An Extreme Value Analysis of Pollutant Concentrations in Surface Soils Due to Atmospheric Deposition

Risk assessments often rely on deterministic models using long-term averages or “steady-state” values of input variables. Such models do not provide the information needed to estimate acute exposures. This study uses extreme value theory to examine the frequency and magnitude of daily pollutant concentrations in surface soils predicted at six U.S. locations. Concentrations are predicted using a deposition-leaching model and 50 years of historical precipitation data. A stochastic model also is used to generate 1000 years of precipitation data as modeling inputs for each location. The annual maximum concentrations at each site are fitted to a Gumbel type I distribution to estimate occurrence probability. For soluble pollutants, the predicted concentration varied substantially with precipitation, and the maximum daily concentrations exceeded annual averages by 4 to 8 times. Observed and synthetic precipitation data produced similar results at most study locations, though the synthetic data provided a slightly better fit to the Gumbel type I distribution. The precipitation model allows the generation of representative precipitation data that extend limited historical records. The extreme value analysis facilitates the evaluation of maximum pollutant concentrations, return periods, and other statistics that are important in evaluating acute exposures.     

New gene assignments using a complete, characterized sheep-hamster somatic cell hybrid panel

The generation and characterization of new sheep-hamster cell hybrids is reported from the fusion of sheep white blood cells with six different hamster auxotrophs. Selection from these and previously generated cell hybrids has led to the production of a panel of 30 hybrids covering the complete sheep genome of 28 chromosomes. Over half of the cell hybrids in this panel contain single sheep chromosomes. By complementation, the following new assignments have been made using the panel: phosphoribosyl N-formylglycinamide amidotransferase (PRFGA) to sheep chromosome (chr) 11; adenylosuccinate synthetase (ADSS) to sheep chr 12; adenylosuccinate lyase (ADSL) to sheep chr 3q; 3-hydroxy-3-methylglutaryl-coenzyme A synthase (HMGCS) to sheep chr 16; dihydrofolate reductase (DHFR) to sheep chr 5; and adenine phosphoribosyltransferase (APRT) to sheep chr 14. The gene phosphoribosylaminoinidazole-carboxamide formyltransferase/Inosinicase (PRACFT) has now been regionally assigned to chr 2q. By isozyme analysis, phosphogluconate dehydrogenase (PGD) was assigned to sheep chr 12, anchoring the sheep syntenic group U1 to this chromosome, and mannose phosphate isomerase (MPI) was assigned to sheep chr 18. Furthermore, the chromosomal assignment of 110 microsatellites was confirmed using this cell panel.     

Environmental and genetic control of crassulacean acid metabolism in two crassulacean species and an F1 hybrid with differing biomass δ13C values

Abstract The growth, biomass δ¹³C values, and ability to accumulate titratable acidity at night were compared in eight environmental treatments for Cremnophila linguifolia, Sedum greggii, and their F₁ hybrid. In the phytotron, differences in treatment daylength, day/night temperature and water availability were all found to have effects on total plant dry weight, nocturnal accumulation of titratable acidity and biomass δ¹³C value of at least some of the genotypes. However, there were differences between the genotypes both in the magnitude and direction of response of the phenotypic properties to the treatment variables. The phytotron δ¹³C values ranged from -12.9 to -19.2‰ for C. linguifolia, from -22.2 to -33.4‰ for S. greggii, and from -19.2 to -24.9‰ for the hybrid. After with-holding water for 76 h both C. linguifolia and the hybrid had midday Ψ_leaf values of -0.23 MPa; however, S. greggii had a value of -1.05 MPa. In contrast to past observations of other species, the daily watered plants of C. linguifolia had less negative δ¹³C values than did the plants watered only weekly.     

Vegetation mapping with the aid of low-altitude aerial photography

Abstract. A technique for fine-scale vegetation mapping with the aid of low-altitude aerial photography was developed. The procedure is as follows: 1. The site is divided into a lattice pattern - in case the site is too large to fit into a single photograph with satisfactory resolution. The coordinates of every lattice point are surveyed to be used as control points for geometric correction. A photograph of each block of the lattice is taken using a remote-controlled camera system lifted by a captive helium balloon. 2. The vegetation is classified on the basis of a phytosociological survey. 3. The shapes and locations of vegetation patches appearing in the photographs are entered into a computer, using a digitizer. A geometric correction is carried out through coordinate transformation referring to the coordinates of the control points and subsequently a draft vegetation map is produced. Finally, discrepancies are corrected and the map is coloured to produce the final version of the vegetation map. This technique was applied to vegetation mapping at a bar, 500 m wide and 2 km long, in the river Yoshino in Shikoku, Japan. A fine-scale vegetation map was obtained and used to analyse the influence of plants on geomorphic processes and community-specific hydrogeomorphic conditions on the bar.     

How Can the Eco‐efficiency of a Region be Measured and Monitored?

The concept of eco-efficiency is commonly referred to as a business link to sustainable development. In this article, ecoefficiency is examined at a regional level as an approach to promoting the competitiveness of economic activities in the Finnish Kymenlaakso region and mitigating their harmful impacts on the environment. The aim is to develop appropriate indicators for monitoring changes in the eco-efficiency of the region. A starting point is to produce indicators for the environmental and economic dimensions of regional development and use them for measuring regional eco-efficiency. The environmental impact indicators are based on a life-cycle assessment method, producing different types of environmental impact indicators: pressure indicators (e.g., emissions of CO₂), impact category indicators (e.g., CO₂ equivalents in the case of climate change), and a total impact indicator (aggregating different impact category indicator results into a single value). Environmental impact indicators based on direct material input, total material input, and total material requirement of the Kymenlaakso region are also assessed. The economic indicators used are the gross domestic product, the value added, and the output of the main economic sectors of Kymenlaakso. In the eco-efficiency assessment, the economic and environmental impact indicators are monitored in the same graph. In a few cases eco-efficiency ratios can also be calculated (the economic indicators are divided by the environmental indicators). Output (= value added + intermediate consumption) is used as an economic indicator related to the environmental impact indicators, which also cover the upstream processes of the region's activities. In the article, we also discuss the strengths and weaknesses of using the different environmental impact indicators.     

Fine mapping of the chicken salmonellosis resistance locus (SAL1)

Salmonella enterica serovar Typhimurium is a Gram-negative bacterium that has a significant impact on both human and animal health. It is one of the most common food-borne pathogens responsible for a self-limiting gastroenteritis in humans and a similar disease in pigs, cattle and chickens. In contrast, intravenous challenge with S. Typhimurium provides a valuable model for systemic infection, often causing a typhoid-like infection, with bacterial replication resulting in the destruction of the spleen and liver of infected animals. Resistance to systemic salmonellosis in chickens is partly genetically determined, with bacterial numbers at systemic sites in resistant lines being up to 1000-fold fewer than in susceptible lines. Identification of genes contributing to disease resistance will enable genetic selection of resistant lines that will reduce Salmonella levels in poultry flocks. We previously identified a novel resistance locus on Chromosome 5, designated SAL1 . Through the availability of high-density SNP panels in the chicken, combined with advanced back-crossing of the resistant and susceptible lines, we sought to refine the SAL1 locus and identify potential positional candidate genes. Using a 6^th generation backcross mapping population, we have confirmed and refined the SAL1 locus as lying between 54.0 and 54.8 Mb on the long arm of Chromosome 5 ( F  = 8.72, P  = 0.00475). This region spans 14 genes, including two very striking functional candidates; CD27-binding protein ( Siva ) and the RAC -alpha serine/threonine protein kinase homolog , AKT1 ( protein kinase B , PKB ).     

A linkage group on pig chromosome 4 comprising the loci for blood group L, GBA, ATP1B1 and three microsatellites

Restriction fragment length polymorphisms (RFLPs) were described for the porcine loci for β-glucosidase (GBA) and the β-polypeptide 1 of the Na⁺, K⁺-transporting ATPase (ATP1B1). Linkage analyses using a three-generation pedigree provided evidence for the assignment of ATP1B1, GBA and two microsatellite loci (S0001 and S0067) to a previously described linkage group comprising the loci for blood group L (EAL) and an anonymous microsatellite (S0097). The linear order of the six markers was determined with confidence by multipoint analyses and the length of the linkage group was estimated at 88 CM. This linkage group was assigned to pig chromosome 4 on the basis of a previous physical localization of the ATP1B1 gene. In situ hybridization data for S0001 presented in this study were consistent with a localization on chromosome 4 and suggested a regional localization to 4pl2-pl3. The present study reveals conflicting data concerning the genetic localization of the K88 loci controlling the expression of the receptors for the E. coli pilus antigens. One group has reported data suggesting a loose linkage between K88 and EAL, now mapped to chromosome 4, whereas two other groups have found linkage between K88 and the transferrin locus (TF), mapped to chromosome 13 by in situ hybridization.