Potential effects of climate change on birds of the Northeast

We used three approaches to assess potential effects of climate change on birds of the Northeast. First, we created distribution and abundance models for common bird species using climate, elevation, and tree species variables and modeled how bird distributions might change as habitats shift. Second, we assessed potential effects on high-elevation birds, especially Bicknell’s thrush (Catharus bicknelli), that may be particularly vulnerable to climate change, by using statistical associations between climate, spruce-fir forest vegetation and bird survey data. Last, we complemented these projections with an assessment of how habitat quality of a migratory songbird, the black-throated blue warbler (Dendroica caerulescens) might be affected by climate change. Large changes in bird communities of the Northeast are likely to result from climate change, and these changes will be most dramatic under a scenario of continued high emissions. Indeed, high-elevation bird species may currently be at the threshold of critical change with as little as 1°C warming reducing suitable habitat by more than half. Species at mid elevations are likely to experience declines in habitat quality that could affect demography. Although not all species will be affected adversely, some of the Northeast’s iconic species, such as common loon and black-capped chickadee, and some of its most abundant species, including several neotropical migrants, are projected to decline significantly in abundance under all climate change scenarios. No clear mitigation strategies are apparent, as shifts in species’ abundances and ranges will occur across all habitat types and for species with widely differing ecologies.     

Modeling potential climate change impacts on the trees of the northeastern United States

We evaluated 134 tree species from the eastern United States for potential response to several scenarios of climate change, and summarized those responses for nine northeastern United States. We modeled and mapped each species individually and show current and potential future distributions for two emission scenarios (A1fi [higher emission] and B1 [lower emission]) and three climate models: the Parallel Climate, the Hadley CM3, and the Geophysical Fluid Dynamics Laboratory model. Climate change could have large impacts on suitable habitat for tree species in this region, especially under a high emissions trajectory. Results indicate that while species with potentially increasing areas of suitable habitat in the Northeastern US substantially outnumber those with decreasing areas of habitat, there are key species that show diminishing habitat area: balsam fir (Abies balsamea), paper birch (Betula papyrifera), red spruce (Picea rubens), bigtooth and quaking aspen (Populus grandidentata and P. tremuloides), and black cherry (Prunus serotina). From these results we identified the top 10 losers and gainers for each US state in the region by scenario and emissions trajectory. By combining individual species importance maps and developing assembly rules for various classes, we created maps of potential forest types for the Northeast showing a general loss of the spruce–fir zone with advancing oak–hickory type. Further data, maps, and analysis can be found at http://www.nrs.fs.fed.us/atlas.     

In vivo and in vitro control activity of plant essential oils against three strains of Aspergillus niger

Environmental Science and Pollution Research - Contamination of environment and food from the prevalent spores and mycotoxins of Aspergillus niger has led to several diseases in humans and other...     

Study of electromagnetic shielding effectiveness of metal oxide polymer composite in their bulk and layered forms

Environmental Science and Pollution Research - In this paper, we present the studies on electromagnetic interference (EMI) shielding effectiveness (SE) of K2CrO4-PMMA composites developed by two...     

Industrial hygiene and toxicity studies in unorganized bone-based industrial units

A large variety of ornamental and decorative items are manufactured from bone waste by various unorganized sectors in India. An initial survey indicated that workers were exposed at various phases of final product. The subjects (12 industrial units) were tested for total suspended particulate matter (TSPM), particulate matter <10  $\upmu $ m (PM₁₀), and particulate matter <2.5  $\upmu $ m (PM_2.5). Prevalent levels of TSPM ranged between 2.90 and 5.89 mg m^???3. Respirable fractions of occupational dust as PM₁₀ and PM_2.5 were found in the range of 0.30?C2.08 and 0.26?C0.50 mg m^???3, respectively. Cytotoxicity study was conducted using hemolysis as a sensitive marker. In an in vitro study, rat RBCs were exposed to the concentration of 25?C1,000  $\upmu $ g/ml for 15?C120 min. A considerable variation was observed in the hemolytic activity of samples collected from different areas. At 500  $\upmu $ g/ml concentration, the hemolytic activity (12 h) was found to be in the range of 18?C25%. Due to limitation in sample mass of respirable fractions, only one concentration (100  $\upmu $ g/ml/2 h) was used for comparative study on hemolysis of RBCs caused by PM₁₀ and PM_2.5. Interestingly, the hemolytic activity was more at PM_2.5 than PM₁₀ and TSPM. These results suggest that the respirable particles are capable of reaching deep into the respiratory system. The finding is significant notably when there are no standards available in occupationally exposed populations. This is the first such study. Data could be of importance to policy makers and regulators.     

Predicting extinctions as a result of climate change

Widespread extinction is a predicted ecological consequence of global warming. Extinction risk under climate change scenarios is a function of distribution breadth. Focusing on trees and birds of the eastern United States, we used joint climate and environment models to examine fit and climate change vulnerability as a function of distribution breadth. We found that extinction vulnerability increases with decreasing distribution size. We also found that model fit decreases with decreasing distribution size, resulting in high prediction uncertainty among narrowly distributed species. High prediction uncertainty creates a conservation dilemma in that excluding these species under-predicts extinction risk and favors mistaken inaction on global warming. By contrast, including narrow endemics results in over-predicting extinction risk and promotes mistaken inaction on behalf of individual species prematurely considered doomed to extinction.     

Glutathione and associated enzymes in toxic cataractogenesis-selenite model

Glutathione, gamma-glutamyl cysteine synthetase (gamma -GCS) and glutathione reductase (GSH-R) activity were determined biochemically in the lens during various stages after subcutaneous administration of sodium selenite in multiple low dosages and single high dosages. The GSH concentration and gamma-GCS and GSH-R activity declined progressively after the selenite administration. The changes observed were discussed in relation to the possible role of selenite interaction with GSH and the enzymes.     

Electrokinetic extraction of lead from kaolinites: I. Numerical modeling

Experimental results obtained to date indicate electrokinetic extraction is viable in removing organic and inorganic contaminants from fine-grained soils. However, electrochemical reactions and soil-contaminant interactions that occur simultaneously may enhance or reduce the removal efficiency of the hazardous waste site remediation process. Many sites worldwide are contaminated by lead and its compounds, resulting in lead poisoning. It is difficult to remove lead from fine-grained soil because of the existence of a great variety of lead complexes and their pH-dependent and reversible physicochemical properties. The feasibility of electrokinetic extraction of lead from kaolinites is investigated theoretically, numerically, and experimentally in this study. This is the first paper of two companion papers presenting the theoretical and numerical modeling of the transport of lead species, and electrochemical reactions and soil-contaminant interactions occurring during the electrokinetic extraction process. The comparison between simulation results and experimental results is presented in the second paper.     

Application of drastic model and GIS: for assessing vulnerability in hard rock granitic aquifer

Geographic information system (GIS) has become one of the leading tools in the field of hydrogeological science that helps in assessing, monitoring, and conserving groundwater resources. Groundwater is a finite resource, which is being overexploited due to increase in demand over the years leading to decrease in its potentiality. In the present study, DRASTIC model has been used to prepare groundwater vulnerable zone in hard rock aquifer of granitic terrain. The main objective is to determine susceptible zone for groundwater pollution by integrating hydrogeological layers in GIS environment. The layers such as depth of aquifer, recharge, aquifer yield, soil type, topography, vadose zone, and transmissivity are incorporated in the DRASTIC model. The final output of the map shows that around 60% of the area falls under low to no risk of pollution zone. The high risk of pollution zones are mostly present towards the margin of southeastern periphery. The lower part of the basin as well as small area on northern side falls under moderate risk of pollution zone. For the assessment of groundwater pollution zone, 24 groundwater samples have been collected from different vulnerable zones. The chemical analysis of sample shows that the southeastern margin of basin has relatively high concentration of nitrate as compared to other parts of the basin. It is present in high pollution zone as well as moderate pollution zone. The present model can be used for assessment and management of groundwater.     

Assessment of temporal variation in water quality of some important rivers in middle Gangetic plains, India

The study explains water quality of three important tributaries of the Ganga River in the middle Gangetic plains in India. Seasonal changes in the water quality of the studied rivers: Gandak, Ghaghra, and Sone were observed. During monsoon, several water quality parameters show considerable changes due to increased runoff from the catchments and other seasonal factors. Multivariate discriminant analysis delineated a few parameters responsible for temporal variation in water quality. Seasonal variation in water quality of the Gandak River was rendered by seven parameters??turbidity, sulfate, pH, phosphate, water temperature, total alkalinity, and sodium, while total alkalinity and water temperature were responsible for seasonal discrimination in water quality of Ghaghra River. Water temperature, turbidity, total dissolved solids, total suspended solids, calcium, and phosphate were important for seasonal discrimination in water quality of Sone River. The seasonal changes in water quality of the rivers were due to seasonal effects and catchment characteristics. The discriminant functions classified most of the cases correctly.