Building partnerships — the Ohio Materials Exchange

This paper discusses a method by which individuals working in government, private business, not-for-profit and educational organizations developed a collaborative statewide program involving the exchange of materials from manufacturers, commercial business and not-for-profit organizations in Ohio.     

Do source-sink dynamics promote the spread of an invasive grass into a novel habitat?

Models of source-sink and other spatial patch dynamics have generated a number of ideas and predictions about species range expansion, the evolution of local adaptation, and the factors influencing population persistence, but relatively few empirical studies have applied these ideas due to the difficulty of measuring both patch-specific demography and movement rates. In this study, I used a combination of mark-recapture experiments, model fitting, and demographic approaches to ask how habitat-specific differences in population growth and dispersal affect spread of the invasive grass Aegilops triuncialis into serpentine environments. A. triuncialis germinated at lower rates but exhibited equivalent survival and greater growth in edge (extreme serpentine) than in core populations, even accounting for density differences between habitats. Estimated growth rates (lambda) for four of five edge subpopulations were strongly positive, ranging from lambda = 1.32 to 2.09 without propagule input from adjacent habitat. Local dispersal was best described by an exponential kernel, with a mean dispersal distance about twice as long on the edge (0.24-0.40 m) as in the core (0.18 m). Twenty-five percent of marked spikes in the edge were not relocated within the patch, suggesting greater rates of either seed predation or long-distance dispersal that reduced population growth. These results suggest that A. triuncialis can successfully spread into extreme serpentine habitats without sustained propagule input from adjacent populations. Further, asymmetric dispersal that may be both habitat- and density-dependent could slow growth rates on the edge. This pattern may also increase the importance of harsh edge patches as a source of long-distance dispersers.     

Comparison of Outdoor and Classroom Ozone Exposures for School Children in Mexico City

Abstract

To evaluate methods of reducing exposure of school children in southwest Mexico City to ambient ozone, outdoor ozone levels were compared to indoor levels under three distinct classroom conditions: windows/doors open, air cleaner off; windows/doors closed, air cleaner off; windows/ doors closed, air cleaner on. Repeated two-minute average measurements of ozone were made within five minutes of each other inside and outside of six different school classrooms while children were in the room. Outdoor ozone two-minute average levels varied between 64 and 361 ppb; mean outdoor levels were above 160 ppb for each of the three conditions. Adjusting for outdoor relative humidity, for a mean outdoor ozone concentration of 170 ppb, the mean predicted indoor ozone concentrations were 125.3 (±5.7) ppb with windows/doors open; 35.4 (±4.6) ppb with windows/ doors closed, air cleaner off; and 28.9 (±4.3) ppb with windows/ doors closed, air cleaner on. The mean predicted ratios of indoor to outdoor ozone concentrations were 0.71 (±0.03) with windows/doors open; 0.18 (±0.02) ppb with windows/doors closed, air cleaner off; and 0.15 (±0.02) ppb with windows/doors closed, air cleaner on. As outdoor ozone concentrations increased, indoor ozone concentrations increased more rapidly with windows and doors open than with windows and doors closed. Ozone exposure in Mexican schools may be significantly reduced, and can usually be kept below the World Health Organization (WHO) guideline of 80 ppb, by closing windows and doors even when ambient ozone levels reach 30Q ppb or more.     

Systematic Development of an Artificial Neural Network Model for Real-Time Prediction of Ground-Level Ozone in Edmonton,Alberta, Canada

Abstract

Ground-level ozone is a secondary pollutant that has recently gained notoriety for its detrimental effects on human and vegetation health. In this paper, a systematic approach is applied to develop artificial neural network (ANN) models for ground-level ozone (O₃) prediction in Edmonton, Alberta, Canada, using ambient monitoring data for input. The intent of these models is to provide regulatory agencies with a tool for addressing data gaps in ambient monitoring information and predicting O₃ events. The models are used to determine the meteorological conditions and precursors that most affect O₃ concentrations. O₃ time-series effects and the efficacy of the systematic approach are also assessed. The developed models showed good predictive success, with coefficient of multiple determination values ranging from 0.75 to 0.94 for forecasts up to 2 hr in advance. The inputs most important for O₃ prediction were temperature and concentrations of nitric oxide, total hydrocarbons, sulfur dioxide, and nitrogen dioxide.     

Biological and chemical assessments of zinc ageing in field soils

As zinc (Zn) is both an essential trace element and potential toxicant, the effects of Zn fixation in soil are of practical significance. Soil samples from four field sites amended with ZnSO₄ were used to investigate ageing of soluble Zn under field conditions over a 2-year period. Lability of Zn measured using ⁶⁵Zn radioisotope dilution showed a significant decrease over time and hence evidence of Zn fixation in three of the four soils. However, 0.01 M CaCl₂ extractions and toxicity measurements using a genetically modified lux-marked bacterial biosensor did not indicate a decrease in soluble/bioavailable Zn over time. This was attributed to the strong regulatory effect of abiotic properties such as pH on these latter measurements. These results also showed that Zn ageing occurred immediately after Zn spiking, emphasising the need to incubate freshly spiked soils before ecotoxicity assessments.     

Aerosol speciation and mass prediction from toluene oxidation under high NOx conditions

A kinetically based gas-particle partitioning box model is used to highlight the importance of parameter representation in the prediction of secondary organic aerosol (SOA) formation following the photo-oxidation of toluene. The model is initialized using experimental data from York University's indoor smog chamber and provides a prediction of the total aerosol yield and speciation. A series of model sensitivity experiments were performed to study the aerosol speciation and mass prediction under high NO_x conditions (VOC/NO_x = 0.2). Sensitivity experiments indicate vapour pressure estimation to be a large area of weakness in predicting aerosol mass, creating an average total error range of 70 μg m^?3 (range of 5–145 μg m^?3), using two different estimation methods. Aerosol speciation proved relatively insensitive to changes in vapour pressure. One species, 3-methyl-6-nitro-catechol, dominated the aerosol phase regardless of the vapour pressure parameterization used and comprised 73–88% of the aerosol by mass. The dominance is associated with the large concentration of 3-methyl-6-nitro-catechol in the gas-phase. The high NO_x initial conditions of this study suggests that the predominance of 3-methyl-6-nitro-catechol likely results from the cresol-forming branch in the Master Chemical Mechanism taking a significant role in secondary organic aerosol formation under high NO_x conditions. Further research into the yields and speciation leading to this reaction product is recommended.     

Evolution of tolerance to PCBs and susceptibility to a bacterial pathogen (Vibrio harveyi) in Atlantic killifish (Fundulus heteroclitus) from New Bedford (MA, USA) harbor

A population of the non-migratory estuarine fish Fundulus heteroclitus (Atlantic killifish) resident to New Bedford (NB), Massachusetts, USA, an urban harbor highly contaminated with polychlorinated biphenyls (PCBs), demonstrates recently evolved tolerance to some aspects of PCB toxicity. PCB toxicology, ecological theory, and some precedence supported expectations of increased susceptibility to pathogens in NB killifish. However, laboratory bacterial challenges of the marine pathogen Vibrio harveyi to wild fish throughout the reproductive season and to their mature laboratory-raised progeny demonstrated comparable survival by NB and reference killifish, and improved survival by NB males. These results are inconsistent with hypothesized trade-offs of adaptation, and suggest that evolved tolerance in NB killifish may include mechanisms that minimize the immunosuppressive effects of PCBs. Compensatory strategies of populations persisting in highly contaminated environments provide a unique perspective for understanding the long-term ecological effects of toxic chemicals.     

Montane Meadows as Indicators of Environmental Change

We used a time series of satellite multispectral imagery for mapping and monitoring six classes of montane meadows arrayed along a moisture gradient (from hydric to mesic to xeric). We hypothesized that mesic meadows would support the highest species diversity of plants, birds, and butterflies because they are more moderate environments. We also hypothesized that mesic meadows would exhibit the greatest seasonal and interannual variability in spectral response across years. Field sampling in each of the meadow types was conducted for plants, birds, and butterflies in 1997 and 1998. Mesic meadows supported the highest plant species diversity, but there was no significant difference in bird or butterfly species diversity among meadow types. These data show that it may be easier to detect significant differences in more species rich taxa (e.g., plants) than taxa that are represented by fewer species (e.g., butterflies and birds). Mesic meadows also showed the greatest seasonal and interannual variability in spectral response. Given the rich biodiversity of mesic montane meadows and their sensitivity to variations in temperature and moisture, they may be important to monitor in the context of environmental change