a wide range of low molecular weight aromatics by MWCNTs. In addition, LSER models at different concentrations were generated, and LSER parameter coefficients were examined to gain insights to the predominant adsorption interactions of low molecular weight aromatics on MWCNTs. The molecular volume term (V) of the LSER model was the most influential descriptor controlling adsorption at all concentrations. At higher equilibrium concentrations, hydrogen bond donating (A) and hydrogen bond accepting (B) terms became significant in the models. The results demonstrate that successful predictive models can be developed for the adsorption of organic compounds by CNTs using QSAR and LSER techniques.

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Thermal inactivation of desiccation-adapted Salmonella spp. in aged chicken litter was investigated in comparison with that in a nonadapted control to examine potential cross-tolerance of desiccation-adapted cells to heat treatment. A mixture of four Salmonella serovars was inoculated into the finished compost with 20, 30, 40, and 50% moisture contents for a 24-h desiccation adaptation. Afterwards, the compost with desiccation-adapted cells was inoculated into the aged chicken litter with the same moisture content for heat treatments at 70, 75, 80, 85, and 150°C. Recovery media were used to allow heat-injured cells to resuscitate. A 5-log reduction in the number of the desiccation-adapted cells in aged chicken litter with a 20% moisture content required >6, >6, ϳ4 to 5, and ϳ3 to 4 h of exposure at 70, 75, 80, and 85°C, respectively. As a comparison, a 5-log reduction in the number of nonadapted control cells in the same chicken litter was achieved within ϳ1.5 to 2, ϳ1 to 1.5, ϳ0.5 to 1, and <0.5 h at 70, 75, 80, and 85°C, respectively. The exposure time required to obtain a 5-log reduction in the number of desiccation-adapted cells gradually became shorter as temperature and moisture content were increased. At 150°C, desiccation-adapted Salmonella cells survived for 50 min in chicken litter with a 20% moisture content, whereas control cells were detectable by enrichment for only 10 min. Our results demonstrated that the thermal resistance of Salmonella in aged chicken litter was increased significantly when the cells were adapted to desiccation. This study also validated the effectiveness of thermal processing being used for producing chicken litter free of Salmonella contamination. Chicken litter is a waste by-product of poultry production and is comprised of feces, wasted feeds, bedding materials, and feathers (1). More than 14 million tons of chicken litter is produced annually in the United States (2). Chicken litter is usually recycled as an organic fertilizer or soil amendment for direct application to agricultural land (3). However, chicken litter may contain loads of human pathogens, such as Salmonella spp., that have great potential to directly or indirectly contaminate fresh produce and cause food-borne disease outbreaks (1). Currently, high-temperature processing is the most commonly applied method to reduce or eliminate potential pathogens in chicken litter (1, 4).Some microorganisms become acclimatized to desiccation stress in a dry environment, and induction of the desiccation stress response in bacterial cells makes them more resistant to the dry condition in which they are present (5). Most importantly, exposure to a single stress is found to be associated with the development of cross-tolerance to multiple unrelated stresses (6). Using laboratory models, various researchers have demonstrated that the desiccated cells exhibit increased thermal resistance (6-8). Previous thermal-inactivation studies on bacterial pathogens in chicken litter have used only nonstressed cells (1, 4). Therefore, to si...