Use of genetic,climatic, and microbiological data to inform reintroduction of a regionally extinct butterfly

Species reintroductions are increasingly used as means of mitigating biodiversity loss. Besides habitat quality at the site targeted for reintroduction, the choice of source population can be critical for success. The butterfly Melanargia russiae (Esper´s marbled white) was extirpated from Hungary over 100 years ago, and a reintroduction program has recently been approved. We used museum specimens of this butterfly, mitochondrial DNA data (mtDNA), endosymbiont screening, and climatic‐similarity analyses to determine which extant populations should be used for its reintroduction. The species displayed 2 main mtDNA lineages across its range: 1 restricted to Iberia and southern France (Iberian lineage) and another found throughout the rest of its range (Eurasian lineage). These 2 lineages possessed highly divergent wsp alleles of the bacterial endosymbiont Wolbachia. The century‐old Hungarian specimens represented an endemic haplotype belonging to the Eurasian lineage, differing by one mutation from the Balkan and eastern European populations. The Hungarian populations of M. russiae occurred in areas with a colder and drier climate relative to most sites with extant known populations. Our results suggest the populations used for reintroduction to Hungary should belong to the Eurasian lineage, preferably from eastern Ukraine (genetically close and living in areas with the highest climatic similarity). Materials stored in museum collections can provide unique opportunities to document historical genetic diversity and help direct conservation.     

Influence of body condition and weather on departures of first-year European robins, <Emphasis Type="Italic">Erithacus rubecula</Emphasis>, from an autumn migratory stopover site

How migratory birds decide when to leave a stopover site is important to the understanding of bird migration strategies. Our study looks at how body condition and the weather affect the decision to depart on nocturnal migratory flight. During two autumn migration seasons (2002–2003), we radio tracked 51 first-year European robins, Erithacus rubecula, at a stopover site on the Courish Spit (Eastern Baltic) from the first day after landing until their migratory departure. The tagged robins stopped over for 1–14 days. There was no clear relationship between stopover duration and energetic condition on arrival. Weather conditions (wind, precipitation, and cloud cover) on departure differed measurably between years. In 2002, robins took off mainly under following winds and clear skies. In 2003, there were mainly light head winds and partially cloudy or overcast skies. This could be explained by the year-specific role of weather factors in making the decision to depart. In both years, robins making short (1–2 days) stopovers took off in more varied weather situations than those individuals with long stopovers. This suggests that robins from the former group were more inclined to continue with migration than longer-stay birds that, apart from re-fuelling, could be waiting for favourable weather. The lack of a relationship between stopover duration and body condition and some departures under unfavourable weather conditions suggest that endogenous spatiotemporal programmes may play an important role in controlling stopover duration in robins.     

Near-field dispersion modeling for regulatory applications

This paper evaluates the application of dispersion models to estimate near-field pollutant concentrations in two case studies. The Industrial Source Complex Short-Term Model (ISCST3) was evaluated with hexavalent chromium measurements collected within 100 m of two facilities in Barrio Logan, San Diego, CA. ISCST3 provided reasonable estimates for higher pollutant concentrations but underestimated lower concentrations. To understand the observed distribution of concentrations in Barrio Logan, a recently conducted tracer experiment was analyzed. The tracer, sulfur hexafluoride, was released at ambient temperature from an urban facility at the University of California at Riverside, and concentrations were measured within 20 m of the source. Modeling results indicated that Industrial Source Complex-Plume Rise Model Enhancement and American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model-Plume Rise Model Enhancement overestimated high concentrations and underestimated low concentrations. A diagnostic study with a simple Gaussian dispersion model that incorporated site-specific meteorology was used to evaluate model results. This study found that incorporating lateral meandering for nonbuoyant urban plumes in Gaussian dispersion models could improve concentration estimates even when downwash is not considered. Incorporating a meandering component in ISCST3 resulted in improvements in estimating hexavalent chromium concentrations in Barrio Logan. Credible near-source concentration estimates depend on accurate characterization of emissions, onsite micrometeorology, and a method to account for lateral meandering in the near field.     

Traffic and meteorological impacts on near-road air quality: summary of methods and trends from the Raleigh Near-Road Study

A growing number of epidemiological studies conducted worldwide suggest an increase in the occurrence of adverse health effects in populations living, working, or going to school near major roadways. A study was designed to assess traffic emissions impacts on air quality and particle toxicity near a heavily traveled highway. In an attempt to describe the complex mixture of pollutants and atmospheric transport mechanisms affecting pollutant dispersion in this near-highway environment, several real-time and time-integrated sampling devices measured air quality concentrations at multiple distances and heights from the road. Pollutants analyzed included U.S. Environmental Protection Agency (EPA)-regulated gases, particulate matter (coarse, fine, and ultrafine), and air toxics. Pollutant measurements were synchronized with real-time traffic and meteorological monitoring devices to provide continuous and integrated assessments of the variation of near-road air pollutant concentrations and particle toxicity with changing traffic and environmental conditions, as well as distance from the road. Measurement results demonstrated the temporal and spatial impact of traffic emissions on near-road air quality. The distribution of mobile source emitted gas and particulate pollutants under all wind and traffic conditions indicated a higher proportion of elevated concentrations near the road, suggesting elevated exposures for populations spending significant amounts of time in this microenvironment. Diurnal variations in pollutant concentrations also demonstrated the impact of traffic activity and meteorology on near-road air quality. Time-resolved measurements of multiple pollutants demonstrated that traffic emissions produced a complex mixture of criteria and air toxic pollutants in this microenvironment. These results provide a foundation for future assessments of these data to identify the relationship of traffic activity and meteorology on air quality concentrations and population exposures.     

PM10 dispersion modeling for Treasure Valley, Idaho

The recorded exceedances of the 24-hr PM10 National Ambient Air Quality Standard (NAAQS) in Treasure Valley, Idaho, have been associated with prolonged stagnation periods during the winter. A comprehensive modeling study of PM10 impact in Treasure Valley was performed to support the State Implementation Plan (SIP). The study included base-year and short-term episodic conditions. The ISCST3 (Industrial Source Complex Short Term 3) model, using the base-year meteorology and gridded emissions of mobile sources, point sources, and wood burning as input, generally agreed well with measurements in both temporal patterns and annual averages. The WYNDvalley model was evaluated using monitoring data and was used to simulate the PM10 impact for episodic exceedances during stagnant winter conditions. An emission inventory was prepared for a base year (1995) and then extrapolated to the years 2000, 2005, 2010, and 2015 in order to determine air quality planning requirements. According to the simulations using base-year emissions and meteorology, exceedances are not expected. However, exceedances at some stations could be expected using projected emissions and episodic meteorology. Results from emission control strategies we developed indicate that mobile-source emissions have the most significant impact; reduction of 25% would be needed to eliminate the simulated exceedances in all projected years.     

Self-fertility in scots pine as a mechanism of resistance to chemical mutagens

Experiments on chemical mutagenesis have shown that the seed progeny of self-fertile Scots pine trees (generations M₁ and M₂) have increased resistance to supermutagens, since the frequency of mitotic pathologies in them has proved to be even lower than in the F₁ progeny of self-sterile trees chronically exposed to anthropogenic impact (automobile exhausts). This is evidence that the use of self-fertile forms in selective breeding for general and specific resistance holds much promise.     

Chemical and biological characterisation of biofilms formed on different substrata in Tisza river (Hungary)

Natural biofilms were simultaneously grown on granite, polished granite, andesite, polycarbonate and Plexi-glass substrata for six weeks in the Tisza River. Biofilm production and abundance of algae were influenced by the substratum. Magnitude of the substratum effect was andesite相似文献   

Resolving neighborhood scale in air toxics modeling: a case study in Wilmington, CA

Air quality modeling is useful for characterizing exposures to air pollutants. Whereas models typically provide results on regional scales, new concerns regarding the potential for differential exposures among racial/ethnic populations and income strata within communities are driving the need for increasingly refined modeling approaches. These approaches need to be capable of resolving concentrations on the scale of tens of meters, across modeling domains 10-100 km2 in size. One approach for refined air quality modeling is to combine Gaussian and regional photochemical grid models. In this paper, the authors demonstrate this approach on a case study of Wilmington, CA, focused on diesel exhaust particulate matter. Modeling results suggest that pollutant concentrations in the vicinity of emission sources are elevated, and, therefore, an understanding of local emission sources is necessary to generate credible modeling results. A probabilistic evaluation of the Gaussian model application indicated that spatial allocation, emission rates, and meteorological data are important contributors to input and parameter uncertainty in the model results. This uncertainty can be substantially reduced through the collection and integration of site-specific information about the location of emission sources and the activity and emission rates of key sources affecting model concentrations.     

Evaluation of land-use regression models used to predict air quality concentrations in an urban area

Cohort studies designed to estimate human health effects of exposures to urban pollutants require accurate determination of ambient concentrations in order to minimize exposure misclassification errors. However, it is often difficult to collect concentration information at each study subject location. In the absence of complete subject-specific measurements, land-use regression (LUR) models have frequently been used for estimating individual levels of exposures to ambient air pollution. The LUR models, however, have several limitations mainly dealing with extensive monitoring data needs and challenges involved in their broader applicability to other locations. In contrast, air quality models can provide high-resolution source–concentration linkages for multiple pollutants, but require detailed emissions and meteorological information. In this study, first we predicted air quality concentrations of PM_2.5, NO_x, and benzene in New Haven, CT using hybrid modeling techniques based on CMAQ and AERMOD model results. Next, we used these values as pseudo-observations to develop and evaluate the different LUR models built using alternative numbers of (training) sites (ranging from 25 to 285 locations out of the total 318 receptors). We then evaluated the fitted LUR models using various approaches, including: 1) internal “Leave-One-Out-Cross-Validation” (LOOCV) procedure within the “training” sites selected; and 2) “Hold-Out” evaluation procedure, where we set aside 33–293 tests sites as independent datasets for external model evaluation. LUR models appeared to perform well in the training datasets. However, when these LUR models were tested against independent hold out (test) datasets, their performance diminished considerably. Our results confirm the challenges facing the LUR community in attempting to fit empirical response surfaces to spatially- and temporally-varying pollution levels using LUR techniques that are site dependent. These results also illustrate the potential benefits of enhancing basic LUR models by utilizing air quality modeling tools or concepts in order to improve their reliability or transferability.