Eukaryotic diversity in premise drinking water using 18S rDNA sequencing: implications for health risks

The goal of this study was to characterize microbial eukaryotes over a 12-month period to provide insight into the occurrence of potential bacterial predators and hosts in premise plumbing. Nearly 6,300 partial 18S rRNA gene sequences from 24 hot (36.9–39.0 °C) and cold (6.8–29.1 °C) drinking water samples were analyzed and classified into major eukaryotic groups. Each major group, consisting of free-living amoebae (FLA)/protozoa, algae, copepods, dinoflagellates, fungi, nematodes, and unique uncultured eukaryotic sequences, showed limited diversity dominated by a few distinct populations, which may be characteristic of oligotrophic environments. Changes in the relative abundance of predators such as nematodes, copepods, and FLA appear to be related to temperature and seasonal changes in water quality. Sequences nearly identical to FLA such as Hartmannella vermiformis, Echinamoeba thermarmum, Pseudoparamoeba pagei, Protacanthamoeba bohemica, Platyamoeba sp., and Vannella sp. were obtained. In addition to FLA, various copepods, rotifers, and nematodes have been reported to internalize viral and bacterial pathogens within drinking water systems thus potentially serving as transport hosts; implications of which are discussed further. Increasing the knowledge of eukaryotic occurrence and their relationship with potential pathogens should aid in assessing microbial risk associated with various eukaryotic organisms in drinking water.     

Validation of Personal Exposure Models for Sulfafe and Aerosol Strong Acidity

Personal exposure models for sulfates (SO₄ ⁼) and aerosol strong acidity (H⁺) were previously developed using concentration and activity pattern data collected from a personal monitoring study conducted in Uniontown, Pennsylvania, during the summer of 1990. Models were constructed based on time-weighted microenvironmental exposures. For SO₄ ⁼, the “best-fit” model included a correction factor, while for H⁺, it included both a correction factor and a neutralization term.

In this paper, we present the validation of these models using data collected in a personal monitoring study conducted in State College, Pennsylvania, during the summer of 1991. Indoor and outdoor concentration and activity pattern data collected in this study were used as inputs for the “best-fit” models for SO₄ ⁼ and H⁺. Predicted personal exposures subsequently were compared to the measured personal exposures from State College to determine their accuracy and precision.

Predicted personal exposures for both SO₄ ⁼ and H⁺ were in excellent agreement with measured personal exposures from State College. The models explained 91 and 62 percent of the variability in personal SO₄ ⁼ and H⁺ exposures, respectively, and were able to estimate personal exposures substantially better than outdoor concentrations alone. Validation results suggest that the models' correction and neutralization factors are not site specific and support the models' future application as a technique to assess the personal acid aerosol exposures of children living in similar rural and semi-rural communities.     

Monitoring study of the near-road PM2.5 concentrations in Maryland

The Maryland State Highway Administration (SHA) monitoring program monitored the impact of vehicular emissions on the concentrations of the fine particles smaller than 2.5 microns (PM2.5). PM2.5 concentrations were monitored in close proximity to a highway in order to determine whether traffic conditions on the roadway impact concentrations at this location. The monitoring program attempted to connect monitored concentrations with the roadway traffic exhaust or with the other sources of PM2.5. PM2.5 concentrations were collected near the Capital Beltway (I-495/I-95) in Largo, Maryland. The monitoring program was launched on May 13, 2009 and continued through the end of 2012. Two co-located monitors, one for continuous PM2.5 measurements and the other for speciation measurements, were used in this program. Meteorological and traffic information was also continuously collected at or near the monitoring site. Additionally, data from the two other monitoring locations, one at the Howard University-Beltsville, MD and one at McMillan Reservoir, DC, was used for comparison with the data collected at the SHA monitoring location. The samples collected by the speciation monitor were analyzed at the RTI and DRI Laboratories to determine the composition and the sources of the collected PM2.5 samples. Based on the apportionment analysis, the contribution of roadway sources is about 12 to 17 percent of PM2.5 at the near-road site.

Implications: PM_2.5 monitoring at 150 m (approximately 500 feet) from a major highway in Maryland near Washington, DC, demonstrated that roadway traffic contributes to the total PM_2.5 concentration near the roadway, but the contribution at such distance is small, in the order of 12–17% of the total.     

DNA damage in Populus tremuloides clones exposed to elevated O3

The effects of elevated concentrations of atmospheric tropospheric ozone (O₃) on DNA damage in five trembling aspen (Populus tremuloides Michx.) clones growing in a free-air enrichment experiment in the presence and absence of elevated concentrations of carbon dioxide (CO₂) were examined. Growing season mean hourly O₃ concentrations were 36.3 and 47.3 ppb for ambient and elevated O₃ plots, respectively. The 4th highest daily maximum 8-h ambient and elevated O₃ concentrations were 79 and 89 ppb, respectively. Elevated CO₂ averaged 524 ppm (+150 ppm) over the growing season. Exposure to O₃ and CO₂ in combination with O₃ increased DNA damage levels above background as measured by the comet assay. Ozone-tolerant clones 271 and 8L showed the highest levels of DNA damage under elevated O₃ compared with ambient air; whereas less tolerant clone 216 and sensitive clones 42E and 259 had comparably lower levels of DNA damage with no significant differences between elevated O₃ and ambient air. Clone 8L was demonstrated to have the highest level of excision DNA repair. In addition, clone 271 had the highest level of oxidative damage as measured by lipid peroxidation. The results suggest that variation in cellular responses to DNA damage between aspen clones may contribute to O₃ tolerance or sensitivity.     

Sustainability of wastewater treatment technologies

A set of indicators that incorporate environmental, societal, and economic sustainability were developed and used to investigate the sustainability of different wastewater treatment technologies, for plant capacities of <5 million gallons per day (MGD) or 18.9 x 10(3) cubic meters (m(3)/day). The technologies evaluated were mechanical (i.e., activated sludge with secondary treatment), lagoon (facultative, anaerobic, and aerobic), and land treatment systems (e.g., slow rate irrigation, rapid infiltration, and overland flow). The economic indicators selected were capital, operation and management, and user costs because they determine the economic affordability of a particular technology to a community. Environmental indicators include energy use, because it indirectly measures resource utilization, and performance of the technology in removing conventional wastewater constituents such as biochemical oxygen demand, ammonia nitrogen, phosphorus, and pathogens. These indicators also determine the reuse potential of the treated wastewater. Societal indicators capture cultural acceptance of the technology through public participation and also measure whether there is improvement in the community from the specific technology through increased job opportunities, better education, or an improved local environment. While selection of a set of indicators is dependent on the geographic and demographic context of a particular community, the overall results of this study show that there are varying degrees of sustainability with each treatment technology.     

Assessing and Prioritizing Ecological Communities for Monitoring in a Regional Habitat Conservation Plan

In nature reserves and habitat conservation areas, monitoring is required to determine if reserves are meeting their goals for preserving species, ecological communities, and ecosystems. Increasingly, reserves are established to protect multiple species and communities, each with their own conservation goals and objectives. As resources are always inadequate to monitor all components, criteria must be applied to prioritize both species and communities for monitoring and management. While methods for prioritizing species based on endangerment or risk have been established, approaches to prioritizing ecological communities for monitoring are not well developed, despite a long-standing emphasis on communities as target elements in reserve design. We established guidelines based on four criteria derived from basic principles of conservation and landscape ecology--extent, representativeness, fragmentation, and endangerment--to prioritize communities in the San Diego Multiple Species Conservation Plan (MSCP). The MSCP was one of the first multiple-species habitat conservation areas established in California, USA, and it has a complex spatial configuration because of the patterns of surrounding land use, which are largely urbanized. In this case study, high priority communities for monitoring include coastal sage scrub (high endangerment, underrepresented within the reserve relative to the region, and moderately fragmented), freshwater wetlands, and coastal habitats (both have high fragmentation, moderate endangerment and representativeness, and low areal extent). This framework may be useful to other conservation planners and land managers for prioritizing the most significant and at-risk communities for monitoring.     

Sustainability Assessment of Future Scenarios: Methodology and Application to Mountain Areas of Europe

BioScene (scenarios for reconciling biodiversity conservation with declining agriculture use in mountain areas in Europe) was a three-year project (2002–2005) funded by the European Union’s Fifth Framework Programme, and aimed to investigate the implications of agricultural restructuring and decline for biodiversity conservation in the mountain areas of Europe. The research took a case study approach to the analysis of the biodiversity processes and outcomes of different scenarios of agri-environmental change in six countries (France, Greece, Norway, Slovakia, Switzerland, and the United Kingdom) covering the major biogeographical regions of Europe. The project was coordinated by Imperial College London, and each study area had a multidisciplinary team including ecologists and social and economic experts, which sought a comprehensive understanding of the drivers for change and their implications for sustainability. A key component was the sustainability assessment (SA) of the alternative scenarios. This article discusses the development and application of the SA methodology developed for BioScene. While the methodology was objectives-led, it was also strongly grounded in baseline ecological and socio-economic data. This article also describes the engagement of stakeholder panels in each study area and the use of causal chain analysis for understanding the likely implications for land use and biodiversity of strategic drivers of change under alternative scenarios for agriculture and rural policy and for biodiversity management. Finally, this article draws conclusions for the application of SA more widely, its use with scenarios, and the benefits of stakeholder engagement in the SA process.     

Effects of uncertainty and variability on population declines and IUCN Red List classifications

The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age‐structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates, particularly when available evidence indicates a potential transition to higher risk categories.     

Phytoremediation of contaminants of emerging concern from soil with industrial hemp (Cannabis sativa L.): a review

Environment, Development and Sustainability - The presence of contaminants of emerging concern (CECs) in wastewater treatment plant effluents is a significant underlying health risk and...     

Practitioner and scientist perceptions of successful amphibian conservation

Conservation requires successful outcomes. However, success is perceived in many different ways depending on the desired outcome. Through a questionnaire survey, we examined perceptions of success among 355 scientists and practitioners working on amphibian conservation from over 150 organizations in more than 50 countries. We also sought to identify how different types of conservation actions and respondent experience and background influenced perceptions. Respondents identified 4 types of success: species and habitat improvements (84% of respondents); effective program management (36%); outreach initiatives such as education and public engagement (25%); and the application of science‐based conservation (15%). The most significant factor influencing overall perceived success was reducing threats. Capacity building was rated least important. Perceptions were influenced by experience, professional affiliation, involvement in conservation practice, and country of residence. More experienced practitioners associated success with improvements to species and habitats and less so with education and engagement initiatives. Although science‐based conservation was rated as important, this factor declined in importance as the number of programs a respondent participated in increased, particularly among those from less economically developed countries. The ultimate measure of conservation success—population recovery—may be difficult to measure in many amphibians; difficult to relate to the conservation actions intended to drive it; and difficult to achieve within conventional funding time frames. The relaunched Amphibian Conservation Action Plan provides a framework for capturing lower level processes and outcomes, identifying gaps, and measuring progress.