Soil organic carbon dynamics of croplands in European Russia: estimates from the “model of humus balance”

The Model of Humus Balance was used to estimate the influence of climate effects and changing agricultural practices on carbon (C) levels in soddy–podzolic soils in the Russian Federation for the years 2000–2050. The model was linked with a spatial database containing soil, climate and farming management layers for identification of spatial change of C sequestration potential. Analysis of relationships between C, soil texture and climate indicated that compared with a business-as-usual scenario, adaptation measures could increase the number of polygons storing soil organic carbon (SOC) by 2010–2020. The rate of possible C loss is sensitive to the different climate scenarios, with a maximum potential for SOC accumulation expected in 2030–2040, thereafter decreasing to 2050. The effect is most pronounced for the arid part of the study area under the emission scenario with the highest rate of increase in atmospheric CO₂ concentration, supporting findings from the dynamic SOC model, RothC. C sequestration during the study period was permanent for clay and clay loam soils with a C content of more than 2%, suggesting that C sequestration should be focused on highly fertile, fine-textured soils. We also show that spatial heterogeneity of soil texture can be a source of uncertainty for estimates of SOC dynamics at the regional scale. Figures in color are available at     

Structure of urban cognitive maps

It has traditionally been accepted that people structure their cognitive map of the city through the five Lynch categories: path, edge, district, node and landmark. This study confirms empirically the existence of these categories in two different experiments applying two forms of multivariate analysis: hierarchical cluster analysis and correspondence analysis based on Euclidean and χ² distances, respectively. The problematic edge category is also discussed, as well as the influence of centre-periphery dimensions on these categories.     

Isoproturon degradation as affected by the growth of two algal species at different concentrations and pH values.

Metabolism of [14C-u-phenyl]isoproturon [3-(4-isopropylphenyl)-1,1-dimethylurea] by two soil and freshwater microorganisms, green alga Chlorella kesslerei and cyanobacterium Anabaena inaequalis, was studied as a function of pH, pesticide concentration, and incubation time. Metabolized isoproturon, in the media, ranged from 0% (Chlorella at pH 5.5 after 1 d) to 22% (Anabaena at pH 5.5 after 10 d). Twenty-five percent faster degradation of isoproturon by Anabaena occurred at pH 5.5 versus pH 7.5, when measured over 10 d. Increased 14C incorporation into tissue, with time and at lower pH, was due mainly to bioaccumulation of [14C]isoproturon and/or its metabolites in the cells. Metabolic degradation resulted in four identifiable (by TLC) metabolites. Based on this, a degradation pathway is proposed, involving mono- and di-N-demethylation, hydroxylation of the isopropyl moiety, and hydrolysis to 4-isopropylaniline. Similarity in the metabolites produced suggests that the enzyme systems responsible for metabolizing isoproturon are almost identical in both photosynthetic micro-algae.     

Modelling local and synoptic scale influences on ozone concentrations in a topographically complex region of Southern Italy

A modelling study with the on-line coupled Eulerian chemical-weather model WRF/Chem for the Southern Italian region around Cosenza (Calabria) was conducted to identify the influences of synoptic scale meteorology, local scale wind systems and local emissions on ozone concentrations in this orographically complex region. Four periods of 5–7 days were chosen, one from each season, which had wind pattern characteristics representative of typical local climatological conditions, in order to study the local versus non-local impacts on ozone transport and formation. To account for the complex terrain, the horizontal resolution of the smallest modelling domain was 3 km. Model results were compared with measurements to demonstrate the capability of the model to reproduce ozone concentrations in the region. The comparison was favourable with a mean bias of ?1.1 ppb. The importance of local emissions on ozone formation and destruction was identified with the use of three different emission scenarios. Generally the influence of regional emissions on the average ozone concentration was small. However during periods when mountain-sea wind systems were well developed and synoptic scale winds were weak, the influence of local emissions from the urban area was at its greatest. The maximum influence of local emissions on ozone concentrations was 18 ppb.