Prediction and uncertainty source analysis of the spatial and temporal disturbance from off-road vehicular traffic in a complex ecosystem

Vehicle use during military training activities results in soil disturbance and vegetation loss. The capacity of lands to sustain training is a function of the sensitivity of lands to vehicle use and the pattern of land use. The sensitivity of land to vehicle use has been extensively studied. Less well understood are the spatial patterns of vehicle disturbance. Since disturbance from off-road vehicular traffic moving through complex landscapes varies spatially, a spatially explicit nonlinear regression model (disturbance model) was used to predict the pattern of vehicle disturbance across a training facility. An uncertainty analysis of the model predictions assessed the spatial distribution of prediction uncertainty and the contribution of different error sources to that uncertainty.For the most part, this analysis showed that mapping and modeling process errors contributed more than 95% of the total uncertainty of predicted disturbance, while satellite imagery error contributed less than 5% of the uncertainty. When the total uncertainty was larger than a threshold, modeling error contributed 60% to 90% of the prediction uncertainty. Otherwise, mapping error contributed about 10% to 50% of the total uncertainty. These uncertainty sources were further partitioned spatially based on other sources of uncertainties associated with vehicle moment, landscape characterization, satellite imagery, etc.     

Correlation between the seasonal distribution of harbour porpoises and their prey in the Sound,Baltic Sea

Low densities of harbour porpoises in winter (November–March) and high densities in summer (April–October) were found in the Sound, connecting the Baltic Sea and Kattegat. Due to their high energy requirements, it is hypothesized that the density of harbour porpoises is related to local prey abundance. This was tested by examining the stomach content of 53 harbour porpoises collected between 1987 and 2010 in the Sound (high season, 34 porpoises; low season, 19 porpoises). A total of 1,442 individual fish specimens from thirteen species were identified. Twelve of these were present in the high–porpoise density season and seven in the low-density season. The distribution of occurrence and the distribution of number of fish species were different between seasons, indicating a shift in prey intake between seasons. Furthermore, during the high-density season, the mean and total prey weight per stomach as well as the prey species diversity was higher. However, no difference was found in the number of prey species between the two seasons, indicating a higher quality of prey in the high-density season. Atlantic cod was found to be the main prey species in terms of weight in the high-density season while Atlantic herring and Atlantic cod were equally important during the low-density season. Prey availability and predictability are suggested as the main drivers for harbour porpoise distribution, and this could be caused by the formation of frontal zones in spring in the northern part of the Sound, leading to prey concentrations in predictable areas.     

Application of capillary electrophoresis combined with a modified BCR sequential extraction for estimating of distribution of selected trace metals in PM2.5 fractions of urban airborne particulate matter

The capillary electrophoresis (CE) method combined with a sequential extraction was applied to determine the distribution of Fe, Zn, Cu, Mn and Cd in urban ambient air PM2.5 samples. PM2.5 was collected on Teflon filters with dichotomous sampler, and the modified extraction procedure following the BCR leaching procedure was used to chemically fractionate metals into "easily exchangeable" with water, "acid extractable" with 0.11 mol/l acetic acid, "reducible" with 0.1 mol/l hydroxylamine hydrochloride acidified to pH 2.0 with nitric acid, and "oxidisable" with oxidation by 8.8 mol/l hydrogen peroxide (H2O2) followed by extraction with 1.0 mol/l ammonium acetate. Based on the obtained results it was concluded that the application of the studied methodology provides chemical fractionation data that reflect the general sources and potential health hazards of the studied metals.     

Identification of differentially expressed genes response to TCDD in rat brain after long-term low-dose exposure

Several cohort studies have reported that dioxin and dioxin-like polychlorinated biphenyls might impair the nervous system and lead to neurological or neurodegenerative diseases in the elder people, but there is limited research on the involved mechanism. By using microarray analysis, we figured out the differentially expressed genes between brain samples from SD rats after low-dose(0.1 μg/(kg?bw)) dioxin exposure for six months and controls. To investigate the function changes in the course of dioxin exposure, Gene Ontology(GO) annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were performed on the differentially expressed genes. And the changes of several picked genes have been verified by real-time PCR. A total of 145 up-regulated and 64 down-regulated genes were identified. The metabolic processes, interleukin-1 secretion and production were significantly associated with the differentially expressed genes. And the genes regulated by dioxin also clustered to cholinergic synapse and long-term potentiation. Candidate biomarker genes such as egr1, gad2, gabrb3, abca1, ccr5 and pycard may be toxicological targets for dioxin. Furthermore, synaptic plasticity and neuro-immune system may be two principal affected areas by dioxin.     

Gene expression changes in blood RNA after swimming in a chlorinated pool

Exposure to disinfection by-products(DBP) such as trihalomethanes(THM) in swimming pools has been linked to adverse health effects in humans, but their biological mechanisms are unclear. We evaluated short-term changes in blood gene expression of adult recreational swimmers after swimming in a chlorinated pool. Volunteers swam 40 min in an indoor chlorinated pool. Blood samples were drawn and four THM(chloroform,bromodichloromethane, dibromochloromethane and bromoform) were measured in exhaled breath before and after swimming. Intensity of physical activity was measured as metabolic equivalents(METs). Gene expression in whole blood m RNA was evaluated using Illumina Human HT-12v3 Expression-Bead Chip. Linear mixed models were used to evaluate the relationship between gene expression changes and THM exposure. Thirty-seven before-after pairs were analyzed. The median increase from baseline to after swimming were: 0.7 to 2.3 for MET, and 1.4 to 7.1 μg/m~3 for exhaled total THM(sum of the four THM).Exhaled THM increased on average 0.94 μg/m~3 per 1 MET. While 1643 probes were differentially expressed post-exposure. Of them, 189 were also associated with exhaled levels of individual/total THM or MET after False Discovery Rate. The observed associations with the exhaled THM were low to moderate(Log-fold change range:-0.17 to 0.15). In conclusion, we identified short-term gene expression changes associated with swimming in a pool that were minor in magnitude and their biological meaning was unspecific. The high collinearity between exhaled THM levels and intensity of physical activity precluded mutually adjusted models with both covariates. These exploratory results should be validated in future studies.     

Changes in soil respiration across a chronosequence of tallgrass prairie reconstructions

Close relationships among climatic factors and soil respiration (R_s) are commonly reported. However, variation in R_s across the landscape is compounded by site-specific differences that impede the development of spatially explicit models. Among factors that influence R_s, the effect of ecosystem age is poorly documented. We hypothesized that R_s increases with grassland age and tested this hypothesis in a chronosequence of tallgrass prairie reconstructions in central Iowa, U.S.A. We also assessed changes in root biomass, root ingrowth, aboveground net primary productivity (ANPP), and the strength of soil temperature and moisture in predicting R_s. We found a significant increase in total growing season R_s with prairie age (R² = 0.79), ranging from 714 g C m^?2 in the youngest reconstruction (age 4) to 939 g C m^?2 in the oldest prairie (age 12). Soil temperature was a strong predictor of intra-seasonal R_s among prairies (R² = 0.78–0.87) but mean growing season soil temperature and moisture did not relate to total R_s. The increase in R_s with age was positively correlated with root biomass (r = 0.80) and ANPP (r = 0.87) but not with root ingrowth. Our findings suggest that growing season R_s increases with tallgrass prairie age, root biomass, and ANPP during young grassland development.