On the evolutionary significance of the size and planarity of the proline ring

Proline is a proteinogenic amino acid in which the side chain forms a ring, the pyrrolidine ring. This is a five-membered ring made up of four carbons and one nitrogen. Here, we study the evolutionary significance of this ring size. It is shown that the size of the pyrrolidine ring has the advantage of being nearly planar and strain-free, based on a general mathematical assertion saying that the angular sum of a polygon is maximum if it is planar and convex. We also provide a sketch of the proof to this assertion. The optimality of the ring size of proline can be derived from a triangle inequality for angles. Quasi-planarity is physiologically significant because it allows an easier and evolutionarily old type of fit into binding grooves of proteins with which proline-rich proteins interact. Finally, we present a comparison with other planar, nearly planar and non-planar biomolecules such as neurotransmitters, hormones and toxins, involving, for example, aromatic rings, cyclopentanone and 1,3-dioxole.     

Accumulation of Organochlorine Compounds in Oysters (Crassostrea Gasar) of an Estuarine Environment: Case of A Tropical Lagoon in the Gulf of Guinea

As part of a pollution monitoring study, oysters (Crassostrea gasar) were sampled in June 1996, in order to determine the concentrations and distribution of chlorinated hydrocarbons in two stations (near Boulay Island and Riviera Golf) of the Ebrie Lagoon, in the Abidjan area.

The chromatographic analysis of the oven dried samples revealed the presence of PCBs (2.13 to 86.22 ppb or ng/g dry weight), DDE (<0.48 to 169.55 ppb), DDD (<1.04 to 60.27 ppb), DDT (1.43 to 77.81 ppb, lindane (<0.22 to 91.64 ppb), aldrin (<0.30 to 154.1 ppb), endrin (<0.23 to 293.31 ppb) and dieldrin (<0.26 to 199.74 ppb). the results indicated high concentrations in oysters sampled near Boulay Island, due to industrial, agricultural and port activities going on in this area.

Compared to DDD/ΣDDT and DDT/ΣDDT, the DDE/ΣDDT ratios were high indicating old DDT inputs. the ΣDDT/PCBs ratios were higher than 1 illustrated the predominance of organochlorine inputs from agriculture activities. the presence of lindane in both stations illustrated the problem of fishing with toxic products.

Negative correlations found between dry tissue weight and organochlorine compounds concentrations showed that young oysters may concentrate more of these substances. More studies are needed in order to make any conclusions on their bioaccumulation trends.     

Vergleich der Raumgliederung Europas mit bestehenden Raumgliederungen – Teil 3

Background, aim and scope The first two articles of this series (Hornsmann et al. 2008; Weustermann et al. 2009) comprised how the Ecological Land Classification of Europe (ELCE) was calculated. Moreover several ecological classes were described exemplarily. In this part 3 of the series the ELCE is compared with two European ecoregionalisations at several levels of differentiation. These are the Digital Map of European ecological regions (DMEER) and the Environmental Stratification of Europe (EnS). In addition the ELCE was opposed to the ecoregionalisation of Germany. The alignment was carried out both functionally and statistically and served as a basis for the examination of the functional consistency of the ELCE. Materials and methods The ecological land classifications were described concerning their input data, the method of derivation and the intended use. The ELCE and the selected three ecoregionalisations were intersected in a GIS and crosstabulated with regard to the acreage of each polygon. These cross tabulations were performed by listing the percentage of ecoregions of e.?g. DMEER to the ecological classes of the ELCE (EC) and vice versa. The similarity of the compared ecoregions was estimated by means of statistics. Results The comparisons show high rates of similarity of the ELCE to the European land classifications. The mean overlap of the EC with the classes of the DMEER is 84 and 69?% vice versa. The EC are covered by the strata of the EnS with 67 and 72?%, respectively. In Germany, ELCE reflects the most important ecological conditions. The mean overlap of the ecoregions in this case is 75 and 80?% vice versa. Discussion The classes of the DMEER show a better overlap of the EC as vice versa due to their larger spatial extent. The main difference between the ELCE and the EnS is based on the procedure of the derivation of the regionalisations. While the classes of the EnS are more differentiated in the South of Europe, the ecoregions of ELCE are smaller and more subdivided in the middle of Europe. The high overlap between the ELCE and the ecoregionalisation of Germany can be indicative for the good account of the ecological structures of the ELCE in the European dimension. Conclusions The ELCE is functionally plausible and a useful complement to the existing land classifications of Europe. Nevertheless, it cannot substitute land classifications on the national level calculated with more detailed input data. The ELCE can be used testing the representativity of environmental monitoring networks in Europe. Recommendations In future, the ELCE should be compared with other national landscape classifications. A new calculation of ELCE would only be useful after the development of a highly powerful derivation method and on the basis of more detailed input data. Moreover, due to the observed climate change in the past 20 years, up-to-date data on climate should be used for the calculations. Perspectives The ELCE could be proven to be functionally consistent. Therefore the fourth article will focus on the investigation of the landscape representativity of environmental monitoring networks on the basis of the ELCE.     

Nitrogen concentrations in mosses indicate the spatial distribution of atmospheric nitrogen deposition in Europe

In 2005/6, nearly 3000 moss samples from (semi-)natural location across 16 European countries were collected for nitrogen analysis. The lowest total nitrogen concentrations in mosses (<0.8%) were observed in northern Finland and northern UK. The highest concentrations (≥1.6%) were found in parts of Belgium, France, Germany, Slovakia, Slovenia and Bulgaria. The asymptotic relationship between the nitrogen concentrations in mosses and EMEP modelled nitrogen deposition (averaged per 50 km × 50 km grid) across Europe showed less scatter when there were at least five moss sampling sites per grid. Factors potentially contributing to the scatter are discussed. In Switzerland, a strong (r² = 0.91) linear relationship was found between the total nitrogen concentration in mosses and measured site-specific bulk nitrogen deposition rates. The total nitrogen concentrations in mosses complement deposition measurements, helping to identify areas in Europe at risk from high nitrogen deposition at a high spatial resolution.     

Emission and burnt smell characteristics from combustion experiments with defined materials

Typical burnt smell often results from fire accidents or in general from incomplete combustion. Recently, eleven compounds were identified, which are basically responsible for this odour. When analyzing residual materials from different fire accidents, the pattern that means the relative ratios of these compounds among each other varies strongly, although always causing a burnt smelling. Consequently, lab-scale combustion experiments were performed in order to investigate the influence of defined materials from domestic environment on the burnt-smell fingerprints. Furthermore, the occurrence of other polar and higher molecular combustion products was studied. It was found that under good combustion conditions, the burnt smell patterns resulting from the single materials were astonishingly consistent, mostly dominated by methylphenols or naphthalene. No correlation could be found between these ‘fingerprints’ and combustion product groups identified by GC/MS-screenings. LC/MS/MS-measurements especially pointed at the existence of higher molecular weight phenolic and acidic functionalized compounds in the combustion residues.     

Estimating Emissions from Air Concentration Measurements

A one-year-long experiment in which two different tracers were simultaneously released from two different locations was used to test various hybrid receptor modeling techniques to estimate the tracer emissions using the measured air concentrations and a meteorological model. Air concentrations were measured over an 8-hour averaging time at three sites 14 to 40 km downwind. When the model was used to estimate emissions at only one tracer source, 6 percent of the short-term (8-h) emission estimates were within a factor of 2 of the actual emissions. Temporal averaging of the 8-h data enhanced the precision of the estimate such that after 10 days 42 percent of the estimates were within a factor of 2 and after six months all of them (each source-receptor pair) were within a factor of 2. To test the ability of the model to separate two sources, both tracer sources were combined, and a multiple linear regression technique was used to determine the emissions from each source from a time series of air concentration measurements representing the sum of both tracers. In general, 50 percent of the short-term estimates were within a factor of 10, 25 percent were biased low, and in another 25 percent the regression technique failed. The bias and failures are attributed to low or no correlation between measured air concentrations and model calculated dispersion factors. In the regression method increased temporal averaging did not consistently improve the emission estimate since the ability of the model to distinguish emissions between sources was diminished with increased averaging time. However, including progressively longer time periods (more data) into the regression or spatially averaging the data over all the receptors was found to be the most effective method to improve the estimated emissions. At best about 75 percent of the estimated monthly emission data were within a factor of 10 of the measured values. This suggests that the usefulness of meteorological models and statistical methods to address questions of source attribution requires many data points to reduce the uncertainty in the emission estimates.     

Science–policy processes for transboundary water governance

In this policy perspective, we outline several conditions to support effective science–policy interaction, with a particular emphasis on improving water governance in transboundary basins. Key conditions include (1) recognizing that science is a crucial but bounded input into water resource decision-making processes; (2) establishing conditions for collaboration and shared commitment among actors; (3) understanding that social or group-learning processes linked to science–policy interaction are enhanced through greater collaboration; (4) accepting that the collaborative production of knowledge about hydrological issues and associated socioeconomic change and institutional responses is essential to build legitimate decision-making processes; and (5) engaging boundary organizations and informal networks of scientists, policy makers, and civil society. We elaborate on these conditions with a diverse set of international examples drawn from a synthesis of our collective experiences in assessing the opportunities and constraints (including the role of power relations) related to governance for water in transboundary settings.