Interaction webs in arctic ecosystems: Determinants of arctic change?

How species interact modulate their dynamics, their response to environmental change, and ultimately the functioning and stability of entire communities. Work conducted at Zackenberg, Northeast Greenland, has changed our view on how networks of arctic biotic interactions are structured, how they vary in time, and how they are changing with current environmental change: firstly, the high arctic interaction webs are much more complex than previously envisaged, and with a structure mainly dictated by its arthropod component. Secondly, the dynamics of species within these webs reflect changes in environmental conditions. Thirdly, biotic interactions within a trophic level may affect other trophic levels, in some cases ultimately affecting land–atmosphere feedbacks. Finally, differential responses to environmental change may decouple interacting species. These insights form Zackenberg emphasize that the combination of long-term, ecosystem-based monitoring, and targeted research projects offers the most fruitful basis for understanding and predicting the future of arctic ecosystems.     

Modeling transit bus fuel consumption on the basis of cycle properties

A method exists to predict heavy-duty vehicle fuel economy and emissions over an "unseen" cycle or during unseen on-road activity on the basis of fuel consumption and emissions data from measured chassis dynamometer test cycles and properties (statistical parameters) of those cycles. No regression is required for the method, which relies solely on the linear association of vehicle performance with cycle properties. This method has been advanced and examined using previously published heavy-duty truck data gathered using the West Virginia University heavy-duty chassis dynamometer with the trucks exercised over limited test cycles. In this study, data were available from a Washington Metropolitan Area Transit Authority emission testing program conducted in 2006. Chassis dynamometer data from two conventional diesel buses, two compressed natural gas buses, and one hybrid diesel bus were evaluated using an expanded driving cycle set of 16 or 17 different driving cycles. Cycle properties and vehicle fuel consumption measurements from three baseline cycles were selected to generate a linear model and then to predict unseen fuel consumption over the remaining 13 or 14 cycles. Average velocity, average positive acceleration, and number of stops per distance were found to be the desired cycle properties for use in the model. The methodology allowed for the prediction of fuel consumption with an average error of 8.5% from vehicles operating on a diverse set of chassis dynamometer cycles on the basis of relatively few experimental measurements. It was found that the data used for prediction should be acquired from a set that must include an idle cycle along with a relatively slow transient cycle and a relatively high speed cycle. The method was also applied to oxides of nitrogen prediction and was found to have less predictive capability than for fuel consumption with an average error of 20.4%.     

Downscaling and visioning of mountain snow packs and other climate change implications in North Vancouver, British Columbia

This paper provides an overview of a collaborative study on visualizing climate change at the local scale. A conceptual framework has been developed, in which local scenarios and visualizations of climate change impacts and response were created to facilitate local dialogue on incorporating climate change into long-term planning and implementation of community development decisions. As part of a larger effort to generate a new integrated participatory visioning process, this paper describes a case study of the District of North Vancouver which created visualizations of changing mountain snow and landscape conditions, and provides new insights on issues and dilemmas in using realistic landscape visualizations to depict scientific modelling projections, local responses to climate change, and uncertainty. Results from this study suggest that the visualizations, and subsequent dialogue sessions, did influence emotional response to climate change as well as self-assessed understanding of adaptation and mitigation response options. However, there is a need to test this visioning process with larger heterogeneous groups of participants in order to better assess its effectiveness in enabling dialogue on local responses to climate change.     

Use of CALPUFF for exposure assessment in a near-field,complex terrain setting

CALPUFF is an atmospheric source-receptor model recommended by the U.S. Environmental Protection Agency for use on a case-by-case basis in complex terrain and wind conditions. The ability of the model to provide useful information for exposure assessments in areas with those topographical and meteorological conditions has received little attention. This is an important knowledge gap for use of CALPUFF outside of regulatory applications, such as exposure analyses conducted in support of risk assessments and health studies. We compared deposition of cadmium (Cd), lead (Pb), and zinc (Zn) calculated with CALPUFF as a result of emissions from a zinc smelter with corresponding concentrations of the metals measured in attic dust and soil samples obtained from the surrounding area. On a point-by-point analysis, predictions from CALPUFF explained 11% (lead) to 53% (zinc) of the variability in concentrations measured in attic dust. Levels of heavy metals in soil interpolated to 100 residential addresses from the distribution of concentrations measured in soil samples also agreed well with deposition predicted with CALPUFF: R² of 0.46, 0.76, and 079 for Pb, Cd, and Zn, respectively. Community-average concentrations of Cd, Pb, and Zn measured in soil were significantly (p < 0.0001) and strongly correlated (R² ranged from 0.77 to 0.98) with predicted deposition rates. These findings demonstrate that CALPUFF can provide reasonably accurate predictions of the patterns of long-term air pollutant deposition in the near-field associated with emissions from a discrete source in complex terrain. Because deposition estimates are calculated as a linear function of air concentrations, CALPUFF is expected to be reliable model for prediction of long-term average, near-field ambient air concentrations in complex terrain as well.     

Strontium isotope study of coal utilization by-products interacting with environmental waters

Sequential leaching experiments on coal utilization by-products (CUB) were coupled with chemical and strontium (Sr) isotopic analyses to better understand the influence of coal type and combustion processes on CUB properties and the release of elements during interaction with environmental waters during disposal. Class C fly ash tended to release the highest quantity of minor and trace elements-including alkaline earth elements, sodium, chromium, copper, manganese, lead, titanium, and zinc-during sequential extraction, with bottom ash yielding the lowest. Strontium isotope ratios ((87)Sr/(86)Sr) in bulk-CUB samples (total dissolution of CUB) are generally higher in class F ash than in class C ash. Bulk-CUB ratios appear to be controlled by the geologic source of the mineral matter in the feed coal, and by Sr added during desulfurization treatments. Leachates of the CUB generally have Sr isotope ratios that are different than the bulk value, demonstrating that Sr was not isotopically homogenized during combustion. Variations in the Sr isotopic composition of CUB leachates were correlated with mobility of several major and trace elements; the data suggest that arsenic and lead are held in phases that contain the more radiogenic (high-(87)Sr/(86)Sr) component. A changing Sr isotope ratio of CUB-interacting waters in a disposal environment could forecast the release of certain strongly bound elements of environmental concern. This study lays the groundwork for the application of Sr isotopes as an environmental tracer for CUB-water interaction.     

Development and Use of a Sedimentation Risk Index for Unpaved Road‐Stream Crossings in the Choctawhatchee Watershed1

Abstract: Unpaved road‐stream crossings increase sediment yields in streams and alter channel morphology and stability. Before restoration and sedimentation reduction strategies can be implemented, a priority listing of unpaved road‐stream crossings must be created. The objectives of this study were to develop a sedimentation risk index (SRI) for unpaved road‐stream crossings and to prioritize 125 sites in the Choctawhatchee watershed (southeastern Alabama) using this model. Field surveys involved qualitative and quantitative observations of 73 metrics related to waterway conditions, crossing structures, road approaches, and roadside soil erosion. The road‐stream crossing risk analyses involved elimination of candidate metrics based on redundancy, skewness, lack of data, professional judgment, lack of nonzero values, unbalanced box plots, and limited ranges of values. A final selection of 12 metrics formed the SRI and weighed factors involving soil erodibility, road sedimentation abatement features, and stream morphology alteration. The SRI was organized into narrative categories (excellent, good, fair, poor, and very poor) based on the distribution of scores. No excellent sites (scores ≥55) were found in this study, 17 (20.7%) were good (low sedimentation risk), 37 (45.1%) were fair (moderate sedimentation risk), 26 (31.7%) were poor (high sedimentation risk), and two (2.5%) were very poor (high sedimentation risk). There was no significant difference in SRI scores among crossing structure type (round culverts, box culverts, and bridges) (H = 4.31, df = 2, p = 0.058). A future study of the Choctawhatchee watershed involving the same study sites could assess the success of restoration plans and activities based on site score improvement or decline.     

Accumulation of mercury and its effect on antioxidant enzymes in brain,liver, and kidneys of mice

Abstract

The effect of mercuric chloride (HgCl₂) on the activities of catalase, Superoxide dismutase (SOD), glutathione peroxidase (GPx), glutathione reductase (GR) and its effect on glutathione (GSH) content were evaluated in different organs (liver, kidneys, and brain) of mice after administration at 0, 0.25, 0.5 and 1.0 mg/kg/day for 14 days. The uptake of mercury shows that the kidneys accumulated the highest levels of mercury compare to brain and liver. The enzyme levels varied in mercury treated organs compare to control. A dose dependent increase of antioxidant enzymes occurred in the liver and kidneys. The increase in enzyme activities correlated with highest mercury accumulation in the kidneys and liver. Mercury is known to generate reactive oxygen species (ROS) in vivo and in vitro, therefore, it is likely that enzyme activities increased to scavenge ROS levels produced as a result of mercury accumulation. Glutathione content increased in liver and kidneys of mercury treated mice compare to control. The results showed that the highest oral dose of mercury significantly increased antioxidant enzymes in kidneys and liver. The increased antioxidant enzymes enhance the antioxidant potential of the organs to reduce oxidative stress.